ML19319D143
| ML19319D143 | |
| Person / Time | |
|---|---|
| Site: | Crystal River  |
| Issue date: | 10/31/1974 |
| From: | FLORIDA POWER CORP. |
| To: | |
| Shared Package | |
| ML19319D139 | List: |
| References | |
| NUDOCS 8003130711 | |
| Download: ML19319D143 (180) | |
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{{#Wiki_filter:. _. _ _ . _. . _ _ . -- O crystal river power plant Environmental Considerations final report to the Interagency Research Advisory Committee g THE ATTACHED FILES ARE OFFICI AL RECORDS OF THE OFFICE OF REGULATION. THEY HAVE BEEN CHARGED TO YOU FOR A LIMITED TIME PERIOD ANS MUST BE RETURNED TO THE CENTRAL RECORDS STATION 008. ANY PAGE(S) REMOVED FOR REPRODUCTION MUST BE RETURNED TO ITS/THEIR ORIGIN AL ORDER. W DEADLINE RETURN DATE O~ E a so
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"'# Florida MARY llNKS, CHIEF Power CORPORATION CENTRAL RECOROS STATION l
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i CRYSTAL RIVER POWER PLANT ENVIRONMENTAL CONSIDERATIONS VOLUME II OCTOBER,1974
TABLE OF CONTENTS VOLUME I INTRODUCTION Florida Power Corporation I-3 I-7 PROGRAM OVERVIEW AND STATISTICAL REVIEW Law Engineering Testing Company POWER PLANTS AND ESTUARIES AT CRYSTAL RIVER, FLORIDA An Energy Evaluation of the System of Power Plants, Estuarine Ecology and Alternatives for Management Howard T. Odum, W.M. Kemp, W.H.B. Smith, H.N. McKellar, D.L. Young, M.E. Lehman, M.L. Homer, L.H. Gunderson, and A.D. Merriam SYSTEMS ECOLOGY GROUP 1 Department of Environmental Engineering Sciences University of Florida INTRODUCTION AND RECOMMENDATIONS I-13 : H.T. Odum ENERGY EVALUATION OF COOLING ALTERNATIVES AND REGIONAL I-29 IMPACT OF POWER PLANTS AT CRYSTAL RIVER M. Kemp MAIN ECOLOGICAL SUBSYSTEMS OF THE ESTUARY AND THEIR I-73 ADAPTATION TO THE POWER PLANTS A. SHALLOW INSHORE ECOSYSTEM OF BOTTOM COMMUNITIES I-77 AND THE EFFECT OF THERMAL PLUME Wade Smith B. METAB0LISM AND MDDELS OF OUTER BAY PLANKTON ECOSYSTEMS I-159 AFFECTED BY POWER PLANT H. McKellar C. OYSTER REEFS AT CRYSTAL RIVER AND THEIR ADAPTATION I-269 TO THERMAL PLUMES M. Lehman : D. ECOSYSTEMS OF THE INTAKE AND DISCHARGE CANALS I-361 M. Kemp E. TIDAL CREEKS AND EFFECTS OF POWER PLANTS I-387 M. Homer i
d TABLE OF CONTENTS VOLUME II AN ENERGY EVALUATION OF THE SYSTEM 0F POWER PLANTS, ESTAURINE ECOLOGY, AND ALTERNATIVES FOR MANAGEMENT (CONTINUED) F. " SALT MARSH AND THE EFFECT OF THERMAL PLUME II-1 D., Young VALUE OF HIGHER ANIMALS AT CRYSTAL RIVER ESTIMATED WITH ENERGY QUALITY RATIOS . II-93 M. Kemp, H. McKellar, and M. Homer MONITORING FUTURE TRENDS AND ONSET OF ADDITIONAL PLUMES WITH A METAB0LISM BUOY II-109 L. Gunderson and A. Merriam APPENDIX A. PAPERS RECENTLY PUBLISHED IN THERMAL ECOLOGY SYMPOSIUM II-ll7
- APPENDIX' A1. ENERGY COST' BENEFIT MODELS FOR EVALUATINGII-ll8 THERMAL PLU H.T. Odum APPENDIX A2. STUDIES OF FLORIDA GULF COAST SALT MARSHES RECEIVING 11-140 THERMAL DISCHARGES -
D.L. Young APPENDIX A3. TOTAL METAB0LISM 0F THERMALLY AFFECTED C0ASTAL SYSTEMS ON II-159 THE WEST C0AST OF FLORIDA W. Smith, H. McKellar, D. Young, and M. Lehman APPENDIX B. ENERGY COST-BENEFIT APPRUACH TO EVALUATING POWER PLANT II-175 ALTERNATIVES H.T. Odum APPENDIX C. PRELIMINARY CALCULATIONS OF ENERGY QUALITY RATIOS OR WORK II-185 EQUIVALENT FACTORS M. Kemp and W. Boynton APPENDIX D. MODELS OF THE INTERACTION OF THE CRYSTAL RIVER POWER PLANT II-209 AND THE ADJACENT OUTEP BAY ECOSYSTEM: RELATION TO COASTAL FISHERIES H. McKellar . , APPENDIX E. SALT MARSH MICROARTHROPOD POPULATIONS II-241 1 E.A. McMahan and D.L. Young
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TABLE OF CONTENTS VOLUME II , FINAL REPORT TO THE FLORIDA POWER CORPORATION II-255 Dr. Samuel C. Snedaker, Principal Resource Management Systems Program Institute of Food and Agricultural Sciences University of Florida dainesville, Florida . REPORT A. EVALUATIONS OF INTERACTIONS BETWEEN A POWER iNERATION II-257 FACILITY AND A CONTIGUOUS ESTUARINE ECOSYS'IEM
, Samuel C. Snedaker REPORT B. IMPINGEMENT AT THE CRYSTAL RIVER POWER GENERATION FACILITY II-259 A-QUANTITATIVE ANALYSIS Samuel C. Snedaker REPORT C. SEDIMENT COMPOSITION AND DISTRIBUTION AT CRYSTAL RIVER II-309 POWER PLANT: EROSION VS. DEPOSITION Daniel J. Cottrell REPORT D. COMPARISONS OF THE BENIHIC FLORA IN ESTUARIES ADJALENT TO II-377
- THE CRYSTAL RIVER POWER GENERATION FACILITY Robin F. Van Tine l VOLUME III FINAL REPORT TO THE FLORIDA POWER CORPORATION SUBMITTED BY Or Samuel C. Snedaker, Principal Investigator (continued)
REPORT E. BENTHIC INVERTEBRATE COMPARIS0NS IN TWO ESTUARIES ADJACENT TO III-l THE CRYSTAL RIVER POWER GENERATION FACILITY Gary Evink end Barbara Green REPORT F. COMPARISON OF SELECTED VERTEBRATE POPULATIONS IN TWO ESTUARIES ADJACENT TO THE CRYSTAL RIVER POWER GENERATION FACILITY III-l Clayton A. Adams REPORT G. EFFECTS OF IMPINGMENT AND ENIRAPMENT ON THE CRYSTAL RIVER III-107 BLUE CRAB, CALLINECTES SAPIDUS RATHBUN, POPULATION Clayton A. Adams, Michael J. Oesterling and Samuel C. Snedaker APPENDIX A. PHYLOGENETIC LISTING OF ESTUARINE SPECIES AT CRYSTAL III-147 RIVER, FLORIDA : . Clayton A. Adams, Gary L. Evink, Michael J. Oesterling, William Seaman and Robin Van Tine 111 i
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- TABLE UF CONTENTS VOLUME III i
APPENDIX B1 IMPINGEMENT DATA RECORD III-165 l Clayton A. Adams, Charles J. Bilgere and Samuel C. Snedaker APPENDIX B2 IMPINGEMENT DATA SUMMARIES III-315 Clayton A. Adams, Charles J. Bilgere and Samuel C. Snedaker INDEPENDENT ENVIRONMENTAL STUDY OF THERMAL EFFECTS OF POWER PLANT DISCHARGE Dr. Kendall L. Carder Principal Investigator Department of Marine Science University of South Florida
" NATURAL HEATING OF SALT MARSH WATERS IN THE AREA 0F THE CRYSTAL RIVER III-379 POWER PLANT" - TECHNICAL REPORT #3 Ronald H. Klausewitz, Steven L. Palmer, Bruce A. Rodgers, and Kendall L. Carder RESULTS ON BATHYMETRY AND BOTTOM TYPE ANALYSIS OF THE CRYSTAL RIVER III-413 POWER PLANT DISCHARGE BASIN - TECHNICAL REPORT #5 Bruce A. Rodgers, Ronald H. Klausewitz, and Thomas J. Keller VOLUME IV ZOOPLANKTON RESEARCH Dr. Frank J. Maturo, Jr.
t Principal Investigator University of Florida Marine Laboratory Gainesville, Florida A SUPPLEMENTARY ZOOPLANKTON SURVEY AT THE CRYSTAL RIVER PLANT SITE IV-1 Frank J. Maturo, Jr., John W. Caldwell, and William Ingram III EFFECTS OF POWER PLANT ENTRAINMENT ON MAJOR SPECIES OF COPEPODS IV-69 . Frank J. Maturo, Jr., Ray Alden and William Ingram III APPENDIX A DATA TABLES IV-103 APPENDIX B BIOLOGICAL PARAMETERS GRAPHS IV-105 APPENDIX C NET MORTALITY GRAPHS . IV-151 APPENDIX D CONTOUR GRAPHS IV-205 APPENDIX E FECUNDITY RATE ANALY' SIS IV-209 APPENDIX F GROWTH CURVES IV-215 , s' . . - l iv l l
TABLE OF CONTENTS VOLUME IV EFFECTS OF POWER PLANT ENTRAINMENT ON MAJOR SPECIES 07 COPEP0DS IV-235 MEASUREMENT OF ZOOPLANKTON MORTALITY USING ADENOSINE iRI-PHOSPHATE AS A VIABLE BIOMASS INDICATOR. Frank J. Maturo, Jr. and Richard D. Drew EFFECT OF POWER PLANT OPERATION ON SHALL01; WATER IV-265 C0ASTAL ZOOPLANKTON Frank J. Maturo, Jr. John W. Caldwell and William. Ingram III GENERAL OBJECTIVES IV-269 OBJECTIVE 1 SOURCE AND DISCHARGE AREAS OF CRYSTAL RIVER IV-282 POWER PLANT'S COOLING WATER IN RELATION TO ZOOPLANKTON SAMPLING STATIONS Richard Cullen and Ron DuBose OBJECTIVE 2 STANDING CROP ESTIMATES IV-282 Tom Chaney OBJECTIVE 3 PRODUCTION OF ZOOPLANKTON POPULATIONS AT CRYSTAL RIVER IV-287 Ray Alden and Frank Hearne OBJECTIVE 4a CTENOPHORE STANDING CROP AND PREDATION IV-299 Eric F. Hallquist OBJECTIVE 4b CHAET0 GNATH PREDATION IV-306 Alex Smart OBJECTIVE 4c JECAPOD PREDATION IV-312 Alex Smart OBJECTIVE 5 A COMPARISON OF POWER PLANT PREDATIO; AND NATURAL IV-331 PREDATION Richard Cullen and Ronald DuBose OBJECTIVE 6 STATISTICAL ANALYSIS OF NATURAL AND POWER PLANT INFLUENCES IV-334 ON ZOOPLANKTON COMMUNITIES AT CRYSTAL RIVER. William Ingram OBJECTIVE 7 COMPARISON OF ZOOPLANKTON DIVERSITY OF SEVERAL IV-392 AREAS IN THE EASTERN GULF 0F MEXICO Herbert Hickox and Arthur Wenderoth 4 V
TABLE OF CONTENTS VOLUME IV PHYTOPLANKTON RESEARCt! Dr. Thoras L. Hopkins Principal Investigator Department of Marine Science University of South Florida PHYTOPLANKTON ECOLOGY IN THE VICINITY OF THE FLORIDA POWER CORPORATION IV-419 GENERATING PLANT AT CRYSTAL RIVER NOVEMBER, 1973 - APRIL, 19/4. Robert A. Gibson, J.0. Roger Johansson, Mark E. Gorman and Thomms L. Hopkins APPENDIX I IV-445 i l l I i I vi i
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4F. SALT MARSHES AND THERMAL ADDITIONS AT CRYSTAL RIVER, FLORIDA Don L. Young Department of Environmental Engineering Sciences University of Florida Gainesville 32611 INTRODUCTION Florida's Gulf Coast estuarine zone in the vicintiy of Florida Power Corporation's Crystal River Site is dominated on the landward side by tidal salt marshes. These marshes occupy the shoreline north of the mouth of the discharge canal and under conditions of high tide are inundated by significant quantities of elevated temp-erature water. Studies of the possible effects of thermal discharges on the marsh ecosystems at Crystal River have been underway since 1972. This report contains results of field measurements in thermal-ly impacted and adjacent control marshes taken to establish if adaptations and adjustments have been made to existing temperature regimes. Computer simulations of ecosystem response to temperature and supplemental measurements carried out in thermally impacted marshes at Jacksonville, Florida were utilized to suggest possible consequences of the operation of Unit 3 on the marsh ecosystem at Crystal River. Indices of overall ecosystem structure and function were chosen as parameters for evaluating the effect of thermal discharges. Plant standing crop characteristics, net production, respiration, total metabolism, decomposition, and selected animal numbers and diversity were examined individually in thermally impacted and l control areas. A synthesis of these results was made utilizing l energy flow diagrams to understand the integrated response of all II-l
system components at the community level. If differences in com-munity structure and function were observed, it was felt that better insight would be gained as to whether thermal discharges act as a stress or a supplementa'l energy source to the marsh ecosystem. Site Studies were carried out at Florida Power Corporation's Crystal River Site near Crystal River, Florida (Figure la). Florida's Gulf coastline is a low energy coast of mixed tides (tides are semi-diurnal, but highs and lows during the same day are of unequal amplitude) with mean tidal range at Crystal River of 0.76 meters (2.5 feet). In 1972 and 1973 two oil-fired steam plants, with a combined maximum capacity of 897 megawatts were located at the land-ward edge of the salt marsh. Sea water from the Gulf of Mexico was employed as condenser coolant at a rate of 2420 m3/minute (640,000 gallons / minute) in a once-through cooling scheme. Sea water is circulated through a system of two canals dredged through the marshes; water is drawn from offshore, passed through the condensers with a naximum temperature rice of 6 C, and discharged into a. shallow estuarine bay, Figure lb. During periods of high tide, the thermal offluent is backed up into the marshes to the north of the mouth of the discharge canal. An area of marsh immediately north of the mouth of the discharge canal was designated as the thermally affected study area (area 1 in Figure Ib) based on hydrological studies by Carder (1971,1972). He j demonstrated that a significant portion of the thermal plume is l pushed onto these marshes by high tides and that elevated tempera-tures in the marshes bordering the bay are highest there. Two II-2 1
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I Figure 1. (a) Location of Florida Power Corporation's Crystal River site. (b) Details of the marsh ecosystem in the vicinity of the plant including experimental study areas. 1 l II-3
control areas (areas 2 and 3 in Figure Ib) were established for comparative purposes in areas beyond the influence of the plume to the north and south of the canal complex. Water temperature measurements obtained in the thermally affected marsh averaged 3-60 C warmer than similar measurements in the nearby controls. The maximum water temperature observed on the thermal marsh by Carder and confirmed with independent measurements during this study was 370 C in the summer. Both the designated control areas and the thermally affected marsh appear to be typical of the marshes in the Crystal River vicinity. They are characterized by approximately the same eleva-tions and floristic compositions. The majority of the marsh is occupied by Juncus roemarianus with Spartina alterniflora commonly found at the seaward edge of the marsh and along creekbanks. They are washed by the tides twice a day. l . \ II-4
METHODS' Measurements of Marsh Structure and Function Evaluation of Marsh Ecosystem Diagram The qualitative marsh ecosystem diagram, Figure 1M, was quanti-fle d from results of field measurements and some values from the literature. The ecosystem model guided the selection of parameters to be measured during this sampling phase and served as a method of synthesizing results for comparisons of marsh types and thermally impacted and control areas. Parallel sets of measurements were taken in thermally impacted and control marshes for the purpose of determining statistically significant differences. Some addi-tional measurements were taken less frequently or intensively to obtain information to complete the model diagrams. Numerical values were placed on the individual pathways, storages, and forcing func-tions in the diagram. Also tables were prepared to accompany each diagram which document the calculations performed and the source of all data used. Duplicate diagrams were quantified for the thermally impacted and control marshes during typical Winter (February) and Sunner (August) conditions. To assist the reader, field methods were categorized as representing forcing functions, structure, or function. Physical Forcing Function Forcing functions are sources of energy or materials which originate external to the marsh system, but which are important in governing the behavior of the system. Solar l II-5 l
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insola' tion," air" temperature, precipita' Yon t ~, w' ater temperatu're, ' salinity, tidal depth, and frequency of inundation vere considered the principal forcing functions of the marsh ecosystem. Insolation, air temperature, and precipitation records published annually for Florida (U. S. Department of Commerce, 1961-1971) were utilized to give annual trends of these parameters. Data were plotted as monthly means incorporating data from 1961 to present. These records were supplemented with additional field measurements taken during this study (1972-1973) to establish if irregularities were apparent. The U. S. Coastal and Geodetic Survey 01cNulty, et al. ,1973) has recorded monthly water temperature at Cedar Key, Florida (approximately 30 miles Northwest of Crystal River) and these records were utilized to establish long teen trends. Water tempera-ture data for discharge and control stations at Crystal River were provided by Florida River Corporation and plotted as weekly mean temperatures. McNulty, e3 gl (1973) constructed a salinity map in the vicinity of Crystal River from previous studies in the area. Frequent spot checks and diel measurements of water temperature and salinity in the stusf areas at Crystal River were taken during this and other research programs and were used to supplement USCGS l information. Daily tidal records for the month of the Withlaccochee River (2 miles North of the Crystal River study area) were available from Tide Tables (NOAA, 1972, 1973, 1974). Water level measurements taken on the marsh over many tidal cycles were used in conjunction II-7 l
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with elevation surveys taken on a portion of the marsh to construct depth and frequency of inundation relationships based on the Tide Table data. Juncus and Spartina Standing Crop Characteristics Field collections and measurements began in June 1972 within the thermally affected Juncus and Spartina communities and in September,1972 in the Spartina control marshes. Collections were made at four-to-six week intervals in both thermally impacted and control marshes until October,1973. The Juncus control marsh was sampled for standing crop only in March and August,1973 during the course of gas metabolism studies. Documentation of the structure of the Juncus and Spartina marshes consisted of almost identical measurements for each species and included: live, dead, and total aerial standing crop per m ; number of live stems, partitioned into 20 en size classes, per m for Spartina (25 cm increments for Juncus); number of dead stems per 2 m ; number of live stems, divided into subjectively defined age classes, per m ; number of flowering plants per m ; leaf area inder (LAl, m2 per m2 ); and finally information about the vertical distri-I I botion of total and live standing crop. Nat'all of this data was utilized in the ecosystem energy flow model, but comparisons of structure and phenology would later aid in the interpretation of l differences between species and the affects of thermal additions. Samples of Juncus and Spartina were obtained from clip har-vest plots. The area of the quadrat and the number of quadrat samples P II-8
taken Et'a point in't'ime have been shows Ito' affect the a'ccuracy ' of the results obtained (Milner and Hughes, 1970). For this 2 study, 0.25 m square quadrats were selected for use. Quadrats were constructed from 1/8" steel rod with one end detachable to facilitate placement in the dense vegetation. One quarter square meter quadrats were found to be a frequently-used size by previous investigators and tests in the field during this tudy showed this size allowed reasonable rapid harvesting and subsequent processing in the laboratory. A statistical analysis was performed in June, 1972 to determine the number of quadrats to be clipped for main-taining a minimum error of 15% about the mean live and dead biomass with a probability of 95% (Mendelson,1971). Nine quadrats of Spartina and five of Juncus were found to be adequate and were used throughout the remainder of the study. Collections of Spartina from each control area were taken at each sampling interval and pooled to achieve a composite control sample size of nine quadrats. A program of stratified sempling was conducted in the distinct vegetation zones of Jun:us and Spartina. Random sampling was per-formed in each of the two vegetation zones; while in the zone of interest, the quadrat was randomly tossed and the area immediately beneath it harvested. All live and dead stems were clipped to within one to two centimeters of the substrate surface with hand shears, placed in sealable, plastic bags, and transported to the laboratory. At the laboratory, samples were stored in a deep freeze or walk-in i ! refrigerator to retard decomposition until processing. During II-9
processing each sample vcs separated by species and live and dead fractions and all stems counted. Pead Spartina leaves present on live plants were removed and placed in the dead category. All live stems were further sorted into 20 cm size classes (25 cm for Juncus) and each stem was subjectively categorized as immature, mature, or senescent. All plants which had flowered were also recorded. All results of the stem counts were expressed as stems per m . Finally all live and dead material in each sample was dried to constant weight at 70*C, weighed, and results multiplied by four for conversion to grams dry weight per m of marsh surface. Values of mean monthly biomass and stem density for thermally impacted and control marshes were subjected to F-tests and t-tests to determine if statistically significant differences existed between marshes. Selected Animal Numbers, Diversity, and Biomass Snails. Littorina irrorata, and fiddler crab, Uca sp., burrows In conjunction with the studies of vegetation structure out-lined above, an effect was made to periodically census two con-spicuous invertebrate populations of the marsh system. During the monthly standing crop harvests, counts were taken of the number of marsh perwinkles, Littorina irrorata and fiddler crab burrows, Uca sp. , in each quadrat. Mean numbers were then calculated and expressed as number of snails or crab burrows per m . Monthly mean snail-densities and fiddler crab burrow counte were subjected to t-tests, preceeded by F-tests, to determine if statistically i significant differences existed between thermally impacted and ; l control areas. No attempt has been made to monitor size classes. l l
' metabolism, or, to correlate the number of crab burrows per area j
! l l to the actual number of crabs inhabiting a unit area of marsh. ! II-10 o
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Microarthropod Populations 4;. Methods used to obtain marsh microarthropod population samples are given in Appendix E of this. report. i i e b i' i l 1 i l d I
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Measurements at Jacksonville Florida Two sampling trips were undertaken at the Jacksonville Electric Authority's Northside Generating Station near Jacksonville (see figure 2M ) during May 22, 23 and September 17, 18, 1973. May was representative of spring conditions and the sampling in. September clopely coincided with the end of the growing season. The sampling progran performed was similar to that cf Crystal River, but much abbreviated. Measurements of water temperature and salinity were taken o n ebb and flood tides in San Carlos creek which receives the thermal effluent, the St. Johns River which serves as a water source for the pcser plant, and in Brown's Creek which was utilized as a control area during both trips. l l Biological sampling was confined to the Spartina community and included the following measurements: live, dead, and total standing crop per m ; 2 numbers of live and dead stems per m ; stem lengths partitioned into 20 centimeter size classes; subjectively determined stem age classification; number of Littorina snails per m ;2and the number of fiddler crab burrows per a . Sampling was done utilizing 0.25m quadrats (identical to Crystal River) and all results were multipled by four to yield results on a m2 basis. A sample size of nine quadrats was selected to be consistent with concurrent studies at Crystal River. Sample sorting, measuring, and weighing procedures l were identical to those already described for Crystal River. l l Samples of Spartina taken in San Carlos Creek were confined,to a 0.5 , mile reach of the creek between the power plant discharge chutes and the l Hecksher Drive crossing; a second set of nine quadrats were harvested in an area extending upstream from the discharge chutes to the plant access l bridge. Temperature surveys revealed. Brown's Creek to be free of thermal
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+.., ._ x .: - .. . -.~ Figure 2M. Location of Jacksonville Electric Authority's Northside Generating Station with study areas identified.
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II-13
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6 6 .: .\i o
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effluents and it was chosen as the control area. During May nine quadrat samples were taken in an area ranging from the mouth of the creek to the middle reaches of the western fork of the creek. In September two sets of nine quadrats were harvested, one each in the western and eastern forks. 11-14
Juncus and Spartina Decomposition:-Studies
, .s.. .. .. . + . .
.~. . .,.. ..
.. .. ..2 ..- <
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Studies of decomposition rates of Juncus and Spartina in the thermally affected and control areas were initiated in February, 1973 and continued until September 5, 1973 (27 weeks) with one exception. Five sample bags in the Spartina control area were destroyed by wave action and the last remaining bags were sacrificed on July 1 after-only 18 weeks. At the beginning of the experiment fresh, live plant material of both species was gathered and allowed to air dry for one week. Sixty litter bags measuring 15 cm wide by 70 cm long were constructed of 1.0 mm mesh plastic window screening. The bags were sealed by double folding the edges and stapling at 5 en intervals to prevent leakage of plant materials via tidal action. Thirty bags were filled with approximately 50 grams of air dried whole Spartina plants each and thirty bags filled with approximately 20 grams of air dried whole scucus plants each. Material in each bag was individually weighed to the nearest 0.1 gram prior to filling. Six random locations for the placement of the bags of each 4 species were selected in thermally affected marsh and six in the
~
control area. Litter bags containing Spartina and Juncus materials were placed in typical habitats occupied by their particular species. Spartina has been observed to decompose while remaining in a vertical position on the marsh; leaf and some stem parts gradually decay until eventually only the shortened, bare stem remains. Finally, the stem weakens at the base of the marsh surface and falls over. The fate of dead Juncus leaves is less obvious. Apparently, after death the leaves remain vertical, frequently supported by the adjoining live 9 II-15
m vegetation. Decomposition continues while in this position probably long after the base of the leaf has weakened and no longer offers support. The upper portion of the leaf is the first to disappear; examination of Juncus culas of ten revealed decayed leaves of 5 to 10 cm length. To simulate natural conditions experienced during decomposition as closely as possible, wooden frames were constructed in the shape of a '*I" and driven into the substrate. The litter bags were suspended from the crosspiece, approximately 1 m above the mud surf ace, and the bottom of each bag was pinned to the ground with a metal stake. Therefore, the bags remained upright with only the bottom of the bag containing the base of the plant stems and/or leaves in direct contact with the substrate. One frame was placed at each of the 12 chosen locations, and 5 bags were suspended from each frame for a total of 15 bags of each species in the thermally affected marsh and 15 in the control areas. Prior to placing the bags in the field, four representative samples of air dried material of each species were dried to con-stant weight at 70 C in a drying oven to determine percent moisture of the initial samples. All samples gave results con-sistent within 5%. This information was used to calculate initial oven-dry weight of plant material in each of the 60 bags. Four bags of each species were randomly retrieved from each area at intervals of 6,10,18, and 27 weeks. The bags were carefully washed, dried to constant weight at 70 C and weighed. to the nearest 0.1 gram. Results were expressed as both ab-solute and percent dry weight remaining. Every bag retrieved was intact and there was no evidence of contamination by soil 1
-/ d II-16 w
4 . , - ..
. ._ s. . , .
organic matter. Nearly every bag, upon inspection, contained amphipods and fungi indicating that, despite the small mesh size, marco-decomposers were able to enter the bags. The mean fractions of material remaining in the thermally impacted and control litter bags from each harvesting period were subjected to t-tests in order to determine if decomposition rates were significantly different. Spartina Estimated Net production gaau;ina's annual growth pattern of minimum live aerial standing crop in the spring with accumulated live standing crop reaching a maximum in late summer allows the use of the harvest method to estimate net community production (Keefe,1972; Milner and Hughes,1970). Net community production is defined as the observed rate of storage of organic matter within the ecosystem. Estimates of net community production do not take into account losses of storage due to herbivores, decomposition , or export from the ecosystem. Net primary production represents total storage of organic material in the plant tissues after the demands of plant respiration are met. Variations of the'elip harvest method have been used by many investigators to estimate salt marsh productivity, but differences in the techniques have made generalizations about results and comparisons difficult. Net primary production (taking into account herbivory, decomposition, and export) was defined by the following relationship (see Appendix 2A) NPP = Q + H + (Q2 + R, + E ) The equation was evaluated by utilizing monthly increments of live and II-17
dead standing crop from the harvest samples (Q + Q 2
), herbivory (H, literature values for Spartina), and dead standing crops values and rates of decomposition from the litter bag studies (R, + E). Photosynthesis measurements performed with 002 gas analysis equipment, detailed in the next section, allowed comparisons of the methods of calculating net primary production to be made.
Juncus and Spartina Community Metabolism To document patterns of photosynthesis, respiration, gross production, and transpiration, ja situ diel gas exchange experiments were conducted with a portable C0g gas analyzer at Crystal River during March and July-August, 1973. Experiments were performed in Juncus and Spartina communities in both the thermally affected marsh and control area 3. Overall objectives of this phase were to compare diel production and consumption patterns of Juncus and Spartina marshes for evaluating their respective roles in the estuarine ecosystem complex and to determine the functional adaptations these communities may have made to the thermal additions. Infra-red gas analyzers (IRGA) work on the principle that the attenuation of a constant cource of infra-red radiation is proportional to the concentration of CO2 present in the transmission medium. Since 002 is a necessary input for photosynthesis and a by-product of respiration, the amount of 00 fixed during the light period and liberated during darkness and measured by the IRGA can be correlated to the movement of carbon, organic matter, and energy flow in the system of interest. Differential techniques were used during these experiments wherein the is IRGA reading
- proportional to the difference in CO e n entration of 2
two gases passed through the analyz,er. The IRGA readings were later II-18
. ~ . .- ..
.e .
converted to ppm CO 2 using a set of calibration curves and equations. During a 15 minute sampling period. 3 pairs of gases were passed sequentially through the IRGA which, when analyzed, allowed ambient air CO t be calculated along with the corresponding difference in CO 2 2 between inlet and exhaust parts of chambers enclosing a portion of the marsh community. Observed differences in CO2 across the chambers were expressed as photosyr. thesis or respiration in units of gC/m /hr. Experiments at Crystal River employed a Beckman 215B IRGA anc. ancillary equipment designed for previous field studies in South Florida (Carter, et al, 1974; Burns, 1973). All equipment was mounted aboard a motorized pontoon barge equipped with an enclosed deck house end was driven on the marsh at high tide and anchored. All sites selected were in a tidal environment and the barge was free to rise and fa' with the semi-diurnal tides. Electric power was supplied by a 4 KW diesel generator positioned 30-40 meters downwind from the study area in another boat. While in the field CO and relative humidity (RH) concentration 2 differentials were monitored between airstreams entering and exiting each of four large, transparent chambers (open systems) which fully enclosed the marsh canopy and were sealed at the mud surface (Figure 3M) . Timers and switches in the equipment circuitry allowed four chambers to be interegated during each hour of operation; all monitoring extended over a continuous 24 hour period. Diel measurements are preferable to short term (1-2 hour) readings because they monitor metabolism over the daily range of all environmental variables. Other variables which were recorded ce" currently with CO and RH were: volumetric flow rate through each chamber with a 2 Hastings hot wire anemometer, inlet and exhaust air temperatures with II-19
Strip Chart
. Recorder
- Ambient air Temperature supplied at Thermoc' ouples opproximately Ambient 4.0 m 3/ min Air Somple Exhoust Flowmeters Air Sompte 7 3 IR Gas j
~
p 1 Analyzer
; // \g,,
---E xh aust The ocouple l
-Inch Diometer .
I " 'j Pumps. l y Plastic Ducting
' I N # '[ $ Continuous 3 ;
Air Somptes j Thermocouple Polyoc el ot e.- __. 1 m { Le ds Chamber i 3I ## (Volume = 0.6 m3) O.92 rn h I l I f I-Blower { Enclosed -- -' , U Sportino l
/J .) -
i F ,
, ,- . . '. l
, -Chamber Enclosure Marsh - -
Sediment ' {i ] 4
'I Mud Seal '
< 0.92 m >
dia. * (b.) - Figure 3M. (a) Illustration of environnental chamber in place on the saltmarsh. (b) Schematic of environmental chamber and 002 and PJi monitoring equipnent.
'" thermocouples,- solar insolation at the top of the vegetation canopy with an Fppley pyranometer, and water level in each chamber during high tide. All information was recorded on continuously operating strip chart recorders except water level which was monitored and recorded by hand.
Since the techniques outlined above required enclosing aportion of the entire marsh community, results showed the integrated response of both the producing (CO2 fixing) and consuming (CO2 releasing) components of the ecosystem. Production included contributions of the higher plants, peri-phyton, and mud algae. Consumption or reapiration of the higher plants, algae, microbes, and animals living in or on the dead plants and mud surface constituted total system respiration. Some separate diel measure-ments of just the soil componeat of the system were also taken by placing chambers over sections of bare mud. Chamber enclosures varied in size and shape because of the different structural properties of Juncus and Spartina. Juncus was normally enclosed 2 within a cylinder approximately 1.5 meters tall which covered 0.22 m (0.53 m diameter) of the marsh surface. Spartina was either enclosed in an identical chamber as above or in a cylindrical chamber 1.0 meter in height which covered 0.66 m2 (0.91 m diameter) of the marsh surface. The chambers were constructed of k" steel rod to minimize shading and f were covered with 0.5 mm polyacetate. Despite the rigor of exposure to a tidal environment, the combination of rigid chambers and polyacetate maintained its structural integrity with few leaks and no major failures. The cover material chosen was examined with a spectroradiometer and found to act as a neutral filter II-21
I l to visible light (0.4-0.7 microns) suppressing incoming visible light by approximately 3-8 percent. Chambers were deployed in a radial pattern off the bow of the barge to avoid shading by the barge and adjacent chambers. Calculations of diurnal rates of photosyr. thesis, respiration, and transpiration were performed utilizing the formulae outlined by Odum (1970). Grams carbon fixed or liberated per hour per unit of structural property Gs of ground surface, m of leaf surface, or g of live biomass) were calculated from the equation given below. CO 2concentration changes measured as ppm by volume were converted to a weight basis by gas law relations: 2 " " X P X 1 RC g 1 mole g gC/m /hr = (Area or Weight)X T 760 mole 22.4 liters 60 min. I hr. 106 where Diff = difference in inlet and exhaust readings from strip chart expressed in scale divisions multiplied by chart division - ppm conversion factor Flow = chamber flow rate, liters / min. Area = ground area or leaf area, m ; or biomass, grams T = absolute temperature, K P = absolute pressure, mm Hg. This value was assumed constant at 760 mm Hg. The above calculation was carried out for each of 25 hourly data sets for each chamber and a curve of the rate of change of carbon was plotted for the 24 hour diel period. Net daytime photosynthesis was the integrated area under the rate of change curve above the zero rate of change line; night time respiration was the area under the rate of change curve below the zero rate of change line. Daily totals from each chamber were expressed as gC/m / day net daytime photosynthesis, night time respiration, or summed to represent gross primary production. 11-22 /
Transpiration calculations were performed by utilizing values of inlet and exhaust side relative humidity and temperature obtained hourly for each chamber from the strip charts and converting them to absolute humidity units, gH2 0/m . Transpiration or water loss in units of gH 0/m 2
/hr were obtained from the f611owing equation:
gH2 0/ area /hr = (Q, - Qg ) (Flow) '60 min. Im Area hr. 103 liters where Q = absol' ate humidity of exhaust, %/m Q g = absolute humidity of inlet, g/m Flow = chamber flow rate, liters / minute Area = ground area or leaf area, m ; or biomass, grams t As in the productivity calculations, hourly results were plotted against time and integrated to obtain the area above the zero rate of change line. This value was expressed as total water loss per day, gH 20/m / day. All of the n,cessary equations and integration routines for the above c'alculations were programmed in PL-1 language and performed on an IBM 360-75 digital computer. Strip chart values of CO e ncentration, RH, 2 temperature, solar insolation, air flow, pressure, and water level were punched onto computer cards and submitted for calculations. t e l I i 11-23 1
-- 7 ; ;L
-^
Aa=1on Computer Simulation of Marsh Response to Thermal Additions , A simplified model designed to contain the essential properties of the !
>4 larger marsh ecosystem diagram (Figure 1) was prepared for computer simulation.
The model's intent was to illucidate the general role of temperature on the f production and consumption patterns of the marsh. Similarity of the model results with observed field measurements would test whether or not all essential factors for the description of ecosystem behavior had been identified and included in the model. Most of the detailed compartments and pathways associated with plants, animals, organic matter, and nutrients in the. complex model were aggregated for simulation. The number of potential external forcing functions were reduced to further facilitate programming and rapid interpretation of trends. The simulation diagram in energy language symbols is given in Figure 4Ma. The simu-1 lation model contained the features of organic matter production by primary producers; seasonal transfer of living plant tissue to a dead status; loss of organic materials to in situ respiration, decomposition, and export; regeneratiou of nutrients through decomposition and general nutrient cycling; and the inter-action of temperature on both production and consumption processes. The list of ecosystem properties described above were translated into a pictorial representation of. energy and material transfers, storage locations, and process pathways with the use of energy language symbols. Detailed dis-cussions about the meaning and mathematical basis of each of the symbols may be found in Odum (1971), , ,
.n Energy mate' rial sources external to the marsh system were A
identified. Storages of energy and/or materials within the system, state variables, were listed and identified by storage symbols. Causal pathways of l energy and material flow between forcing functions and storage modules were connected with lines; where pathways intersected a functional dependence inter-
~
action between the"two flows was indicated. This in'terac't' ion may be of' many 11-24 c J
--,w, , ,- . . , . --,---,,.a- - - - - , . - , - , . - -
Os ## Exposi [cNJ -Je 50 '
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- cws 02 gan, 280. 50.
rat H. 2 5 *c DE^o - PART gg 50. So . HEAT 180.
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220. a3 J. Je 50. -b b OW ' A gg .jos / p%Ch Cowsuxc4
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. Grams /m' RESP RAT 468 L ae m im Ime.
(a) us sr cy,<. sr..iaw, cece, o, , k,0, NJ,- b,0.9 - h o, De4o SP4cTus4 574.a.w4 Cror,Og d.St. . k,0. - k,,0, H - k,0, dt . Avantasta. Peasvuoeus Os d_22. k 0,n + k,,0,H k303 H J, d+
-ku O, + Jr .
Swum, Jr Jr = J.- b, J,Q3H . g h l L i Figure 4M. (a) Energy diagram of marsh analog simulation model including initial conditions. (b) Differential equations written for each state variable of the model. II-25
- - m . _ _ _ _ _ _.
i l i forms : additive, subtractive, multiplicative, exponential, logarithmic, etc. All interactions for this model were assumed to be multiplicative. The completed symbol diagram also represents a net work of differential equations. An ordinary differential equation can be written for each state
; 1 variable by summing the inflowing and outflowing pathways of each storage !
l module (Figure 4Mb). Numerical values were placed on each pathway and storage module based on values available form field studies and literature. Values l were uses for parameters not measured directly during this study. Initial values chosen for all model components were representative of March conditions and flow values were expressed as monthly rates. The light and temperature ; regimes had March initial conditions but were programmed as sine waves to simulate seasonal variation of these parameters. Before analog simulation began, the set of differential equations re-quired magnitude scaling since the analog computer relates dependent variables of the system of equations to voltages within the computer. It is necessary to insure that potential output values do not exceed the maximum machine voltage. Numerical equation coefficients are normalized by dividing each by the maximum anticipated value of that term. The resulting scaled coefficients are trans-formed into potentiometric settings on the analog computer. From the system of di'ferential equations an analog computer patching diagram or program was prepared and patched onto an Applied Dynamics AD-30 j computer. i
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I l II-26 i l
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. ., . e . . . -
RESUL'TS Measurements of Marsh Structure and Function Evaluation of Marsh Ecosystem Diagram This section synthesizes the results of individual experiments which follow in subsequent sections. Figures 1R and 3R are quantified marsh ecosystem diagrams of the thermally impacted marsh for February (Winter) and August (Summer) seasons. Figures 2R and 4R are similar diagrams for the control marshes also representing Winter and Summer conditions. Compartments and pathways are labelled and numerical values are assigned to them based on data collected during the field sampling program. Tables 1R, 2R, 3R, and 4R accompany the thermally impacted and control marsh diagrams respectively and concisely document each value enumerated on the diagrams. Each quantity on the diagram is cross-referenced to che table to aid the reader in finding the parameter he wishes to examine. Physical Forcing Functions Figure SR illustrates the seasonal variation in solar insolation, air temperature and water temperature, at, or near, the latitude of Crystal River. The area receives annual insolation of 4500 KCal/m / day (450 geal/cm / day) and the mean annual air temperature regime (mean, 22*C; range,-17* to 28'C) is characteristic of a subtropical climate, Sunlight is most intense (5950 KCal/m / day) in the late spring; summer values are reduced by the cloud cover associated with thundershower activity in the late afternoons. During the sumer, the air temperature is consistently warm (mean, 27.5*C; range,16 to 36*C) . Winter air temperatures are variable (mean,17.5'C; range, -5 to 29'C), but rarely fall below freezing. II-27
are mus= menn I V - 1.0 m lm a lgy o a 1t.;O.7 e~- D,aIi - I T
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"Y .I @3 cpg G4 S4M475 5.0 0 d w I 03 s Pla.8/dav 3 23 O,., I3 34 % \\
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"iHbEHf" m es 15 3?7 44 m o.8 '
4% .DS In am Jia 7 0 # is 0.028 1 J2 i e % s
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4.b ty & (_ OW. G ; 3= sod $raiau'n s.o Figure IR. Evaluated energy diagram for the thermally impacted salt marsh, summer conditions.
. Table I R A - Salt Marsh Ecosystem Forcing Functions (Summer Values) Thermally. Impacted Marsh Diagram ~
N3tation Value Description of Calculation Reference Ig 1.0 m H3 0/ Water level variation. Ms is a daily man variation basd on man tidal range at the Withlacoochee River entrance and modified by personal
'n2/ day field observations. Semi-diurnal tides exist at Crystal River with a range of 0.77m (2.5 feet). Field observations indicate 0.5m to be a realistic depth of water on the marsh at high tide. Depth of water on '
the marsh at high tide. Daily variation = 0.5m/high tide /m 2x 2 high tides / day
= 1.0m H20/m2marsh surface / day 1 5.0 grams Concentration of organic matter in nearshore waters which cover the marsh Gibson, this *Po't.
2 O organic matter / at high tide:; 69mip e k hc., Jim., and Gib. vot e . 4
-e m3 I 0.03g P/m 3 Total phosph'orus concentration in near shore waters which cover the Henry McKellar, personal marsh at high tide
- oway c.4 TcC J"". "I G*b- V dM% communication f 1 30*C Temperature in nearshore waters which cover the marsh at high tide Carder 1971-72; Young 1973 4
1 VC Average temperatun adMtion by Crystal River Power Mant Wnits 1 Carder, M 72 poung B73 5 and 2) to nearshore waters which cover the marsh at high tide Not available Freshwater input to marsh derived from terrestial sources I6 I Not available Organic matter concentration within freshwater inputs to marsh 7 1 Not available Phosphorus concentration within freshwater inputs to marsh 8 1 9 Not available Heat concentration within freshwater inputs to marsh Note about freshwater sources: The principal sources of freshwater inputs to the marshes in the vicinity of the Crystal River power plant are the Crystal and Withlacoochee Rivers. However inputs quoted from nearshore ocean water include these river values. Because there are so few f reshwater creeks draining terrestial ecosystems, local rainfall is probably the major contributor of freshwater to the marshes. This input is very small when compared . to tidal flushing and little error is introduced into the model by ignoring these inputs at this time.
,. Tr.ble IRb. Ssit Karah Ecocyaten Storages (Sumn:r Valurs) 1harmally IrpIcted March Diagram Notation .Value' Description of Calculation Referenc'e c
Qi N.A., m 3 Water in the marsh. This value presently unknown, but portions of the ' marsh have been surveyed & volume. estimates will be calculated shortly. Q- 2
.03 g/m3 Total phosphorus concentration in marsh water column. Based on seasonal W. Smith, personal measurements at Crystal River. Identical to nearshore waters. communication Young, 1973
. Q3 4.0 g organic organic matter concentration in marsh water column. Assumed concentration See I 2 matter /m3 same as nearshore waters.
Q4 34*C Average water temperature in marsh water column. Values obtained from direct Carder, 1971 w field measruements. Observed values range from 31*C to 37'C. Carder, 1972. [ o Young,1973.
'540.g dry wt/m 2 Juncus roemarianus live plantitanding crop; values obtained from field QS measurements at Crystal River. See fig.94 of salt marsh field data.
2 Q6 -1.0 m Area of marsh covered by Juncus. Since this diagram is a unit model representing behavior of Im2 of surface, area is set to 1.0 m2, } p f Q7 580.g dry wt/m"- Spartina alterniflora live plant standing crop. values obtained from field measurements at Crystal River. See Fig.8Aof salt marsh field data.
.Q8 1.0 m2 Area of marsh covered by Spartina. Same explanation as Q6 ' '
Q9 37.g dry wt/m 2 Epiphytic & Benthic Algae live standing crop. Values were obtained by utiliz- Day, et al, 1973 ing algae biomass data /r. tem length from Day, et al and using stem number /m2 from Crystal River 3 C3. DR-g algae /m2 = 0.05 g/10cm X 40 cm X 185. sten = 37.0 g/m2 stem ml !- Q 10 650. g dry wt/m2 Detritus or dead plant standing crop. Values were obtained from field measure- , ments at Crystal River. Both Spartina and Juncus are shotm to contribute to the Detritus pool, and the value calculated for the diagram assumes an equal fraction
Table JRbco~ntinued Dicgram Notation Value Description of Calculation Reference of both plants. Detritus, g/m2 = 461. + 850 - 650 g/m2 2 Juncus = 850 g/m2 , G) . 9R. Spartina = 450 g/m2 , p,9, g g, 4
-Q g 3.0 X 10 g ,
organic matter / Organic matter in sediments. Values were obtained from field measurements Coultas, 1969.
-. m2 at Crystal River and by consulting literature values by Coultas. The . 1971.
I figure quoted in the diagram represents an average concentration to a M depth of 0.5 meters. , g/m2 = g X 0.5 m = 6.0 X 104 g/m3 X 0.5 m = 3.0 X 104g 0.M./m2 m3 Q12 5.0 g Phosphorus / m2 Total phosphorus in sediments. Phosphorus soil samples have been taken Pomeroy, et al.i1967 at Crystal River but not completely analyzed. For this diagram a value is used which represents marshes in Georgia. k' hen data from Crystal River becomes available, they will be used. Q13 0.1 g/m 2 Insect standing crop. Insect samphs have been taken at Crystal River McMahan, et al. 1971, to obtain estimates of biomass and species diversity. Until samples are processed, a value of 0.1 g/m2 of insect biomass will be used which has been found in North Carolina marshes. See Table 11 for preliminary results of summer sampics. Q14 0.8 g dry ut/m2 Biomass of marsh creek residents. Data on biomass of creek fishes obtained FPC Environmental by Adams, et al at Crystal River. Report to Interagency 20 September, Discharge: 11412 g wet ut preserved Assune preserved wet wt = 85% wet ut r-w_.--- - . - - _ - -
Tablo lRb continued Diagram Notation Value Description of Calculations Reference
.'. Total wet wt = 13400 grams Assume dry wt = 20% wet wt
. . Total dry wt = 0.20 (13400.g) = 2680. g dry wt Interpretation of aerial photos geveah the watershed of the discharge creek to be approximately 3500 m~.
g dry wt fish /m2 - 2680 g = 0.77 g/m 2 3500 mZ NOTE: Blue crabs were found to be abundant in the summer, but no estimates M of size or biomass were made. Thus, no figures for blue crabs are d, given at this time. Ho. 3 Q15
/Ja . g/m2 Biomass of detritivores. Detritivores during this study refer to marsh snails, Teal, 1962.
polychaetes, and crabs. Snails numbers and counts of number cf fiddler crab Day, et al, 1973 burrows were recorded periodically. These allow approximate biomass values to be calcu'_ated. T7dk.7R. , Crabs: 344 burrows /m2. Field data, 7/29/737 Assume 5 burrows = 1 crab N w v, F es c *'<d
.'.344/5 = 69 crabs /m2. 34 cme, g i.e3 wiloe c4 L5.n gim t m,,,,,e,3;w4een Snails: average of I snail /m2. Assume snail weighs 0.2 g org
..g/m2 = 1 0.2 = 0.2 g/n2 Polychaetes: Use literature values (Day, et al & Teal) g/m2 = 1.0 g org/m2 TOTAL: = jf.I + 0.2 + 1.0 = % .3 g/m2 f<
Q16 0.05 g/m2 Resident and migrant bird biomass. No measurements attenpted. Literature values Day, et al, 1973 (Day et al) used. 2.1 g/m2 Estuarine fish biomass. Data supplied by Snedaker representing inner bay drop Q17 FPC Environmental net values for summer were employed. Report to Inter-agency Committee, g/m2 = 2.1 g dry wt/m 2 Oct. 1973. d
Table IRC Salt Marsh Ecosystem Pathways (Summer Values) Thermally Impacted Area. Disgram . Notation Value Description of Calculations Reference Jy 4*C Average temperature addition from units 1 and 2 at Crystal River See reference for I 4 J2 5300 KCa/m / day Average solar insolation at Crystal River. -Sct3 2 f. R-b J3 18.6g or Spartina community gross production or total metabolism. Summer field matter /mganic
/ day measurements taken with gas metabolism gear. See Table 14Ain Salt Marsh Field Data. This value corresponds to solar insolation of approximately 5300 kcal/m2/ day. Value = 9.3 gC/m2/ day = 18.6 organic matter /m2/ day.
s J Spartina community respiration; results from summer field measurements taken 7 4 4.0gorganic matter /m / day with gas metabolism gear. (Tablel4=). This value corresponds to solar d insolation of approximatcly 5300 kcal/m /2 day. Value = 2.0 gC/m 2/ day = 4.0 g organic matter /m 2/ day. J 12.6 g organic Juncus community gross production or total metabolism Results from summer S matter /m2/ day field measurements taken with gas metabolism gear (Tabic /JO.2This value corresponds to solar insolation of approximate 1 5300 kcal/m / day. Value = 6.3 gC/m2 / day = 12.6 g organic matter /m / day. J 4.6 g or Juncus community respiration. Results from summer field measurements taken 6 matter /mganic
/ day with gas metabolism gear (Table G@, This value corresponds to solar insolation of approximately 5300 kcal/m2/ day. Value = 2.4 gC/m2 / day = 4.8 g organic matter /m2/ day.
J 0.6 g 0.M./m 2/ Loss of higher plant standing crop to insect herbivory. Literature values quoted smalley,$1960. 7 day indiate this loss to be from 2-8% of net production. Qualitative and quantita- Teal, 1962. tive observations of insect grazing at Crystal River confirm these values Spartina net production = gross - respiration = 18.6 - 4.0 = 14.6 go.M./m2/ day Ascume herbivory = 5% Loss to herbivory = 14.6 X .05 = 0.73 g 0.tt./m2/ day Juncus Net Production = Gross - respitation = 14.6 - 4.6 = 10.0 g 0.M./m /2 day Assume herbivory = 5% Loss to herbivory = 10 X .05 = 0.50 g 0.M./m /2 day
C
.' Tcblo IRC continurd ,
V Dirgram k Notation.'Value Description of Calculation Reference For the diagram value average the two rates assuming equal areas of Spartina and JUncus: 0.73 + 0.5 = 0.6 g/m / day2 2 J 8 4.5 g/m 2/ day Transfer of' live Spartina standing crop to Detritus. As outlined in an Young, 1973. earlier publication (Young,1973) the amount of live Spartina transferred to the dead is calculated by adding the observed increase of dead material over an interval in time to the estimated amount of dead material lost through decomposition and export during the same time interval. Measurements at Crystal River revealed an increase of 80.4 g dry wt/m2 between June 3 and Sept. H 3 (92 days). During the same period there was an estimated loss of dead h material due. to in situ decomposition and export of 536.0 grams dry wt/m2, This was calculated by multiplying the dead standing crop from Fig.dA by . the decomposition rate obtained from litter bag studies %/ day, by the
, number of. days of interest (92) . See Table 10 in field data sununary for
- decomposition rates.
Therefore transfer of live to dead in 92 days = 80.4 gas /m2 + 331.3 g/m2
= All.7 ges/m2 /92 days ,.
= 4.5 gram /m2 fa,y p J
9 5.75 g/m 2/ day Transfer of live Juncus standing crop to Detritus. Although Juncus standing crops have temporal patterns different from Spartina, the procedure used for J8 can be employed for Juncus as a first approximation. From Fig. the estimated increase in standing dead from June 1 to August 9' !! is 290 g/m . Loss of dead material due to decomposition was found to be 112.7 g/m2. The time interval is 70 days. Therefore transfer of live to dead in 70 days = 290 + 112.7 = 402.7/70 days
= 5.75 g/m2/ day J 10 0.06 g organic Transfer of Detritus to sediments. Two references gave age of Florida Culf Coultas, 1969.
matter /m2/ day Coast marsh peats as 3000 years. Depths were also given which yielded a Kurz and Wagner, 1957. l sedimentation rate of .0004 meter /yr. Discussion of Q11 revealed 6 X 104
- g/m3 of organic matter in the soil. Annual deposition =
i 6X10+4 g/m3 x 4X10-4 m/yr
= 24 g/m2 /yr = 0.06 g/m2/ day. '
l > l l l l
A Table IRCcontinued 4 Dicgram ' ) Notation Value Description of Calculation Reference J 11 1.160 g/m2 / day Export of Spartina Detritus to water column. Calculations for Jg showed a loss of dead material due to in situ decomposition and export of 338 gms/ m2 /92 days which is 3.fo 3/m2/ day. Assume 50% export: Export = 1.3 0 g/m 2/ fay. J 12 0.8 g/m 2/ day Export of Juncus Detritus to water column. Calculations for J9 showed a loss of dead material due to decomposition and export of 112.7 grams /m2/70 days which is 1.6 g/m /2 day. Assume export is 50% of total loss. Export = 0.8 gAn2/ day . J .028 gP/m2/ day Phosphorus uptake from sediments b Keefe and Boynton, 1973, 13 concentration of Spartina as 0.15%y of Spartir.a. dry wt.Reference gives phosphorus Assume nutrient uptake is 0.15% of daily total metabolism: grams P/m / day = .0015(18.6 g/m2/ day)=
.028 g/m2/ day.
J y4 .023 gP/m2/ day Phosphorus uptake from sediments by Juncus. Assume Juncus is also 0.15% Keefe and Boynton, 1973 Phosphorus by wt and repeat calculation of Jy3: 0 grams P/m2/ day = .0015(14.6 g/m2/ day)= 0 .023 g/m2/ day. . w
't
=
mua mtume rt; p 1 N*Y . A la Q3 G2 04 w p 5.sOHWb 9@ ';p dant
,K
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' GM, l.43 99 wa g 3 " O.93 [ s S
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=
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dI ( r[ sg [ 3n m4 5.o Figure 2R. Evaluated energy diagram for the control marsh, summer conditions.
i i 224 Table ~ . Salt Marsh Ecosystem Forcing Functions (Summer Values) Control Marshes. Dirgram Not tion Value . Description of Calculation Reference
- I 1.0 m H20/m2/ day Same as Thermal Marsh Calculations 1
2 5.0 g 0.M./m3 Same as Thermal Marsh Calculations l I3 0.03 gP/m Same as Thermal Marsh Calculations I4 30*C Same as Thermal Marsh calculations I S 0*C Average temperature addition by Crystal River Power Plant (units 1 and2) Carder, 1972. to neashore waters which cover the marsh at high tide. Carder, 1971. - 16 N.A. Same as Thermal Marsh Calculations "1 7 N.A. Same as Thermal Marsh Calculations 1 8 N.A. Same as Thermal Marsh Calculations
.I N.A. Same as Thermal Marsh Calculations 9
e, n
~. Table 28. Salt Marsh Ecosystem Storages (Sununer Values) Control Marshes. Diagram Notation Value Description of Calculation Reference Qi N.A. Same as Thermal Marsh Calculations Q2 0.03 gP/m3 Same as Thermal Marsh Calculations Q3 , 4.0 go.M./m3 Same as Thermal Marsh Calculations 30*C Q4 Average water temperature in marsh water column. Values range from 28 . Carder, 1972. 32*C.
. Carder, 1971.
Young 1973. Q 5.40. g/m2 S Values of Juncus live standing crop are temporarily assumed to equal Thermal Marsh values. Q6 1.0 m2 Same as Thermal Marsh Calculdons MQ 7 580. g/m2 Spartina live standing crop. Values obtained from field measurements at
& Crystal River, Fig.6 R of summer data sununary, m
Q 1.0 m Same as Thermal Marsh Calculation 8, Q9 36. g/m 2 Epiphytic and Benthic algae live standing crop. Values were obtained by Day et al,'1973. utilizing algae biomass data per stem length from Day, et al and stemsAu2 from Crystal River. g algae /m2 = 0.05 g/10 cm X 40 cm X 182. stems /m2 stem
= 36. g/m 2 Q 536. g/m2 Detritus or dead plant standing crop. Values for Spartina were obtained 10 from field measurements at Crystal P.iver. Juncus values are assumed equal to Thermal Marsh values. Only one detritus storage is shown in the diagram and the value associated with it assumes an equal fraction of both plants present.
Spartina: 2 gg
, Juncus: 222. g/m 850. g/m2 ,F.7,,) 9R Detritus, g/m2 = 222 + 850 = 536 ,g/m 2
t
L' , Table 2K% continued Dirgrim Notation Value Description of Calculation Reference Q 11 3.0 X 104 g Same as Thermal Marsh Calculations 0.M./m2 Q12 5.0 g 0 M./m2 Same as Thermal Marsh Calculations Q 13 0.1 g/m2 Same as Thermal Marsh Calculations Q14 1.43 g dry wt An2 Biomass of Marsh Creek residents. Data for control creeks obtained by Adams, et al, 27 September, control:21261. g wet wt preserved , Total wet wt = 21261. X 1 = 25013. grams
.85 -
L e Totaldrywt=0.20X25013 grams-5003. grams Area o f control creek approximately 3500 m . g dry vt fish /m = 5003. = 1.43 g dry wt/m2 Q15 II E 8/m 2 Biomass of Detritivores. These calculations make the same assumptions as those Norner*3 P N (d for the Thermal marsh. Snails & polychaetes are assumed to have identical bio- ComnwnKtdoon mass as Thermal Marsh. Crabs: 227. burrows /m2 Field data, 8/7/73. g/m2 = 227. burrows /m2 X 1 crab X 0.25 1 5 burrows crab
= 10.5 grams /m 2
. Total biomass = 10. 5 + 0.2 g/m2
+ 1.0 g/m2
= lt .7 g/m2 Q16 0.05 g/m2 Same as Thermal Marsh Calculations Q7 i 2.6 g/m2 Estuarine Fish Biomass. Data provided by Snedaker which represented inner FPC Environmental bay drop net; summer values were used. Report to Interagency 2
g/m = 2.6 g dry wt/m
.i
-- _ - _ - _ - _ - - .~ - _ . ..-
4 i Table 2EC. Salt Marsh Ecosystem Pathways (Summer Values) Control Marshes. e Diagram Notation Value- _ Description of Calculations Reference 2 Ji 0*C Average temperature addition from Crystal River units 1 and 2. J 5300 kcal/ 2/ day Same as Thermal Marsh Calculations 2 J 3 18.0 g 0.M./m2 / Spartina community taal metabolism. These are results of summer field day measurements with gas metabolism gear (Table 64Aof summer data summary). This value corresoonds to2 solar insolation of approximately 5500 kcal/ m2/ day. Value: 9.0 gC/m / day = 18.0 g 0.M./m 2/ day
.J4 3.0 g 0.M./m2/ Soartina community respiration. This is also obtained from summer field day measurements with gas metabolism gear-(Table M4of summer data summary).
p The value corresponds to solar insolation of approximately 5300 kcal/m2/ day. L Value: 1.5 gC/m2/ day = 3.0 go.M./m2/ day. o J 3 6.0 g 0.M./m2/ Juncus community total metabolism. Values obtained in the summer with day gas metabolism' apparatus (Table 138. Metabolism corresponds to approximate ' solar fasolation of 5300. kcal/m /2day. Value: 8.0 gC/m2/ day = 16.0 go.M./m2/ day J6 6.0 go.M./m 2/. Juncus Community Respiration. Values obtained in the summer with gas day metabolism apparatus (Table 13S. Metabolism corresponds to approximate solar insolation of 5300. kcal/m2/ day. Value: 3.0 gC/m2/ day = 6.0 go.M./m 2/ day J7 - 0.63 go.M./m 2/ Loss of higher plant standing crop to insect herbivory. Same assumptions ^ day and calculations apply here as in the Thermal Marsh except estimates of primary production. Spartina: Net production = 18.-3.=15 go.M./m 2/ day Loss to Insects =.0.05 X 15 = 0.75 g/m2/ day Juncus: Net production = 16.-6. = 10 go.M./m2 day ' Loss to Insects = 0.05 X 10 = 0.5 g/m / day For the diagram value average the two rates assuming equal areas df Spartina - and Juncus: 0.75 + 0.5 = 0.63 g/m2/ day 2 1 I . t I
f' . Table 2RCcontinued + Dirgram Notition Value Description of Calculation Reference u 2.40 g/m2/ day J-. 8 Transfer of live Spartina standing crop to detritus. Same assumption and ..' calculatic,ns apply here as in the Thermal Marsh except estimates of , change in standing crop and decomposition. Measurements at Crystal River j-reveal no change in the level of standing crop during summer (Fig. 9 in data summary) . During the summer between June 3-Sept. 3 an estimated 171 grams of dead material were lost to decomposition and export (See Table 10 for estimates of decomposition rates). 't g Therefore, total transfer from live to dead in 92 days = - 55 + lu,. = g/m2 /92 days ,
= 2.40 g/m 2/ day e-.
[J e 9 5.54 g/m2/ day Transfer of live juncus standing crop to Detritus. This calculation is identical to the previous calculation in the Thermal Marsh except decom-position rates are slightly less (Table %). Temporal standing crops are for now assumed equal to Thermal Marsh values. Increase in standing dead - 290 g/m2/70 days ' Loss of dead material througt; decompw;1 tion and export = 97. g/m 2/70 days Total: 290 + 97. - 387. g/m'/70 days = 5.54 g/m /2 day J 0.06 g/m 2/ day Same as Thermal Marsh Calculatbus l J yy 0.93 g/m 2/ day Export of Spartina detritus to water column. Calculations for Jn showed a total loss of dead material through export and decomposition to'be 171. g/m2/92 days = 1.86 g/m2/ day. Assume export = 50% of loss. Export = 0.93 g/n2/ lay - J 0.69 g/m 2/ day Export of Juncus detritus to water column. Calculations for J9 showed a total loss of dead material through export and decomposition to be 97 g/m / 2 70 days = 1,39 g/m2/ day. Assume export = 50% of lons: export = 0.69 g/m2/ day J 13 0.027 gP/m2/ day Phosphorus uptake from sediments by Spartina. Same assumptions as calculations performed in Thermal Marsh, except une control area's gross production (J 3 gP/m2 / day = .0015(18.0 g/m2 / day) = .027 gP/m 2/ day ,
+
Table 2RC continued .] Diagram-Notation Value Description of Calculation Reference
'J ' 2 14 O.024 gP/m / day Phosphorus uptake from sediments by Juncus. Same assumptions as calculations in Thermal Marsh except substitute Control Area gross production (J5 ):
gP/m2 / day = .0015(16.0 g/m2/ day) = .024 gP/m2/ day 9 9.* a b' 8 6 l e (
\
1 . l TERBtSTAL gyg ggucg OCEE) INFLt'EM E OA MlunLldey 0* Vl l
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( , 5 5 "E"" 3vso4 5.0 <. Figure 3R. Evaluated energy diagram for the thermally impacted ' marsh, winter conditions. NOTE' Calculations for terms shown in this figure follow the methods indicated in Tables IRA and 2RA. For details write Mr. Don Young Dept. of Administration, Division of State Planning, Tallahassee, Florida 32304. f-
Tratts7tAL ~ octa m umac
\ D.4m/r,,a jg,, = \
03 A2 QA a x. n,., apr rgm "L' .03 H,4 T 38 e-hdx gg ] sj e g , X
' ' x7 k \/ t X *'
i wrv
' O
- 0
- % 0.55 -
i
~
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p
) e O. 7 , Qn .
gg ' I h SFART 3 : 1= V KGI/n ldey a Z4
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)
#1 TtR9tSTIAL
/,
x a Io t y two e_ +- 0. , Qf y' / y si w m cus y 4/ u J ( h A . 0 U. d' 3g. 4 stoimats 5.0 Figure 4R. Evaluated energy diagram for the control marsh, winter conditions. ' NOTE For details Calculations write Mr. Don forYoung, terms shown in this figure follow the methods indof Administration, Division of State Plannkng,in Table Dept.
, , . r, ,
. , , ,, ir .
- ?. . - ' - - * * '
40
. U J 30 _
a g 20 _ 6 e 10 - m E O -
-10 , . . t ' ' ' ' ' ' ' '
f F M A M J J A S O N D (a) 700 - N 50 b
;400 ec s
- 300 & Y s
5 e 200 - E e 100 - 5 g , , , , , , e i i , i i J r M A M J J A S O N D (b) Fig. SR. (a) Monthly air temperature at Tampa, "lorida. U.S. Department of commerce. 1961-1971. (b) Solar insolation (direct and diffuse) re-ceived monthly at Tampa, Florida. Vertical lines represent the range and bars i 1 SE around the mean of 11 years of data (1961-1971). U.S. Department of commerce. 1961-1971. II-45 s
! j ' 8 u , !-l l i !
- c.- -
o g .6l g ;- - . -
. 40 - - - -
-i-u..y
, .' ~
e 30 l%N i (- V
% g-
. 1
% l i
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- s 0 t - . i. ' ]i. * .*. '
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...... l
~
J F M A M J J A S O N D Key: Control Areas:
. Buoy K at Crystal River control area
. Temperature at Cedar Key. McNulty, et.:;1.1972.
Discharge Area: Buoy E at mouth of discharge canal 1971 1972 l X X 1973 C O 1974 ) Fig, SR (c) Seasonal water temperatures at Crystal River in the vicinity of the tidal marshes. II-46 s
,1.- . . . . .
. . .;.,y.-
-.c ~ .,
Figure SReis a comparison of water temperatures in the thermally impacted and nearby control areas at Crystal River. Ambient water temperatures normally vary between 15 and 30*C, but temperatures in extremely shallow waters typical of the marsh habitat were observed to reach 32*C in the summer. Temperatures in the thermally impacted marsh are consistently 4 to 6*C warmer than ambient waters. This difference is at a maximum during the sunner because of high electrical demand and resultant heat trans-fer to power plant cooling waters. The highest water temperatures observed on the thermal marsh range between 37 and 38'C in tae summer. Aspects of surf ace hydrology, as they relate to the marsh, are summarized in Figuret6R and 7R. Annual rainfall is approximately 51 inches (1295 cm), 60% of which occurs during the months of June to September. The seasonal pattern is evident in the high autumn discharge characteristics of the Withlacoochee River North of the power plant site, Figure 6Rb. Discharge of the spring-fed Crystal River is highest in the Winter and Spring probably reflecting a lag in the response to seasonal rainfall. Combined annual average 3 discharge from both rivers is small (2150 cfs, 61.0 m /sec) and the import of terrestially derived materials and nutrients to the marshes near Crystal River is probably small compared to tidal flushing. Annual water surfaca elevation (relative to 2ETQ. changes at Crystal River are shown in Figure 7R. Mean water surface levels vary approximately 1 foot (0.3 m) with highest levels in summer II-47 1
c a a .mn:2m a: m .1 2::ua uu=_m ma
.m ?!H rn: 1m
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., u .'[.,*un ._ w t.. I : t .
.m .,.. .m
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= M HHii #ii M MiinEE iuLs# Mi M EMMsuils R ldi M Un !Hi nu Ei o
- a. '.iii g
g; g;; ;;p.;m g. .it gn..- .m a,tf:g tE! !E. Erd...
- g. .pg r:p m.. y jjg !.H
!!h. ;. f g...g. . y .
. 1500 = an a3.j .. m; ; em a n:r un + :m; ru e !r..;:: n:j r!
4 dE ntr a t. .: :tt. .ii! . ::t :t. ntl +++t *** nn :t: m! :t. du :::1 :mem m = :n:i::-:li :th nt. d: i::w:d.; n.3 .
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. 11is. . !!i! Ui ..I. iH. .IM. "IN'I"*$iid.i
.4 m: p:r:;,;: ut: :m ~~ --
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++- =jj ..gI:: nu :.itn.
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.... ru; n{:. ut; :m d"tt m: := . .n -ttrm: : .. . n.
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~
1000 r. scc. an
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4g
- m ::tr ar nt;:!n. . :n nn E"f:t= :+n :r a.: :.9. .:!n m: .
anm .:.g;-gp; t
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8 m :H: : , . ). :;,# . . , , ri; r: : . t. u;t :: ::l"'tM. :tn : a. :a: m:m t nr! :t ::=:tt
- m . . .: :.n i t: c:: ::: p. - -
- e :lt u ui :. -
S nn :m :m au l em! rp :1p :/ ttu ,;#ar, d: !! n.m@""r ut :d"! :ttr ut: rut u:
- r.:. t:
. l: r.a['. : q. ::n ::= att un :
;g: n t nlj fu gri: 7:n p & n i: jjn
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- t r: D i
e 00 a it i m: 4: r
. :.r':.t. :tt; J v:m :E--
- n
~ni: t:
/e/ . g;, ak. ,_d:-g
. .n _s:r.p.; .:;;, Mn .~.
* *j :""p g3(". C 5 # m
- g+j;y#1" "=" g4g"MW::#{- y"C
$t u C :U:
,a 500 un#p :u m.; f
~
pm.:.f.'t: 2"mr ac- Cn pu
'T"i'f*pf'- y".E" "' "'in[jnii
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$ # iHi iii M MME iiE MddfrTigM MD !!U M E
O J F M A M J J A S O N D r Key: O Withlacoochee River: Average flow, 1264 cfs. 1 l
@ Crystal River: Average flow, 883. efs
. au s
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t
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88 a:: .:n?": m: :m 2: tun mrn;*g Anncal rainfall = 51. inche* - - * - * - * + --- * 'mm) -- * .*i -i!!' ' **~is* - -- -- ' -- 's - - (' 12' 9 5'. gg ::n *:: t =**,jgu,j::nt:I*1
=mm m:mt nt & m :m r.n w+ au =
- f:: ::!* O!! .. M* 1*a r *! *. ::::rn M un
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.7 .'!t7 .n*
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s .a n 1]!} .. , . 1.., .
,; ,U,:, . . . .I.m ., g ::{.' 12.t;mtu 3:1 .;n ::u ;.4M :::: :Ut 1:*.
n: :tt = m: uu= 00 m ;n " . . - --++- -L *;*: L:: '- IR;
- -::= .+.-. -
- 1;;"'
.e c ;m... nt' ::a nr un = nu :m /P m :n C**dm*+". :
u,n " un 6: k- m..+.ra:::Hi-n. +.n .-: :
- . . . + .
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+.
c5 EM HJMsWsmi :4 FH Mis itsEEM ini M !#iEr R:s == HE-#H 43 n sus M Efi M*iu MMim einis:EM =!! a Mi M iEh sa '" J J F M A M J J A S O N D Time, Months Fig. 6R: Surface hydrology characteristics in the vicinity of Crystal River, Florida. McNulty
.et_. _al . 1972.
, 4 4 % D-II-48
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2 .. .. . . . J F M A M J J A S 0 N D Time, Months Fig. 7R. Predicted water surface elevation relative to Mean Low Water at Crystal River, Florida during 1972 and 1973. NOAA, 1972, 1973. .,'
and early fall and lowest levels in the Winter. Changes in mean water surface levels and tidal range in the vicinity of Crystal Rivcr and Cedar Key, Florida, are the highest along the Gulf of Mexico coast but are small when compared to the Atlantic Coast. Juncus and Spartina Standing Crop Characteristics Figure 8R is a comparison of Spartina live, dead, and total standing crops biomass in the thermally impacted and control marsh from June, 1972 through October, 1973. Monthly trends of live standing crop, Figure 8Ra, were similar to those found by other researchers in southeastern US marshes (Morgan, 1961; Marshall, 1970; and Day, et al., 1973). Growth from February through August followed a sigmoid curve with maximum live standing crop . attained at the end of August, the minimum present in Febr2ary, and maximum monthly changes in May and June. Data from 1972 and J 1973 showed that the same live standing crop (550 to 580 grams dry weight per m ) was present at the end of the growing season in the thermally impacted marsh. This result may be misleading because of a change in the method of determining live standing crop. Before October, 1972, live plant biomass included dead leaves still attached to live plants; af ter thia date all dead i material was removed from live plants and categorized as dead material. Thus, the August, 1972 estimate of live standing crop was over- ; l estimated because of the inclusion of an unknown amount of dead material. A comparison of 1973 live standing crops in Figure 8Ra suggested that growth was initiated earlier in the heated marsh and remained ahead 4 II-50
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_. 4 .. . . . - ,g g_ .g 0 - J J A S O N D J F M A 'M J J A S O i Fig. 8R. Annual Spartina alterniflora standing crop characteristics during 1972,73 at crystal River including a comparison of thermally l affected and control areas. Vertical lines represent the range and bars i S .E. around the mean of nine samples. Asteriaks denote months where t-tests revealed a statistically significant difference (957, confidence level) in standing crops between thermally affected and control marshes. 11-51
' of the' control until the end of July. Although mean live standing ;
l I crop in the thermal marsh appeared to be consistently higher t throughout the growing season, non-paired t-tests confirmed signi-i ficant differences at the 95% confidence level only in late March and early August. The mean live biomass of the thermally impacted marsh exceeded the controls in March possibly as a result of the heated effluents. In early August, the values for mean live 1 i biomass of the controls were statistically greater than that of the I thermally impacted marsh. However, this difference was probably ' an artifact of the sample processing. The August thermal marsh biomass samples were kept in a deep freeze for approximately 5 to 6 weeks before they were sorted and weighed. Sublimation of organic matter may have occurred during this period. Qualitative observations in > the thermal marsh during August did not suggest any loss of standing crop as indicated by the estimated means. Furthermore, standing I crop values obtained from CO2gas metabolism chamber harvests taken during the same period yielded approximately the same mean weights 1 in both marshes. These results will be further discussed in a sub-sequent section, " Juncus and Spartina Community Metabolism." Comparative I data for the Fall season were lacking in both years, but biomass levels and the slope of the biomass curves in December,1972, January, 1973 and October,1973 suggest a more rapid transition of live material to the dead category in the control marshes than in the thermally affected marsh. Several striking contrasts existed in the dead standing crop curve, Figure 8Rb. A continuous increase in dead material occurred throughout-the study in the thermal marsh, Large, statistically T ;significant differences in dead standing crop were apparent.between-the samner of 1972 and 1973. The 1972 summer estimates were low II-52 e .-. . - ,-- . _ , _ _ _ _ _ _- - - - . _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _
because of the change in processing methods discussed previously. Also hurricane Alma passed near Crystal River in June,1972 causing 1.5 to 2.0 m storm tides which may have washed large quantities of dead material out of the marshes, or concentrated it in raf ts in the marsh. This effect was not quantified during this study. Non-paired T-tests between dead standing crop monthly means of the thermally affected and control areas during 1973 were statistically significant in each month except April. Control marsh means were nearly constant throughout the year, oscillating around a value of 250 grams /m . Thermal marsh means exhibited a general increase throughout 1973 reaching almost 500 grams /m in October. Figure 8Rc illustrates the combined seasonal behavior of the live and dead standing crops. Summer peaks of total standing crop were also quite different for 1972 and 1973. Differances in the thermal and control marshes were also apparent. Mean total standing crops were shown with T-tests to be significantly higher in the thermal marsh during four months of the 1973 growing season: March, May, June, and October. Juncus seasonal standing crop trends within the thermally impacted marsh are given in Figure 9R. Live, dead, and total standing crop values reveal much less seasonal variation than that found for Spartina. Live standing crop, Figure 9Ra, fluctuated around 500 grams 2/m ; T-tests indicated no significant differences in live standing crop throughout the year. Mean dead standing crop (Figure 9Rb) was almost twice large as the live. Seasonal fluctuation of dead material was also greater than that found for the live material. II-53
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7~ a..g . _ . ._ l . :_. ; :.{_, . [ _- . . .f 0 ' ' ' ' J J A S O N D J F M A M J J A l 1972 1973 l l Fig. 9R. Seasonal variation of J1EMl.ua standing crop within . l the thermally affected marsh. Bars represent
+ S.E. around the mean of five samples.
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Spartina stem density determinations, Figure 10R, and the distribution of stems among various length (Figure 11R) and age classes (Figure 12R) indicated parallel trends as morphological development in the thermally impacted and control marshes. Live plant stem densities (Figure 10Ra) were highest in late Summer and early Fall (September through October) as a result of new shoot production; the lowest stem densities were found in June. The constancy of stem numbers from February through June implied that the period of greatest mortality of new shoots was from October through February. Subtle differences in plant density characteristics of the heated and unheated marshes were suggested. The thermally impacted marsh seemed to contain greater numbers of live stems during 1972 and early 1973, but differences in mean numbers of live stems were found to be statistically significant (95% confidence level) only during September, 1972. Both marshes experienced increases
~in total live stems in the late Summer and Fall of 1972 and 1973.
Figure llR, in conjunction with Figure 12R, revealed this increase to be the result of the appearance of new shoots less than 40 cm tall. Length histograms for October and November,1972 and August to September, 1973 suggested that shoot production was initiated sooner in the thermal marsh. T-tests revealed that the thermal marsh contained statistically significant more shoots in the 0-20 cm class than the control marshes in October and November,1972. But similar tests between marshes for August, September, and II-55 ___ , s. , --m.--
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; -- -j- ...;{ Con'tr$1 krsh ' ' ' , '" j"i J J A S O N D J F M A M J J A 0 N 1972 1973 Fig. 10R. Annual Spartina alterniflora stem density characteristics (stems /m2 )
during 1972, 73 at Crystal River including a comparison of thermally a'ffected and control areas. Vertical lines represent the range and bars S.E. around the mean of nine samples. Asterisks denote months where t-tests revealed a statistically significant difference (957. confidence level) in stem densities between thermally affected and control marshes.
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a , e a ss).. ia a:.> n'3 1_p .a s so t , a'3-. aa on. sa. , .n o , a , .o . u,w am no Fig. 11R. Length-frequency histogram of Spartina alterniflora live stem lengths taken in thermally affected and control areas. Asterisks denote length categories where. statistically significantly different means were found between marsh types by t-tests at the 957. confidence level h ig g q m amb hO II-57
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l _ :J. _% , .. : e .I i d.. J .' Fig. 12R Age-frequency histogram of Spartina alterniflora live stems found in thermally affected and control areas. Asterisks denote age categories where statistically significant diff-erent means (at the 95% confidence level) were found for marsh types by t-tests. i.c-:.ren . .j
- e. u .. : r., , , s . . . . . . . g ,,,qv . . ,.,,.
j II-58
~ = .*
- October, 1973, 0-20 cm stem classes showed no significant differences. Since T-tests described earlier did not show significant differences in total live stem densities in the following Spring and Summer (1973), it was inferred that total new shoot production was identical in both marshes. hbrtality of live stems from October and November, 1972 to June, 1973 was also similar in both marshes; 36 stems /m2 (17%) in the thermal marsh and 20 stems /m (12%) in the controls.
The monthly progression of stems to longer length categories during the growing season (Figure 11R) indicated that stems in the thermal marsh grew to longer lengths, faster, during Spring and early Summer months. The thermal marsh possessed statistically significantly more stems (as determined by T-tests) in the 60 to 80 cm class during May, 1973 and more stems in the 80 to 100 cm class during June, 1973 than the control marshes. The thermally impacted marsh also retained statistically significantly more stems categorized as mature (Figure 12R) than did the control marsh during October,1973; a larger percentage of the control marsh ceased growing and became seniscent during late September and October. Total numbers of dead stems remained relatively constant throughout the study and no pronounced changes were observed (Figure 10Rb). Apparent peaks of dead stems were noticed in the
' Fall,1972, February,1973, and in September,1973. Fall and September peaks coincide with flowering and sendscence of mature plants. February peaks in both marshes may be a result of increased II-59
s-; .g _. __ . - - mortality throughout the Winter season. A reduction in dead stem density occurred in March, April, and May which also corresponded to the beginning of an annual rise in sea level elevation and periods of Spring tides. Stem densities remained constant during the Summer until September. T-tests showed higher statistically significant dead stem monthly means in the thermal marsh during February, June, July, and September,1973. Spartina flowering plant densities determined for tha ther-mally impacted and control marshes are shown in Table SR. Flowering
- was initiated in the control marshes during late August or early September of both years. Spartina appeared to continue to flower through October and possibly as late as early November. Flowering occurred sooner in the thermally impneted marsh and among natural patches bordering the discharge canal. Spartina along the canal banks started to flower in late July; flowering in the adjacent marsh began in the first two weeks of August. T-tests revealed significant differences in flower stem densities (stems /m ) of September, 1974 samples in both the marsh and canal Spartina habitats.
No significant differencee could be detected proved for later months which indicated that densities at the end of the flowering l l period was equal in both heated and unheated areas. 11-60 l
- ' .. . Tabla SR - -
Spartina Flowering Stem Density Comparisons for Two Consecutive Growing Seasons, 1972-73. Asterisks denote periods where T-tests revealed a statistically significant difference (95% confidence level) in mean stem densities betdeen thermally impacted and control areas. Flowering Stem Density, Flowering Stem Density Date Stems /m2 S.E. n Stems /m2 S.E. n Thermally Affected Areas Control Areas 28,29 July,1972 Flowering on Canal Banks, but No data not in the Marshes 16,18 August, 1972 0.9 0,9 9 No data 20 September, 1972 4.9 1.6 9 4.9 2.5 9 22 October, 1972 23.6 4.3 9 20.0 4.0 2 12 November,1972 No data 29.5 6.63 8 17 December, 1972 11.6 4.0 9 No data 7 January,1972 No data 3.6 1.7 9 28,29 July, 1973 Flowering Underway on Canal No Flowering Observed Banks 7 August, 1973 Flowering Initiated in Marsh No Flowering Observed 4 September, 1973 (Marsh) 3.6 1.04 9 0.9 0.9 9 25.2 2.4 10
- 13.6 1.57 20 *
(Canal) 46.4 16.5 5
- 0.0 0.0 5
- 55.8 5.4 20 No data 5 October, 1973 36.4 7.7 9 38.7 9.0 9 t
j .'. I II-61
Selected Animal Numbers, Biomass, and Diversity Snails, Littorina irrorata, and Fiddler Crab, Uca sp., Burrows Numbers of Littorina found in the thermally affected and control Spartina marshes during the study are given in Table 7R. The popu-lations in both marshes were patchy which was manifested by the large standard errors. Although the populations appear to reach in a maxi-mum in the summer (June-July), values from consecutive monthly samples in each marsh were not statistically different (95% confidence level). Comparisons between annual maximum and minimum population estimates of each marsh were statistically different at the 95% confidence level. Monthly comparisons of mean snail numbers between marshes were signi-ficantly different only in February when no snails were counted in the control marsh. Table SR summarizes the density of fiddler crab burrows in the thermally affected and control Spartina marshes. Burrow density estimates reached significant peaks in the late summer in both marshes of each study year. A second peak was measured in the control marsh during March, after which numbers declined significantly to a low in early July. No statistically discernable secondary peak was found to occur in the thermal marsh; the number of burrows remained constant throughout the winter and spring. T-tests revealed that the density of burrows was statistically greater in the thermal marsh during July, August, September, and October, 1973. Microarthropod Populations Results of the microarthropod sampling is found in Appendix E of this report. %-
.)
/
II-62 1 i
Table 7R Monthly Densities of 1:arsh Periwinkles, Littorina irrorata in Thermally Affected and Control Marshes Expressed as Numbers /m Date Thermally Affected Marsh Control Marsh Numbers /mZ i 1 SE n Numbers /mZ i 1 :SE n 18 August, 1972 3.11 1 2.19 9 No data 20 September, 1972 2.67 1 2.19 9 No data 29 October, 1972 9 7.11 1 2.49 No Data 12 November, 1972 No data 6.5 2.82 8 17 December, 1972 3.56 1 1.82 9 No data 7 January,1973 No data 3.4 i 3.43 7 h 6 February, 1973 5.78 1 2.22 9* 0.0 8* O 24 March, 1973 2.29 1 1.19 7 3.43 1 1.84 7 26 April, 1973 1.33 1 1.33 3 6.4 1 1.60 5 3 June,1973 11.43 1 6.95 7 9.14 1 2.86 7 30 June,1973 10.0 1 4.59 6 11.3 1 4.06 6 7 August, 1973 2.4 1 1.60 5 4.0 1 4.0 5 4 September, 1973 0.8 1 0.8 5 3.2 1 2.34 5 . 6 October, 1973 4.0 1 1.0 4 4.0 1 3.10 5 ,
~
Annual Mean 4.54 1 5.14 i i
- t-tests revealed that mean snail densities between marshes were statistically significantly different (95%
confidence level) during these months. -
7'
*. Tcbis 8R
. Monthly Denrities of Fiddict Crsb Burrows, Uce tp., in Thermally Affected and Control Marshes Expressed as Numbers /n2 Date Thermally,,Affected Marah Control Marsh
( Numbers /m 1 1 S.E. n Numbers /m' t 1 S.E. n 20, September, 1972 313 1 36.6 7 No data 29 0ctober, 1972 425. 23.8 8 No data 12 , November, 1972 No data 485. i 40.6 7 17IDecember,1972 278. i 29.9 9 No data 77danuary, 1973 No data 340. i 41.8 9 6 February, 1973 331, 1 42. 9 319, i 20.6 8 24 March, 1973 332 1 32.1 4 406. i 20.7 4 26' April, 1973 No data 285.6 1 70.7 5 3 June,1973 300. i 0. 1 207 1 20.0 8 30 , June , 1973 286.2 1 28.9 9* 5* 169.6 1 45.4 7 August, 1973 346.7 1 35.2 9* 9* 227.1 1 30.9 4 September,1973 442.7 1 24.0 9* 248.4 1 24.5 9* 6 October,-1973 290.7 1 18.9 9* 189.3 i 17.5 9* ; Annual Mean 334.5 1 18. 287.7 1 32.0 l il l t-tests revealed that mean numbers of burrows between marshes were statistically significantly different (95% confidence level) during these months. !
/
Measurements at Jacksonville, Florida Results of the collections made at the Jacksonville Electric Authority's Northside Generating Station in Jacksonville are given in Table 8R. For convenience, results from the same months for Crystal River are also shown. During May and September maximum water temperatures in San Carlos Creek, which receives the thermal discharges at Jacksonville, were approximately 70 C above those found in the control area. Atemperature difference of 4-5 0 C was detected between thermally affected and control areas at Crystal River. When operational, Unit 3 at Crystal River is expected to increase discharge water temperatures 1-2 0 C. Therefore, differences in marsh grass standing crop, snail numbers, and fiddler crab bur-row densities observed between thermally affected and control areas at Jacksonville might by typical of future conditions at Crystal River with the addition of Unit 3. In May no statistically significant difference in mean values of Spartina live and dead standing crop, snail numbers, or the density of fiddler crab burrows were found. Although not significantly different, Spartina live standing crops seemed higher in control areas. Comparisons between standing crops of the two discharge samples (9 quadrats each) at different proximities to the discharge outfall suggested a greater impact nearer the outfall. Adjacent to the outfall live standing crop averaged 350 g/m2 while values taken further upstream averaged 470. g/m 2. These differences were not 1 l l significantly different. Dead standing crop seemed higher near the outfall, 431 g/m2 vs 350 g/m 2. Mean values of dead material from all dis-charge locations were similar to those of the control. Ratios of l II-65
4-Table 8R. Summary of Field Samples Collected in Thermally Mffected and Control Marshes at Jacksonville, Florida. Comparable data Collected at Crystal River are included for Comparison. Jacksonville Crystal River Parameter Thermally Impacted Control Thermally Impacted Control May, 1973 n=18 n=9 n=9 n=9
. Maximum daily water temperature, C 32 - 34 C 26 C 300C 250C Spartina live standing crop; g/m 2 1 SE 410. 1 38. 503. t 40. 348. i 46, 299. t 57.
Spartina dead standing crop; g/m 2 t 1 SE 392. i 47. 375. 1 30. 381. 1 41.
- 210. t 72.
- U Live / Dead 1.05 1.34 0.91 1.42 1
> Snails; number /m 2 1 SE 18. 1 4.7 13. I 4.9 11.4 ! 7.0 9.1 1 2.9 Crab burrows; number /m 2 1 1 SE 330. 1 67. 370. I 10. 300. 1 0.0 207. I 20.
September, 1973 n=18 n=18 n=9 n=9
. Maximum daily water temperature, OC 38 - 390 C 32 C 35 - 360 C 32 C
.Spartina live standing crop; g/m21 1 SE 682. I 75. 579. 1 82. 580. I 78. 580, 1 47.
Spartina dead standing crop; g/m2 i 1 SE 301. 1 45. 283. 1 60. 461. I 41.
- 222. I 24. * ;
Live / Dead 2.27 2.04 1.26 2.61 Snails; number /m 2 1 1 SE 16. 1 3.3 24. i 7.5 0.8 t 0.8 3.2 i 2.3 Crab burrows; number /m 2 1 SE 269. ! 15. 237. i 50. 443. 1 24.
- 248. I 25
- live to dead standing crop were lowest in thermally impacted areas at both Jacksonville and Crystal River indicating proportionally more dead material there.
Similarly during September, t-tests revealed no significant differences in mean values of the biological parameteres between thermally affected and control areas. However, live standing crop in the discharge marshes seemed higher; atrend opposite of that observed in May. Changes in live standing crop between May and September were higher (272 g/m2 vs 76 g/m 2) in the thermally affected marsh. Snail population numbers seemed to increase between May and September, while fiddler crab burrow densities declined. Changes in animal characteristics were opposite those found at Crystal River. i l t II-67
Juncus and Spartina Decomposition Studies Results of the decomposition studies are given in Figures 13R and 14R and Table 9R. Percent dry weight remaining in the litter bags placed in the thermally affected and control marshes was plot-ted against time. Spartina decomposition products remaining were consistently less in bags taken from the thermal marsh; t-tests revealed that mean dry weights of the thermally impacted and control marshes were significantly different after periods of 70 and 135 days. Juncus disappearance rates from the bags were much less J than those of Spartina. After 200 days of decomposition, 70% of the original Juncus remained whereas only 12% of the Spartina was retained in the bags. No statistically significant differences were detected for Juncus mean dry weights remaining in thr. molly affected and control marshes. Short term decomposition rates for both plant species in the thermally affected and control marshes were determined a.nd are given in Table 9R. Rates are expressed as percent loss per day and were calculated for each time interval of the decomposi: ion ex-periment. Spartina loss rates were higher in the thermslly affected marsh and with one exception, April 1-April 26, were almost constant throughout the experiment. Decomposition rates of Spa:: tina in the control marsh increased during the experiment except for a decrease also noted during April 1 - April 26. Juncus decomposition rates in both marshes increased during the experiment; and although the relative rates between marsh types varied at different periods, the overall loss rates appeared to be similar. Turnover rates of the litter, expressed as half-
, , , s . ..
j II-68
l l l 100
~
W
- Nw N
50
- N N
l % N= E \ 5
.4
" Thermally Affected m y
- 7 # 10' Control o
b a 5. 5 0 March April May June July August September 1 1 1 1 1 1 1 o ' y o 1_ 'l <r [ 0 30 60 90 120 150 180 210 , Elapsed Time, days - cigure 13R. Comparison of Spartina decomposition rates in thermally affected and control marshes at Crystal River.
100 - _ x.__ _m 50. en
'I d R
8 cE Thermally Affected oo Control L
- b a
U 5 8 0 m March April May June July August September 1 1 1 1 1 1 1 o o q q u q 3 _ 1 0 30 60 90 120 150 180 210 Elapsed Time, days Figure 14R. Comparison of Juncus decomposition rates in thermally affected and control -marshes at Crystal River.
Table 9R. Spartina and Juncus Decomposition Rates Decompositin Rate, %/ day Time Interval, 1973 Thermally Affected Marsh Control Marsh Spartina Feb 15 - April 1 (45 days) 0.83 0.57 April 1 - April 26 (25 days) 0.50 0.41 April 26 - June 30 (65 days) 0.86 0.76 June 30 - Sept. 5 (66 days) 0.83 -- Mean: 0.80 0.63 Biological half-life, days 87 110 Juncus Feb. 15 ' April 1 (45 days) 0.06 0.016 t i April 1 - April 26 (25 days) 0.11 0.29 April 26 - July 1 (66 days) 0.28 0.06 t- July 1 - Sept. 5 0.23 0.30 Mean: 0.19 0.16 Biological half-life, days 365 433 1 6 II-71
. ~ . _ _ . , . ..._ - - . . . _ , - . - -
life, were calculated with the mean decomposition rates assuming an exponential decay function. Half-lives in the thermally affected marshes were less for both plant species. Spartina's half-life was one-fourth that of Juncus. 'k e 4
,.w, .t.....
.,. _ _ , a
' II-72
u Spartina Estimated Net Production ,. , Table 10 R is a comparison of net production estimates for Spartina in the thermally affected and control marshes. Results show that the thermally affected marsh exhibited substantially higher
^
(67%) net production than controls. Changes in live standing crop were similar in both marshes, 434.7 g/m2/yr (thermally impacted) vs 447.0 g/m2/yr (control). The thermal marsh had an accumulation of dead material three times that of the control marshes. Loss of dead material to decomposition and export in the thermal marsh was more than twice that of the controls, 778.g/m 2/yr and 329.6 g/m 2/yr, respectively. Greater dead standing crops and higher decomposition rates, Table 10 R, associated with conditions in the thermal marsh were responsible for the higher losses through decomposition. These comparisons indicate a greater turnover of live and dead material in the marshes exposed to elevated temperatures. Monthly subtotals of net production (far right column in Table 10 R) further documented the effect of elevated water tempera-tures on the length of the growing season. During the period 6 February-23 March, net production in the thermal marsh exceeded that of the controls by a factor of three. Net production in the thermal marsh extended through 6 October, while net production ceased after 3 September in the controls. Thermal discharges at Crystal River accelerate growth in the spring and extend growth later into the fall. I l II-73 s
. . .-, - - _ , , . - - - - , ~ . . 7
i T21s ICR *
- Comparison of Spartina Net Production in Thermally Affected and Control Marshes
& Live A Dead lass of reada =
Live Standing Between Dead Standing
}
Crop Sampling Crop Between Through Inst Productiend . Date SampItag Decompositten Alive + g dry weight /s2 Periods a dry weight /m2 a dry weight /m, . Periods A Dood + Decoup. Thereally Affected Marsh ' 6 February 144.9 337,3 55.1 +59.0 137.0 23 m rch 200.0 251.1 26 Aprl! 258.5 ( ' 8
- 346.6 3 June 348.3
- 380.9 30 June 472.0 *
- 421.3 .
30 July 421.0 454.4 3 September 579.6 461.3
~ 6 October 562.1 470.1
. k g Subtotals: 434.7 182.5 778.0 Total H 1395.2 0- '
Control Marsh N 6 February 132.0 245.2
+17.0 + 2.0 23 March 149.0 247.2 63.2 82.2
+75.6 0.0
- 26 April 224.6 247.2 34 5
- 110.1
+74.2 (-37.2)b 3 June 298.3 210.0 66*0 140.2 30 June 403.6 226.8 +16.8 44.8 166.4 ,
. *l34.8 7 August 538.4 265.6 *38.8
- 244.7
+40.6 e 3 September 579.0 222.0 64 5.6)b H.0 90.6
(.118.3)* c 6 October 460.9 274.8 (+52.8) (62.3)* 0.0 Subtotats: 447.0 57.6 329.6 Total 834.2 Footnotes
' Decomposition c6aculated by multiplying the average standing dead of the time interval by everage da!!y decomposition rate during that interval (Table 9 R) by the number of days in the time inte val. i Numbers in parentheses not included in estimates of production.
'2 CL-'=e the month of October in the control marsh Net Production was sero. Olive Standing crop was !!8.1 grams and 115.1 grams are accounted for by S e d + Decomposition indicating no not sain of material. Thus the numbers la parentheses were not included in the subtotals.
'Herbivory w - =cluded from these calculations, but literature sources indicate it to be approntantely 5% of met production.
Juncus and Spartina Community Metabolism Late winter measurements of diel community metabolism (daytime net production, nighttime respiration, and gross primary production) for the Juncus and Spartina communities are given in Tables llR and 12R. Results of the diel measurements suggest higher values of metabolism in the control areas, but there is considerable day-to-day variation in metabolism, especially in the thermally affected marsh. Field studies were conducted over a period of two weeks, one week in the thermal marsh followed by a second week in the control marsh. Air temperatures, tidal amplicude and periodicity, and solar insolation varied during these two weeks which complicated direct interpretation and comparison of values in the tables. To accurately assess daytime photosynthesis characteristics, Figures 1SR and 16R were constructed. Hourly rates of net daytime production occurring when no water was present on the marshes were plotted from data of each diel run. Figure 16R suggests little difference in photosynthetic response of Spartina between thermally affected or control marshes. Juncus metabolism (Fig. 15R) appears slightly higher in the control areas. These results still do not account for air temperature effects on metabolism since the dark reactions of photosynthesis are biochemical and thus tempera-ture dependent. Air temperatures (Tables llR and 12R) were cooler in the thermal marsh throughout most of the sampling period. Comparisons of temperature effects on community respiration have not yet been prepared, but values in Tables llR and 12R suggest that the daily rate values would be comparable. A comparison of Juncus and Spartina metabolism results indicates that during late winter and early spring Juncus is more i t II-75
^
.1 -
7 Table llR. Winter CO2 Gas Metabolism Measurements of Juncus in Thermally Affected and Control Marshes l Metabolisy [ Mean Daily grams Carbon /m / day Air Solar Temperature, Insolagion, Net Daytime Nighttime Gross Metabolism Date OC Kcal/m / day Production, P Respiration, R P+R Thermally Affected Marsh March 3,4 18.7 4757 1.4 3.3 4.7 March 3,4 18.7 4770 1.6 3.8 5.4 y .' March 4,5 19.9 3281 2.8 1.1 3.9 March 4,5 19.7 3369 3.4 1.7 5.1 March 5,6 20.9 3201 2.6 1.5 4.1 March 5,6 20.8 3261 3.3 1.1 4.4 March 6,7 22.8 4140 3.6 2.5 6.1 I March 7,8 22.8 2871 1.3 1.7 3.0 March 8,9 21.7 2211 1.6 3.3 4.9 i i Control Marsh March 14,13 22.6 4228 5.3 4.9 10.2 March 14,15 23.4 5058 6.4 3.2 9.6
-March 15,16 24.1 4527 7.3 1.0 8.3
Table 12R. Winter CO2 Metabolism Measurements of Spartina in Thermally Affected and Control Marshes Metabolisg grams Carbon /m / day Mean Daily Air Solar Net Daytime Nighttime Gross Metabolism Cate Temperature, O C Insolagion, Kcal/m / day Production, P Respiration, R P+R Thermally Affected Marsh March 3,4 18.3 4542 1.0 5.0 6.0
. March 3,4 18.5 4638 0.2 4.6 4.8 March 4,5 19.4 3222 1.3 1.0 2.3 y March 4,5 19.5 3336 1.8 0.7 2.5 O
March 5,6 20.4 3204 1.4 1.1 2.5 March 5,6 20.7 3309 1.7 0.7 2.4 March 6,7 22.5 4218 2.3 0.9 3.2 i 4113 March 6,7 22.6 1.5 0.7 2.2 March 7,8 22.3 3447 1.6 1.4 3.0 l March 7,8 22.3 2787 1.0 1.6 2.6 March 8,9 21.6 1932 1.6 2.1 3.7 , March 8,9 22.3 2064 1.5 1.5 3.0 h Control Marsh March 12,13 22.8 4167 3.8 2.2 6.0 March 14,15 23.5 5046 3.6 1.3 4.9 March 15,16 24.2 4311 3.0 1.9 4.9
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i Solar Insolation, gCal/cm 2/ min Figure 15R. Winter (March, 1973) comparison of Juncus photosynthesis as a function of solar insolation. Water level equals zero. (a) Thermally affected marsh (b) Control marsh _. s u . _ a l II-78 l i
a
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4 g i p , i . . . , . _ , _ , . . . z - w_ e : - a =r > H- ~' C% - az-.Qu r i m .. ! , : n..y , - - at. . _ a s- -+. - - :a id u ?.g " i? =J i .'s- .- 1 _a Solar Insolation, gCal/cm 2/ min Figure 16R. Winter (March, 1973) comparison of Spartina l photosynthesis as a function of solar l insolation. Water level equals zero. (a) Thermally affected marsh (b) Control marsh II-79
a: ._ . _ j productive than Soartina (Tables llR and 12R) . The shape of the , photosynthetic response curves shows that Juncus net production increases rapidly at lew light levels (0.0-0.3 cal /cm 2/ min), but levels off and remains constant beyond 0.3-0.4 cal /cm /2 min. This is a typical response exhibited by C3 or shade adapted plants. Spartina photosynthetic response appears to continually increase with higher solar insolation; above 1.0 cal /cm 2/ min, net photosynthesis of both Juncus and Spartina approach 0.5-0.6 gCarbon/ m2 /hr. Identical tables and figures summarizing summer community metabolism results in both marshes were prepared. Metabolism results in Tables 13R and 14R show Juncus metabolism to be slightly reduced in the thermally affected marsh relative to controls. Spartina total metabolism is similar in both marshes, but nighttime respiration is higher in the thermal marsh. Comparison of photo-synthetic activity in Figures 17R and 18R reveal each species to have almost identical responses to sunlight in thermally affected and control areas. And Spartina and Juncus response curves retain the same relative shapes as identified under winter conditions. But the magnitude of Spartina photosynthesis is higher in the summer. The shape and magnitude of Juncus photosynthetic response seems to be the same during winter and summer conditions. Thus net photosynthesis of Spartina exceeds Juncus during summer months. Respiration of Juncus appeared greater than that of Spartina in the control areas; Juncus and Spartina respiration were similar in the thermal marsh (Tables 13R and 14R) . Total metabolism of
~
, s II-80
Table 13R. Summer CO2 Gas Metabolism Measurements of Juncus in Thermally Affected and Control Marshes
=
Metabolism, Mean Daily grams Carbon /m 2/ day Air Solar Temperature, Insola.-ion, Net Daytime Nighttime Gross Metabolism Date U C Kcal/m / day Production, P Respiration, R P+R Thermally Affected Marsh July 25,26 28.4 5530 2.6 2.5 5.1 July 25,26 28.5 5530 2.8 2.7 5.5 July 26,27 29.9 5970 6.1 2.3 8.4 July 26,27 29.7 5970 4.2 2.1 6.3 July 27,28 30.2 3545 4.9 2.1 7.0 July 27,28 30.3 3545 3.2 1.6 4.8 July 29,30 30.0 3550 3.1 2.8 5.9 Control Marsh August 3,4 27.5 2720 2.4 2.8 5.2 August 3,4 27.4 2720 5.8 2.0 7.8 August 4,5 28.1 3500 4.1 2.9 7.0 August 4,5 28.9 5160 3.7 4.7 8.4 August 5,6 28.2 4150 6.6 3.7 10.3 ,
- 4. _ _ _ _ _ _ _
Tcble 14R. Summer CO 2 Gcs Metabolica Me2curemento of Sp?rtin7 in Thermally Affected and Control Marshes Metabolism
~
Mean Daily grams Carbon /m S/ day Air Solar Temperature, Insolation, Net Daytime Nighttime Gross Metabolism Date C Kcal/m 2/ day Production, P Respiration, R P+R _ Thermally'Affected Marsh
' July 25,26 28.4 5530 5.3 2.5 7.8
; July 25,25 28.5 5530 10.2 1.9 12.1
{ m
' July 26,27 29.9 5970 7.7 1.5 9.2 July 26,27 29.7 5970 6.1 2.0 8.1 July 27,28 30.2 3545 4.1 2.1 6.2 July 27,28 30.3 3545 4.8 2.6 7.4 j July 29,30 30.0 3550 2.6 2.1 4.5 dontrol Marsh ,
. August 3,4 27.3 2720 4.7 0.6 5.3 August 4,5 28.0 3500 8.9 1.8 10.6 August 4,5 27.9 3500 6.1 0.6 6.7 August 4,5 29.2 5160 8.8 2.1 10.9
. August 4,5 28.6 5160 3.0 1.0 4.0
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'Spartina photosynthesis as a function of solar insolation. Water level equals zero. !
.o .s. , , . . (a) Thermally.affected. marsh' '
~ ,
l l (b) Control marsh ! 4 II-84 , 1
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both species were similar in the control areas, but Juncus metab-olism appeared depressed relative to Spartina in the thermal marsh. a 3 e t 1 1 l' I i i i i. l ! II-85 i. (. - :. -
- - - - - - - - - - . - . - . ~ . , . . - _ . . . . . - . . . . . _ , _ . _ _ _ . _ _ _ , . _ , , ,
Analon Computer Simulation of Marsh Response to Thermal Additions This simulation run was made and is shewn in Figure 19R. Run 1 represented marsh response to normal estuarine temperature fluctuations for 10*C in the Winter to 30*C in the Summer. Simulation values of live and dead standing crop, photosynthesis, and respiration followed the seasonal patterns observed in field measurements. Also minimum and maximum values obtained with the simulation showed good agreement with field results. Run 2 was programmed for a 5'C annual increase in water temperature to
- represent the thermal additions for Units 1 and 2 at Crystal Eiver. Simulation results indicated that live and dead standing crops, photosynthesis, and respiration were all increased with higher water temperatures. All of these responses except higher live standing crop have been verified with field measurements at Crystal River. The " push-pull" temperature effect on marsh production and consumption pathways postulated in the model diagram is confirmed by Run 2. Slightly lower steady-state values of available phosphorus showed during Run 2 also indicate the higher uptake of and recycling of nutrients by the system as a response to elevated temperatures. No simulations have yet been made to evaluate the future affect of Unit 3.
II-86
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Figure 19R. Salt marsh model simulation results. II-87 __
5
SUMMARY
Various parameters of marsh ecosystem structure and function were studied over an annual cycle in two salt marshes at Crystal River to deter-mine'the effect of thermal additions. Live standing crop of Spartina in the thermally affected marsh and controls were similar throughout the growing season. Standing crop in March was h.gher in the thermal marsh and stem length measurements indicated that plants in the thermal marsh grew faster in the spring. Maximum Spartiaa live standing crop at the end of the growing 2 season (580 g/m ) was identical in both marshes. But growth was extended approximately one month further into the fall in the thermal marsh. Spartina dead standing crop in the thermal marsh was statistically significantly higher throughout the year. Dead standing crop in the control r marsh remained nealy constant throughout the growing season; the thermally impacted marsh accumulated three times as much dead material, 183 g/m , during the growing season. Decomposition of dead Spartina proceeded faster, esti-tally in the spring, in the thermal marsh. The higher dead standing crops a: 9 ' composition rates within the thermally affected marsh resulted in a larger turnover of material 2 2 during the growing season, 780 g/m n 330 g/m in the controls. Decomposition rates for Juncus were similar in both marshes. Net primary production of Spartina, calculated from changes in live and dead standing crop and decomposition, was higher in the thermally impacted 2 2 marsh than controls, 1400 g/m /yr 3 830 g/m /yr, respectively. . Measurements of community metabolism revealed the photosynthetic responses of Spartina and Juncus to be similar in thermally impacted and control areas during the wint.er. Also winter nighttime respiration data for both species in the thermal marsh were similar to values obtained in the control marsh. Total metabolism of Jureus in the thermal marsh seemed deprersed relative to the II-88
control area during J the.' summer. Spartina' photosynthesis in the[ summer-was, - - , identical in both marshes, but respiration was higher in the thermal marsh, 4.0 g/m / day, versus 3.0 g/m2 / day in the controls. Littorina snails were found in similar numbers in both the thermally affected and control marshes. Fiddler crab burrows were more numerous in the thermal marsh. Inse::t collections indicated equal numbers of insects in both Juncus marshes. Insect diversity within the Juncus uarsh was lower (50 species / 1000 individuals vs,61 species /1000 individuals) in the thermal marsh re2ative to the controls. Insect numbers appeared slightly higher in thermally impacted Spartina marshem when compared to controls; no differer.ce in diversity was detected. The adaptations observed in the thermal marshes are consistent with Locka's principle that surviving systems are those which maximize the flow of energy through the system. The thermal marshes are apparently utilizing some of the potential energy of the thermal discharges to carry on higher levels of metabolism. Computer simulaticns utilizing a " push-pull" tempera-ture effect repeated the trends of the field observations. Measurements in a thermally affected marsh 1-20C hotter than what is presently axperienced at Crystal River showed no differences between the thermally impacted marsh and nearby controls. i II-89
n, s a .s ~
~ ^
LITERATURE CITED Adams, C.A., Oesterling, M.J., Miss, J., and W. seaman, Jr. 1973. Fish
. abundance and biomass in two tidal creeks near Florida Power Corpora-tion's generating station (Crystal River, Floride), in Environmental Report to Interagency Committee, Oct. Florida Power Corp., St. Peters-burg.
Burns L. A. 1973. Seadade community metabolism: results from first experi-mental field session. UF/FP&L Report No. 005, submitted to Florida Power and Light Corp. from Resource Management System Program, IFAS, S.C. Snedaker, Principal Investigator. Carder, K.L. 1972. Independent environmental study of thermal effects of power plant discharge. In: Environmental Status Report, July-Sept. Florida Power Corp. , St. Petersburg. 1971. An independent environmental study of thermal effects of power plant discharge. In: Environmental Status Report, July-Dec. Florida Power Corp., St. Petersburg. Carter, M.R., et al. 1973. Ecosystems analysis of the Big Cypress Swamp and estuaries, EPA, Region IV, Atlanta. Coultas, C. L. 1971. Some saline marsh soils in North Florida, Part II. Soil and Crop Science Soc. of Fla. Proc. 31:275-282. 1 Coultas, C. L. 1969. Some Saline Marsh soil in North Florida Part I. Soil and Crop Science Soc. of Fla. Proc. 29:111-123. Day, J. W., W. G. Smith, P. R. Wagner, and W. C. Stowe. 1973. Community Structure and Carbon Budget of a Salt Marsh and Shallow Eay Estuarine System in Louisiana. 79 pp. Center for Vetland Resources Publication LSU SG-72-04. Louisiana State Univ. Eaton Rouge. Keefe, C.W. 1972. Marsh production: a summary of the literature. Contri. Mar. Sci. 16: 163-181. Kurz, H. and K. Wagner. 1957. Tidal marshes of the Gulf and Atlantic coasts of Northern Florida and Charleston, South Carolina. Fla. State Univ. Studies No. 24. Tallahassee, Fla. 169 pp. Marshall, D. E. 1970. Characteristics of Spartina marsh receiving treated municipal sewage wastes. M.S. thesis, Dept. of Zoology, Univ. of N. Carolina. Chapel Hill, 51 pp. McMahan, E. A., Knight, R. L., and A. R. Camp. 1971. Acomparison of micro-arthropod populations in sewage exposed and sewage free Spartina salt marshee.' Env. Entom. 1(2):244-132. McNulty, J. K., Lindall, W. N., Jr., and J.' E. Sykes. 1972. Cooperative Gulf of Mexico esturarine inventory and study, Florida: Phase I, are descrip-tion. 126 pp. NOAA Technical Report NMFS CIRC-368. US Dept of Commerce, Seattle. t Milner, C. and R. E. Hughes. 1968. Methods for the measurement of the pri-mary' production'of gr'ais1nd. a IBP Handbook"No. 6, Blackwe'll, Oxford. 70pp. 11-90
' ~ ' ' Morgan,lV.'N.11961. Annual'$ngiospermproYuct'ionion.a'ealtmarsh.'M.S.' .
thesis. Univ. of Delaware. 34 pp. NOAA. 1972-74. Tide tables. Odum, H. T. 1970. Environment, Power, and Society, Wiley Interscience, New York, 331 pp. Odum, H. T. 1970. A Tropical Rain Forest. Office of Information Services. USAEC. Pomeroy, L. R. , R. E. Johannes, E. P. Odum, and B. Roffman.1969. The phosphorus and zone cycles and productivity of a salt march in Symposium on Radioecology. D. J. Nelson and F. C. Evans (eds.) , U.S. A.E.C. , (Con f-670503) . Smalley, A. E. 1960. Energy Flow of a salt marsh grasshopper population. Ecology 41:67l 677. Snedaker, S. C. 1973. Benthic Marine Ecology Program (Crystal River): drop net collections in Environmental Report to Interagency Committee, Oct. Fla. Power Corp., St'. Petersburg. Teal, J. M. 1962. Energy flow in the salt marsh ecosystem of Georgia. Ecology 43:614-624. U.S. Dept. of Commerce. 1961-71. Climatological data: National summaries. Young, D. L. 1973. ctudies of Florida Gulf Coast Spartina Alterniflora and Juncus roemarianus salt marshes receiving thermal discharges, in Thermal Ecology, J. W. Gibbons and R. R. Sharitz (eds.), AEC Symposium Series, (C0!IF-730505) . l 1 II-91 ,
^
. ^
- 5. VALUE OF HIGHER ANIMALS AT CRYSTAL RIVER ESTIMATED WITH ENERGY QUALITY RATIOS W. M. Kemp, H. McKellar, and M. Homar Department of Environmental Engineering Sciences University of Florida Gainesville, Florida 32611 In the complex food webs of estuarine ecosystems as found at Crystal River, myriad work functions are performed by component or-ganisms. These various kinds of work done by larger animals (inc,lud-ing basic maintenance metabolism, reproductive work, migratory acti-vities, and feeding metabolism) maintain the organism's own structure and energy flows while also providing stabilizing energy links be-tween ecosystems and their components.
In a given trophic system, energy passes into and through the web from sunlight to primar-/ producers to herbivores and detritivores, and on to pri-mary and secondary carnivores. Considerable amounts (about 90 percent per trophic level) of the heat content of this energy is lost as it flows from the point of primary light energy fixation to the work of top carnivores. The heat which is lost to the trophic system at each successive step, however, provides essential work which is channeled into the process of building complex, higher quality biological machinery (physiologically functionirg biological structure) at each higher trophic level. While higher trophic components process less energy (i.e. heat content) and build less standing stocks per m.it area than do lower level organisms, l the energy flows which their structures produce are of higher qualit, , (in terms of ability to do work) than the work energies flowing at l I ! lower trophic levels. Therefore, a kcal of energy expended by a spotted sea trout accomplishes more work than a kcal of energy from oyster metabolism, and is therefore of greater work value to the system. Man's activities which remove animals from an estuarine ecosystem, either directly as by fishing harvest or inadvertantly as onto power plant intake screens, Lave various effects on that ecosystem and its ability II-93 ________ ' ' 1111"- _ ___ __ _ __ _ _.
~ --- - ^ -
w l- .. _ .. -. _ , to do work. For example, the removal of one kilogram of mature mullet ^ biomass (as mostly herbivore and detritivore) would have less effect on ' the total work value of the ecosystem than to remove one kilogram of
. adult spotted sea trout (top carnivore). This results because the I
quality of metabolic energy flows from the trout is considerably great-er than from the mullet in terms of ability to do equivalent amounts of work. 1 l Therefore trophic position is an index for " energy quality" of work performed by the members of a given food web. We set forth in this j paper an attempt to quantify the spectrum of " energy qualities" for the estuarine ecosystem adjacent to the Crystal River power plant, so as to assess the impact of this power plant on the estuary. Although ;che calculations provided herein are specific to the Crystal River situation, we propose that the methodology has general application to all ecosystems. An energy diagram of the trophic web for dominant organisms at , Crystal River is provided in Figure 1, including principle flows and t storages. Much information concerning the food web structure among l important fish species in Gulf coast bays was provided in the literature l (Reid,1954; Kilby,1955; Springer and Woodburn,1960; Tabb,1961; Simmons and Breuer,1962; and Carr and Adams,1973), and was used as a guide for the patterns in Figure 1. Biomass estimates of the trophic compartments were based, in part, I on measurements taken from the Crystal River bays (Fla. Power Corp. Environ. Status Reporto, 1972-1974). For those species such as blue crabs (Calinectes sapidus), mullet (Mygu cephalus), and sea trout (Cynoscion nebulosus) for whien data were not available for the Crystal River area, biomass estimates were based on published data from other Gulf coast i systems (Jones, Ogletree, Thompson, and Flenneker, 1963; Hoese and Jones, 1963; Wagner,1973; and Day, Smith, Wagner and Stowe, 1973). i 1 Energy flow, for the trophic exchanges specified in the model were estimated based on a wealth of physiology data available in the liter-
-ature and a few attempts to relate in vitro results to in vivo situations, including unpublished data of Homer (1973). Where more detail was needed for individual species, information on individual respiration, food in-l take, and assimilation was required.
s., , - - - - e 11-94 I L
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2 8E EA Flows: mg. org./ m / day Stocks: mg. org./ m g 9 ~ 2-3x. v - Fig. 1. Energ Diagram for Trophic Web at Crystal River Including Important
Respiration of fish at rest was related to its body by the formula of Winberg (1956): O R = 0.3 W .8 where R was the resting condition respiration rate in mg 0 /hr/2 fish and W was the wet weight of the fish. Winberg suggested that the metabolic rate of fish in nature should he taken as twice the resting rate, R. Therefore, the respiration of fish components in the food chain model was estimated as 2R. The energy budget of a fish population can be generally established with knowledge of rates of food ingestion, egestion, metabolism and growth. If the growth rate is assumed to be the rate at which energies are made available to higher trophic levels then the energy budget of a population may be represented as in Figure 2 . Winberg (1956) found that the energy of egestion and excretion were generally around 20% of the food intake of most fish, a figure which is of ten used for energy . - budget calculations (Mann, 1965; MacKinnon, 1972). For fis.h less than 100 ; wet weight, growth rates of approximately 50% of food intake have been documented (Wagner,1972; Warren and Davis, 1967). The remaining 307. of the ingested energies were assumed to be lost by metabolism in this size range of fish. Using these approximations, the energy budget of this size range of fish were represented as in Fig. 2a. Therefore, with metabolism established by Winberg's formula, the remaining energy flows associated with fish components of a general size class less than 100 g wet weight in the model were calculated accordingly. Similar data for fish in a larger size class range between 100 and 500 g wet weight (MacKinnon,1972; Pandian,1970; Edwards et. al., 1969) provided some basis for approximating energy relationships as indicated in Fig. 2b. Very little data exists for evaluating energy budgets of larger fish ( > 500 g. ). However, data for smaller size classes of fish, shown in F 3 2a and 2b , indicated a trend where larger fish metabolized a greater proportion of the food they ingested and, therefore, transferred a lesser percentage to higher trophi; levels. This apparent trend was extended to the energy budget relationships of fish in size classes greater than 500 g as shown in Fig. 2c. II-96
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~-
l l l l Fig. 2. General energy budget configurations for fish populations used in evaluating Fig. 1. J i= food ration, J 2= feces, l J 3= total metabolism, J =4feedback work for ecosystem, J 3= growth and transfer to next trophic level. i l II-97
+ . . . m 1 With Fig. 1, completely evaluated an attempt was made to general-ise trophic and metabolic relationships for this ecosystem by parti-tioning the consumption, metabolism and biomass of the various species in the system into trophic work function categories. This partition-ing was done according to the percentage of a given organism's diet spent in each of the general trophic categories. Table 1 provides the calculations used in this allocation procedure and Fig. 3. is the more general energy budget diagram based on Table 1. Notice that this dia-gram emphasizes the bifurcation of trophic energy into two branches (detritus and grazing). The relationships illitstrated in this figure are more generally applicable than Fig. 1. to other estuaries of the Gulf coast where species different from those dominant at Crystal River are pe: forming the same basic work functions.
The relationships of energy flows to energy storages in Fig. 3 are ultimately based on those derived in Fig. 2 and are therefore es- - - sentially the same. However, each compcaent of this trophic function diagram now contains a wide size range of animals. J4 J i= food rations J 2= feces J 3= total metabolism J 4= active portion of metaboliser
' Trophic J5=gr wth= mortality J1 J6= assimilation f)( Co ent j >J5 3
2 l J qf 3 U_ Fig. 4 General diagram of component of trophic function web to illustrate calculation of energy quality ratio (EQR). II-98 4
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ge 28 s
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l Detritus 7 Branc.h . Fig. 3. Energy Diagram of Trophic Work Functions in Estuary Near Crystal River 4 ) i i
A __ _. Based on the work of MacKinnon (1972) and Mann (1965) it was estimated that, of the total metabolism of a given organism, about 33% is used in direct standard metabolic maintenance work and the remaining 67% is used in work which feeds back to upstream components of the eco-system. This feedback is largely the work which is used to convert the energy of an upstream component into the flesh of the downstream component performing the work. Therefore, the energy of metabolism in this feedback flow is equivalent in real work units to the energy of the upstream biomass which is released to flow downstream. The concept of energy quality ratio (which is defined in Section 1 of this report) is used to equate the feedback and downstream flows. Referring to Fig. 4., the work value of the two flows are made equiv-alent by multiplying each by its respective energy quality ratio (EQR): Ji x (EQR of upstream flesh) = J5 x (EQR of downstream metabolism) In a similar manner the work value of a components flesh is made * , equivalent to the work value of its metabolism thus: J2 x (EQR of flesh) = J4 x (EQR of metabolism) Table 2 lists the fourteen simultaneous equations derived from the above relationships. Letting the EQR for primary production (sugar) equal unity, the equations can be solved for all other ratios in terum of sugar. Turning to the specific issues of the Crystal River power plant impact on the estuary, EQRs for metabolism of the 13 dominant organ-isms entrapped on the power plant intake screens are calculated based on typical trophic habits for each species. Table 3 categorizes the dietary habits of each into the trophic groups of Fig. 3., and Table 4 then pro-rates the EQR's calculated for each trophic group according to the fraction of a given organism's diet which represents each trophic habit. Finally, Table 5 provides estimates of EQR's for the groups of inverd::brates and innature fish which are entrained into the power plant cooling water flow. The work value of an organism in its system can then be calculated (relative to the work of primary production) as the product of its , II-100 I i i
l l l l
- r. - I Table 2. Equations and Calculations of Trophic Work Functions Energy Quality Ratios (EQR) i Ecuations Solutions Detritus Branch:
]
detti66 seconEar
- 0) O.5 EqR , = 1.1 EQR.2 EQRi (carnice me6an=Yiw)= 46.5 j d) 30 EQR 2 -18.8 EQR 3 EQR 2 (N;ee@ )
- 21.2.
(.3) 12.6 EQR3-@ EQR4 W fde Nh)- 3 M C4) 1600 EQR4 =105(3EQR, EQR 4 (&Hiere M)
- 9. 5 (5) 7e9 gggg .2400 EQRu EGpQs (de%ere me%ok h 14.3 (6) 142o EQ R,, = 192.o EQR7 WP , (Mritos &,)
= 4, 2.
(7) 94o EQR 7 = 2400 EGRs EQR7 (detritus metabew) = 5.8 (8) ZZoo EGRs = 5000EGR,' EQRs (PWue re9;rdon)= 2.3 l Grazing Branch: (9) GI3 EQR ,,= C4 EQR. EQR,o(fa7n)e m/EI:w) = 24.6 0o) 11. 2. EQ R , - b EQ R,,. E'qlei, fcfd@,Pr of ) = 8o Gi) 4 eor,, 14 EGR,3 EQRe (M7,l"o"c*e.L,,,,) - i4.9 Q2) 56o EQR,3 = Soo EGRg EQRi3 (herWore flesh) = 4.3
- 03) 2.co EQR g= 700 EQRs EQR4(berwom mdabdy= g.o
- 64) 2200 EQR a =5000 EQRg* EQRs (Predocr vakn)= 2.3 Letting EQR, (primary production) equal unity, all others are calculated in tenas of it.
II-101
. -. .=. - - - - . ... -. . . .
Table 3. Trophic Habits of Major Organismo Entrapped on Crystal River Power Plant Intake Screens.
- 7. Trophic Work Function <
Diet Composition Grazing Food Chain Detritus Food Chain Species Entrapped (7. Each Item) Herb. Prim. Ca rn. Sec. Ca rn. Detrit. Prim. Carn. Sec. Carn. Oncocephalus radistus crabs 50 amphipods 50 23 13 51 13 Chilomycterus schoepf t ys ers
, 50 25 25 Callinectes saDidus y rt 100 polychaetes 33 Lactophrys cuadricornis oysters 33 33 9 33 24 crabs 33 algae 33 Lanodon rhomboides zooplankton 33 33 18 8 22 19 0 fish 33
, Ascidacea ritus zooplankton 50 Eucinostomus aula polychaetes 45 5 25 70 algae 5 I Lolino sp. shrimp 0 2 10 58 30 fish 30 Bairdiella chrysura macroinverts 40 21 7 55 17
$ zooplankton 30
.. Harennula pensacolae zooplankton 100 50 50 shrimp 33 Caranx hippos small fish 33 11 6 65 18 mullet 33
^ Muril cephalus 25 75 de r tus Polvdactylus octonemus zooplankton 100 50 50 I
Table 4. Calculation of Energy Quality Ratios for Organisms Entrapped on Crystal River Power Plant Intake Screens. , Fraction Trophic Work Functions Prorated Crazina Food Chain Detritus Food Chain (EQR) sugar , Species Entrapped Herd. - P rim. Carn. Sec. Carn. Detrit. Prim. Ca rn. Sec. Carn. Oncocephalus radiatus 0.23x14.9 0.13x24.6 0.51x33.8 0.13x46.5 29.8
= 3.4 = 3.2 =17.2 = 6.0 Chilomycterus schoepfi 0.50x14.9 0.25x24.6 0.25x46. 5 25.3
. = 7.5 = 6.2 =11.6 .
Callinectes sapidus 0.22x14.9 0.78x33.8 29.7 s = 3.3 =26.4 s 4 Lactophrys cuadricornis 0.33x14.9 0.09x24.6 0.33x33.8 0.24x46.5 29.5 g = 4.9 - 2.2 ,
=11.2 =11.2
. x .0 0.18x14.9 0.08x24.6 0.22x33.8 0.19x46.5 Lanodon rhomboides 23.7
= 2.8 = 2.7 = 2.0 = 7.4 = 8.8 0.50x 8.0 0.50x14.3 y_
Ascidacea
= 4.8 = 7. 2 i
0.05x 8.0 0.25x14.9 0.70x33.8 27.8 Eucinostomus aula = 0.4 = 3.7 =23.7 0.02x14.9 0.10x24.5 0.58x33.8 0.30x46.5 36.4 Lolino sp.
= 0.3 = 2.5 =19.6 =14.0 Bairdiella chrysura 0.21x14.9 0.07x24.5 0.55x33.8 0.17x46.5 31.3
= 3.1 = 1.7 =18.6 = 7.9 i
Harenaula pensacolae 0.51x14.9 0.50x33.8 24.4
= 7.5 =16.9 Caranx hippos 0.11x14.9 0.06x24.5 0.65x33.8 0.18x46.5 33.5
- =22.0 i = 1.6 = 1.5 = 8.4 ,
0.25x 8.0 0.75x14.3 j Munit cephalus
=10,7 12.7
= 2.0 0.50x14.9 0.50x33.8 24.4 Polvdactus octonemus l .
I-f,
,~ .< , _. ._
metabolism and its energy quality ratio. Using the consistent assump-tions and calculations provided in this report, we now have a quanti-tative basis for assigning a proper value to each organism as part of a ceaplex system. 4 Table 5. Energy Quality Ratios for Organisms Entrained In Power Plant Cooling Water Flow. Energy Ouality Ratio
- Organism As Juveniles As Adults Zooplankton Copepods 11.1 11.1 Shrimp juveniles 14.3 14.3 Mollusk veligers 11.1 12.9 Crab larvae 11.1 29.6 Fish eggs and larvae 11.1 25.0
, Chaetognaths and Medusce 24.0 24.0 l
Juvenile Fish 20.4 25.0 , Referenced to sugar which is given unity quality.
~
II-10'.
v- , ,;,, , .. LITERAIURE CITED Carr, W.E.S., and C.A. Adams. 1973. Food habits of juvenile marine fishes occupying seagrass beca in the estuarine zone near Crystal River, Florida. Trans. Amer. Fish. Soc. , 102(3):511-540 Day, S.W.JR., W.G. Smith, P.R. Wagner, and W.C. Stowe. 1973. Community structure and carbon budget of a salt marsh and shallow bay estuarine system in 7?;*siana. Publicat!'n No. LSU-SG-72-04, Center for Wetlands Resources, Louisiana State University, Baton, Rouge, La. 80 pp. Edwards, R.R.C., D.M. Finlayson, and J.H. Steele. 1969. The ecology of 0-group plaice and dabs in Loch Ewe. II. Experimental Studies of metabolism. J. Exp. Mar. Biol. Ocol. 3:1-17 , Hoese, H.D. , and R.S. Jones.1973. Seasonality of larger animals in a Texas turtle grass community. Publ. Inst. Mar. Univ. Tex. 9:37-47 Homer, M.L. 1973. Unpublished data. Jones, R.S., W. Ogletree, S. Thompson, and W. Flenilsen. 1963. Helicopter borne purse net for population sampling at shallow marine bays. Publ. Inst. Mar. Sci., Univ. of Texas, 9:1-5 Kilby, J.D. 1955. The fishes of two gulf coastal areas of Florida. Tulane Stud. Zool. 2:176-247 MacKinnon, J.C. 1972. Summer storage of energy and its use for winter metabolism and gonad maturation in American Plaice (Hippoglossoides l platessoides). .J. Fish. Res. Bd. Can. 29: 1749-1759 l l . i l 11-105 l
, . . ._ _ - ----- p Mann, K.H. 1965. Energy transformations by a population of fish in the River Thames. J. Animal. Ecol. 34:253:275 Pandian, T.J.1967. Intake, digestion, absorption, and conversion of food in the fishea Megalops cyprinoides, and Ophiocephalus striatus.
Mar. Biol. 1:16-32 Reid , G.K. , Jr. 1954. An ecological study of the Gulf of Mexico fishes in the vicinity of Cedar Key, Florida. Bull. Mar. Sci. Sulf Carib. 4:1-74 Simmons, E.G.,'and J.P. Breuer. 1.52. A study of redfish, Sciaenops ocellata, Linnaeus, and Black drum, Pogonias :romis, Linnaeus. Pub. Inst. Mar. Sci. Univ. Tex. 8:184-211 Springer, V.G., and K.D. Woodburn. 1960. An ecological study of the fishes of the Tampa Bay area. Fla. St. Bd. Conserv. Mar. Lab. , Prof. Dap. Ser. 1:1-104 l 1 Tabb, D.C.-1961. A contribution to the biology of the spotted seatrout of l i east-central Florida. Fla. State Bd. Conserv. Tech. Ser. No. 35, 23 pp. Wagner, P.R. 1972. Seasonal biomass, abundance, and distribution of estuarine dependent fishes in the Caminada Bay system of Louisiana. Unpubl. Ph.D. dissertation, Louisiana St. Univ., Baton Rouge, 165 p. Warren, C.E., and G.E. Davis. 1967. Lab studies of the feeding bioenergetics and growth in fish. Iri S.D. Gerking (ed), The biological basis for fresh water fish production. Blackwell, Oxford 1 I II-106 l l
i t Winberg, G.G. 1956. Rate of metabolism and food requirements of fishes. l Nauch. Fr. Beloruss. Gos. Univ. im. V.I. Lenina, Minsk, 253 p. (Transl. from Russian by Fish. Res. Bd. Can. Transl. Ser. No.194,
*1960) '-
4 1 .I t l
)
l I 3 { 1 I I I I ! i i II-107, L-
- 6. MONITORING FUTURE TRENDS AND ONSET OF ADDITIONAL PLUMES WITH A METABOLISM BUOY Lance Gunderson and Ane Merriam 1
Department of Borany University of Florida Gainesville, Florida 3?611 2 Department of Environmental Enginetring Sciences University of Florida Gainesville, Florida 32611 Previous measurements of metabolism using the diurnal oxygen or pH method (section 4) show that this index (metabolism) along with others such as diversity might be monitored to show the impact on the bay as additional units go on line. As contracted, a polyurethane, wood and steel research buoy was constructed. This raft was developed to hold equipment for recording of dissolved oxygen, pH, temperature and conductivity measurements. These parameters can be checked for diurnal ranges on a weekly basis so that many tedious man-hours are eliminated. The buoy was tested summer of 1974 and is presently producing regular records. The buoy can be moved to one of four permanent stations for any time period designated as needed to observe trends as the plant goes on line. The buoy was constructed using pre-formed polyurethane pontoon sections upon which a wood and metal frame was used to tie the sections together. A box, to contain the equipment .was constructed from 3/16" stainless steel for durability and security reasons, and was bolted to the frame. A sketch and rough dimensions of the buoy are shown in Fig. 1. The aquipment was purchased _as a kit (model 6D-2-10) Hydrolab Corporation. The arrangement of these instruments inside the box is shown in Fig. 2.- The system consists of a shock-resistant sonde with the varying i II-109 e t _
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o probes plus a stirring motor for reliable dissolved oxygen readings. This sonde is suspended through a well in the box as shown in Fig.1. The measurements are monitored through a multipurpose meter. The output of the meter is tapped through a data scanner which assigns a channel to the diflerent parameters, and each channel is read for 500 seconds. Concurrently the data is recorded as a strip chart recorder. A sample of the chart is shown in Fig. 3. . data are manipulated to give diurnal curves as in Fig. 4. The mec e - :ribed in detail in section 4. Because of exorbitant cost of battery replacement the system was converted to run off a 12 volt automobile battery which can be recharged. The batterier and oxygen membrane are changed once a week. At this time all systems are calibrated. The four permanent stations now monitored are shown in Fig. 5. Stations 1 and 2 are in the discharge region, stations 3 and 4 in the intake or control. Stations 1 and 3 are in benthic plant-dominated systems, while stations 2 and 4 are in the deeper water, plankton dominated system. The buoy is being placed at each station for a week so that seasonal and non-seasonal variations can be detected. Also the data may give further indi-cation whether full diurnal curves are necessary for metabolism analysis or if dawn-dusk (minimum-maximum) dissolved oxygen readings are sufficient. In summary, using the buoy to measure either diurnal dissolved oxygen or pH and relating these turves to the water temperature, a reliable index can be formed. Using this index of system metabolism along with others (diversity, etc.) the effects of additional plants and possibly larger thermal plumes can be readily determined. II-112 p 9 a 4 gf # # * # l l 1 I
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I l APPENDIX A These papers were presented at a Thermal Ecology Symposium May 3-5, 1974, in Augusta, Georgia and recently published in Thermal Ecology, J.W. Gibbons and R.R. Sharitz (eds.) . AEC Symposium Series (CONF 730505). 670 p. Our later work changes the conclusions somewhat as follows: Later measurements by Wade Smith did show a decreased metabolism in the plume area by about 50" whereas the preliminary data did not show a statistically significant diff'rence. The dollar cost of cooling towers rose from early estimates of 1 I million dollars a year to 17 million per year. The estimate used for the calculations in " Energy Cost-Benefit Models for Evaluating Thermal Plumes" by Odum was $5 million a year at the time of page procf checking.
.hus the energy impact of this paper is 1/3 too small.
l l l l l 11-117 l
. _ s= ..- , . - , . . _
, &- ' n - - _ w ._. - APPENDIX Al ENERGY. COST-BENEFIT MODELS FOR EVALUATING THERMAL PLUMES. II') WARD T ODUM Department of Env.ronmental Enpneering Sciences. University of Florida. Gainesville,
lorida ABSTRACT Systems models, analog computer simulations, ent gy cost-benefit tabulations, and measurements of productivity and total metabolism are used to consider the role of increased scmperature inflows at Crystal River, Florida. The estua y has received a power-plant thermal plume for 6 years. The potential energy content of heat flows in the gradient is calculated as an auxiliary energy source, and the role of elevated teraperature is considered as affecting productivity and recycling. Energy circuit diagrams and simulations are given for Eyrings's model, for Morowitt's ordar model having au:ocatalytic temperature action, and for a model with more complex nutrient and sewage recycle actions of temperature. In most models increases in temperature serve as both a push and a pull action on orderly structure, increased temperature may increase the system > total productivity and useful power if the temperature change is accompanied by increawd resources with which to interact. Experience with microcosms and measurements at Crystal River bear out the suggestions from models that power plar.ts may have neutral or positive energy impacts on estuarine ecosystenes if the ecosystems are given time for self-designing adaptation. The negative energy impact of these siternatives may be much less than the large eneyy cost to the general economy of man and nature caused by cooling towers.
Flowing from the coohng canals of man's power plants in accelerating quantity are heated waters carrymg potential energics. The diluted poteritial energy does
,vork in the environment. proportional to the Fradient of temperature involved in these large flows, by interacting with ecoevstems, such as lakes, rivers, and estuaries, and with the atmosphere into which the heat gradually disperses by conduction, consecti~ o n, evaporation, and ultimately by outbound radiation. In the theme of this conference, we ask what the nature of the thermal work is and to what degree it changes ecosystems, benefits them, or stresses them. In this paper energ/-circuit models, calculations, and simulations are used to consider 628 s b O +
11-118
a 1 v ENERGY COST-BENEFIT MODELS 629 work of thermal effluents. Theories and principles are illustrated with a specific example: the Florida Power Corporation power plants at Crystal River, Florida, and a decision regarding construction of a coohng tower. The thermal plume from an 800-MW power plant at Crystal River has been flowing into a shallow oyster reef estuary for 6 years, allowing time for ecological adaptation to the thermal load. Study of this situation allows a test of the question of the usefulnc>s of thermal plumes to estuarine ecosystems. Since the plants are public
- utilitics with profit levels set by public service commissions, the costs of cooling towers are paid by the public,and conversely savings resulting from not building coohng towers might be used in conservation expenditures cisewhere. What is the best use of the conservation dollar?
PERSPECTIVE ON A POWER PLANT IN ITS REGION The 32 county area served by the Florida Power Corporation is shown in Fig.1.1his is a relatively rural area of Florid. , which has towns, agriculture, forestry plantations, lakes, estuaries, swamps, and other nonhuman ecosystems. Perspective on the value and importance of the power system to the overall system ut man and nature may be gained by summarizing the approum.ite potential energy flows, includmg those of the power system with an energy-circuit model (Fig. 2). Est, mates of the various energy flows are gwen in Table 1. The work of ti.e sua in photosynthesis and in stirrmg air masses, the energy transferred to the earth fror, friction of the winds driwn from outside, the mtlows ; f waves and tide on the coast, the inflows of motor fuels for cars and trucks, natural gas for heating, and the oil for the power plants are depicted. The potential energy driving the power plant is about 5% of the region's budget All the numbers in Tables I and 2 are preliminary and tentative and are being examined in a current rewarch program for the Flonda Power Corporation and for heenung .igencies that are considering these new approaches to environ-
~
mental decisions. For more details, see progress reports forthcoming trom this project, What is intended here is a presentation of the approxh that includes all sources of work equally, those from nature and those associated more directly with money payments. More dcrailed perspective concerning the power plants at Crystal River (Fig. 3)~is given with an energy-flow diagram (lig. 4) based on calculations in Table 2. Two-thirds of the energy flow from the fuel barges passes ultimately out through' the cooling waters to the estuary and one-third passes out through the electric power transmission lines. Also shown m Table 2 are some main flows of money from power sales outflowing to purchase fucts and work services of high energy amp!'fier value from society. In Fig. 4 and in Ta', c 2, energies of the plant are compared with other flows affecting a 2000-acre section of estuary at Crystal River.
'r
-II-119 ;
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630 ODUM N
# MONTICELLO x 83 GOCALA e2 5 es g og WINTER WALT DISNEY 6 PARK WORLD ti f 10 g e LAKE WALES S
I e7 ST. PETE RSBU RG 4 0 26 50 M,les Fig.1 Area of Horida covered by electrical distribution of Florida Power Corporation and summarised in energy diagram of Fig. 2. POTENTIAL ENERGY IN A THERMAL PLUME, POWER DENSITY IN RECEIVING AREA The hot waters that flow out from cooling systems still retain potential energy, although not enough to be very economically harnessed as an only
+
source. The potential cnergy, as it flows into the environment along with other energy flows, makes a contribution to that system, initially that effect may be disordering, but, after organisms and processes adapt, the energies become coupled to the positive aspects as wc!!. Lotka's principle suggests that adaptations follow so as to utilize all energy sources in a way useful to that system's continuation. l II-120 i lJ >
r ENERGY COST-SENEFIT MODELS 631 45 45' is s PL NT l l COME
\ FUEL GS FUEL \ g i
\
's s 's s 55
\
\
g 12 50 s 28 N 10* \
\ s \ \
wino g 'g
\ g n
\ I 375 LAND g xX
** S
~
PLANT r - 470
$UN f
51 -
% = X X X X X 33 HE AT IN / / / /
vi WATER 0 01 pry WAVES b i 32 X X e ESTUARY YY Y Y A 16 TIDE 100 kcauvm 1035
=-
Hg. 2 Energy diagram for 32 county area of Florida shown in 1 ig.1. Numbers are flows of purential energy entering the area (Table I). See appendiz for identification of symbols. The amount of potential energy flowing in a heat gradient is the product ot' the total calories inflowing time's the Carnot ratio, which indicates the percentage of the heat supply that is capable of doing work. For a thermal plume 7*C above ambient and a temperature of 27'C (300*K), the kilocalories of potential energy doing work n given by Eq.1.
. AT kilocatories m 3 Power contribution =-- -
(1) 1 m3 day where the heat capacity is about I g-cal /cm3 and the daily discharge from the power plant is 3 5 x lo" m'/ day. Wlues substituted for Crystal River flows in 1973 are given in Eq. 2. II-121
r- : w .
, m._ --
sc ._ _ _ . _ _ . _ . f
- , 632 ODUM TABLEI ANNUAL ENERGY BUDGET
- FOR A POWER DISTF!CT IN FLORIDA (FLORIDA POWER CORPORATION) l Area,20,000 miles 2 (5.12 x 10 m );2 smoothed coastal frontage,464 km)
Power density, 5.31 x 1o*8 Money equivalent Source 10'8 kcal/ year kcal m*8 day-' billion 5/yeart l:rce Wind' 12 0.6 0.6 Productivity of land 8 - 375 19.R 18.7 Productivity of estuary out 5 miles
- 33 1.8 1.7 Sun's heatrng. 2* gradient
- 470 25.0 23.5 Tides 8 1.6 0.08 0.08 Waves
- I 0.05 0.05 Subtotal free 893 47.3 44.6 Ikught Power-plant fuels Crystal River' ! .2 0.06 0.06 Others' - 38 2.0 1.9 Natural gas' 55 2.9 2.7 Motor fuels 34 1.8 1.7 Suhtural hought I30.2 6.8 6.4 Total 1023.2 54.1 51.0
*Necesurity a preliminary :alcr!ation with data of varying certainty.
12 x 10* kcal/5. ~ Notes: I. WinJ: 5 mph at lu* cm; eJJy diffusion,10.000 cm /sec; 8 air density, 8 1.2 x Ier8 g/cm ;44.7 cm/sec per mph; 3.15 x 10'sec/ year; 2.39 x 10-' ' kcal/ erg; regional area, 5.12 m 10'
- sme ,
(1.2) l($ Ho 447)I 8 (2.39H 3.15H 5.12)(Il gg u 10', kcallycar
- 2. ProJuetivity of land; productivity, 20 kcal m*8 day: 365 days, area. 5.12 x 10
mr8 (2.0)(3.65)(5.3 2) x 10' 8 kcal/ year ( 3. Productivity of estuary out 5 miles: area,464 km of coast; M km width; productivity, i 24 kcal m'8 day; Io' m 8/km ; 365 days. I (4.64HR.0)(2.4H3.65) a 10 kcal/ year , 4. Thermal-gradient' work from sun's heating: insolation,1.4 x 108 kcal m'8 year '; *
'Carnot ratio,2*/3thf'; area,5.1 x 10 m 82 II-122 m
5 , . w * . ENERGY COST -B ENEFIT MODELS 633 TABLE 1 (Continued) (1.4 H 2 H 5.1) x 10 kcal/ year
. (3.00)
- 5. Tides absorbed in zone to 5 miles: 100 cm/ days gravity, 9MO (m/sec 86 365 days:
8 denuty,1.020 g/cm8 ; 2.38 x 10- kcal/ erg; 3.72 m toi: sm : ( 3.65)(1.020H 2.3 M K 3.7)(9.8) ' x 10' kcal/ year . 8 8
- 6. Waves: 50 cm high; gravity,980 cm/sec :Jensity,1.02 g/cm : length of coast hne, 464 kna 2.38 x 10- kcal/ erg; 3.15 x 10' wc/ year; velocity of waves. I m/ws; energy per area of wave, a gh8 /H:
( 5.o n8 (9.8 H 1.02 H 4.64 H 2. 3 N H 3.15 H 1 ) x 10' kcallycar , (81
- 7. Crystal River power inflow- 0.08 x 10* kW; 80% of capacity; cfficiency,40";.;0.239 kcal sec kW"; 3.15 x 10' wc/ year; (0.0M HO.M)to.2 39 H 3.151 s10'8 kcal/ year
- 8. Other power plants: 2.54 x 10' kW,80% of capacity; cfficiency, 40%; 0.239 kcal/kW; 3.15 m 10' welycar:
(2.54 HO.8 HO.2 39 H 3.151 x 10's kcallycar
- 9. Natural gas: 3.62 x 10 ft 3/ year in Florida; 450 kcal/ft'a 34% of Florida population.
(3.62)(4.50HO.34) x 10' 8 kcal/ year 8
- 10. Atotor fuels 3.215 x 10' gal; 34% of population of Florida in the region; 3.86 x 10 cm / gal;10 kcal/g,o N gism8 .
8 (3.215)(0.34)(3.86HlHO.R) x 10' 8 kcal/ year = 34 x 10' 8 3 7- 7 X 103 Leal 3.5 x 10' m 3/ day Power contributior. = 300
. m
= 5.7 x 10' kcal/ day (2)
If the depth Of thc estuary over which the circulation is distributed is 1.5 m and if total flushing results in estuary turnover four times a day, the areauf the estuary receiving the plume is 9.2 x 10' m2 (discharge volume divided by depth l 2 II-123 . 1 l
-4 _ _ _ . . . ~ - -
J
; - e6w- - - ~~ - . L-- - - - - - - -
634 ODUM
. TABLE 2 ENERGY FLOWS IN ESTUARY AT CRYSTAL RIVER OVER
. AN AREA AFFECTED IN 1 DAY (9.2 X 10* m2 )*t iteen ' Lcal m-a day 10* kcal/ Jay Metabolism (Jay proJuction plus night respiration)' 2H 252 Tidal energy almorbed' ~ U.ONS 0.M Wave energy alnorl*J' 2.5 23 Solar energy absorbed and connectcJ to potential energy of thermal gradiens' 27 249 Plunw potential energy' 62 570 Plume consumption (canal metabolism)* 1.3 12 Plume Linctic energy tuntribution' O.2 2 Energy to teplace 20*. plume rooplankton' O.2 2 Cooling tower (55 x 10' year) 30.5 275
*All numbern are tentative pending improved data, 11 actors to divide into production rates to get fouil fuel work equivalent are still tentative and urre not apphcJ here.
Noter
- 1. Metabolism frnm S mith et al. (this volume) times 4 kcal/g 02 .
i
- 2. Tide. I m/ days see note 5 in Table I; this area U.0IM%.
- 3. Waveu 30 cm high. grmty, 980 cm!>cs'; density,1.02 g/cm'; 10 km of scant; 2.38 m lu Leal /crg,3.15 m lu' seei> car, ss-L>su), I rni ce; 365. lays /> car; 8
(31 (9.M H l .02 H I H 2.3 H H 3.15 H I ) ,
, ,9 (M)t).65)
- 4. Inwlanon,4000 Lsal r(8 day, multiphcJ hy Carnot ratio 2'/300*.
- 5. Thermal-plume potential energy 3.5 x 10* m'/ day; Carnot ratio, f/300*,7 x In' kcal/m 8hea t .
(3.5 H 7 H 7) 10'
-(3)(9.21 x p kcal/ day
- 6. Metabolism of canale intale canal f(1.9 g m'8 day ~'H3 87 w 10' m')) plus escurrent canal H 19.2 g m'8 JJy Hl.15 x 10' m')] = 2.95 x 10' g/ day x 4 Leal /g = 12 x Iu' Leal /
Jav.
- 7. Kinctic energy of plume: 1.02 g'em's 10 cm/m. 3.H x 10' m'/ Jay; 225 m' crow mtion 2.39 x 10-' ' kcal/crg; M.6 x 10* sec/Ja3 :
H 3 M x lu' a y g gy,, p 3 g , 39 3g,g3,9 : 21 f(2.25 x lo3HM 6 x 10* )]
I" k '8 H. (4 kcal/ GNU.067 g/m' biomaw rouplanktonH 3.M x 10' m'/JavHo.20)
, lu*. citiciency of replasement .
= 2 m lu* Lest/ Jay 9.Coohng tower: 55 m its*ycar,2 x lu* ksal/5; 365 dayt 5 H 2) x 10' Leal / day 3.65 g , , , *
, . +*
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L' ENERGY COST-BENEFIT MODELS 635 Clb '%lrHLACOOCHEE river , CROSS FLORtDA BARGE CANAL c0 co
. DISCHARGE B AY
,***,I
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L _ _ _ _ _ _' 2_21"I'S'N 1 F PC PLANT
- -~~
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,'r, CONTROL ARE A 3
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CRYSTAL RIVE R Fig. 3 Estuary at Crystal River, Florida, showing intake and outflow canals from plants of Florida Power Corporation, times 4). On an area basis, the potential energy of the thermal-heat contribution is obtained by dividing the di..y power flow by the area (Table 2).The result is about 62 keal m-2 day which is twice the ecolog;eal rnetabolism (daytime net photosynthesis plus nighttime respiration) of 28 kcal m'8 day (Smith et al., this volunw).- The procedure used here prorates the power delivery into work over the area of the estuary in which it is absorbed during the same period. The 62 kcal of work coninbuted from the thermal gradient per square meter per day can be
-II-125
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II-126
I l ENERGY COST-8ENEFIT MODELS 637 called power density, llow the thermal-gradient pore::ial energies are being delivered into work is not known ex: Jy, but they undoubtedly are doing extra work in the estuarine circulation, in sea-air craporation, as well as accelerating biological pmcesses. Whether these substantial energies are positive or negative is not determined by this calculation. Lotka's principle suggests that selection adapts physical and biological associations into a system that maximizes the use of available energies. One may therefore expect the adapted ecosystems developing after 6 years of this thermal regime to have maximized some possibilities for use of the special energies. Direct examination of the energy flows of the ecological system was made to test these properties. ECOSYSTEMSIN THE PLUME AND ADJACENT COOL AREAS The power plant at Crystal River discharges its thermal plume into a shallow tidal estuary that turns its waters over several times a day owing to tide, runoff, and plant plume flushing. The outflow (Fig. 3, upper arrow) crosses an inner bay with bottom plants and animals and an outer bay that has more plankton metabolism. The levels of productivity and respiration of these waters are about
-2 5gO2m -2 day ind winter and 7 g 02m day" :n summer (Smith et al., this volume), not measurably different from the areas studied to the north and south of the plant. Apparently the ecosystem, now adapted after 6 years of receiving the plume, is as productive and doing as much ceokigical work as the cooler systems around it. In summer 197 3 metabolism was one third less.
Species diversities were estimated for animals (Table 3) and zooplankton (Table 4) on the oyster reefs in the plume area. The similarities of numbers in the waters near and away from the plume suggest that the general variety and quality of the ecosystems are similar. S. Snedaker, studying bottom animals and fishes, reports similar stocks and variety in these ecmponents of the biota. Apparently, within the limits of error of these comparisons, the plume system now has an ecosystem equally viable to that of the north and south. Final word on this depends on completion of annual studies that are now in progress. THE POWER PLANT AS A LARGE ORG ANISM IN THE ESTUARY From measurements of changes of oxygen as water passes through the canals, the ecosystems of the canals m:re found to be like other rocky substrates exposed to current. They consume more than they produce and serve to recycle nutrients as if they were a big consumer (Smith et al., this volume). Included in the metall effect was the consumption of the intake and excurrent canal and the export of plankton damaged but not consumed within thecanals. The plant's overall metabolism was estimated in Table 2 at 4 million grams of organic matter
!L II-127
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. c;.-a jur. ~- ; c1 _a __~ . _ . _ . .
33 -
+
s ' GS ODUM TABLE 3 SPECIES DIVERSITY ON OYSTER REEFS *t
., (Species found while counting 1000 individuals)
Descharge ares Control ares 8 12
'l3 to I4 15 12 17.19 16 13 13,13 12 Mean 12.6 13.6 S.D. 2.44 3.03
'S.E. 0.921 1,362
' Data by M. Lehman at Crystal River, January-February 1973 (thesis work in progress),
tihe results of t-tests on the mean values of spesics per thousand indicate no significant difference at a 95*. confidense level between the two areas. TABl.E 4 ZOOPLANKTON DIVERSITY, JULY- AUGUST 1972t (Species found while counting 1000 individuals) Stations away Stations near plume from plume 24,20,19,21 25 20 23 9,27.31.18 33,18.25.24 lM IM 19 Mean 19.8 22.7 S. D. 1.36 1.15 S. I:, 0.60R - 0.676
' ' Data ley C. Sirnon at Crystal River, who uwd a No.10 net.
tF. Maturo found 22 species per Immi in a Decemlier 1973 wries taken over 24 hr near the mouth of the intake sanal. s40 ^ a >a.s... d-128
=
m
. . . < .s . .
ENERGY COST-BENEFIT MODELS 639 (or oxygen) per day. Since the c<tuary has an average daily metabolism of about 7 g m-2 day, the plant was equivalent to 135 acres of bottom ecosystem. The enerFy involvement (notes 6 to 8 in Table 2) was 16 million kcal/ day (5.8 bdlion kcal/ year)..The energy involvement in plant consumption was found to
. be less than that of a coolitig tower.
An energy involvement that serves as a consumer function may cither stimulate estuarine metabolism or be a detriment, depending on the relative shortages in the balance of production and respiration. Many ecosystems are limited by the effectiveness of their consum-r recycling and are aided by added respiration. PERSPECTIVES ON ENERGY FLOWS IN THE ESTUARY Energy flows characteristic of that area of the estuary which is involved by a day's circula_ tion of water are given in Table 2. The area was determined as the plume discharge divided by the average depth of 1.5 m of the inner estuary and multiphed by the number of dilution turnover times due. to tides and other circulation. The basic natural processes of metabolism and solar heating, tide, and waves are much larger than the plume's actions of consumption, stirring. and disruption of zooplankton. The thermal energy of the plume is large enough to make a large contribution to the estuary, but, since observed metabohsm and diversity are'similar to that in other areas, this energy is apparently being harnessed as much for biologically favorabic effects as it is for negative ones. ENERGY COST OF COOLING TOWER An .lternative to the thermal plume is a cooling tower, which is estimated to cost at least 5 million dollars per year, including maintenance and capital costs. A diversion of this much money involves the development of work in economics elsewhere which ultimately provides the materials and services for the tower. lf no tower were budt, these funds could develop another energy-flow system in the immediate area. The energy diversion is several times larger than the energy impact of the plume estuary (Table 2). The energy cost of the tower is several times larger than the enerFy consumption of the plant and canak. A tower
- would . pass the large plume potential energy into the air where other environmental chaages and adaptations would result.
l PUSH AND PULL MECHANISMS OF THERMAL ACTION Discussions of the action of temperature on complex hving systems are often begun by considering molecular processes that charuterire the many txochemical pathways of an ecosystem. Increased thermal energy increases the l 1 l l II-129 l i i l 1 ~ , . . _ . _ _ . I
;aam my Awa;. r: .~ , s a . *
. z.
mQj.[j:( -- -
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~
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- numbe of _ energized molecules with energies of activrtion that exceed 'the '
. energy barriers for reaction according to the Maxwell-Boltzmann distribution of energy around molecules. Such theory _ accounts for heressed reaction rate (J)
_.with temperature (T_),uften described as the Arrhenius & tion,
- J = Ne-E/RT , (3)
.where E is the free enerly of activation of the reaction's energy barrier and N
~ and R are constants. Pre. esses that make a hving sy stem's processes go faster can have beneficial temperature effects unless the process is one that drains structure and reserves. -
s The structure that constitutes ecosystems is low in entropy state, has its own stored potential energy values, and, as required by the second energy law, tends to drive _. degrading entropy-increasing structural-dispersing actions that are
. accelerated by higher temperatures. The Eyrings (1963) combmed the action of -
temperature in accelerating rates of reactiu. .vith the acceleration of tempera-
~
,ture in degrading the protein enzyme structure that was supporting the reaction.
- The result is Eq. 4, where AF is the frectnergy difference in structural protein and its denatured state A model'of this system and an analog simulation are shown in 1ig. 5. For some settings, J increases with temperature over the usual hvi_ng range and then precipitously' declines at higher temperatures,' as in the
.evample shown, c'-
N + e+/RT I4)
- 3*1+e .M / M T Morowitz (1968), considering the range of temperature in which hfe and
- ecosystems. operate, suggests- an L order function that is the ratio of the -
llelmholtz free energy of structural storage to the thermal energies stored and contributing to disordering.
-AA I"W (5)
Lwhere k is the Stefan-RoltzmJnn constant, llis model is expressed in energy
~
symbols in I ig. 6. The etfect of mixed energy resources in favoring the structural E forming tendencies (measured by the numerator) is directly related to 'the tendencies for temperature increase to disorder entropy structure (as given in the denominator). Morowitz states that this function increases with energy to a E imaximum and then dechnes because there are bounds to storage of potential y energy in chemical form at high temperature. _ These theories indicate that, even at the simplest levels of maintaining chemical structure, there 'are push and pull actions of temperature on structure. l 3
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II-130
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. s 641 ENE'RGY COST-SENEFIT MODELS A,-annt
.,n r DENANRED ENZYME ENZYYE ENERGY w SOURCE
\ A '
/ /
Y-
-==~
(a)
,-a. ,n r J
u T (b) Fig. 5 Energy circuit diagram of the Eyring model of the effect of tempera-ture on reaction raw direcdy and through its action on denacuration of enzymes. (a) Energy circuit diayam. (b) One representative analog simulation in which the steady-state values are scanned in an x-y plot as a function of temperatuce. See appendim for identification of symbols, the ultimate effect of temperature being the net balance of these actions. Between the considerations of molecular response to temperature and the level of overall ecosystem response are hundreds of systems interactions.These draw their temperature actions in part from their molecular or environmental parts but may combine them in ways that produce quite different results. For example. Kelly (1971) did analog simulations of temperature action in several basic ecosystem population models. In one of these the temperature action of a pathway into storage was the same as that on the outflow pathway (Fig. 7).The II-131
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~~
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L=$ L' = d'; Fig. 6 Energy-circuit diagram of the balance of order and disorder as formulated by Morowiti (1968). Two quedents (Land L')used by Morowitz to characterise ordering tendencies are shown as being calculated widi an outside enngy source. See appendix for identification of symbols. Steady states for different input energies generated on an analog computer by Tim Gayle showed a masimum. e t'ni T O k i k2 g.
/
Fig. 7 Model in which Kelly (1971) found a canceling effect of temperature on structure bi spite of accelerated energy flow. See appendis for identifica-tion of symlools. 4: e , .f ..t. o , , a s . *
- s .^~~
11-132
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ENERGY COS1-8ENEFIT MODELS 643 action of temperature on the storage ues canceled by a balance of input and loss. In any surviving system the inflows of energy must more than make up for any increased drains due to temperature. Control mechanisms have evolved, for all sites of living systems from molecular to ecological dimensions, for accelerat-ing energy input to keep up with energy degradation.The essence of this mecha-nism which must necessarily accompany adapted syst ms is given in a modified self maintaining module (Fig. 8). The adapted system must adjust input energies to equal drains. The function of the degradation sensor is to controlinflow and is equivalent to multiplying the input-energy forcing function by the square of the structural storage (Q). Kelly's (1971) simulation (Fig. 9) shows the degradation-sensed simulation model to be stable with relatively small variation from fluctuating temperature.This model resembles one by Von Foerster, Marx, and Amiot (1960) in having a square effect of structure on growth, although Von Fcerster's had no energy-limit considerations (Fig.10). A more general model is given in Fig.11, which has disordering effects of 5 - temperature coupled intimately and simultaneously to the positive growth part of the system. This model also has a constant-flow source of energy rather than an unlimited one. Also included is a cycle of materials (nutrients, for example) whicn are incorporated in growth and released by temperature stimulation of decomposition. Provision is also made for external inflows and losses of nutrients. I O
,.s n r
/
x % T
\/ \/
3 ] , t x
)
i i Fig. 8 Model of temperature action (T) on depreciation of structure which is sensed and coupled to proportionately increase order generating input pathways. See appendix for identification of symbols. II-133 l
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$. fluctuating temperature-N l l d 28 56 12 5 25 3 TIME, see TIME, sec
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._ Both Botn constant fluctuating
_ _ Fauctuating mout. _ comtant temoevature
! l 12 5 25 12 5 25 TIME. see itME, sec (b! Idi Fig. 9 l'our simula tions of temperature action un the structure of a self maintaining unit with model like that in Fig. 8 (modified from Kelly, 1971). (a) Example in which more structure and earlier stabilisation occurs with higher temperature. (h) Growth with constant temperature (T) and input encrey til compared with growtit under conditions of sinusoidal input simu sting diurnal effects. (c) Temperstare as sine wase but input energy constant. (d) Growth when inpus energy is sinusoidally saried but temperature is constant.
Gnen in l'ig.12 are some responses of the modelin l'ig.11 with coefficients appropnate to ihe ecos) stem in the inner bay at Crystal itis er (1:ig. 4). At higher temperatures and low nutrient condition, there is more metabuhsm but smaller mm. Storages there are large enough to make the^ system stable, although the model was made to owillate by making turnover times small. When a nutrient inflow is supplied to the high-temperature system, productivity rises and structure may increase. Models with recycling pathways of work and materials provide more of the mechanisms denloped by natural surviving systems for adjusting input coeffi-cients to system needs. Recychng of matter and work is equivalent to multiplicarnt adjustments of input coefficients to masimize functions favoring I s , , , - II-134
I I 645 ENERGY COST-BENEFIT MODELS 0
/
X 2 e 0*g0 p,,, Fig.10 Energywitcuit transladen of Von Foester's (1960) model for growth of the United States, which assumes unlimited energy See appendis for identificadon of symbols. s NUTRIENT SOURCE O 0
/
UU<X X STRUCTURE D HEAT HEAT OR RED - p MATTER f'
=-
Y f SUN \ X X 5
/
Fig. Il A model of thermal effects on ecosystems, including thermak sdmulated ordwing, disordering, recycling, and facilitating roles of external inflows of light and heat advections and nutrients. See appendis for identification of symbols.
. II-135
pagn ,,
,2 gg _
;3 W
. 646 ODUM suuctu..
s ~ suoctu . wl. ,t, Qute.ents Pfoductively Pt lutteesty p T T (a)- (b)
. Fig.12 Two analog-computer simulations of the model shown in Fig. II.
Steady states are riotted for sarying temperatures of the hot-water inflows ta) No nutrient infinw or nuttlows th) wmc nutrient inflow and outfluw. survival bf structure, lierter recycling at higher temperatures may reduce effects of hmiting nutrients (Young, this volume, and Smith et al., this solume). Prehminary simulations of temperature etfects on subsystems at Crystal River have been made (Young, this volume,and Smith et al., this volume). Each had recycle and push-pull temperature actions. These systems showed con-siderable stat,....y ' and no elcar-cut . indication of - detriment to ecological
. structure in the range of temperature observed at Crystal River.
At this stage of our knowledge so many temperature effects are known that one - may be hesitant to assept' simplistic oserall models to preact the phenomena of 'an estuary, llowever, such models may be helpful in under.
'standmg how and why the Crystal River estuary can maintain viable ecosystems at various temperatures A characteristic of the concept of temperature action as a push and pull on strusture is the dependence of the ultinute result on energy supply to the push -
actinn. If potentui energies are large and increase along with temperature, the dange in' heat' nuy generate more order; but, if the energy sources are restructured constant, or declining with the added heat, the action on structure is only negative. The model in l'ig.12 aho shows the nutrients lieing recycled laster at higher temperature. THERMAL MICROCOSMS 7 Perhaps the best examples of temperature regulation by whole ecosystems are those derived f rom studies of microcosms that were adapted at various temperatures and thme adapted at one temperature an i exposed to temperature changes. , I reshwater microsmms showed little change in metahohsm with teinperature changes (Itcycrs, 1962, 1963). Microcosms from the rain forest
^
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s . .,_ .1 I 11-136
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./
. _ . .=
1 1 1 3 - , im - ENERGY COST-BENEFIT MODELS 647 which were exposed to varying temperatures had metabolism similarly un-responsive to temperature (Cumming and Beyers,1970). Long range temperature adaptations were studied by Kelly (1971), who exposed freshwater microcosms in growth chambers to fluctuating and varying temperatures. lie observed a succession and evolution of ecosystems producing adaptations in metabolism and diversity proportional to the average tempera-ture. With analog-computer models of photosynthesis and respiration, Kelly was able to simulate the diurnal and successional aspects of the r.etabolism of the microcosms. Apparently, the simple modeis with a few characteristic pathways summarire the main classes of interaction that in the real world involve billions of duplicate pathway actions of similar type. In other words, a single Alichaelis Atenton action can be used as a model to simulate billions of such mechanisms that are in series and in parallel to form the real system. Aietabolisms of microcosms subjected to the same genetic seeding but adapted to different temperatures were similar, although different organisms produced the adapted ecosystems (AteFarland ard Pickens,1962). Blue-green algae dominated the high-temperature systems. If the selective adaptations adjust to the energy needs, then basic energy models can be predictive without specifymg the kinds of living components. A1odels of thermal and ecological mechanisms help us to understand the often observed adaptation to increased temperature which sometimes results in increased productivities and changes in diversity. The generally higher diversity of. some tropical waters is a possible example, although the stability of the temperature regime may be responsible in part. A famous example of temperature adaptation was Tamiya's (1944) pilot plant with ChlorrIta at different temperatures. Ile had a thernul-mutant strain in the plant with the higher temperature. Both the higher and lower temperature systems were 'similar in pho osynthetic efficiency, each adapting with its associated microbes and cycles to make similar usage of the light.
' Another example is the study by Duke (1967) of the productivity of natural hot springs in western Texas. In steady temperature of 59*C, she found regular patterns of photosynthesis with photosynthetic production of 4 to 7 g m-2 day
t
SUMMARY
-ECOLOGICAL ENGINEERING OF THERMAL ADAPTATION Our models, microcosms, and perspectives on the system of living and nonliving components suggest means by which the energies of thermal plumes may be tolerated and perhaps used by adaptive self-designing ecological systems,
.naking special and expensive technologies, such as cooling towers, unnecessary waste. Since one can also imagine circumstances where energy requirements for adaptation are higher than the energy resources, direct measurements of indexes II-137
~ _ , -
mp mg.,ww. a;u ~ n .w - ... ~a . . - - -- 448 OOUM of adaptation are required to verify the quality a- 'sohsm of the adapting ecosystems that develop 'to form a partnershi, . ntan's technology. The energy cost-benefit calculations are useful to show relative costs in units that affect the tr>tal public welfare in ways that money alone does not. ACKNOWLEDGMENTS
- This paper includes work sponsored by a contract with the Florida Power Corporation and work sponsored by contract AT(401)-4398 with the Division
. of Biomedical and Environmental Research, U. S. Atomic Energy Commission.
Comments of associates on these projects are gratefully acknowledged: Chester Kylstra, Sam Snedeker, Wade Smith, lienry McKellar, Donald Young, Melvin Lehman, Michael Kemp, and oth:rs, REFERENCES
~
lleyers,' R. J.,1963 The Metabolism of Twelve Laboratory Microecosystems,1: col. 4fonogr., 33,281 306. 1962,' Relationships lietween Temperature and the Metabolism of Experiments. Ecosystems .Ncicurr, 136 940-982. Cumming. F, P., and R. J. licyers,1970, Further Laboratory Studies of Forest Floor Microcosms, in A T ruptcall(arn Forest.11. T OJum and R. F. Pigeon (Eds.), pp.154 'a 1-56, U.S. Atomic Energy Commission, TID 24270 tPRNC lJNL Duke, M. E,1967, A Production Study of a Thermal Spring. Ph. D. Dissertation, The Universey of Texas. Fyring,11., and L. M. liyring.1963 Afedern Chemical Kinciscs, Van Nostrand Reinhold Company, New York. Kelly, K, A.,1971, The Effects of Fluctuating Temperature on the Metabolism of Laboratory 1:reshwater Microcosms. Ph. D. Dis.ertation, University of North Carolina.
' Mci arlanJ. W., anJ J. Pickens,1962, University of Texas Institute of Marine science, Port
- Atansas, unpublished report to National Institutes of Ilealth.
Morowits, s' J.,196N,1 nergy lluta in itialogy Academic Press, Inc., New York. OJum,11.T.,1973, An Energy Circuit I.anguage for Ecological and boeial Systems: Its Physical Baus, in Systems Analynn and Sunndarrun en i cology, BernarJ C. Patten (EJ.), Chap. 4, pp. I 39 2 t l, Academic Press, Inc., New York. _,1971,0.nvervument, Puterr. and Socorry, John Wiley & Sons, inc., New York.
,1967. Energetics of WorlJ Food Production,in The World FooJTroblem. A Report of the PresJent's Science AJvisory Comnutte, Vol. 3, pp. $$-94 The White liouse.
lannya, 1944, Growing Chlorella for Food and Fred, in ProcerJwgs of the norld Symposinm on Appised solar tnergy, Pburnux, Arnon.e. pp.231 241. Von Foerster,11., P. M. Marx, and W. Amiot,1960, Doomsday; l riday,' 13 November A.D. 2026 Arsence, 132, 1291 1295. II-138
w e ,. ..- .. .u . . . ., _ , . ,,, , 649 ENE 4GY COST-8ENEFIT MODELS APPENDIX: ENERGY. NETWORK SYMBOLS
- Amplifier Enternet energy tource 9F Energy storage and its inherent cost Energy recetwer e th Constant amount of recycl ng material 9 P-Heat unk
/
II Aggregated syribol for self-maintaining system 9P Aggregated symbol for system
/ running on sunlight Symbol for cecessary inieract.or of two Pathway with an energy barrier different kirids of energy flo*5 preventing back force or flow I\
h) )*
,/ i, 9F ?P Combenation of inter actions Econom.c transactor
' Adapted from Odum (1567,1971, and 1973). Letters used on symbols in the figures are defined in text.
l l l
.II-139
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APPENDIX A2 STUDIES OF FLORIDA GULF COAST SALT MARSHES RECEIVING THERMAL DISCHARGES DON L YOUNG Departinevit ut hnvirunenental I ngineering $siensen. Univer.ity at 1 lorida, Game.ville, a lorida ABSTRACT Two Florida Gulf Coast malt triar hcm werc .tuJacJ over an annual c) sic to Josument nur.h c6ussstem re.ponse to thermal addition. f rom an elettrkity generatmg mission. The overall nursh metabohsm, insluJang plant proJuction and respiration, and utesicJ ammal populaima numbers were 6hown 4. mJasatoro ut the impast of thermal addition Water temperature m the thernully attecicJ mar.h averagcJ J to #C w4rinct than in the neart y somrol nursh. 'I he nuxemum water tempcraiuscs resorJed Juring the 6umms<r were 37' m the thermal marsh and J2*C in the sontrul m4r.h. The apparent net proJustwn c41su-lated f rom mes.urements of monthly thanges in Sparrsna aircrusflers live ansl .icast standing s tops, mstuding $stimati . of dstomposnion and export Jurmg the sprmg growing sessun (i vbruary .\14y),8 wa. $47 g (dry weight)/m' m the thermal pur h, comparcJ with 282 g (Jry weightum in the suntrol mar sh. The sommumty metatioli.ni int asurernent. perturnwJ with CO, ga.-analy.i. cijuipnwns in .\ tars-h 1973 inJasate sommunity respiration of S 7 8 g (: m Jay ' m the thsrmal marsh and 2 21 g (: m J4) ' in t he sontro nurshes The overall clicct of higher water ternperature appcars to be higher levels of' organtic-rnatter turnover. and nwtabohim with a ratio ashieved betwcen pruJustion and respiration whish is similar to sontrol nurshes. Populatwn comparison indisats no >>gmtkant dif ferense m snail numbers, ahhough fiddler rab appear to be 16 s numcrous in the thermally aftesteJ mar.h. This paper prmedes information to land planners on the structure and f unstion tif J Florida salt marsh toastal ecoy stem and its conditnin after 5 3 cars of adaptation to thermal loadmg f rom a cimtiguous electricity-generating station. Detidon makers and coastalvonc resourse managers are responsible lor mter-facing man's high-energ) systems, which are subsidierd b) large quantitics of fossil fuels, with the natural coastal crosystems maintamed by natural energies. Planning success can be ensured if the evolvmg systems containing both man and nature are designed to provide that combinaticm which maximites the value of the region under consideration (ll. T, Odum, Littlejohn, and lluber,1972; and Bayley and Odum,197D. Such a goal in planning tequires knowledge of the 532 II-140 l
m s .:. FLORIDA SAL.T MARSHES 533 structure and function of natural ecosystems, their role on a regional scale, and their response and adaptation to man induced perturbations; decisions of resource allocation without such knowledge are tenuous. Florida is currently experiencing intensive growth and development within its coastal zone, and a by product of urbanization is waste heat from industrial-plant processes and electricity generating stations. One of the aspects of importance to planners in Florida is the interaction of thermal plumes entering coastal salt marshes. Murray and Reeves (1972) point out that more saline water is used for cooling purposes in Florida than m any other state. They estimate that 9.3 x 10' gal of heated water per day are returned to Florida's estuaries. As of this writing approximately 25 coastal power plants are in operation and roughly 20% are sited in or near tidal salt marshes (Florida Division of State Planning.1973). Eighteen percent, or 129,000 acres, of the Florida Gulf Coast estuarine zone described by McNulty. Lindall, and Sykes
- (1972) is occupied by tidal salt marshes. A comparison of the areal extent of marshes in Florida to other castern states (Teal and Teal,1969; and Day et al.,
1973) reveals Florida as second only to Louisiana in total tidal marsh acreage. Because of the recognized importanee of coastal marshes in supporting marine food chains, in building up the land, in serving as greenbelts, and in providing shelter from storm surges, questions arise as to the impact of thermal discharges on the marshes. IJnder new regimes of elevated temperature, are the basic structural and functional processes of the marsh ecosystem altered? What are the self-designing adaptations used by the new system for its long term survival? What is the value of the new, adapted system to the larger system of man and nature? Indexes of ovn.'l community structure and metabolism were chosen as parameters for evaluating the effect of thermal discharges. Discussion in this paper is limited to effects on Spartina altennflora. Monthly harvest samples of Spartina standing crop, in situ infrared gas-analysis measurements cf metabohsm, and htter-bag experiments were undertaken to investigate the effect of heated effluents on standing crop and net production, respiration and total metabohsm, and decomposition, respectively. Comparisons were made of the above parame-ters between thermally affected and control marshes to determine the Icvel or quantity of biological activity m each. If differences in commumty metabolism are observed, insight may be gained as to whether thermal plumes act as a stress or a supplementary energy source to the marsh community, in addition, surveys of the population densities of marsh snail, Littorina, and fiddler crab, Uca, were made in each marsh to obtain information about the ab.hty of these two
' invertebrates to tolerate elevated temperatures.
SITE Studies were carr ed out at the Florida Power Corporation Crystal River site near Crystal River, Fla. (Fig.1). Florida's Gulf coasthne is a low-energy coast of II-141
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4 WithidCWw Cevissi p O %er %er Power "I'%e Psang l F lorici. O 100 8,, Meies a Can,s Ares ] (Contron # idi Area 1 (Tne,m ,y, AHateo h M*'Sh3 0,wn,, Canas \ -- _
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FPC Pow,,
~ A'ee 3 ICOntrofl ent.n* r banal Gulf or Mr..co o ,- >-
c:.. ce,er, Q
-.A %
' 5'*nderd M.se Fig, i tal Lutstion of the Florida Power Corporation Crystal River site.
'(le) Octaib of the marsh nosystern in the wiinity of the plant, in=luding esperimental study arves 9
II-142
p s -- g 3, m A , , r
*a3S FLORtDA SALT MARSHES
. mixed tides (tides are semidiurnal, but highs and lows durmg the ume day are us
- unequal amplitude) the mean tidal range at. Crystal River is u.70 m (2.5 to. In 1972 and 1973 two oil-fired steam plants, with a combined nuximum capasity of 897 MW, were located at the landward edge of the uit nursh. Scauater trum the Gulf of Mexico was used as condenser coolant at a rate ut 242iim'imin
. (640.000 gal / min) in a once through cooling scheme. Seawater is cuculated through a system of two canals dredged through the marshes; water is drawn from offshore, passed through the condensers wi*h a maximum temperature rise of 6*C, and discharged into a shallow estuarine bay (Fig.1). Durmg periods ut high tide, the thermal effluent is backed up into the rnarshes to the noith of the mouth of the discharge canal.
An area of nursh immediately north of the mouth of the discharge i azul wa-designated as the thermally affected study area (area 1 m Hg. I on the hasn..i a hydrological studies by Carder (1971,1972). Carder demonstrated that significant portion of the thermal plume is pushed unto these marshes by high tides and that cicvated temperatures in the marshes bordering the bay asc h:phni there. .Two control areas (areas 2 and 3 in Fig.1) ucre established sur comparative purposes in areas beyond the influence of the plume to the noith and south of the canal complex. Water-temperature measurements ubtamed m the thermally affected marsh averaged 3 to 6*C warmer than umilar measure-ments in the nearby controls. The maximum water temperature observed un the thermal marsh by Carder and confirmed with independent measurements during this study was 37*C in the summer. Both the designated control areas and the thermally atteeted maish appear to be typical of the marshes in the Crystal River vicinity. 'l hey are shaiacterwed by approximately the same elevations and floristic compositions, with Nuerma commonly found at the seaward edge of the nrarsh and along creek banks. 'l he control areas and the marsh are washed by the tides twice a day. METHODS Field collections and measurements began in June 1972 in the thermally affected marsh and in Septe eer 1972 m the control marshes. I he slip quadrat. or harvest rnethod, was used to estimate standing crop and, later, to citimate net production of Spartina. This method is applicable to vegetation that exhibits an annual pattern of minimum standing crop in the spring, with assumulated inc standing ' crop reaching a maximum in' late summer (E. P. Odum,1971t and 7 Keefe,1972L The amounts of live and dead standmg crops were momtuicd throughout the growing season, and the sum of the increases in the amounts of t live and dead organic materials is indicative of net community produstion. Estimates of losses to herbivory and export ot materials permitted cal 6ulations of net community production and the refinement of citimates of net prnnai) production. Nine randomly selected samples of aboveground vegetation tquadrat
' size = 0.2 5 m* ) were removed at 4- to o-week intervals trum the theinull) 1-y 11-143
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-i7 S36 _ YOUNG.
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affected 'and the control marshes. Collections from each control area were taken at ever; :*mpling interval and pooled to achieve a composite control sample size of nine quao J.s. Each sample was separated by species and live and dead
; fractions,' dned to constant : weight at 70*C, and wei,;hed; the results were muhiphed by 4 for conversion to grams (dry weight) per square meter of marsh surf ace. Stem densittes, expressed as stems per square meter, were obtained by countmg hve and dead stems contained within each quadrat samoted.
In situ gas-exchange measurements were made in the field during early March 1973 to obtain comparative information concerning the levels of total metabohsr.s of both marsh commumties. This method estimates total metabo-lism by monitormg the concentration _of CO2 -in air entering and leaving a rigid transparent shamber that enclosed the marsh grass canopy and was scaled at the mud surface. Since this technique enclosed a portion of the entire community, results showed the integrated response of both producing (CO fixing) and
- consuming (CO releasing) corr.ponents of the system. Production included contributions of the higher plants, periphyton, and mud algae. Consumption or respiration of the higher plants, algae, microbes, and ammals hving in or on the dead plants and mud surface constituted total-system respiration. These measarements represent metabolism of the entire community and the soil, l'xperiments were conducted for o days (March 3-9) in area I and for 5 days
- (March t !-16) in are4 3. Since gas-analysis techniques monitor only the metabolism of the system exposed to air, concurrent measurements by other i
techniques must be made of that portion of the system covered by water to esumate total me'abohsm during high tides. No sampling ot' the water column was performed in March. Details of the complete sampling apparatus,includmg sensors, pumps, valves,- recceders, and timers, have been described by H. T, Odum (1970) and Lugo (1969). Calculations of diurnal rates of photosynthesis and respiration were perf ormed using the techniques and formulas outhned by Odum (1970). A brief mention of the gas-analysis methods in this paper will suffice because of the large amount of data collected and the necessarily limited interpretation allowed as of this writing. These initial reported values are important for meerpretatio.. of the other ficld measurements, but they should be considered by themselves - preliminary. f inal results of these expenments will be published at a later date. Studies of decomposition rates of Sp.trtin.e in the thermally af fected and the control areas were begun in Febrt.ary 1973. Fresh live plant material was pthered and allowed to air dry for approximately I week. Litter bags measunng
'15 cm wide and 70 cm long were constructed of 1.0-mm mesh plastie wmdow
^ screening. The bags were s' ealed by folding the edges twice and stapling them at 5-cm intervals to prevent leakage of plant materials via tidal action. Each of 30 bags was filled with approximately 50 g of air-dried whole plants. Materialin
- each bag was individually weighed to the nearest 0.1 g prior to filling.
The bags _wcre placed at six randomly selected locations (three in the thermally atfected marsh and three in the control area). Sp.arrin.e has been g k G4gA 5 O5
- E y S F e j ,
- 4 11-144 l
i [' # I , b . , . 'g'j s. ~ FLORIDA SALT MARSHES 537 observed to decompose while remaining in a vert ,41 i position on :he marsh; leaf and some stem parts gradually decay until, eve. tually, only the shortened bare stem remains. Finally the stem weakens at the case of the marsh surface and falls over. Natural conditions were simulated as :losely as possible by constructing T-shaped wooden frames and driving them into the substrate. The litter bags were suspended from the crosspiece, positioned approximately I m above the mud surface, and the bottom of each bag was pinned to the mud surface with a metal stake. Thus the bags remained upright, with only the bottom of the bag containing the base of the plant stems in direct contact with the substrate. One frame was placed at each of the six locations, and five bags were suspended from each frame (15 bags in the thermally affected marsh and 15 in the control areas). Before the bags were placed in the field, four representative samples of
~
air-dried material were dried to constant weight at 70*C in a drying oven to determine the percent moisture of the mitial samples. All samples gave results cons 6 tent within 5% This information was used to calculate the imtial ovendry weight of the plant materialin each of the 30 bags. Four bags were randomly retrieved from each area at 6- and 10-week intervals. Plant material was removed from the bags, dried to constant weight at 70'C, and weighed to the nearest 0.1 g; the results were expressed as percent dry weight remaining. Every bag retrieved was intact, and there was no evidence of contamination by soil organic matter. Nearly every bag examined contained amphipods and fungi, indicating that, despite the small mesh size, some macrodecomposers were able to enter the bags. In conjunction with the studies of structure and metabolism, an effort was made to census two conspicuous mvertebrate populations of the marsh system. A comparison of the numbers of animals present may serve as an indicator of animal adaptation to elevated temperatures. During the monthly standing-crop harvests, counts were taken of the number of marsh periwinkles, Littorina irrorata, and fiddler crab. Uca sp., burrows in each quadrat. Mean numbers were then calculated and expressed as number of snails or crab burrews per square meter. No attempt has been made to monitor size classes and metabolism or to
' correlate the number of crab burrows per area to the actual number of etabs inhabiting a unit area of marsh.
RESULTS The results of the various experiments are given under headings of Sparrina standmg crop, total or gross metabolism, decomposition, and ammal popula-tio ns. Spartins Standing Crop Standing-crop data for an annual growth cycle in the thermally affected marsh are shown in Fig. 2, Monthly trends are similar to those found by other 11-145
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g , I I I i f l I I i i ! JUNE JULY AUG. SEPT. OCT. NOV. DEC. JAN FE8 UAR APR. MAY MONTH Fig. 2 Annual Sp.rrtin.s standing crop in the thermally affected marsh, includ-ing a comparison with standing crops from control areas during February-May. , thermally affected marsh. , control areas. Vertical lines represent
- I standard error around the mean of nine samples. The community net pro-duction (June 1972-June 1973) was estimated by mmming a live + A dead.
$ 51.7 g m-a 3 ,,, i ,
researchers in southeastern ". ; marshes (Morgan,1901; Marshall,1970; and Day et al.,1973). Ilo*.ever, the calculated net gain of biomans during the 2 growing season of 550 g (dry weight)/m obtained in this study is low. Figure 2 and Table I compare winter and spring standing-crop' levels in the thermally affected and control marshes. Trends of the changes in standing-crop levels over time are similar in both areas. The minimum live standmg-crop values for both mirshes were observed in hbruary; maximum dead standing crop occurred in both areas during March. A nonpaired t-test was performed to test for differences between treans of monthly live and dead standing crops on both
. marshes. Results showe.1 no significant differences in live material at the 95%
confidence level except during March. Differences in dead material were all significant. Incremental changes in Spartina live and dead standing crop during the growmg season. (including appropriate corrections for in situ consumption of dead material, tidal export, and herbivory) can be used to estimate net primary production. These processes are summarized in a simplified energy diagram (Fig. 3) that represents the mechanisms of energy capture, production of orgaait matter, respiration, transformation of living material to a dead status, and decomposition. Spartina net production during an mterval of time is shown in Fig. 3 to be equal to the change in live standmg crop (di) plus the fraction of live material removed by herbivores (II) plus the amount of hve material which dies and is transf erred to the dead compartment (62 + R,u + E). a . II-146 E
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+
TABLEI
. COMPARISON OF Sp.trtin.r NET PRODUCTION IN TIIERMALLY AFFECTED AND , CONTROL MARSilES a live A dead Loss of dead' Live between Dead between through Net production standing crop, sampling standing crop, sampling decomposition. ( A live + .?
Date g(Jay ws)/m' . periods g(dry wt)/m' periods g(dry wa)fm' a dead + decomp.)$ Thermally Affected Marsh m N Feb.6 144.9 337.4 8 Mar, 2 3 200.0
+ 5 8.5 396.4
(-49.8)t 70.0 128.5 o m
- Apr. 26 258.5 346.6 68.6 4 + 89.8 + 3 4.3 s92.7 y,,, 3 34, 3 380.9 Subtotals 203.4 93.3 250.1 $
t-
-4 Summation of monthly bk> mass increments through June 3: 546.8 Coneret Marsh d 1
Feb.6 132.0
- I 'O 245.2
+ 0 623 88.9
.E Mar. 23 149.0 247.2 Apr. 26 224 6
* 247.2
'I '
J.>ne 3 298.8
*"' 210.0
(- " " O' I Subtatals I66.8 + 2.0 112.7 Summatkin of monthly bkomass increments through June 3. 2H1.5
*Decompoution was calculated by multiplying the dead standing crop at the beginning of the time interval by the average daily Jccompowsion rate Jurmg that interval (Fig. 5) t>y the number of days in the time interval.
1 Numbers in parentheses are not included in the production estimates.
$11erbivory was awamed to be sero Juring sampimg period.
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k l sp w 8 ' SYMOOL EfY DIAGRAW N01 Afl0N ' 1HERMAL MAR $H CONTROL MAR $H L=e Herb =orv Ded
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- Op
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- I 39 * 'l
- 114 = l_3. 9 to e
- 0 04 * 'l
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- Op
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- O 04 * 'I a 0 4 Respwalion, RC AP*Eu II 8 4 82 N NPPGPP, 0,*0 2 *E. 2 5/13 9 = 0 I8 e 4'4 90 = 0_08 0 10, + Op
- fI RC 2 Sieman/GPP days -145/13 9 = 10 4 -132'4 9 = 27 0 0 0,T,PP Searvea ME T A80 LISM Gros reductea. GPP O,
- H
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- Ru
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- H 38 + 2 48)
- 8 9 = 33 9 0 4
- 0
- H 4)
- 3 0 = 4 8 :
Net moduciea. NPP 0,
- H * (Oy R.
- fI I ??
- 0
- 1131 + 2 489 - 5 01 0 4
- 0
- to 4
- 141 = 10 l RetPaassa. Rp Re >8.1 ' 3 0_ l NPP CPP 0,
- M
- top + R
- El 5 0t'13 9 0 36 l a 4 8
- 0 38 0,
- H + 10,
- R
- l l
- R, OemanGPP days 0, %PP - 145'13 9
- 10 4 -13248*275 Fig. 3 Fnergy Jiapams summariinig the noservea movement of organic material measured in the thermally affected and control marshes during the I ebruary-March period. Quantities dhlsyed on the diagrams are in units of grams (dry weight) of organic matter per square meter for tanks j (converted from Table 2 by multiplying grens of carbon by 2) and grams per square meter per day for pathways. Melow the diapams are equations 4-defining net and gross production which are derived from relatie=es implicit in the diagrams.
f 9
= w
_.a
.~ <
- . .n t
FLORIDA SALT PAARSHES 541 Table 1 is a comparison of net production estimates between marshes, based on the procedure outlincd above. Ilerbivory was assumed to be zero during the time span of Table 1, based on observations of ne;;ligible leaf damage. During the 31nonth interval examined, the thermally affected marsh had almost twice the 2 2 net production of the control marshes (547 g/m vs. 282 g/m 3, Stem-density determinations for both marshes (Fig. 4) showed that thermally affected marshes contain greater numbers of live and dead stems per
- square meter than do control marshes. Since live-plant standing crops for both marshes were nearly identical, the higher density of stems suggested a dwarfing
'of stem size in the thermal marsh.With the data for February from Figs. 2 and 4, the mean weight per st-m values for live olants were calculated to be 0.78 and 0.94 g per stem in the thermal and control areas, respectively. Mean weight per stem figures for both marshes were subjected to a nonpaired t-test, and the differences in population meant were found to be statistically significant at the 95 % confidence level.
Total Metabolism Table 2 summarizes metabolism measurements made in the ther utly affected and control marshes using garanalysis techniques. Wlues are for daytime photosynthesis, nighttime respiration, diel total metabolism, solar insolation,and mean daily air temperature. Rates of total community metabolism were similar in both thermally affected and control' marsh communities; mean i
- rates were near 7 to 8 g C niz day", which represents about 12 to 16 g of organic matter or 56 to 64 kcal ni' day". A t-test showed no statistically si;nificant differences between the means at the 95% confidence level. Significant differences were indicated in the nighttime respiration rates between the two marshes. During the March sampling the thermally affected marsh exhibited daily respiration that was twice that of the control marsh (5.71 vs.
2.21 g C ni tday"). In data examined thus far, variations in total metabolism from day to day may have been due to differences in solar i. isolation, ambient air temperature, and irregularities of the tidal cycle. Decomposition Results of the decomposition experiments are given in Fig. 5. After 6 weeks there was an indication of slightly higher losses of material from bags placed in the thermally affected areas, but a t-test revealed no significant difference at the 1 95% confidence level. However, after 10 weeks there was a statistically l significant higher loss of material from the thermally affected marsh. After 10 weeks 67% of the original material remained in the control areas and only 56% in the thermally affected marsh; these values correspond to a mean loss per day l of 0.45 and 0.63%, respectively. ! l i l l l l II-149 . i
- J z -
t - . .-
( :sf $ f~'E % ,. M .s. 542 YOUNG 250 200 - DEAD -
't
,t
}i5o -
'I .
i . /l % /WU h' E' ~
'f f-ll 'N Il
,, -[ I--~~f-q) m 50 -
o i 1 l l l l I I 300 Livt 250 - --
"E 3--
I 200 % ;s _ J N ' l } p -- .. , i- / l 's s
~ 150 --
/ \ ____, / --
5 '
/
.o !
3 g 100- - m 50 . - I l i I I I l I O SEPT OCT NOV DEC. JAN FEB MAR. APR MONTH
, Fig. 4 Comparison of Spartinastem densities in the-m4Hy affected (-) and control ( + 4 maras. Verticallines represent the range, and turs repreecnt 21 sundard error around the mean of nine samples. +
II-150
> ; r,., .
~
FLORIDA SALT . MARSHES 543 TABLE 2
- CO2 GAS EXCilANGE MEASUREMENTS OF TOTAL METABOLISM IN Ti!ERMALLY AFFECTED AND CONTROL MAR 511ES Metabolism. g C m s day
Mean Solar Gross daily air radiation, Net daytime Nighttime metabolism Date temp..*C . kcal m-a day-' production (P) respiration (R) (P + M) Thermally Affected Marsh Mar. 3-4 22.0 4590 1.35 6.20 7.55 Mar. 3 -4 22.0 4590 2.40 4.71 .10 Mar. 8-9 23.0 2004 1.25 2.79 4.04 Mar. 8-9 values surrested to March 3-4 solar radiation levelx 4590/2004 = 2.224)- 2.78 6.21 8.99 Mean 2.18 5.71 7.8R Control Marsh Mar.12-13 27.2 5050 3.79 2.55 6.34 Mar.14 2 5.tl 5094 5.96 2.22 M.!I Mar.14-15 25.8 5094 4.57 1.t60 0.43 Mean 4.77 2.21 0.96 Animal Populations Estimates of population densities of Litturina and Uca burrows present in the two marshes are summarized in Tables 3 and 4. Crab burrows were counted only at low tides, which accounts for gaps,in the data. Snail populations were patchy, which was manifested by'the large standard errors. .\ lean annual snail densities were quite similar m both marshes; however, crab burrows were more numerous in the control marshes.
' DISCUSSION On the basis of a review of nursh-productivity literature, Keefe (1972) notes an apparent latitudinal variation in Sparrin t standmg crop and net production inferred from seawnal increments of standmg crop. Standmg crop and net production tend to increase from north to wuth. IloweverJNpartina standing crop and the resultant seasonal change in standing crop (5 50 g-2m yeaf' ) fou nd during this study at . Cr). cal River, which is near the southern limit ut grass-dominated salt marshes, are low when compared to studies identified by Keefe. Estimates of net production by others range from approximately 500 to 600 g m-2 y,3f i(Morgan,.1961; and Williams and Murdon,1909) to 2800 g 11-151 1
]
~
'~ ~
T-' if}% e * %_h :i. uS 1 - _;. . :.
.a. u . .. . l -
$44 YOUNG 100
-l i I I I I I gConteos Marsh g80 7hermally hta,M N 2't E
5 i
> 60 - -
8 . March 1 Apfel i May 1 40 Il I I ih l I Il 0 'O 20 30 40 1,0 rc 70 80 Tivt. atsys Hg. 5 Comparison of Sp.ertias decomposition rates in thermally affected and control snarshes. Verikal lines represent the range, and liars represent al semidard error around the mean of four samples. TABLE 1 l'OPULATION l'.STIMATES OF SNAILS, Litturtna irrorar . IN TI'LRMALLY AlsFECTED AND( JNTROL MARSIIES Thermally affected mera Control marsh Month Numberim' s 15 E. N Number /m' I S.E. N August 3,ll 2,19 9 No J.t.
$splendser 2.67 a 2.2 8 9 No J4:4 O*tober 7.11 2.47 9 2.o n 2 0 2 Noventer No data o.5 s 2.82 N LAsember 3.56 s 1.82 9 No Jata january No Jata 3.4 3,43 7 lchruary $,78 a 2.22 ' 9 0.0 N Marsh 2,29 s 1,19 7 3.43 1.84 7 April 1,3 ) 1,)l ) 6.4 a 1.60 $
Annual mean 3.69 : 0.77 3.62 t 1.03
~
, . , , , .e u ../. ,y --4 , , c,. - , , , ,o .i - 1-II-152.
n y 1,, ,, ', 's . : a. ? ,i ' %* -
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FLORIDA SALT MARSHES 545 TABLE 4 DENSITIES OF FIDDLER CRAB, Uca sp.,8URROWS IN TIIERMALLY AFFECTED AND CONTROL MARSilES Thermally e/fected marsh Control marsh Mench Number /m 8 s 1 S.E. N Number /m'
- I S.E. N September 313 : 36.6 7 No data October 425 s 23.8 8 634 06.0 2 Noverr.ber - No data 485t40.0 7 Decenter 278 a 29 9 9 No data January . No data 340t48% 9 February 331 a 42.0 9 319 a 20 6 8 March 332 32.1 4 406 s 20.7 4 A,,ril No data 327 a 75.5 4 Annual mean 3 36 a 24.3 419 s 50.2 m'8 yeaf' (Day et al.,1973). Low apparent productivity at Crystal River may be due to one or more factors. The nutrient concentration of nearshore waters that flush the marshes is low. For example, total phosphorus concentrations in these waters annually average between 1.0 and 1.5 pg-atom / liter, which is similar to open Galf waters (McKellar,1973). Tides provide an important energy subsidy to marshes (E. P, Odum and Fanning,1973), and the tidal fluctuations at Crystal Rwer are small in amplitude relative to the tidal range of the Atlantic coast. Perhaps the mild winters and more regular seasons characteristic of Florida account in scme measure for a smaller tluctuation of standing crop than is typicalof northern marshes.
Examination of the energy diagrams in Fig. 3 aids the interpretation of the various growth and adaptation trends observed in the standing crop, metaboiism, and decomposition experiments. The energy diagrams portray the essential process of organic-matter production and the eventual fate of this matter in the Spartin.: marsh ecosystem. The two storage " tanks" or modules denote the standing crop of live and dead materialithe lines or pathways correspond to the
- dominant fluxes of organic matter fiom the storage compartments. Values displayed on the storages and pathways were those obtamed from the field sampling program, including respiration "rlues from gas analysis for the
~
February-Marcn period; all previously quoted values for the period are expressed as grams . (dry weight) of organic matter per day in Fig. 3. Decomposition of dead standing crop, which represents both in situ decomposi-tion and export, is denoted by a smgle value, which was measured by litter bags. Exact values are yet to be determined for export, and this flow is labeled with a question mark. Flows entering a storage tank must equal the sum of all outflows plus the change of the level within the tank during the time interval considered. Net production and gross production, both for the community and Sparrana. are e< II-153 w . ,y y- p-,-# .. , , , ,y---
-*4 -i. ,y-_
r e%a 1 646 YOUNG detmed m Fig. 3 by equations derived from the energy dugrams. For example, Ap.ntma net production is equal to the summation of the thange in live standmg 5 top, loss to herbivores, and the quantity of hve material which dies and is transferred to the dead standing compartment. The flux of live materialinto the dead standmg compartment is "back calcul4ted," usmg the observed inaenes m the dead standmg crop and the 5ombined estimates of in situ decompoution and
- c. port rates obtamed f rom the intter bag studies.
t he data in Table I and Figs. 2 and 3 show that February-March increnes of hve standmg crop of Spartma are three times as great m the thermally affc(ted marsh as in the tuntrol area. Thus intrencd water temperatures app.iremi) hasten the beginning of the growmg scawn. Subsequent standmg-stop maements during the renuinder of the sprmg < non are umilar for both marshes, the userall inuene of hve standmg crop , the thermal marsh is 22% gecatsr chan in the controls. Anderwn (1969) . ade a quahtative obsersation that hve Spartm.: growing ncar the diuharge of a power plant in Maryland appeared more robust than that in nearby marshes whwh rc6eived ambient
~
waters 1hc change in dead standmg crop in the thermal marsh contributes 2ti% of the estimated net production durmg February and Marsh and 17% throughout the growing senon. These figures are sigmficant when compared to the control marsh, where there is cuentially no gain in dead standing trop durmg the growmg senon. Owmg to higher dead standmg crops and I.igher decompoution rates (11g. 5), the total loss of material through decompoution and export n whc as high m the thernul marsh n in the control aren. The contribution from desumposition to the estimated net production during the sprmg senon is approxinutely 50% m the thermal marsh and 40% in the controls. Comparnon of changes in dead standing crop and lossci from decompoution and export reveals the thernully affected marsh procenes, or turns uter, a larger portion of nuterial from the hve compartment. itatios of biomass to gross production calculated in Fig. 3 show the turnovc sm'c of the thermal marsh to be one-third that of the control marsh The net ef fect .f monthly standmg-trop shanges and detompoution is greater production of plant material in the thermal marsh (546.8 vs. 281.5 g/m8 ) during the sprmg penod. Community metabolism measurements by gn analysa (orroborate the Imdmgs of higher metabolic actwity m the thermally af f ected marsh. Total 24 hr, or gross, metabobim appears shghtly higher m the thermal marsh, " however, nighttime tripiration is ugnitietntly higher, 5.7 g vs. 2.21 gim 8 Dnparitics, unrnolved a of thi, writing, exnt in the daytime net production values l'or the two marshes. Metabohs measurements mdiate higher photo-synthesis in the control marshes Few direct measurements of metabolism have been attempted in salt marshes. Teal and Kanwisher (1901) menured the respiration of mud, Spartma stems, and the entire marsh commumty m produttne Georgu nurshes. Teal (1962) found Xpartma to exhibit the tollowing mean yearly metaboksm; gross, 2.3 to H.3 g C m-a day"i net. 0.9 to 3.08 g C
. o 11-154
l 2 -
, , , , ,. .,r.-
547 FLORIDA SALT MARSHES m'8 day'8 ; and respiration,1.74 to 3.89 g C m-3 day lie summarizes total community metabolism as: gross,14.0 g C m-1 day'8 i net 1.4 g C m'8 day"i and respiration,11.2 g C m"8 day During thi< atudy metabolism rates obtained
' by. gas analysis in March fall into the range of values calculated by Teal. Gas metabohsm data from Crystal River are stal being interpreted, and results and conclusions based on these data should be ' considered preliminary.
As was shown in the preceding paragraphe respiration of the marsh community increased in areas that received thermal discharges. Ilowever, it is more meaningful to compare the ability of the two marsh communities to compensate for increased respiratory demands by simultaneous, proportional increases in net production. The ratio of net production to gross production indicates the fraction of the total community metabolic budget which is available for net production. Vah.cs of this ratio during .. e February-March penod are given for both marshes in Fig. 3. Note the similarity of this ratio for both marshes, implying that net production remains nearly a constant percentage of the marsh metabolic budget. ldentical calculations, not reported in Fig. 3, wcre made using the entire spring growing season production estinutes given in Table 1 (together with March respiration measurements), and similar ratios between marshes were found to exist through June 3. The adaptations observed in the thermal marshes at Crystal River are consis-tent with 1.otka's (1922) princip!c that surviving ecosystems are those which maximize the flow of energy through the system. The thermal marsh is apparently using some of tne potential energy contained within the thermal discharges to carry on higher levels of metabidism. The mechanism through w hich production and respiration are accelerated under regimes of elevated temperature is still unclear, but one possibility is inercased organic matter decomposition and concurrent nutrient regeneration. liigher temperatures tend to accelerate decomposition and respiration, but, for a system to remain viable, it must achieve a balance between disordering outflows and production (or inflows). Models described by Odum 01. T. Odum, this volume) illustrate theoretical
" push-pull" r ts of temperature on ecosystem behavior. Chemical reaction rates an ing of materials proceed faster at elevated temperatures; there-fore in , production observed in an adapted system, which contains a finite stock .iaterials necessary for production, such as nutrients, may be due to inct recycle and subsequent uptake of these materials.
- No nutrient determinations have yet been made on live and decaying plant material during this study, but Ustach (1969) has shown that radioisotopes of ,
I chromium, cesium, and zine are rapidly leached from dead Spartisi. at a rate that exceeds the loss of dry weight. The biogeochemical cycling of cesium n similar l i to that of potassium, and the behavior of chromium and zine may indicate the fate of micronutrients (molybdenum and zinc) necessary for plant function. Ustach also suggests . the role of increased environmental temperature in l augmenting decomposition rates. Phosphorus, calcium, and other macronutrients are lost in forest litter in proportion to the reduction in dry weight (Ewel, i I l I 1 II-155'
p swygu , av . , _, vu , _ .. .
' 540 YOUNG i
1968). Creater decomposition rates in areas of elevated temperature may quickly release a larger fraction of the bound nutrients, which are reused by Spartina for further production. The larger amounts of dead material on the thernul nursh nuy _be an adaptation by that system for concentrating and transferring a greater fraction of nutrients normally bound in live plant tissue to a compartment where they are quickly made available through decomposition for reuse. Results of the stem density measurements also reveal a possible adaptation to elevated temperatures. The inverse size-metabolism principle (11.T. Odum, 1956) may help to explain the presence -f smaller " dwarfed" plants in the thermal marsh. A smallet plant with its higher metabolism per unit weight and more rapid turnover nuy process the same energy and material flows with less structure and biomass (ll.T. Odum, McConnell, and Abbott,1958), in areas where elevated temperature provides an additional energy source, snuli organism siae may have selective advantage by allowing the processing of proportionally more energy for production, respiration, and recyctmg of products of respiration. The types of animals present and their numbers also provide information , about the structure of an ecosystem. Lettorina migrate up and down the Sparrana stems in rhythm with the tide. As adults they have the ability to avoid the hot I water for much of the time, which may explam why no significant differences are found m the mean annual numbers between the two marshes. Littorina have a waterborne larval stage; so the density figures also suggest no unusual mortalities during infancy when they are directly exposed to the elevated water temperatures. Mean annual fiddler crab burrow numbers are lower in the [ thermally affected marsh. Measurements of sediment temperature were taken ! during winter and spring with a thermistor. type soil temperature probe. [_ Temperatures to a depth of 70 cm were 2 to 3*C warmer in the therm 4lly affected nursh. Since these crabs spend a significant amount of time in their burrows, it is conceivable that higher substrate temperatures may limit their abdity to adapt and survive in the thermal marsh. Fiddler crabs may normally be important members of the community for expediting thc breakdown of detritus , and facihtating nutrient regeneration, if they are present in fewer numbers after l ecosystem adaptation to higher temperatures, perhaps the service previously carried out by the crabs is now being performed by other organisms to ensure the long-term survival of the nursh ecosystem. In summary, the apparent effect of increased water temperatures on salt marsh structure and function is to accelerate biological and chemical procenes. The salt marsh has self designed mechanisms to utilize the potential energy of the thermal discharges for compenuting increased respiration demands with some proportional increases in production. Estuarine ecosystems may possess an inherent ability to adapt to such pertubations because of the natural
. fluctuations of temperature, sahnity, waves, etc.,in the coastal zone. The results of this study indicate that man should not continuously seek to apply costly . , y ,. . . , , . , , -. .
II-156 s
y V - P FLORIDA SALT MARSHES 549 technology to minimite his waste products. Instead, he snould under certain circumstances recognize the natural ecosystems that have the necessary flexibility to serve as effective interfaces in processirg and putting his wastes to use at no cost to him. ACKNOWLEDGMENTS This paper is taken from an M.S. Thesis in the Departmert of Environmental Engineering Sciences, University of Ilorida, Gainesville, Fla. The project was directed by S. C. Snedaker and II. T. Odum, who deserve special thanks for their patience, support, and enci.,ragement. It was supported by a contract with the Florida Power Corporation. acknowledge Charles Bilgere, Walter tioynton, David Dorman, Mark Homer, and others for assistance with field collections. Technical advice, suggestions, and ficid assistance were given by Sam Jones and Ken Dugger on gas metabolism experiments. Metabolic equipment was provided by the Environmental Protection Agency. REFERENCES Anderson, R R.,1909. Temperature and Rooted Aquatic Plants. Chesapede Sa,10, 157 164. Bayley, S., and H. T. OJum, 1973 Energy Evaluation of the Water Management Alternatives in the Upper St. Johns River Basin of Florida, draft of report submitted to the Enveronmental Protection Agency, Carder, K. L.,1972, independent Environmental 5 udy of Thermal Effects or Power Plant Dissharge, in Environmental Status Report, . uly-September 1972, FloriJa Power Corporation, St. Petersburg.
-,1978 An Independent Environmental Siudy of Thermal Effcots of Power Plant Dissharge, in Environmental 5tatus Report, J uly-December 1971, Fforida Power Corporation. St. Petersburg.
D4y, J. W., W G. Smith. P R. Wagner, and W. C. Stowe,1973, Community structure and Carbon Budget of a Salt Wrsh and $ hallow Bay Estuarme System in Louisian4, Center for Wetland Resources. Publisation No. LSU-SG-7244, Louisiana State University, Bacon Rouge. Ewel, J. J.,1968. Dynamics of Litter Accumulation Under Forest Succession in Eastern Guatemalan lowlands, M. S. Thesis, Department of Botany, Umversity of Florida, Gainesville, Florida Division of State Planning,1973 Florida 10,000.000 Scenario Project Memo-randum No. 3, T.llahassee. Keefe, C, W. '1972, Marsh Production: A Summary of the Literature, Contrib tiar. Sct,16. 163 1811. letka, A. J.,1922 Contribution to the Energetics of Evolution, Proc. Nat. Acad. Sci, Si 147155,
- Lugo, A. E.,1969, Energy Water and Carbon Budgets of a Granite Oute op Community, Ph. D. Dissertation, Department of Botany, University of North Caruhna, Chapel Hill Marshall, D. E.,1970, Characteristics of Spartina Marsh Receiving Treated Municipal Sewage Wastes, M. S. Thesis, Department of Zoology, University of North Caruhna, Chapel Hill 11-157 s
3 - , ,
F % M usih x.a _ .. __ _. ~_ . 560 YOUNG McKellar,11. N., J r.,1973, University of Florida, personal communication. McNulty, J, K., W. N. Lindall, Jr., and J. E. Sykes,1972, Cooperatrve Gulf of Menico Estuarine inventory anJ Study, Flor:J4: Phase I, Area Description. Technical Report NMFS{lRC 168, National Oceanic and Atmospheric Administration U. S. Department of Commerce Seattle. Morgan, V. II.,1901, Annual Angiosperm Production on a Salt Marsh, M. $, Thesis, UnWersity of Delaware, Newark. Murray, C. R., and E B. Reeves,1972, EstanJfed Usf o[ Wafer E4 #ht UNrffd Sfaffs is 1970, U. S. Geologisal Survey, Circular No. 676 Washington, OJum, F.. P 1971, Faul.sene stals of Ecology, W. B. Saunders Company, Philadelphia.
. and M. F., Fanning,1973, Comparison of the ProJuctmty on Sp.rrttua altereiflora and Sp.errea. cynosarondes an Georgia Coastal Marshes, Ga. Acad. Sci, Emil., 31(11:1 12.
OJum,11. T.,1956, Elliciencies, Siae of Organisms, and Community Structure, Ecology, 37: $92 597 _, C. B. Littlejohn, and W. C, iluber,1972, An Envivnmental Evaluation of the Gordon Rwer Arca of Naples, Florida, and the impact of Developmental Plans, a report to the County Comminioners of Colher County, Fl4,
. W McConnell. anJ W. Abbott,1938, The Chlorophyll a of Communities, Pabl. Inst.
At.or. Sa , Umw. Tux , 5 6s-96. _, anJ R. F. Pigeo,- tl JsJ,1970 A Trefecal Mars (orcss. TID 24270 (PRNC 138). Test, J. M.,19o2, Energy Flow in the Salt Marsh Ecosystem of Georgia, Fculogy, 43: 614-624. _ , and J. Kanwisher,1961, Can Exchange in a Georgia Salt Marsh, Linuvol. Octanogr.,6. 388 399.
,, ,anJ M.T:41, 1909, l.fe awJ Drash of the Sal Marsh Little, Brown and Company, Bostort Ustash, J. F.,1969, T he Decomposition of Sparssna alterniflora, M. S. Thesis, Department of / oology, North Carchna State University, Ratcigh, Williams, R. II., and M. B. MurJock,1969. The Po.ential importance of Spartina alstrmflore in Conveying /ine, Mangancie, and Iron into Estuarme Food Chains, in Proceedings of the sesonJ National Symposium on Radioewlogy, D,J. Nction anJ F. C. Evans (Eds.).
USAl C Report CONF o70503, pp. 431439, 4 s .s i .. , , . . . , - ,;
- II-158
.i+ , . ,
* * -i .. . . s APPENDIX A3 TOTAL METABOLISM OF. THERMALLY AFFECTED COASTAL SYSTEMS ON THE WEST COAST OF FLORIDA WADI' II. it. Mit I fI. IIANK % Kl:I.I.AH. DON L. YOUNG, afh.I .1\l'$. YIN l., LLll\lAN Department of Lewironmental Lngineering sucnses. Umvera.ty of Florida.
Gamesville. I lorida ABSTRACT The total sommumty metahohsm of estuarme bay systems rnciving thcrmal shwharge from an efneris power generatmg station on the west cu4st of 1lorkla was measure 1 stuJin were made m summa an.1 wmter uung the tree watcr diurnal oygen curve muhod. Mean summer va lues of both nce da) time photo-) nthnis an.1 mght rnpirath,n m the ha> > ucms 8 were ahuut 4 to 5 g 0, m Ja s ' Wmact values were generallt une-halt to one-third the summer s alun No ugnitwant .hfterense hstu ren alf n ted an.1 sentrol areas was Jemonstrated. Summer and winter photosy nthesn/ respiration (l*/10 ratan usrc 1.14 and u.91 ropatively, m the plume 4tfnted arsas, and is Yo and u t J. resputwsly, m the suntrol areas. 'lotas metahuhsm was alwa measurcJ an the mrake askt shssharge sanals of the power plant. ~lhne saudiss siklisarcil that both sanal systems were highh hercrotrophis, with P/M ratun rang,ng f rom o u2 to 0.50. Durmg October total met 4hohwn tiwa Jastime produstion plus nighttime rnpirationi was 4.7 g 0, m day '. in the maale canal and 15.1 g 03 nia Jav" in the deshargs sanal During 1'chruary total metabolism was 3.1 aiki N.6 g O, m8 Jay
- tot the mtake and shssharge sanals, ropn tis tly t he 5 m 1u 5 m of sanals pri.Juse.17 s to 75~. los oxygen than the same area of ha) now ucm an.1 respered 4hous I 5 tmin more op gen than the same arca of hay.
As man increases his use of famil and nudear fuels to meet hn energy requirements the demand for large volumes of conhng water lui !cetric power generation will also increase. Thus, the ctfects of this waste hvat load on the aquatic ecosystems become a vital concern. What is the role of thermal addition in promoting the self design and adaptation of a new or thiferent system? Does thermal loadmg serve as an energy source or a stress to the impasteil system or is the effect a neutral one? If adaptation occurs. what is the nature of the new ecosystem, and a thn new partnership of man and nature as desirable as the one 475 r 9 \ D e s, -
. J..tH2 11-159
m - - - ': , "' - ~ c_,% . ,_. . _ . . 476 - SMITH. McKELLAR. YOUNG, AND LEHMAN displaced? These questions are now being considered in studies of the bay areas adjacent to the Florida Power Corporation electric power generating station near Crystal River, Fla., where a thermal effluent has been flowing into a coastal area for 6 years.
- One way to estimate the overall state of an ecosystem is to measure total photosynthetic production and total nighttime respiration.-A diurnal oxygen procedure was used to measure total community metabolism in the thermally affected area and in control areas. The purpose was to investigate the integrated response of all system components to the .ew conditions and thus to determine the degree to which the parts have adjusted and changed their function of energy processing. -
Besides thermal effects there are other changes in the cooling water as it passes through the plant and its associated canals. Total metabolic levels were also studied in the intake and discharge canals to gain insight into the nature of this interface system. The productive and consumptive functions may indicate the degree to which cooling waters were changed during passage through the canals. Tot.1 metabolism m the canals was also considered as a basis for estimating the relative role of the power plant and its associated canal systems as a metabche component of the userall coastal ecosystem. Thdits The plant site in Citrus County is 12 km (7.5 miles) north of rP town of Crystal River on the low wave energy portion of the west coast of Fiarida. The shallow, sloping near-shore bottom (46 km to the 5 fathom contour)is generally coincident with the drowned karst topography of this portion of west central Florida. Fresh water sources in the general area include the Crystal River 4.8 km
- to. thel south with a mean flow of 1500 m / 3min (400,000 gal / min) and the Withlacoochee River and the Cross Florida Barge Canal 6.4 and 5.8 km to the north, respectively, with a combined flow of 2150 m / 3min'(570.000 gal / min)
- ( Fig.1 ).
The plant is on the landward edge of a tidal shit marsh dominated byJuncus
- sp. Two units, with a combined total output of 897 MW, are currently in operation. Unit I started in July 1966 and Unit 2, in November 1969. The two units cycle water for once-through cooling at a. combined flow of 640.000
. gal / min. The maximum condenser temperature rise is 6.l*C (ll'F).
The intake canal extends approximately 4.8 km into the Gulf of Mexico and has an average depth of 6 to 7 m and a mdth of about 75 m. Cooling water passes down th'c canal at about 8 cm/sce before being pumped through the ' condensers and into the discharge canal, where its temperature rises 5 to 6*C,
- The discharge canal is about 1.6 km long, with an average depth and width of about 4.5 and 50 m.' respectively. The smaller cross-sectional area causes the
-stream velocity to be about twice that in the intake canal. The residence time of water masses in the canals is about 20 hr for the intake canal and about 3.5 hr for the discharge canal.
{p g m Ft
- b .
.11-160 l
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METABOLISM OF THERMALLY AFFECTED COASTAL SYSTEMS 477 Since the beginning of power plant operation in July 1966, estuarin communities have become established in the canal environment. The steady current conditions possibly serve as an energy subsidy for such organisms as oysters and resident and migratory nekton. Some algae grow along the sides of both canals. Transient planktonic producers and consumers spend about I day passing through the canals before entering the plume-affected bays. A documented stress to the discharge-canal ecosystem was the daily injection of sodium hypochlorite into the condenser tubes of the power plant to control the growth of marine fouling organisms. Fox and Moyer (1972) found that phytoplankton production ("C uptake) in the chlorinated discharge water was about half that in the unchlorinated intake water. Turbid conditions suspending bottom sediments developed periodically in both canals when large oil barges entered the intake canal. Overall, the canal has supported a surviving ecosystem that serves as an interface between the natural and the thermally affected coastal ecosystems. Two types of bay systems are affected by the thermal plume (Fig. 2). Immediately adjacent to the salt marsh is an inner bay,less than 1 m in average depth, composed of a mixture of grassy bottoms, oyster associations, algal bottoms, and areas of sand and mud. Seaward of a row of oyster bars is a deeper outer basin, about 2 m in aserage depth,in which the plankton and reef ecosystems become important. The bays referred to here are actually the immediate landward edge of the open Gulf of Mexico.
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METHODS
'lhe diurnal oxy 3ren t une method used here for the luy o stenw was modified Irom the teshnique .feweribed by Odum and lloskms (10586 and by Odum (19671 for use in tidal waters. The same method. modified for use in tioning water (Odum. luSM. was aho used for the can.d stud3 .- Owgen was measured by the aride mo.hficatiori of the Wmkler technique t.\mene.in Pubbe
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METABOLISM OF THERMALLY AFFECTED COASTAL SYSTEMS 479 Ilealth Association, 1971) adapted for use with smaller sample-collection bottles. Mini-Winkler Field Kit and Modification of Winkler Method B cause of the large number of samples to be processed and the need for compactness, a mini-Winkler fic!d kit developed at the University of Texas Institute of Alanne Science was used. Standard flat-topped 125-ml reagent bottles were used for sample collection. Samples were tixed with 0.5 ml of manganous sulfate and aeide reagent. After acidification with 0.5 mi of concentrated sulfuric acid,100-ml subsamples were titrated with 0.0125N sodium thiosulfate. The average volume of a 54 bottle subsample was 122.8 mi, with a variance of 2.74. The difference in titrant volume between replicate pairs , of samples was small. On the basis of a sample of 486 repheare pairs,72.6*. differed by 2 drops (0.1 ml) or less. This would he of the same order as the expected environmental variation between water patches.1.uw of accuracy, therefore, was minimal and was far outweighed by the convenience of this
' technique.
Modification of Free Water Diurnal Method for Tidal Waters Stations were sampled approumately every 3 hr over a 24-hr penod. Two buckets of surface water were collected about I min apart at cach station, and sample bottles were filled from the bo. om wi:h a rubber tube uphon. Stratificatmn of the water column was occauonally noted, but, because of its variable occurrence, no attempt was maJe to (orr ct for its powible ef fect on metabolic calculations. Time, temperature, salimty, and depth were noted at each station.' Heauw of the large tidal flushing, the advection of water masses from outside areas was important. Eight to _ ten stations .wcre =ampled in the early part of the project to aness this effect on the diurnal oxygen cune within the study area. Aleasurements showed a general umilarity in the daily increase and decrease of oxygen at all statiom; this (jct suggested that adsection was from areas of similar metabolism. Therefore it was decided that any errors introduced by advection effects were small, and the number of stations was reduced to five or us. .
' A diurnal metabolism graph was con tructed' for eat-h station, using a standard format for easy visual comparison of samples with others m the literature. leigure 3 shows the averaged data from five stations m the inner hay area. Oxygen per square meter was obtained by multiplymg oxygen 3
concentration (g/m ) by the depth at that hour. Percent naturation was calculated for the temperature and sahnity with the formula of Truesdale, Downing, and lewden (1955). The divergence of Truesdale's saturation values from those presented by the ' American Public llcalth Association (APilA) (1955) was renewed by Churchill, lluckingham, and Elmore (1%2) w ho showed 11-163 _ s _ _ --m .
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I I 60 0 0600 1200 1800 2a00 Tsvi tal Fig. 5 (al Esample of format for diumal rsygen analysis used for calculating baysystem metabolism. The data represent an eserage for five inner bay stations, Aug. 2 to 3,1972. (b) The untorrected rate ofwhange curve ( -4 is taken direcdy from the 24 hr graph of asygen per square meter. The currected rate curve (-) la adjusted fier thanging water depth. Itasched area below sero rate ef shange line indicates night respiration. Itasched area abuse sero jete-of thange line indicates net daytime photosynthesis. ' deviations at 'emperatures t less than 25*C. Masimum deviations, however, were I:ss than 5% of the Standard Methods values; thus the crrors incurred in this study by using Truesdale's values were considered negligible. Average curves were constructed from individual station curves by averaging hourly values for oxygen concentration, depth, temperature and salinity. Oxygen per square meter and percent saturation were then calculated from the averaged data. A curve for osygen rate of change was constructed from the graph for average oxygen per square meter. The oxygen shange each hour was measured II-164
r. META 80LISM OF THERMALLY AFFECTED COASTAL SYSTEMS 481 and plotted on the half hour. This raw curve reflected changes in oxygen concentration under i square meter due to changing depth as well as to photosynthesis and respiration. A correction factor for changing depth was obtained by multiplying the incremental depth change for each hour by the average oxygen concentration during that hour. This value was added to the rate curve it the tide was falling and subtracted if the tide was rising. Diffusion was measured with a small nitrogen-filled plastic dome that floated on the water surface 111211 (19 70), based on original work of Copeland and Duffer (1964)). A field oxygen probe measured the return of oxygen to the dome from the water under the normal conditions of underwater circulation. The diffusion rate was calculated in grams per square meter per hour per 100% saturation deficit from the area of water surface covered, volume of the dome, and saturation value of wrter oxygen. This was the maximum rate of diffusion into oxygen-free water or out of water 200% saturated with oxygen. The actual diffusion correction for each hour was obtained by multiplying the maximum rate by the actual saturation deficit during that hour. At Crystal River the diffusion rate appeared to be mostly a function of t;dalwurrent velocity. Preliminary data indicated that only falling tides generated currents producing Jiffusion rates large enough to make a significant correction in the rateufshange cunes for usygen. Corrections as high as 20% changed th.e productmty calculation only 5% or so. Diffusion was small for most curves obtained and was usually ignored in the productivity calculation. Although additional data may change the values reported here, these changes will probably not affect the conclusions. The final rate-of-change graph (Fig. 3) shows the rise of oxygen due to net photosynthesis during the day and the decrease due to respiration at night. Net daytime photosynthesis is the area under the rate of-change curve above the aero rate of-change line. Nighttime respiration is the area below the rate-of change curve below the zero rate-of-change line. Upstream-Downstream Method for Canal Studies in a flowing water system where inflowing water has varying oxygen concentrations, metabolism must be determined from diurnal curves for both an upstream and a downstream station (Odum.1956). The rate of oxygen change is calculated as the difference between the upstream concentration at time t and the downstream concentration at time t + at, divided by At; At is the time required for the water to pass from the upstream to the downstream station (distance between stations divided by stream velocity). Stream velocities were determined by dividing the volume transport through the power plant (2415 m3 / min or 640,000 gal / min) by the cross-sectional area of the canal. The calculated velocities for the intake and discharge canals were 8 and 17 cm/sec, respectively. The rate of oxygen change per square meter was determined by dividing the rate per cubic meter by the averag depth of the canal between the t 6 II-165 _j
y . .p ry , . ,,, .u. _ _ _ __ _. . 3 a 482 SMITH, McKELLAR, YOUNG, AND LEHMAN i two stations. An example of the upstream-downstream diurnal oxygen curve is gisen in Fig. 4, w hich shows the diurnal changes in the discharge canal on Feb. 6 to 7.1973. Oxygen diffusion across the air-water interface in the canals was estimated by the stream morphology method of Churchill, liuckingham, and Elmore (1962), modified for diurnal oxygen calculations by llall (1970). The equation correlates diffusion rates in streams with depth and velocity. Estimates of the maximum rate of diffusion in the canals were consistently below 0.1 g Os m'8 ht" per 100% saturation deficit. Checks for diffusion in each diurnal study using the highest percent saturation observed showed the maximum possible rate of
-diffusion to be always less than 5% of the total net oxygen chanFe for 24 hr.
Therefore diffusion corrections in the canal metabolism curves were considered ncFhgible. Diurnal metabolism studies were conducted in the intake and discharge canals Oct. 14,1972, when the ambient temperature was still fairly high (25'CL
' These ' studies were repeated on Feb.6 to 7, 1973, when the ambient temperature (14*C) was near the annual minimum. The two stations in the intake canal were about 30tNI m apart, with a f hetween stations of 10.2 hr.
Stations in the discharge canal were about 1750 m apart, with a /t between stations of 2.7 br. RESULTS Bay Systems Results of summer and winter diurnal metabolism measurements in the bay systems are gisen in Tabics 1 and 2. l.ow early summer production IP + R)lescis
. near 3 to 5 g 02 m'8 day" rose quiskly by July to values near 10 g 02m-2 day" ' Variation in metabolism from day to day was powibly related to variations in cloudiness, turbidity, and the timing of the tidal cycle. Summer wiues were similar between the plume affected discharge bay and control areas.
A test showed no significant difference at the 95*. confidence level. Winter metabolism w.ts pencrally one third to one half the summer levels, and there was no ugnifkant difference in the values beturen areas. 't he P/R ratios ucre near 1 in the summer and dropped below 1 in the winter. Canal Systems Table 3 gises the average diurnal temperature, net daytime production, nighttime respiration, and the P/R ratio for cach of the canal metabolism studies. During October the net daytime production in the discharge canal was about 80% lawer than in the intake canal. Nighttime respiration in the discharge canal was about five times higher than that in the intake canal. During February the total metaleobsm (P + 10 in both canals was reduccJ to lesels approximately
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- 404 SMITH, Mr.KELLAR. YOUNG, AND LEHMAN TABLE 1 DlURNAL OXYGEN CURVE MEASUKEMENTS OF TOTAL METABOLISM IN PLUME AFFECTED ARF.A5 Metabolism,' g 0, m.: day d Number of stations P R sampled (day net) (nigho P+R summer Dmharge hay 6/14-15/72 5 1 96 3.NH 3.84 tannerl 6/29-lo/72 5 2.44 2.No 5.24 7/7-M/72 5 7.tui 6.63 13 63 9/M -9/72 5 4.50- 4.63 9.1 j Dewherpe bay 6/14-15/72 4 2.75 1.75 4.5o touterl 6/29 -3o/72 4 3.NM 2.u6 5 94 7,7-M/72 4 4.44 3.75 N.19 9/N-9/72 4 4 65 4 65 9.30 Mean 4o 3.5 7.5 Standard deviation 1 61 1.72 P/R I 14
%1nter Dmharge bay 12/14-15/72 5 1.56 I 9M 3.54 tinnerl 1/22-23/73 3 1.25 1.13 2.3s 1/34 - 2/1/73 1 1.3 M 2.75 4.13 Dis herye bay 12/12-13/72 1 2.05 2.95 5.6o toutert 12/14-15/72 4 1.70 2.10 3.No 12/16-17/72 1 2.80 0.42 3.22 1/22-23/73 3 2.lu 3.3M 6.12 Mean 23 3 .9 4o Stenelard deviathen o.01 3 o5 P/R o 91
- Wlues shown are averages from numlace of stations sampicJ
$0% of those in October. During February the net daytime production m the diwharge canal was about six times hi Fher than in the inrake canal, showing a reversal of the relationship found in October. Nighttime respiration was still higher in the Jiuharge canal by a factor of 2.5. The P/R ratios during both the
- October and February studies showed that con umption in both canah significantly outweighed production, and indicated that both were highly heterotrophic systems. The persistence of net respiration in the discharge canal between sunrise and noon in February corresponds to the 0800 to 1000 injections of chlorine into water passing through the plant (Fig. 4).
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METABOLISM OF THERMALLY AFFECTED COASTAL SYSTEMS 4W., TABLE 2 DIURNAL OXYGEN CURVE MEASL'REMENTS OF TOTAL METABOLISM IN CONTROL AREAS Metabolism ' g 03 m'8 day" Number of stations P 'R sampled (<* .f ne tt fright) P+R Summer Fort Idand N/2-3172 4 6.3 6.2 12.5 (inner uation4 N/16 -17/72 4 4.HN 9.26 Fort Idand N/2-3/72 5 5.54 5.3N 10.92 (outer watene N/16-17/72 5 5.54 5.63 11.17 Hodges idand N/10-II/72 9 3.25 4.13 7.3 N Mean 50 5.2 I o.2 Standard desiation 1.20 0 7N F/R o.9n Winter
- Fort IdanJ 2/13-14/73 3 2.3M 3.94 6.32 linner watend Fort Idand 2/l3-14/73 3 1.62 2.96 4.58 fouter watione
. IlodgesIdanJ 2/22-23/73 2 1.25 3.06 4.31 2/22-23/73 3 1.4 1.6 3.0 Nest intake tanal 12/l H-19/72 I l.H3 2.03 3.N6 at marker 20 Mean 1.7 2. 7 44 Standard deviation 1.30 1.65
' P/R o.63
' Values shown are averages for number of stations sampicJ.
j DISCUSSION Bay Systems The summer total-metabchsm range of 3 to 14 g O2m-2day *' measured in this study fell within the lower two-thirds of the range of values obtained from many different types of Texas bay systems (Odum,1967). Our values, however, were nearly the sarre as those of bays with consumer reefs, the type of Texas system most similar to the Crystal River area. Day et al. (1973) alw found values of this magnitude in a small shallow bay in Louisiana. 3 II-169 _ = --
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- 406. ' SMITH, McKELLAR YOUNG. AND LEHMAN Temperature may ~have a push-pull effect on ecosystem function, accelerating productitm as well as respiration. Therefore the effect of heat could be either stimulating or stressing. If push and pull are of the same magnitude, the net effect may be to accelerate retychng while maintaimng the same stock levels.
Another effect may be to cause component readjustment and adaptation.
'shif ting species composition and deminante to maintain optimum energy
- processing under the new conditions. A combination of these two. actions may also occur.
The similanty of metabolic function between the plume-affected area and other nearby toastal environments may indicate the adaptation of the ctosystem that developed after mid-1966 under the influence of the thermal regime of the power plants. If the metabolism of the control areas is indicative of prechermal TABLE 5 TEMPERATURE AND TOTAL METABOLISM IN Tile INTAKE AND DISCllARGE CAN \LS Av. diurnal Metabolism, g 0, m 8 day tem p., Net day time Nighttime
'C producchm rc .psrat km P/R O.. 14.1972 Intake unal 24.7 I.55 3.10 0.5p Disharge rsnal 29,9 o.Jo 14 95 o 02 Feb. o - 7,197 J In4Le canal 14.4 0.25 2.M5 0 09 Ins harge canal 20 o 1.55 7.in t o.22 loading levels, these data imply that the new system may be as functional as the one replaced. The exact nature of the adaptations was not evident from metabohsm measurements, which gave only the relative levels of photosynthetic production = and respiratory work functions.- Measurements of subsystem metabolism and levels and the kinds of stocks relative to other areas would be
- necewary to determine how the overall system had adjusted its individual compiments to the new conditions. Also, these data may not indicate the desirability of the new system vs. the old. Iloweser, as a single measure of overall system function, total metabolism ma'y. serve as an index of the magnitude of energy procesing in the existing etosystem.
These data may relate to the controversy concerning estuarine vs. ocean siting of power plants. Estuaries may be adapted to such multiple stresses as targe or rapid salinity change and larFe diurnal temperature ranFes. For a system to survive under these conditions, it must channel energy into mechanisms that cope with strew. This leases ten energy available for maintaining dnvruty and 4 g , 4 9 0 6 g m . p %. / 9 11-170 , 3 n V.- do . - - - * - 1a--- -
7 META 8OLISM OF THERMALLY AFFECTED COASTAL SYSTEMS 487 specialised functmns. A supplementary heat load therefore may cause minimum disturbance bceauw the sprem may already be adapted to strest On the other hand. the ocean enuronment may have systems designed on the ham of forcing functions of smaller and more predictable parameter ranges. As a result, the need to channel cncrgy mto adaptarmn to strew may be minimized. This would allow the maintainante of energetically expenure system disersity and speciah4ation of function. Impoun t a stress in the form of an additmnal heat load may hase a large effest because no mechamsms may exist to deal with it. Canal Systems The studies of anal-system metabolism showed that both intake and diwharge can.il ecosystems ucre highly heterotrophic. Chcmical and biological changes in the coobng water as it was cartulated through the canals sould be similar to those mduced by any heterotrophic system. lieterotrophic stream systems with P/R ratios as low as 0.008 under polluted conditmns (Odum,1956) hase been documented mainly for freshwater systems. llowever, unpolluted streams also may tend to be heterotrophie if they receive a sufficient mflux of organi: matter (llall.1970L Currents in stream systems stimulate heterotrophy by providing a constant influx of orgamc matter at no energy cost to organisms and by remosing respiratorv waste. Nixon et al. (1971) found that osygen uptake by a bed of bay muwels (llrrilus cdulo I.J follows an approumate h> perbolic response to increasing current speed. 't he higher velocity m the dissharge canal. as well as the higher temperature. probably contributed to its higher metabohe levcit Other factors stimulating heterotrophy in the power plant canal systems could be such stresses to photosynthesis as (1) limitation of light to bottym producers, resulting from the depth and the steep walls. (2) chlormation, and (3) periodic turbidity. lieterotrophic components of balanced systems stimulate overall productivity by performing such work functions as recyding minerals for the total system. One means of determining the relative impact of heterotrophy in the canals on inc surrounding scosystems may be to compare the total metabolism in the canals with that m natural bay systems. The entire area covered by both mtake and diwharge canals was 5 x 10' m2 (124 acrest During October when the ambient temperature was still high. net daytime production of the entire area of both canals was 6.3 x lo' g 0:/ Jay (Table 4). Dividing this value by the average summer net daytime production of 4.5 g O 2 m' Jay-' (Table IP obwned for the bay systems mdicated that net production it: the canals was equiulent to the net production of 1.4 x lo' m2 (35 acred of natural bay system. Similarly, mght respiration in the canals in October was
'This uluc n the nn an of average sunimcrrime values for plume atfested and (ontrol areat ~t ha average value was used here snse there was no statistical dif feren(c demonstrated twtween metabolmm in the plume attested and control aren.
II-171 m,
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sp -: - ~ - ~ 488 SMITH, McKELLAR, YOUNG, AND LEHMAN equivalent to a night respiration of 6.6 X 10 8 m 3 (163 acres) of bay system.
- Similar bay system equivalents were found for winter values of net daytime production and night respiration in the canals (Table 4). Therefore, the canal crosystems produced 70 to 75% less oxygen than the same area of bay crosystem and respired about' l.5 times more oxygen than the same area of bay.
If total respiration in the discharge bays was twice the nighttime respiration (Tables I and 2), the annual range was 5 to 10 g Os m3 day". The calculations of Nixon et al. (1971) from Collier (1939) showed that the total respiration of an oyster reef was 12 g 0 m'8 day * , An oyster reef, therefore, consumes oxygen at a rate I to 2 times that of the overall bay system. Since the canal f TABLE 4 TOTAL AlETABOLIS\1 OVER ENTIRE AREA OF BOTil CANAL.S (124 acres) AND AREA OF NATUR AL BAY SYSTEAl WITil EQUIVALENT AlETAI,0USAt* Canal May ecosystem metabolism, equivalent, Io' g 0,Iday acres tktober Net dayrinie produs tion eJ 35 Nghttime respiration 29.o 16J February Net Jaytime production 2.) J2 N: thetime respiration 19.1 197
*%ce Jiwuwion in text.
systems also respire oxyFen at a rate I to 2 times that of the e ill bay system, the consumption of the power plant canal sys* cms is perh.ps si..,dar to an oyster cef of the same area. Such calculations may be helpful in defining the relative role of the power plant and its aunciated canals as a component in the coastal ceosyst em. ACKNOWLEDGMENTS The study reported here was performed as part of a project entitled "Alodels and Alcasurements for Determining the Role of the Power Plants at Crystal River
, in the Coastal System of Florida," suggested as contract GIDet9 with Florida Power Corporation and ihreeted ley ll. T. Odum.
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METABOLISM OF THERMALLY AFFECTED COASTAL. SYSTEMS 489 C. liigh, M.'llomer, W. Hoynton, M. Kernp, and N. Black sided in collecting field data. J. L., Fim and M. Keirn furnished field equipment and supplies. R.J. Beyers of the Savannah River Ecology I.aboratory advised on methods in the early stages of the project. The Florida State University System Institute of Oscanography provided their research vessel R/V SUSIO during December 1972. D. McMulhn of Flonda Power Corporation maintained the research boats used in this study. REFERENCES American Pubhe llealth Association,1971, St.rnJard Afethods for the lixJunnarroa of li'arer Jud \\,rW(WJter. lith cJ., New York. _ ,195 5.StanJard tietholsfur the I xaminatron of LYater. Setsage, and Industnal \t'astes, toch eJ., Federation of Sewage and Industrial Wastes Asweiation. New York. Churchdi, M. A., H. A. Budingham, and 11. L. Elmore,1962. The PrcJictron of Strearn Nearratron Mate s. Tennessee Valley Authority, Division of Ilealth and Safety. Environmental liygiene Branch, Chattanooga Tenn. Colher A.,1959, Some Observations on the Respiration of the American Oyster Crassostrea arrgeurs,e (Gmelin), Publ. Inst. Af orr. Sci, l'uru 'I cx., 6i 92104. Copeland. B. J., and W. R. Duffer,1964, The Use of a Clear Plassie Dome to Measure Gaseous Diffuseon Rates in Natural Waters,l.imsol Occ.rnogr., 9:494-499, Day, J. W., W. G. Smith, P. M. Wagner. and W. C. Stowe,197 3.Comutunity Structure and Carkun linJget of a halt starsh and Shallow Bay I stuarrue Systent en I.onnrana. Center for Wetland Rewurces, Louisiana State University, Baton Rouge. Fox, J. . L. and M. S. Moyer,1972 Effects of Power Plant Chlorination on Marme
%ruhiota. in i uvernumental %tatus Report. July-December. Viorida Pou er Corporation, St. Petersburg.
11411. C. A. %. 197o, Migration and Metabohsm in a Stream 1%osystem. Ph. D. Thesis. Department of biology, Unn'ersity of North Caruhna. Chapel lhil. Nixon, S. W., C. A. Oviatt, C, Rogers, and K. Taylor,1971. Man and Metabolism of a Muswl BcJ. Occologra (#crirns, 8: 21 30. OJum,81. T.,1967, Biok>gical Circuits and the Marine Systems of Texas, in Pollstron and Alarrue i cology. T. A. Olson and F. J. Hurgess IEJs.). Interwience Publishers, a division of John Wiley #s Sons, Inc., New York 1956, Primary Productum of riowing Waters i emnol. Oct. nogr. 2 85-97. _, and C. M. flo4 ins,195M. Comparative Studies on the Metabolism of Marine Waters, Publ. loont.- \t.rr. %cs., Cun 1ex., 5s 16 46. Truesdale, G. A., A. L Downeng, and C. E. Lowden,1955. The Soluhdity of Oxygen in Pure Water and Sea Water,J. .trpt. Le nn Si 53 62.
. ~.
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APPENDIX B Energy Cost Benefit Approach to Evaluating Power Plant Alternatives Howard T. Odum Environmental Engineering Sciences and Center for Wetlands University of Florida Gainesville 32611 A vital economy requires good use of free resources of the environment, effective utilization of energy resources, and elimination of unnecessary wasteful expenditures of money and thus energy. Our economy is intertwined with that of nature with part of our basis for life supplied by energy flows of the environment acting to produce winds, rains, tides, the seashore-building waves, the vegerarton that filters, cleans, and restores soils etc. We rarely evaluate or are aware of these very large energy
. supports from nature that come mainly from the sun's action in keeping air, water and other materials of the biosphere circulating. The rest of our encrgy basis is from fuels that we buy with money and for this basis we are kept painfully aware by payment of the money that we must earn. The two kinds of energy are shown in Fig.1.
Because of the close intertwining of the several kinds of energies that support our economy (some natural, and some paid for), we can hurt our economy and make it uncompetitive with loss of incomes, increased taxes, etc., if we make decisions that waste energy. We waste energy if we interfere unnecessarily with the free flow of energies of the environmental 1 l areas. We waste energy if we build technology that is not nscessary. We waste energy if we try to add a new '~lustry, if that new industry interferes with more of the old natural energy support to the economy that the new industry contributes. We waste energy if we try to invest our accumulated resources in new enterprises if there are no new resources that will be II-175 j 1 1
- j
I U,, I h Price l Money
; incorne i
I Free Intertwined Fuels a Natural Energy v Economy of m- N-b Bought Goods a l
" Man 8 Nature
' V Flows Wind', Purchases Services Tides, Rain Degraded Heat Leaves System Unable to do Work 9 I d
Fig. 1. Diagram showing two main kinds of energy that support the intertwined economy of man and nature: Natural free flows and purchased fuels and goods and services based on fuels. l l l l ,a. 11-176
tappea by the new enterprise. In other words new enterprises will fail if energy costs are in excess of the energy returns that ultimately develops from the investment. Energy Cost Benefit Idea for Decision Making In the previous paragraph we suggest that the correct way to make an economy most vital, most prosperous, and continuing to be competitive with other areas or other plans that might have been developed is to maximize the energy income and minimize the energy waste. To calculate the total energy available we need to add the two kinds of energy shown in Figure 1: (1) the natural energies , and the (2) bought energies. The bought energies depend on the regions overall income of money which can go back ouc to buy fuels and goods and services that are in turn based on energy flows elsewhere. The amount of energy that income buye depends on world prices, and these prices are going up because of the increased energy cost of getting energy as we have to dig and drill deeper and deeper into the ground and further offshcre. If a decision needs to be made that involves a new enterprise such as a power plant, it should be made so as to maximize the energy that can be developed and minimize the waste. One may measure the energy change in free contributions from the environment and from the new activity with its various alternative means of operation. The combination that provides the maximum energy benefit and least energy cost is the one that contributes most to the economy of both man and nature. Rama=her that man's economy is so intimately interwoven with nature that a stress on che environment's productivity ultimately is a drain on man's money economy as well. II-177
+ _ , ,# _ . _ . __ .. .. ,_ _
f Thus we have evolved the energy cost-benefit analysis as a new ! procedure for tabulating the annual energy contributions and losses associated with proposals so as to recommend which plans are best. The method psts economics and environment in perspective using the conson denominator of energy as the basis since energy can be a measure of all useful work upon which the systems depend. Measurements are made of the energy flow into work from all natural or bought contributions directly and indirectly and calculated in units of Calories (Kilocalories) which is the same unit one sees in TV' advertisements'about diet. Work of man, machines, winds, etc. can be measured in Calories. 4 Energy Concentration Factors Towards Useful. Work There is one critical detail about making energy comparisons that is new and makes the energy cost-benefit procedure different from some efforts in this direction made earlier. Different forch of energy are in different concentrations.- A flow of gasoline is a very concentrated flow of energy, 36,000 Calories or more in a gallon in a form that can cause very effective work of machines. A flow of sunlight, however, is a very dilute flow of energy with one thousand trillionth of a calorie in a gallon of space through which light is passing. When energy has done its work it ends up in
' dispersed heat without sharp differences in temperature. Such dispersed heat is really the random motions of the molecules,and man has no way to get further work out of calories that have been degraded into the dispersed heat version. One can only hook heat engines to heat sources when therc
! are great' differences in_ temperature as between the hot boiler of a steam power plant and the cool outside. Thus a Calorie of energy is not a measure II-178 I l~ 1
, - , n - - - , . - . _
t, .. of the ability to do' work unless one also indicates what kidd of energy form' it is ia. If it is in a concentrated form like gasoline it can do much work per calorie; if it is dilu'te energy like sunlight, it can do only a little energy per calorie because it uses energy in being concentrated. It can do no work if it is already in dispersed heat form . Thus there are conversion factors to show the relative work abilities of each type of energy. In one procedure we convert all energies to FOSSIL FUEL WORK EQUIVALENTS. A Calorie of sunlight for example, seems to have a , work contributing ability to our economy of around 1/2000th of a calorie of coal or oil. Most people are already familiar with the fact that it takes about 4 calories of coal to generate one calorie of electrical energy. Electrical energy is a high quality, high concentrated form of energy and thus costs more energy to develop and can generate more work per calorie in processes. Electrical energy can do things that lower energy forms cannot. Summarizing the procedure, one may make an energy cost-benefit calculation by calculating the annual flows of energy involved in a proposed enterprise, the changes in energy flows of the environment represent all these in fossil fuel work equivalents using the conversion factors between various forms of energy and fossil fuels. Then one adds up the pluses and minuses associated with the questions being considered and recommends the one with the highest ratio of energy benefits to energy costs. This procedure gives due credit I to the environment, whereas the traditional money cost-benefit method gives l l no credit to environmental contributions, or to the energy resource changes l l involved. Consider next an example, the question of a cooling tower versus enviro m atal cooling. II-179 es
+ e
,m
Cooling Tower Question In several places in Florida cooling towers are being considered in comparison to the alternative of flowing marine or fresh waters through the plant for cooling, a process that initially changes the aquatic ecosystems causing them to develop a different kind of ecosystem one in balance with the plant's operation. There are many studies going on throughout the United States by Federal, state, local agencies and by power authorities to measure the stresses that develop during the transition from old ecosystem to the new one. A very open question is the relative value of the old ecosystems compared to systems adapting to heat flows. When the temperature differences are small there may be positive effects on the ecosystems. If temperature effects were very large (larger than allowed by various permitting agencies) normal life would not prosper in these ecosystems. Many questions such as the action of power plants on aquatic plankton are involved. The plant acts somewhat like a giant oyster in filtering and recycling some of the aquatic planktonic life. The main question is whether the artificial giant oyster (the power plant's action) is similar, stressing, or energy enriching. Studies in progress are probably able to show what percent of the original ecosystem's biological productive energy budget in driving the food chains that support fish etc. has been increased or decreased. The question we address in this article is not that one, but the evaluating of the environnental i impact as compared to the other energy inpacts on the combined economy of both , l man and nature together. Energy Cost Benefit Table Given in Table 1 lb very simplified version is the kind of calculation we l l l are attempting to make with the energy cost-benefit procedure for annual ). 11-180 ! W
y impact of a cooling tower comparsd to an environmental area. Just for sake of a sample calculation without reference to any particular plant suppose 1 tha annual running cost of a cooling tower in dollars including amortizing the cost of construction, repair, operation, maintenance, etc. is 5 million dollars in 1974 dollars. If about 30,000 Calories of work (fossil fuel equivalent) are done throughout our economy for every dollar that circulates, then the cooling to'erw puts a cost load on our economy of 150 billion kilocalories of fossil fuel equivalents per year. This is a waste to whatever extent that it is a greater energy cost than an alternative. Suppose i
- the alternative cooling were to completely inhibit the biological production t
of one square mile of estuary (2.58 million square meters). This may be l 1 10 times whet is actually being observed. In this, we regard as inhibited j the biological community production based on the interplay of sunlight 1 incoming at 4000 Calories per square meter per day. Multiplying this by i 365 days and 2.58 million square meters in a square mile one has the annual contribution of solar based economy upon which the estuarine life is based. I (For this calculation we left out tides and winds although these are ! included in the real analyses we are doing in real examples). Suppose the ( fossil fuel equivalents of the solar based food chain is 1/2000th of this. The result is 1.89 billion kilocalories per year, a much smaller value than the cooling tower. In this example the cooling tower turns out to be a waste and should not be built. So far preliminary calculations at Anclote j and Crystal River suggest that cooling towers are wasteful enere also. Final report on the detailed calculations on the system at Crystal River are due this Fall.
- Many government recommendations are bning made now about power plants, i
barge canals, draining swamps, choices of water use, etc. that are made by < II-181 m .,. ~ , . . . - . . _ . _ ,__ _ _ . . - _a
+
. . - . . .. ~.. -
political judgements of boards and individu.ls under pressures without
\
objective. comparison of environmental values and money values. Many of these may be wrong; sometimes a development adds net energy; sometimes it decreases net energy. The energy cost benefit analysis method is now sufficiently accurate to substitute for judgements which are made without substance. Some of the concentration factors will need tightening up for greater accuracy. The public end the judicial sw w will have to learn the manner by which the greater good is measured by t.,.n work. We may even need a State and Federal constitutionaJ amendment that says that no man has the right to re- ce the net energy resource of the public or his neighbors, since this affacts the public good and ability to survive. I i 1
~
f II-182 l i !
Table 1. Sample of an Energy Cost-Benefit Calculation for Two Power Plant Cooling Alternatives. Annual Work in Kilocalories of Fossil Fuel Work Equivalents. Cooling Tower Estuarine Cooling Special Energy Cost - 150. x 10' O Environmental Energy 9 Disruption 0 - 1. 9 x 10 I I l l l I l II-183
* ^
4 t i , APPENDIX C PRELIMINARY CAIfULATIONS & ENERGY QUALITY RATIOS, T WORK EQUIVAIENT FACIGtS. 4 f 4 W.M. Kemp W.R. Boynton with assistantee of M. Sell and.J. Zucchetto Systems Ecology Department of Environmental Engineering Sciences University of Florida Gainesville, Fla. 32611 1 l t l L II-185
, ., u ,
(1) CALCUIATIOi T ENERGY QUALITY RATIO FOR WIND This calculation uses data for the energy balance of the earth's atmosphere (from Hess,1967, af ter Phillips,1956) and the EQR (sun-wind) is calculated based on the amount of solar energy required to generate the resulting wind energy. 273 K.E. K.E. mean 90 P.E. P.E. Sun 1 5 19 642 st e s A X 96 648 X)X h/ T/ 127 119 109 74
@" ,@ o
@ 3.
Y v @v : EDDY VISCOSITY POTENTIAL KINETIC DIFFERENTIAL ENERGY OF ENERGY OF 4 HEATING MEAN FLOW MEAN FLOW 448 25,318 72 5,795 ing i 648 273 FRICTION ' POTENTIAL KINETIC fr m Hess ENERGY OF ENERGY OF ( 74 D:STUR8ANCES DISTURBANCES 524 642 ,,447 EDDY VISCOSITY II-186
s-
-Calculations under two assumptions:
A ~ 34462 " I. Energy quality of sun to wind = B + C 119 + 74 II. A second method _ assumes all back pumping and terms B and C should be included in the calculation. A " 34462 "
- EQ. of sun to wind =B + C + D + E 427 References Odum, H.T. : 1974. Marine Ecosystems with energy circuit diagrams. Chap. 6 in Nato Conf. Modeling and the Ocean. Elsevier Publ.
Hess, S.L. 1959. Introduction t) Theoretical Meteorology. Holt, Rinehart and Winston, N.Y. 362 pp. Phillips, J.1956. ' Q.J. Royal Met. Soc. 82 (352): 123-64. 4. l + II-187
~ '- - - -
-1, ,_ , __
(2) CAlfULATION E ENERGY QUALITY RATIO FGt TIDES. . This chiculation is based on the use of tidal energies to generate electric power at one exiting site, La Rance, France, and one well-studied proposed site, Bay of Fundy, Maine. The calculation considers the construction, operation and maintenance costs for power plant, the loss in tidal area in adjacent areas resulting from construction of dikes, and the cost to store energy in pumped storage to be equivalent in value to the cycling, coal fired electric power generating plants. onstructio . Operation Pumped Costs Mainkenanc Storage 9 1.9 10 3 (F WE) i
>0.}X10 1 (FFWE) i1 Tidal Versatile Tidal Power 27.3 X 10 Power X\ alactric
.(TWE) Plant f / power 9
non-versati4e--[ 19.8 X 10 electric (FFWE) over f_ adjacent - system T X l' 12.9 X 10 9 V
, , loss of Tidal -
Energy in T (TWE) Adjacent Areas EQR (Tide - Fossil Fuel) = al er umed EQR (Tide-Dollar) = 0.41 (3 x 10 ) = 1.37 x 10 9 t
- II-188
l l l
'II. 'Example - La Rance ~
Total Capacity = 240 Mw (2410 Mw Units) 6 , CapitalCost=g-120/KWgeneratingcapacity=$864.x10 Net Energy Output = 544 GWh/yr 0 Area of Impounded Pool = 22 x 10 m Output of 1-10 N turbine for various levels of head Itax. output (Mw) Head Mode 9m 7m 5m 3m Direct (basin to sea) 10 N 10 8 3.2 Indirect (sea to basin) 10 9.5 5.5 2 Assumed Annual Costs and Capital Cost Amortized (from Lawton, 1972)
= $.0075/KWH 0 0
= $.0075/KWH x 544 x 10 KWH/yr = $4.1 x 10 /yr Assumed Annual Costs (including cost of pumped storage) 0 6
='$.0087/KWH x 544 x 10 KWH/yr = $4.7 x 10 /yr 34.86 GH = 165.0 x 10 6KWH/yr
= ($4.7 x 10 ) x Annual Energy Output If Always Generating at Capacity 0
240 W x 8760 = 2.1 x 10 MWh/yr
= 2100 CWh/yr Percent of Capacity Being Generated with Rance Tides
= .26 = 26%
2 II-189 4 g usw.-v -
, rm. ,
~e- _ -_, _ __
Natural Tidal Energy Available (7m range)
- W = pg A x
= (1.025 g/cm )(980 cm/sec)(2.2 x 10 11cm 2 )(7 x 102 c,)2 2
= 54.1 x'1018,,,,
18
= 54.1 x 10 ergs (2/ cycle)(705 cyclas/yr)(3.15 107 sec)
~
14
= 24.2 x 10 - 24.2 x 10 Kw (8.66 x 10 )
= 209.6 x 10 7" yr Energy Quality Ratio
'(7m range)
Tide Energy: 209.6 x 10 7KWH/yr 7 Power Plant Output: 54.4 x 10 KWH/yr x ( 0 ) = 53.0 x 10 KWH/yr Annual Costs: ($.0087/KWH) (544 x 106KWH/yr) (34.80 )(.975) = 16.1 x 10 7 Net Output = 36.9 x 10 KWH/yr (EQR) 7m tide = 2 69 = 5.7
References:
Anon. 1966.Eng 202:17-24. and " Economics of Lawton, F.L.1972." Tidal Power,"Tidal Power in Gray andinCashus Bay of (eds).Ti Fundy"dal Power. Plenum Press, N.Y. McLellan, H.J.1958. Energy considerations in Bay of Fundy System. J. Fish Red. Bd. Canada 15(2):115-134. 4 II-190
,4 ('. I. Example for Bay of Fundy (site 7.1, Shepody Bay, single basin, double effect) Installed capacity - 2916 MW ,108 Gen units. 6 Annual Electrical Energy Prod. - 5402 x 10 KWH 8 Basin Area = 2 x 10 fe (MLW) -- 9 x 10 f t2(MWH)
= 5 x 108ft2(ggL)
Basin Volume - 5.5 x 1010ft 3
= 4.6 x 10 m Tidal Range (RMS) = 32 ft Reduction in Tidal Amplitude in Surrounding areas resulting from Plant at site 7.1 7
Energy Reduction - 23% ( for a 10 x 108 ft.2 ocol Tidal Range Reduction = 4.5* J( Cost Dependable Peak = $32.65/kw/yr Pumped Store Cost (Capital only) = $6.80/kw/yr Assumed Economic Plant Life = 75 yrs. Capital Cost = $699.7 x 10 6 Annual Cost (including amount of capital and interest on loan) 6
= $53.6 x 10 /yr
= $0.0075/KWH Cost of Operation 6
$53.5 x 10 x 34.86 m = 1870 x 10 KWH/yr 6
Pt aped Storage Cost
$6.80 (capital) + 25% (oper) = $6.80 + $ 1.70 = $ 8.50/KW 0
($8.50/KW)(1x10 KW)* = $8.5 x 10 /yr x = 297 x'10 Total Cost to Get Electricity of Coal-Generated Quality
= $62.1 x 106/yr = 2167 x 10 6KWH/yr
- see Fig. 3 , ; p. 119 11-191
. n u, . . . - . , .- .
d A. Tidal Energy Used (Both Directly and Indirectly) to Operate Power Plant (1) Tidal Power Across Dyked Section: 30 x 10'yr" (2) Losses in Tidal Power Available in Pool Behind the Construction of Dyke. 9 H (.23) x (30 x 10' ") = 6.9 x 10 r (3) Iosses in Tidal Power Availa' ole to Adjacent Areas (.20) x (30 x 10' ") = 6.0 x 109" 9" Total Tidal Power Used in Project = 42.9 c 10 B. Total Cost (in FWE) to Get Electricity of Coal-Generated Quality (i.e. available to meet demand) 2.2 x 10' yr C. Annual Electrical Output (in FWE) 19.8 x 10' " D. Net Output (in FFWE) 17.6 x 10' " E. Energy Quality Factor for Tide Relative to Fossil Fuel
-17.6 = 0.41 I*
or
= 2.5 E 42.9 FF 17.6 Tide Annual Electrical Output in F NE:
6 0 i (5402 x 10 KWH)(3.6 ", g,) = 19,800 x 10 KWH/yr II-192
Energy of Tides (1) (from McLellan,1958)
, Apr Fo Vo g ,g 2r f 2 T 3
Vo = 2.2 fps = 67 cm/spc p=1.025gm/cm Assume - 41 g = 980 cm/sec 7 aa - 32.4 ft = 9.84 m (o=16.2ft=4.94m=4.94x10cm I = 120 ft - 36.6 m - 3.66 x 10 cm 1 = 5.2 Km = 5.2 x 105 c, A = 19 x 10 cm 5 = (19 x 10 cm )(1.025 g/cm )(980 cm/sec )(4.94 x 10 cm)(67 cm /sec) 2
= 3.15 x 10 16 =
6 3.15 x 10 KWH x 8.66 x 10 3
= 27.3 x 10 9 (2) Avg.Nat. Energy = 2590 MW = 2.59 x 10 KW i
~
= 2.59 x 10 KW x 8.66 x 10 5 9 WH
= 22.4 x 10 yr (3) Work from a pressure field E. = g A x
}
= (1.025 gm/cm )(980 cm/sec )(4.6 x 1011c ,2)(9.84 x2 0
= 2.24 x 10 ergs 0
= 2.24 x 10 ergs (2/ cycle)(705 cycles /yr) 3 he
= 3.16 x 10 ergs /yr(3,15 x 0 sec = 10 sec
~
= 106KW x 8.66 x 10 5 = 8.66 x 10' yr- yr 11-193
(3) CALCULATIN OF ENERGY QUALITY RATIO FOR OCEAN WAVES This calculation considers the sediment transport work done by ocean waves and the equivalent fossil fuel work required to transport the same quantities of sediment over the same distances. f l Wave Energy 2.01 X 10 Kcal Upshore Downshore Sediment 73 X 10'3 ; Sediment yds # Xd j 3X 10 0yd
- 3 8
Dredge 3.65 X 10 Kca
>(
Energy g
/ \
\
l I n " b Y
~ ~J
- '$14 .6 X 10 3 -
Dredge I Money EQR (Wave - Fossil Fuel) = 0. 3 = 0.182
~0 l EQR (Wave - Dollar) = (18.2 x 10 -2)(3 x 104 ) = 6.1 x 10 II-194
E Joao
, tooo j sooo k p $$ ,/.A ! ' !
%\* e v
f from Caldwell, B.E.B. I (d no
/
8 gl oo l so as.v, w .r s a 'o s awa <ao clongshore energy it.~/bs.fml//lons) / day / ft.becch 6 Assume wave energy = 10 ft Ih/ day /ft length of beach = 17,000 ft. 6 2 E = (10 )(1.7 x 10 )(3.65 x 10 )(3.14 x 10-0) = 20.1 x 108
= 2.01 x 10'Kcal/yr Sand accretion (from graph)
V = 200 cu. yd/ day = 73,000 cu yd/yr Cost of removing sand 1 1
$0.20/cu yd (1950 Dollars) x 25,000 = 5000 3 3
Total cost of dredging 8 5000 Kcal/yd x 73,000 cu yd = 3.65 x 10 gc,7 9 Fossil Fuel Work Equivalent of waves @ 10 ft lb/ day /ft
.365
= .182 2.01 FFWE -
EQR = 5.51 II-195 .
- m. .
References:
Bascom, W. 1964. Waves and Beaches, the Dynamics of the Ocean Surface. Doubleday and Co. Garden City, N.Y. 267 pp. Ingle, J.R.1966. The Movement of Beach Sand. An Analysis Using Flourescent Crains. Elsevier Publ., N.Y. Weigel, R.L. 1964. Oceanographical Engineering.. Prentice-Hhil, Inc., Englewood Cliffs, N.J. l l t i I1-196
I (4) CALCULATION OF ENERGY QUALITY RATIO FOR WATER HEAD ( k Summarizing with Diagram
- lh Y \w f *go& 8/ %
s%'o~ sN & s?+ ** sd Yearly , P.E. Rivet c) 1 Head rw ons rev of hand Dam Dikes and 2.05 x 1011(elec ( 4.139 x 10 11Kcal/yr 8.196 x 1011Kcal/yr I 117* Q Powerhouse * (gross output) (n t output) 5)
?
*All numbers except h are at fossil fuel quality level.
Relationship between river head and fossil fuel is 11 6.73 x 10 11 = 1.63; that is, river head calories are 1.61 times more 4.139 x 10 concentrated than fossil fuel calories. River head calories are 2.46 times less concentrated than electrical calories. h II-197
Energy Quality Ratio
.All data are cross referenced in Fig. 1
- 1) Power Plant output in KWH (yearly average) 238,090,000 KWH 238,090,000 KWH x 860.5 Kcal/KWH = 2.049 x 10 11 Kcal/yr converting to fossil fuel equivalents 2.049 x 10 11 Kcal/yr x 4 = 8.196 x 10 11 Kcal/yr (from Apalachicola River Basin Reservoir Regulation Manual)
- 2) talculation of input energy net head, full load, in feet = 30.5 ft.
turbine discharge (cfs) 1 unit operating 5,500 2 units operating 12,000 3 units operating 18,300 Average annual flow past dam = 21,311 cfs (from Apalachicola River Basin Reservoir Regulation Manual) l Calculating power developed from this flow with a head of 30.5 f t. HW H = height (ft) Pw = 9{ W = weight (1bs) T.= time interval
, Pw = power (ft poinds/sec)
V = volume of water Pw = HwQ w = weight (1bs/ft 3) 1 whereQ=f=volumetricflowrateinft/seeoutofreservoir II-198
Pw = HwQ
= (30.5 f t)(62.3 lbs/f t 3)(21,311 f t /sec)
= 4.049 x 107 ft-lbs/sec Pw'= 4.049 x 107 ft-lbs/sec x 1.945 x 10~ b ec 5
= 7.875 x 10 Kcal/ min Pw = 7.875 x 10 Kcal/ min x 60 min /hr x 24hr/ day x 365 days /yr 11 Pw = 4.139 x 10 Kcal/yr (formula from Healy, T.J., 1974)
- 3) Life time of _ lock-dam-hydrofa:ilities estimated to be 50 yrs (Mr. Roy C. Harrison, personal communication)
- 4) Calculation of construction costs Powerhouse $15,392,120 Lock 8,940,191 Sp111 ways and Dikes 26,906.434
$51,238,745 (1953 dollars)
The dam and hydrofacility appear to operate independent of lock and because of this the cost of the lock is not included in this calculation.
.'. Total cost in 1953 dollars = $42,966,243 Adjusting this figure to 1973 dollars we multiply by9c 1.6.
This must be done se that the $25,000 Kcal/$ ratio can be used, which is based on the 1973 figures.
., TowA fossil fuel investment = $68,745,988 x 25,000 Kcal/$
12
= 1.719 x 10 Kcal Prorated cost ovar 50 years = 0.344 x 10 1 kcal/yr O (Mr. Charles H. Snow, personal communication)
II-199 c_ m. . -
A
- 5) Calculation of yearly maintenence costs powerhouse $83,199/yr spillway and dikes $52.981/yr
$136,180/yr Converting to Kcal/yr using 25,000 Kcal/$
1I
$136,180/yr x 25,000 Kcal/$ = .034 x 10 Kcal/yr (Mr. Charles H. Snow, personal communication)
- 6) Calculation of costs associated with modified environments; i.e.
conversion of forests to reservoir. environmental costs = (forest loss /yr + river loss) - (reservoir gain) loss of forest metabolism - (33.5 x 10 3acres)(20 x 10 Kcal/yr) 32 (4.046 x 10 m / acre) 11
= 27.11 x 10 Kcal/yr loss of river metabolism = (4.0 x 10 acres)( 10 x 10 Kcal/yr)
(4.046 x 10 3,2/ acre)
= 1.62 x 10I kcal/yr gain in reservoir metabolism = (37.5 x 10 3acres)(4.6 x 10 3Kcal/yr -) 32 (4.046 x 10 m / acre)
-= 6.98 x 10 1 cal /yr differential cost = (27.11 x 10 + 1.62 x 1011) - (6.98 x 1011)
= 21.75 x 10 11 Kcal/yr Converting this to fossil fuel quality 21.75 x 10 11 ,
gyg l @ 20 (W. Boynton, 1974. Unpublished report) 11-200 l l
References
'Apalachicola. River Basin Reservoir Regulation Manual.
Appendix A. Jim Woodruff Reservoir, Apalachicola River, Fla. Mobile District. U.S. Army Corps of Engineers. Mobile, Alabama. Revised Aug., 1972. i Boynton, W.R. 1974. Regional modeling and Energy Cost-Benefit Calculations Regarding Proposed U.S. Army Corps of Engineers Dam on the Apalachicola River at Blountstown, Florida.* Dept. of Environmental Engineering, Univ. of Florida, Gainesville, Florida. Unpublished document submitted to Corps of Engineers in response to call for comments on Proposed Apalachicola River Dem.
- Report based on Studies of Models for Coastal Management sponsored by NOAA, Sea Grant Project #R/EM-3, H.T. Odum, Principle Investigator.
Mr. Roy V. Harvison Hydro Power Branch. Operations Division. Mobile District. U.S. Army Corps of Engineers. P.O. Box 2288. Mobile, Alabama. Personal communication. Healy, T.J. 1974. Energy, Electric Power, and Man. Boyd and Fraser Publishing Co. San Francisco. 356 p. Mr. Charles H. Snow E.E. Hydro Power Branch. Operations Division. Mobile District. U.S. Army Corps of Engineers. P.O. Box 2288. Mobile, Alabama. Personal communication. i l 11-201
y-y ., ,
. , L,
(5) CALCUIATIOi 0F ENERGY QUALITY RATIO FOR WATER AS DILUTANT This calculation is based on the fossil fuel and dollar cost of
' desalinating ocean water. It is assumed that the fossil fuel work
^
required at a desalinization plant is equivalent to the work of the hydrologic cycle in supplying fresh water. O&M Mate.*ials
& Service /s 1.7 x 10 /
Kcal/10008 al. ke
/
j$0.69
,I -
Sea # Desalin- - Fresh Water ization
~
Water 0 AF Plant .8 x 10 AF Kcal/1000g I i f
- qr EQR (freshwater'- fossil ruel) = *f0 = 1.06 II-202
Of 78 plants surveyed around the world the most efficient plants produced water at cost $ 60 .82/1000 gal. KC"1 Input energy (FFWE) = $.69 x 25,000 3
= 1.2 x 10 Kcal/1000 gal Free energy as dilutant of 1000 gal fresh water produced.
A F = ( 35 )(1.99 cal /deg-mole)(300 )(In 3 000 grams of salt = (1000 gal saltwater)x(8.55 lb/ gal)x(35 965 water)x( 54 y)
= 141,000 g salt 5 a salt O F = (126 cal /g salt) 1.41 x 10 , , = 1.77 x 10' gal.
EQR of fresh water as dilutant in FFWE = = 1.04
References:
Odum, H.T. 1970. Energy values of water resources. Proc 19th So. Water Res. Poll Contr. Conf. (56-64) . United Nations. 1969. First United Nations Desalinization Plant Operation Survey. U.N. Publ., N.Y. United Nations. 1967. Proc. of the Interregional Seminar of the Economic Application of Water Desalination. U.N. Publ. , N.Y. United Nations.1970. Solar Distillation as a means of meeting small-scale water demands. U.N. Publ., N.Y. II-203
(6) CALCULATICN OF ENERGY QUALITY OF LARGE SCALE WATER MOVEMENT. This calculation is based on the increased gross primary productivity measured in aquatic microcosas as the water current stirring the system is increased. The ratio of increased water kinetic energy to increased , primary production gives the EQR for kinetic energy compared to primary production. Water Movement I K.E. Condition 1: K.E. = .038 real hr
- K Condition 2: K.E. = .038 X 10 Plant Biomass 3
D i Light Input
] \ \ \ 1
) Cond tion 1:
P'= .00675
~
Condition 2: P = .00065 f y 3 r EQR (water movement - sugar) = "( ) Ke 0 . 0
= 0.16 II-204
. y - g
Graph of productivi't'y ' versus linetic' energy has str aight line '..- 1 Portion initially (not limited by other factors). AUG. 24,1956 SEPT. 8,195G 2- 2< OXYGEN P
"%n i _ i.
P R R O.1 O'2
. d.1 0'.2 CURRENT VELOCITY M/SEC Approximate x-section Area, A = 78.5 cm Energy of Water Movement:
V = 0.2 m/sec = 20 cm/sec 3 Pke = 1/2 P A V3 = 1/2 (1.02 g/cm )(78.5 cm )(8x10 3 s ) 5 3s -11
= 3.20 x 10 ergs /sec (3.6 x 10 )( 2.38 x 10 )
= 0.38 Kcal/hr Energy of Metabolism Increase Pm = (1.5 mg/hr) x 10 -3 g/mg x 4.5 mg
= 6.75 x 10-3Kcal/hr = .00675 Kcal/hr EQR (sugar - Water movement) = 0.2 References Odum, H.T. ; C.M. Hoskin. 1957. Metabolism of a laboratory stream microcosm. Publ. Inst. Mar. Sci. 4:2 (115-133).
t II-205
l l I 1
+
I (7) CALCULATION OF ENERGY QUALITY RATIOS MR WOOD, COAL AND FUEL OIL This calculation is based on the conversion of the three fuels into mechanical energy using a steam engine. Conversion of, Wood M Gross Primary Production Sugar Labile Wood sugar Biomass Insol-J1 y l ation X y P i f 7 L Net Tree Production EQR (wood-sugar) . Gross Tree Production 1 Net Tree Production = 1262 g/m /yr Cross Tree Production = 2662 g/m /yr EQR (wood-sugar) = 2662 , 1262 Transportation and Storage Costs Wood (Boiler Efficiency) O & M Cost Coal m , Fuel \ Steam \ e ngine[ i O Fuel I L~ T i II-206
at, ,. . -.. . .. .....- . q ., . , ., . . :. :, . . ., .. . .. ,. .
-Numbers for transportation costs and boiler efficiencies are.given only relative to one another and not absolute. values.
Ratio cd[ Storage and Transportation Costs for Wood, Coal and Fuel Oil (Based cgt Bulk Densities) Wood Coal Fuel Oil 15 11.5 10 Johnson and Huntley, 1916) Boiler Furnace Efficiencies Including Effects cd[ Ash Production, Air Requirements, Water Vapo; Production and Combustion Temperatures (Perry, 1 1934) Wood
- Coal Fuel Oil 55% 62.5% 75%
- Estimated from available data for above factors.
Calorific ~ Values for Fuels b Wood" Coal Fuel Oil" (Pine) (Steaming Coal) (Pennsylvanian) 20,000 Beu tu B 4000 13500
- 4. Perry, J.H.1934 b.JohnsonangHuntley,1916 Other Operations 1 Costs for Steam Engine "
Wood Coal Fuel Oil high moderate low-
- c. .Tohnson and Huntley, 1916 11-207
^' *^ - - ~ -
Energy Quality Ratios Calculated for Three Fuels
- a. EQR wood-sugar = 2.1
*I ' **I atio of b.EQR Coal-sugar = 2.1 (transp. costs)(furnace effic.)(calorific values)
=(2.1(iff5)(Sh)(13.5)=10.25 1.3 1.13 3.375 c.EQR fuel oil-sugar = 2.1 ( )( )( ) = 21.5
References:
Johnson, R.W. and_L.G. Huntley. 1916, Principles of 011 and Gas Production Perry, J.H. 1934. Chemical Engineers Handbook. McGraw= Hill, New York Woodwell, G.M. and R.H. Whittaker. 1967. Primary production and the cation budget of the Brookhaven Forest in H.E. Young (ed). Symposium on Primary Productivity and Mineral Cycling in Natural Ecosystems. Univ. Maine Press, Orono.
)
l I l l 1 1 0 k ( II-208
[.N .r APPENDIX D MODEIS OF THE INTERACTION OF THE CRYSTAL RIVER POWER PLANT AND THE ADJACENT OUTER BAY ECOSYSTEM: RELATION TO COASTAL FISHERIES For an Environmental Conservation Fellowship Awatded in September, 1973 Henry N. McKellar, Jr. Systems Ecology Department of Environmental Engineering Sciences University of Florida s Progress Report to the National Wildlife Federation January 1974 II-209
- '. ?,*: . . . .. I i i ABSTRACT l
\
\
This is a progress report to the National Wildlife Federation for an ; Environmental Conservation Fellowship awarded this fall *o evaluate the inter-action of the Crystal River power plant with the adjacent outer bay ecosystems and marine fisheries on the west Florida coast. Using conceptual energy flow models to examine data and concepts the following results have been thus far obtained: Total community metabolism of the thermally affected (discharge) bay during the summer (7.0 grams organic matter /m / day) was not significantly different from that in a control bay (7.4 g/m / day). However, the discharge bay was more plankton dominated and had lower biomass in the major trophic levels and corresponding faster turnover rates. The summer turnover times for the discharge bay and control bay ecosystems were about 5 days and 7 days, respectively. Commercial fishery trends since 1959 indicated several possible inter-actions with the operation of the power plant although no definite relationships have been demonstrated. On an energy quantity basis, commercial fisheries of the area represented 7 x 10" % of the total community gross primary production. On an energy quality basis, the same yield represented about 1% of the area's total gross
-primary production. The concept of energy quality was developed as a method of gaining greater perspective of the energetics of fisheries and its role in the overall ecosystem.
This work was partially supported by a Florida Power Corporation contract to Dr. H. T. Odum and wi . be used in the development of my dissertation. b II-210 t .a .y
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INTRODUCTION As the number of electrical power generating stations along the United States coastline increases, many questions concerning the coupling of coastal power plants with the adjacent marine environment remain unanswered. The discharge of large volumes of heated water represents additional energy sources as thermal gradiente and stirring actions. Entrainment of planktonic organistas in the cooling water and the addition of. intake and discharge canals and spoil banks to the coastal morphology are yet other factors to be accounted for. With time, the ecosystems exposed ts tiase new influences will re-adjust and re-design in order to maximize the use of c heir total energies. However, the total impact and the overall result of the power plant-marine ecosystem inter-action is yet to be full understood and evaluated. Ecosystem modeling has evolved as a valuable tool in gaining perspective on such complex interactions. Using energy circuit symbols formalized by Odum (1971) a conceptual model was formulated to represent the energy flow through a coastal ecosystem (Fig. 1). This model shows external sources of heat, plankton, phosphorus, and organic detritus being pumped through the system by the stirring energies of tides and currents. Sunlight entering the system contributes to the ambient water temperature and to gross primary , 1 production of organic matter (Jy and J2 ) by planktonic and benthic flora. This production occurs at rates proportional to functions of temperature,
-limiting nutrient concentration (phosphorus), and self-maintaining feedback energies. High plankton biomass is shown to inhibit light penetration to benthic plants through shading.
Following primary production, energy is transferred through a branching and converging web of interactions among zooplankton, higher consumers (benthic invertebrates and nekton), and detrital storage with its rich association of microbes.- Respiratory losses (J through 3 J ) 7from each compartment occur at rates proportional to a function of temperature and the organic storage of each compartment. . Zooplankton and higher consumers are shown to increase self-maintaining feedback energies in proportion to their own respiratory losses,- thereby providing some adaptive responses to the effects of higher temperature. Accompanying respiration is the regeneration of phosphorus back to forms available for photosynthetic reactions. l l II-211 l l y yvq'9 + Iwa p.
a Figure 1. (Next page) A Conceptual Model of Energy Flow Through a General Coastal Ecosystem With Flushing Energies of Tides and Currents, Fishing Pressure From the Human Sector, and Migrating Stocks of Nekton. Symbol Key (Odum, 1971)
........... External Driving Force
; Passive Energy Storage
........... Heat Sink, Respiration V
_ap '\ : ........... Green Plant, Primary Producer J JL = A -
% _ ........... Consumer, Animal
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o An additional influence of temperature, as indicated in the model, is the logic control of fish and macro-invertebrate migration to and from the system according to programed temperature preferences. Corresponding effects on local concentrations of commercial and sport fish and invertebrates affect fishery yields from the system. The overall effect of temperature in this model is to increase biological exchanges involved with production and consumption. Up to a certain limit, heat is known to stimulate primary production through the enzymatic processes of photosynthesis (Jorgensen and Nielson, 1969). Heat also stimulates respira-tory losses from producers and consumers. Nicol (1967) summarizes temperature responses of a wioe range of marine organisms documenting a general two to three-fold increase in respiration with each 10 C rise in temperature. Copeland and Davis (1972) found that total community metabolism in heated artificial pools containing estuarine water and biota was higher than in similar unheated pools. The heated systems were more autotrophic during the summer and more heterotrophic during the winter. Additional studies have documented many effects of temperature on specific components of the marine ecosystem (Anderson,1969; Hargrave,1969; Vernberg and Vernberg, 1969; Heinle, 1969; and Ankar and Jansson, 1973) which could be included in a more detailed modeling effort. The model in Figure 1 represents a more general framework with which to conceptualize a total marine ecosystem and its response to temperature. When fully quantified, such models have been shown to be very useful as tools in ev'aluating overall impact of man-nature interactions (Odum, 1962; odum, Littlejohn, and Huber; 1972). Since September,1973, I have been involved with an overall project to evaluate the environmental impact on the adjacent Gulf coast ecosystem of the fossil fuel power plants at Crystal River, Florida. As part of this effort I have made quarterly measurements of total community metabolism in the outer bays near the power plant with supplementary measurements of plankton metab-olism, standing stocks of phosphorus fractions, planktonic chlorophyll-a and pheopigments. Data have been gathered from both the outer bay system receiving the thermal plume and from a similar system not affected by the plant's therral discharge. Data for spring and summer,1973, have been drawn together with additional data on macrophytes, vertebrates, and macro-invertebrates from other phases of the project published in the quarterly Environmental Progress Reports to the Florida Power Corporation. Models such as in Fig. 1 11-214 asu =
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were designed to present this data in a common framework to point out the
' ~ ~
major s'tr$icSural' 'and 'fInbtional dif fere'nces 'bletween"t'hIou'ce'r' dis' charge bVy' ' ' and the outer control bay. Additional models have been composed showing in more detail the energy flow through the higher consumers in the system thus emphasizing relationships involving fishery production and yield from the region. In additon to using energy quantities in viewing these relationships, a method has been developed to account for energy quality in the evaluations. The use of similar energy quality relationships to power plant activities was also presented by Odum, et. al. (1973) . The plant site in Citrus County is 12 km (7.5 miles) north of Crystal River on the low wave energy portion of the west coast of Florida (Fig. 2). The shallow sloping bottom is generally characteristic of the drowned limestone plateau of this portion of west central Florida. Fresh water sources in the general area' include the Crystal River 4.8 km to the south, and the Withla-coochee River and Cross Florida Barge Canal 6.4 and 5.8 km to the north, respectively. Salinities occur within a range from 18 ppt to 27 ppt. and the normal temperature range is from 14 to 30 C (Grimes, 1971). The mean tidal range for this part of the coast is about 1 meter (McNulty, Linda 11, and Sykes; 1972). The plant is on the landward edge of a cidal saltmarsh dominated by Juncus sp. The two units currently in operation (Unit I since July, 1966 and Unit II'since November,1969) give a combined total output of 897 megawatts.
~
The two units cycle water for once-through cooling at a combined flow of 640,000 gpm. Maximum condenser temperature rise is 6.1 C. The two amin types of coastal systems characteristic of this part of the Gulf coast (Reid,1954) are distinguished as the inner and outer bays (Fig. 3). The inner bay, characterized by shallow flats often exposed at low tide, tends to be's bottom domincted system with dense summer growths of marine grasses dominated by Haladule.wrighti. At many locations along the coast these shallow flats become bare during the winter. Seaward of the shallow inner bay the mean depth drops to approximately 2 meters. These outer bays are characterized by
- deeper flats .where species of shade adapted red and green algae (Gracilaria, Spyridia, Caulerpa) dominate the benthic flora and phytoplankton gain an important.. role in the daily production of organic matter. Patches of Sargassum are also common.
Data presented here have been generated from the outer bay stations indicated in Fig. 2 and compared with data from an area of similar depth south of the power. plant -(See Fig.1) presumably unaf fected by the thermal plume. II-215
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METHODS
-The metabolic activity of the total marine comunity can be calculated from the diurnal rise and fall of dissolved oxygen in the water (Odum and Hoskin, 1958). The original method has been slightly modified for use at Crystal River to account for tidal fluctuation (Smith,. McKellar, Young, and I.ehman; 1973). Fig. 4 shows the average diurnal curves of oxygen, depth, temperature, salinity, and rate of oxygen change for four stations in the outer discharge bay in October, 1973. When corrected for oxygen exchange with the atmosphere (not shown here) the integrated area above zero rate of oxygen change yields net daytime comunity production (P Net Day) and the area below zero rate of change is nighttime community respiration (RNight}*
rates of daytime respiration are assumed to be similar to R ** Night estimate of total comunity respiration over 24 hours is 2 x R A ' "8 I Night
- the best estimate of gross primary production is PNet Day + Night
- During the spring and sumer an abbreviated method for determining total metabolism was employed. By determining the oxygen minimum and maximum near dawn and dusk, respectively, the diurnal oxygen curve us estimated and metabolism was calculated as described above. The use of dawn-dusk method enabled total metabolism to be estimated for both the discharge bay and the control bay on the same days, thereby accounting for day-to-day variations due to differences in insolation.
Total comunity metabolism represents an overall indicator of the rate of energy flow through the ecosystem. The magnitude of total community meta-bolism with corresponding P/R ratios yield much information concerning the general functioning of the system under study as shown by Copeland and Dorris, (1964),He111er (1962), Odum and Hoskin (1958), and Odtsn and Wilson (1962). Plankton metabolism was measured by oxygen changes in standard light and dark bottle experiments incubated g situ at a 50 cm depth for 24 hours. Plankton respiration was caletilated as the mean oxygen change in triplicate dark bottles, net plankton production was the mean oxygen change in triplicate light bottles, and gross plankton production was the sum of respiration and net production. Phosphorus fractions were determined by the methods of Murphy ' and Riley (1962) and Menzel and Corwin (1965). Chlorophyll-a and pheo-pigments were determined by the method of Iorenzen (1967). I II-218 -
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RESULTS AND DISCUSSION Total Community Metabolism Spring values of total metabolism (Table 1) were similar to winter values ver ays (Smith, et.al. ,'1973) with an average sum of (PNet Day +2 Night) in May of -4.7 g/m / day in the discharge bay and 2.7 g/m / day in the control bay. Although discharge bay metabolism appeared to be higher it was not statisti ally different from the control bay average. Summer values of total metabolism were approximately twice the observed spring values with an average. P + R of about 7.0 g/m / day in the discharge bay and about 7.4 g/m / day in the control area. Again, these values showed no statistical difference between the ecntrol and discharge bays. The indication is, therefore, presented that if the outer discharge bay has been changed by the power plant influence, adaptive mechanisms have maintained the metabolic work functions at levels similar to the unaffected bay. Of particular interest in determining the main driving forces for the bays is the fact that the variance of values for net daytime production was two to four times' higher than for nighttime respiration. This difference indicates a significant external source of organic matter providing a constant fuel for respiration in addition to that provided within the system by photosynthesis. While day-to-day fluctuations in insolation may cause a high variability in net daytime production, community respiration may be significantly supplemented by organic imports from the inner baps and marshes. 5 51ankton Metabolism Phosphorus, and Chlorophyll
-Quarterly ch'ecks of planktonic metabolism, phosphorus fractions, chlorophyll-a and pheo-pigments add additional information toward interpreting data for total metabolism (See Table 2). While statistical treatment of these parameters is limited, the data may indicate certain trends to be later verified.
During the winter both planktonic production and respiration in the ~ discharge bay appeared to be slightly higher than in the control bay. Winter P/R ratios in the control bay were close to 1 but were less than 1 in the discharge bay. During the sunumer planktonic production in the discharge bay appeared to be much higher than in the control area. While P/R ratios were still close to 1 in the control area they indicated significant net production in the discharge area. I A II-220
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Table 1. Total Community Metabolism in outer Bay . Spring and Summer, 1973 (g 02/m / day) Outer Dischary,e Bay Control Bay f, P(Net Day) R(Night) P(Net Day) . R(Night) , . Spring: 2.19 1.73 1.70 1.09 - ; 9 _10 May 10 - 11 May 2.9 2.62 1.46 1.29 -i X- 2.55 2.18 1.58 1.19 [ S .25 .40 .03 .02 U N Summer: , 2 - 3 July 4.77 3.16 4.50 3.71 ., 9 - 10 July * (1430-1430 hrs.) 4.76 3.30 , 9 - 10 July 3.90 1.99 3.75 3.31 ', 10 - 11 July 3.97 4.59 6.36 3.90 11 - 12 July * (1255-1255 hrs.) 3.18 4.38 11 - 12 July 0.95 3.52 0.40 3.89 9 - 10 August 3.27 3.76 3.72 3.62
- 10 - 11 August 3.30 3.49 3.,3 3.45 ..
X 3.56 3.40 3.66 3.75 2 3.14 0.12 , S 1.69 0.60
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- Starred dates indicate results obtained from full diurnal oxygen curves. All other values ;r were obtained from the dawn-dusk procedure. .
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Table 2. Plankton Metabelism, Phosphorus, Chlorophyll-a, and Pheo-pigments Means of Samples Taken on (n) Number of Days
- Phosphorus Chlorophyll-a Ph'eopigment
' Plankton Metabolism (g02/m / Day) (44;- at/ 1) ~ 349/1)
(/g/1)
~
Gross Production Respiration Total Particulate Ortho Dfssolved Winter: 1.17(1) 1.03(1) f Discharge Bay 0.50(2) .97(2) .98(1) .49 (1) .2(1) .37(1) Control Bay 0.31(3) .31(3) .78(1) .42(1) .09(1) .31(1) 1.10(1) . 70(1) O. Spring: Discharge Bay 1.43(1) .73(1) .07(1) .63(1) 2.57(2) .37(2) Control Bay 2.0 (1) 1.43(1) .03(1) .54(1) 3.21(2) .82(2) Summer: Discharge Bay 4.61(2) 1.03(2) 1.40(3) .76(3) .24(3) .40(3) 4.11(J) .66(3) 1.2.(2) 1.17(2) 1.38(1) .66(1) .19(1) .53(1) 2.67(1) 1.04(1) Control Bay
- Plankton metabolism values for each day represent the averages of triplicate light-dark bottle Oy changes where respiration = mean of dark bottle oxygen changes; net production = mean of light bottle changes; and gross
,! production = respiration + net production.
Values- for phosphorus fractions, chlorophyll, and pheo-pigments for each day represent averages of 2 stations in each' area with duplicate analyses for each station. 4 4 n 4 1
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Total phosphorus in the water column showed a general increase ~ from winter to summer conditions. The higher total phosphorus in the control area in the spring possibly reflects a higher plankton concentration as indicated by greater concentrations of particulate phosphorus and chlorophyll-a. Ortho-phosphate (dissolved inorganic phosphorus) was consistently higher in the discharge area possibly indicating the effect of elevated temperature on t'te regeneration of inorganic nutrients. Models Discharge Bay vs Control Bay. Figures 5 and 6 represent models of the outer control bay and the outer discharge bay, respectively, in which the major standing stocks and ficws have been evaluated for the sanner,1973. Included in the models are the best current estimates of (a) summer stocks of organic storage in each of the model compartments, (b) gross productivity (Jgplus J )2 as contributed by phytoplankton and benthic plants, and (c) respiratory losses (J 3thru J ) 7from each compartment. Biomass figures were derived mainly from studies on benthic macrophytes, vertebrates, and macro-invertebrates by Snedaker et.al. presented in the Florida Power Corporations Quarterly Environmental Progress Reports (Fall, 1973). Productivity and respiration values were estimated directly from the metabolism data in Tables 1 and 2 (this report). Table 3 lists all the values used in these models along with the necessary calculations and assumptions. Synoptic studies during the summer indicated that in the outer discharge bay, phytoplankton production was approximately 60% of the total community gross production while total planktonic respiration was about 16% of the total community respiration (Fig. 6). In the control area similar data indicated that phytoplankton metabolism was about 15% of total community metabolism with respect to both production and respiration. The two system's total metabolic functions were apparently similar. If changes in the total system have occurred due to influences from the power plant, they have not apparently_affected total community metabolism and the
, discharge system is las capable of processing energy as the unaffected outer bay.
Comparing producer standing stocks, gross production, and respiretion of the two systems, a difference is shown in the nature of producer contribu-tion to the organic budget of the system. The net yield of organic matter from the producers to the system (gross production minus plant respiration) II-223
k Tidea and Currente .
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. \,,' E****"*1 Fish Stock m 4 g N
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- f , 11 N ,
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/ '
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)L 2*O 3p J7 y
3 e /.2 v i/ w y v T l 12Y . 2 Stocks grams /m 2 Flows a grams /m jg,y, l Total Respiration s 7,g l l Fig. 5. Conceptual Model of the Outer Control Bay with Estimates of Summer Stocks and Flows of Organic Matter and Phosphorous, i oc o g" - t co w< . . :2
n 8 Tides ed - wer J#f ' OCurrente ' F1 as toop! g i thes,-horus , D N!!u
- Phytoplankt tusphoru , 'F ,
~
7 -
-c ,, .7 . p, . . .. ,
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Temperature . . I ,
~
g g,g,,,,g s 32 5'C7 ' * " s Fish Stock H - f' h w
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~
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' L 35
*0S 07
~2.0 ,g J7 27 ,
q v Stocks grams /n 2 Flows a gre'es/m / day TotalRespitSions'(s.f Fig. 6. Conceptual Mbdel of Outer Discharge Bay with Estimates of Sununer Stocks and Flows of Organic Matter and Phosphorous. ma .
.m .g. .
i .wo o b LNifG
- . . . . . _e . _ . _ _ . N . Table 3 . Estimates ' lor Storages and Exchange Rates of Organic Matter in the Control Bay (C) and outer Discharge Bay (D). I i, Value Explanation Forcing Functions Sunlight 5500 kcal/m2/ day (C) Average summer insolation for the southeast (Odum, 1971) * .; 5500 kcal/m / day (D) l Temperature 29.5'C (C) ' Average during 8 summer d',arnals f 32.5*C (D) . Standing Stocks i 2
- t -Phytoplankton 1.0 g/m2 (C) Using the summer average chlorophyll-a concentration (Table ) and 'l 1.5 g/m (D) assuming 100 g carbon /g chi-a (Steele and Baied,1965), 2 g organic matter /g carbon, and an average depth of 1.8.m in the outer bay.
y Benthic Plants 45.2 g/m2 (C) Using Van Tyne's benthic sea grass and algae dry weights (FPC Environmental da 34.3 g/m2 (D) Progress Rept. 1973. Fall). Assuming dry weight of plants to be all Sl organic matter. l Organic Detritus 50 g/m2 (C) Estimate assuming detritus pool to be 1 - 1.5 times the standing stock and Microbes 50 g/m (D) of producers. Zooplankton .16 g/m2 (C) Prom several spot-check tous made with 202 mesh net. Assuming dry
.25 g/m (D) weight = organic matter (Be et al., 1971)
Benthic Inverte- 25.0 g/m2 (C) Snedaker's (FPC Env. Prog. Rept. Fa11. 1973) venturi and drop net data brates and Nekton. 20.0 g/m (D) for organisms occurring in areas covered by mud or algae; plus M. Lehman's estimate of oyster reef crganism biomass (pers comm.) Phosphorus .07 g P/m2 (C) Summer data; McKellar,1973, this report
.07 g P/m (D)
Flows J g , Phytoplankton 1.1 g/m / day (C) Summer data; McKellar,1973, this report (See text) Production 4.2 g/m / day (D) . 3 J y , Benthic Plant 6.3 g/m / day (C) Summer data; McKellar,1973, this report (See text) 2.8 g/m / day (D) Production . t___ _
' .t Table 3 . (Continued)
Value , Explanation J Zooplankton .03 g/m / day (C) Zooplankton turnover assumed to be 5 days which is consistent with some ' I Respiration .05 g/m / day (D) values given in Raymont (1963) 4 Total plankton respiration (see text) - Zooplankton respiration R a D 2 J5, organic Detritus 2.0 g/m / day (C) , Assuming detrital respiration of 1.C eg organics respired /g organic
& Microbe Resp. 2.0 g/m / day (D) matter /hr (hargrave, 1972) (Value for detrital respiration)- .
- 2 .
2 Assuming a 20-day turnover time for higher concentrations He R . m/ D 2 J 3. Benthic Plant 3.2 g/m / Jay C) Taken as the difference between total community respiration and estimates Respiration 2.7 g/m suay (D) listed above g J 8, Phosphorus .07gP/ a / day (C) Assuming gross productioni of organic matter is ~1.0% phosphorus y Uptake .07g P/u / day (D)
- U J 9. Total Phosphorus .07g P/6. /2day (C) Assuming total loss of organic matter die to component respiration was N Release 1.0% phosphorus
.0,7g P/m / day (D)
+
e
=
4 appeared to be about 3 g/m / day in both the control and discharge bays. However, that net yield in the control bay is from benthic plants with a large biohass and slow turnover rate (ptg, 5) , whereas in the discharge bay, the net yield is from phytoplankton with a small biomass and rapid turnover (Fig. 6). In the control bay the phytoplankton appeared to have an overall turnover time of about 1 day. Their net daytime production was about balanced by nighttime respiration and they contributed only small amounts of net organic matter to tha' system. The benthic plants, with a turnover time from 7 to 11 days, had a P/R ratio of about 1.5 thereby providing a net organic yield to the system. In the discharge bay phytoplankton appeared to have a turnover tome of less than a day with a P/R ratio of about 4. The benthic plants turned over about every 10 days with a P/R ratio of about 1. In general, mature diverse ecosystema have a lower ratio of total production to total biomass than in successional systems with lower diversity (Margalef, 1968). Using production and biomass values shown in these models the production / biomass ratio indicates a system turnover time of about 7 days in the control bay and about 5 days in the discharge bay. This relationship possibly indicates that the power plant influence may tend to keep the discharge areas in a succes-sional-like state with higher rates of energy transfer per unit biomass. While these structural and functional differences , indicated in these models, do not.apparently affect the total community's metabolic functions, they may have longer range consequences as the systems make the transition to conditions imposed when Unit III, a nuclear powered plant, begins operation in the winter,1 1975. Food preferences of higher consumers nay provide a mechanism for other differences between benthic plant vs phytoplaakton based systems. Future simulations of the two types of systems will address the consequences of these types of differences with respect to varying degrees of thermal loading. Citrus County Fisheries. Some insight to questions concerning the possible i . influence of the power plant on higher comsumers in the ecosystem, especially those of courarcial and sport fishery importance, may be gained from fishery statistics for Citrus County (Summary of Florida Commercial Landings, Fla. State Bd. - Conserv. , Salt Water Fishery Div. , Marine Fishery Research). In _1972 the total weight and dollar value of the county commercial landings were distributed as follows: L II-228 3a.,J W~ ,
- * = = - - s
#'t.
' * *
- J' a of f at; '% of Total .- # ~ ' ' " "
Dollar Value (3.93 x 100 lbs) ($620.057) Fin Fish 37 27
' Shellfish 59 40 Bait Shrimp ~4 33 Black Mullet (Mugil cephalus) and the Spotted Sea Trout (Cynoscion nebulosus) 3
. constituted 87% of the total finfish weight and 85% of the total finfish dollar value. Shellfish landings in Citrus County were 98% Blue Crabs (Calinectes sapidus). Bait shrimp data in the Summary of Florida Commercial Landings is listed in numbers of individuals rather than in weights so a
- ratio of 100 individuals / pound was assumed for these calculations (Cato, 1974, personnal communication). While bait shrimp landings constituted only 4% of
- the weight of total Citrus County landings they represented a third of the county's commercial fishery dollar value. Citrus county provides the state of Florida with 14% of its total Blue Crab catches and 20% of its bait shrimp landings. As yet, no data hase been gathered on the magnitude of sport fishing i
in the area, but the importance of bait shrimp as a commercial business 4 certainly indicates that sport fishing is a very important factor which must be accounted for. Trends in commercial fishery landings since 1959 may indicate certain effects of the power on the county fisheries (Fig. 7). Shellfish landings, which are approximately entirely Blue Crabs, showed a large increase in 1963 which was furthur increased in 1964 and again in 1965. Although the first power plant at Crystal River did not go on line until 1966, construction of the intake and discharge canals and spoil banks presumably was begun several years earlier. Recent investigations of Blue Crab migrations in the area (Snedaker and Oesterling,1974) have begun to indicate a general northward migration of Blue Crabs with a corresponding concentration on the south side fof the-intake canal spoil banks (see Fig. 2). Although this trend is yet to he proven, it may be a possible contributing factor to the stimulation of Blue Crab landings in the county. Local crab fishermen, however, complain "of recent decreases in Blue Crab landings which brings some doubt concerning the accuracy of published fishery statistics. I II-229 Ib -
~
5.0 Commercial Total Landings Landings, Citrus County ,_ Florida 4.0 -
~
Shell Fish e 3.0 * (Blue Crabs)
' ' ~ Ns s
W
$2.0-A
,,_ ~~_ --
1.0 - Food Fish Unit I Unit II on lir.: on line
. A A
'60 ' 61 ' 62 ' 63 ' 64 ' 65' 66 ' 67 '68 ' 69 70 ' 71'72 '
YEAR 120' Bait Shrimp Landings for Citrus County, Florida 100 eg 80-x 60, A E 40. e / 20-A A
' 60 ' 61'62 ' 63 ' 64 ' 65
- 66 ' 67 ' 68 ' 69 ' 70 ' 71 ' 72 '
YEAR Figure 7 Trends since 1959 of commercial fishery landings reported in Citrus County, Florida. Data from Summary of Florida Commercial Landings , Fla. State. Bd. Conserv. , Salt Water Fishery Div., Marine Fishery Research. II-230 u.em
i l 1
~
, s .
Bait shrimp landings showed a large increase in 1967 and indicated a general rising trend through 1972. In addition to a possible heat stimulation of shrimp production in the bay due to the power plant operation, a relation-ship to possible enhancements of sport fishing with a corresponding stimulation of the bait shrimp market is also plausible. While being far from conclusive, these data do indicate several interactions which should be included in models for the Crystal River area. In addition to heat effects on metabolism and migrations as shown in Figures 5 and 6, models could also include (1) effects of spoil banks in blocking natural migrations leading to local concentrations or depletions of migrating stocks and (2) the interplay among attraction or repulsion of sport fish by heat and the spoil banks, the corresponding effect on local sport fishing, and the resultant market for commercially harvested bait. Such features are included in Figure 8. which shows a simplified flow of energy from annual gross primary production (GPP) in the region to food web relation-ships of the region's most important commercial and sport fish. In the previous models (Figs. 5 and 6) component respiration was shown P.o regenerate nutrients as feedback to the system. Fig. 8 generalizes all feedback work services of component respiration as being necessary to the reinforcement of total energy flow through the ecosystem. More detailed structure of the f ood web could be deduced from information in Odum (1971), Reid (1954), Simmons and Breuer (1962), and Carr and Adams (1973). Figure 8 brings attention to the magnitudes of gross primary production 8 2 over the 3 x 10 m of Citrus County coastal ecosystems and the magnitudes of commercial landings of important species in kg-organic matter / year. The 6 x 10' Kg annual gross primary production was transferred through the eco-system and was realized in 1972 as a total commercial fishing harvest of 4.2 x 10' Kg. This harvest represents a .007% conversion. Hellier (1962) found that f n the Laguna Madre, Texas, the efficietcy of conversion of gross community primary production to. fish growth was about .07% (not including macro-invertebrates). Information concerning there types of relationships will become necessary in future attempts to scale and simulate these models of community production and fishery dynamics. II-231
1 l POWER po n. ,y p1oaearray *
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y M SYSTEM - '
- e. .. -
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, * '"ce m '#
Kg- odGnxic, narreg 1r y Ds L "/sn l RESP /RA7/oM , Figure. 8. Model emphasizing possible interactions of the Power plant's thermal discharge and canal spoil banks with the coastal marine fishery. Note the difference in magnitude of total gross primary production and the cosusercial fishery yelid for Citrus County
t ,. . ,,. .. ~ ,.w. , ,. . . ., Energy Quality. Classical physics defines energy as the ability to do work. Recent work involved with the present project has developed the proposition l that work capacity depends on both energy quality as well as energy quantity. l A kilocalorie of high grade energy has more capacity for doing work for the system than a kilocalorie of low grade energy. In the case of energy transfer through an ecosystem, energy quantities decrease rapidly up the food chain. However, this decrease must correspond to increases in energy quality of structure and function. Therefore, a unit of energy expended by a large top carnivore has higher quality and thus more value to the system than a unit of energy expended by aquatic plants in primary production. Lower quality structure and functions ir. an ecosystem provide energies to build units of higher structural and functional quality which feed back special work services for the good of tae overall system. In comparing energies of different components in the system they must be expressed in units of the same energy quality The quantification of this concept provides a means for evaluating and comparing aspects of the marine system such as the energies of gross primary production and those of fisheries, for example. In an effort to quantify energy quality, Fig. 9 was designed to show the relative flow of energy through a food chain situation. The flow begins with 100 units of gross primary production, 50 of which is respired by the plant community. A significant fraction of the net production branches through the detrital compartment where microbes provide additional processing o'f the energy. Herbivores and Omnivores derive energies equally from plant and detrital sources, passing a large fraction back to the detrical pool as pseudo-feces, and some on to carnivores. As energy is passed through the food chain to top-level carnivores, energy quantity is lost through respiratory work of each compartment. Corresponding to each respiratory drain, some service is fed back for the overall maintenance of the system. What is the quality of these work services and the energy involvement of each trophic level? If it is assumed that this system is adapted and is functioning with an optimum involvement from each trophic level then the work services of each level (as indicated by its respiration) is necessary for the overall functioning of the system. Therefore, the quality of the work service of each trophic level could be calculated as the ratio of the system's total energy budget to the respiration of each compartment. For example, the 1 unit of top carnivore II-233 h
o x N
'l I Blue \
Shrimp lMullet Crabs \ Small fish *
\
\
; ,- l Mollusks . Black Drum Trout
.' Polychaetes 'Sheepshead ; Red Drum getc. Perch Jack i I etc. I
; etc.
I
. HERBIVORES and M
i "IOP
" OMNIVORES CARNIVORES SUN , l CARNIVORES
.h* WIND l
20 5 O 1 A l WAVES l \\\\ jj7777 100 g,p,p, ETC. \! { g gj;yri y i . 30 DETRITUS .0 \ !
. :=-: :- 15 O; A 50 25 20 4 , 1 i
; $/ y l 1/ v V
~ - ~
l s Energy Quality = GPP = 2 4 4 5 25 , 100
*:rog}ic ,
- I lletabolism Figure 9. Idealized food chain showing the relationship b'etween decreases in energy quantity and concentration of energy quality.
' ~
respiration wou$d have' an energy quality equal
- to 105 Snits of gr$ss'primhy * '
production since it is necessa y for the delivery of that production through the system. If the levels of energy quality shown in Fig. 9 are representative for a coastal marine ecosystem then the energy involvement of commercial fisheries in the coastal ecosystem can be calculated as in Table 4 According to these calculations the total energies removed from the coastal ecosystem is worth about 3 x 10 kilocalories/ year in the same quality of gross primary production. This.cotal gross primary production was calculated earlier (see 1# . 8) to
- be 6 x 10' Kg organic macter per year. Defining primary production as energy quality (1) and converting this tocal production to caloric values (5 kcal/ gram organic matter) yields a value of 3 x 10 13 Kcal. Therefore, the total energy involvement of commercial fisheries represents about 17. of the system's primary production when energy quality is accounted for. This fraction is about 140 times higher than the efficiency calculated on a simple weight (energy quantity) hasis.
In summary, the concept of energy quality offers a new method to gain greater perspective on the energetics of e'cosystems, fisheries, and their interaction. A better understanding of trophic structures and respiratory work functions of individual components is needed to sharpen the energy quality concept and to establish it as a major tool in ecosystem analysis. f-II-235
~
L_ ~ !
Table 4 Eaergies Removed From. Coastal Ecosystem. Ihrough Commercial Fishing- Citrus County-1972. 1,
//ARVESb y MfDf8ousm [#) y ENE4G Y y D4Ys y>(en/ Ats/lye44
(/cyonwienate 9 02 Quaity yese 9,q,
~
ORGANISM
)( jg 3 g agg, ggy, g4y X Mg Shrimp !
- O I I 8 82 Mullet '
20 I "
/h. b Blue Crabs 28/*I d' -
/8 se - se /fg.2 7
, Black Drum C.O3/ t/
25 ee
- g, o g Sheepshead 6.$00 4 "
25 " " o.ooo5 Sea Trout k+N h /C O 8e 'I g,g Red Drum *3 " /6 d " " 2g. f Jack " l0 0 ** " 3 fso. h i D T 4 /. 309./ (1) Harvest data from " Summary of Fla. Conun. Mar. Landings, Fla. State Bd. Conserv." Assuming 0.2 g dry we./ g wet wt. and 0.9 g organic matter /g dry wt. for fish, and 0.5 " " " "" " "
" 0.54 " " " crustaceans (2) Data from Nicol (1967) with assumptions for metabolic differences between large and small crustaceans and top and middle carnivorous fish.
(3) Blue Crabs were given an energy quality between omnivores and carnivors. 1 1 l l
. . ., , , , . ,. . . a.>.. .. .. REFERENCES Anderson, P. R. 1969. Temperature and rooted aquatic plants. Ches. Sci 10: 157-164. Ankar,S. and B. O. Jansson. 1973. Effects of an unusual natural temperature increase on a Baltic soft-bottom community. Mar. Biol. 18:9-18 Be, A. W. H. , J. M. Forns , and O. A. Roels . 1971. Plankton abundance in the North Atlantic Ocean. In: J. D. Costlow (ed.) Fertility of the Sea. Gordon and Breach. p.17-50. Carr, W. E. S., and C. A. Adams. 1973. Food habits of juvenile marine fishes occupying seagrass beds in the estuarine zone near Crystal River, Flo rida. Trans. Jun. Fish. Soc. 102: 511-540. s Cato, J. 1974. Sea Grant Office, University of Florida. person. comm. Copeland, B. J. , and H. Lee Davis. 1972. Estuarine ecosystems and high t temperatures. Water Res. Res. Inst. Univ. No. Carolina. Report no. 68. Copeland, B. J., and T. Dorris. 1964. Community metabolism in esosystems receiving oil refinery ef fluents. Limnol. Oceanogr. 9: 431-447. Florida Power Corporation, 1973. Quarterly Environmental Progress Report. Hargrave , B. T. 1969. Aerobic decomposition of sediment and detritus as a function of particle surface area and organic content. Limnol. oceanogr. 17: 583-596. Heinle, D. R. 1969. Temperature and zooplankton. Ches. Sci. 10: 186-289. Hellier, T. R. 1962. Fish production and biomass studies in relation to photosynthesis in Laguna Madre of Texas. Publ. Inst. Mar. Sci. Univ. T' Tex. 8: 23-55. Jorgensen, E. G. , and E. Steemann Nielsen. 1965. Adaptation in plankton algae.
- p. 38-46 In: C. R. Goldman (ed) Primary Productivity in Aquatic Environments.
Mem. Ist. Ital. Idrobiol. ,18 suppl. University of California Press , Berkely. Lorenzen, C. J. 1967. Determination of chlorophyll and pheo-pigments; spectrophotometric equations. Limnol. Oceanogr.12: 342-436. Menzel,'D. W., and N. Corwin. 1965. The measurement of total phosphorus in sea water based on the liberation of organically bound fractions by persulfate oxidation. Limnol. Oceanogr.10: 280-282. Murphy, J. and J. P. Riley. 1962. A modified single-solution method for the determination of phosphate in natural waters. Anal. Chim. Acta. 27: 31-36. 11-237
-m
Nicol, J. A. Colin. 1967. The Biology of Marine Animals. 2nd ed. John Wiley and Sons, Inc. New York. 669p. Odum, E. P. 1971. Fondamentals of Ecology. 3rd ed. W. B. Saunders Co. Philadelphia, Penn. 573 p. Odum, H. T., and C. M. Hoskin. 1958. Comparative studies on the metabolism of marine waters. Publ. Inst. Mar . S ci . Univ. Texas. 5: 65-69. Odum, H. T., W. Smith, H. McKellar, D. Young, M. Lehman, and M. Kemp. 1973. Preliminary presentation of models to show interactions of power plants at Crystal River Florida and energy const and benefits 6or alternatives of management of cooling waters. Progress Report to Florida Power Corp. and Liscensing Agencies. 45 p. (Univ. Fla) Odum, H. T.1962. Use of energy diagrams for environmental impact statements. In; Tools for Coastal Management, Proceedings of the Conference. 14-19 Feb. 1972. Wash. D. C. Odum, H. T., and R. Wilson. 1962. Furthur studies on reaeration and metabolism of Texas Bays, 1958-1960 Publ. Inst. Mar. Sci. Univ. Texas 8: 23-55. Odum, H. T. 1971. Environment, Power, and Society. Wiley-Interscience. New York. 331 p. Odum, H. T. , C. Littlejohn, and W. C. Huber. 1972. An environmental evaluation of the Gordon River area of Naples, Florida, and the impact of develop-mental plans. Report to County Commissioners of Collier County Florida. 101 p. Odum, W. E. 1971. Pathways of energy flow in a south Florida estuary. Sea Grant Bulletin No. 7. Raymont, J. B. 1963. Plankton and Productivity in the Oceans. Pergammon Press. 660 p. Reid, G. K. Jr. _1954. An ecological study of the Gulf of Mexico fishes in the vicinity of Cedar Key, Florida. Bull. Mar. Sci . Gulf. Carib. 4:1-74. Simmons, E. B. and J. P. Breuer. 1962. A study of Redfish, Sciaenops ocellata (L.) and Black Drum, Pogonias cromis (L.) Publ. Inst. Mar. Sci. Univ. Texas 8: 184-211. Snedaker, S. C. ,- and M. Oesterling. 1974. Resource Management Systems Program. Univ. Fla. Pers comm. Steele, J. H. and I.E. B ird. 1965. The chlorophyll-a content of particulate organic matter in the Northern North Sea. Limnol. Oceanogr. 10: 261-267. i II-238 -
-. -, .~ - ~ ~ ~
;.w -.
- 7 ,
~
~ Smith, W. H. B., H. McKellar, D. Young, and M. Lehman. 1973. Total metabolism of thermally affected coastal systems on the west coast of Florida. In: J. W. Gibbons and R. R. Sharitz, (eds.) AEC l" ,
Symposium Series (Conf-730505). Vernberg, F. J., sud W. B. Vernberg. 1969. Thermal influence on Invertebrace respiration. _Ches. Sci. 10: 234-248. i + I e ( II-239 n w>- ._ ,~ ..
r ACKNOWLEDGEMENTS The author acknowledges with thanks the efforts of Jackie Murray, John Cox, and Mark Homer for their help in the collection and analysis of field data. Under the guidance of Dr. H. T. Odtan, most of the concepts presented here evolved from discussions among the entire Systems Ecology section in the Department of Environmental Engineering Sciences, University of Florida. Special acknowledgements go to those directly involved with this project, Mike Kemp, Mel Lehman, Wade Smith, and Don Young. I-t II-240
- . . . . - ~ _ . . . - . - . . , . - - ,. ,_
... , . , r. . ~. . .. ~ , . . , . , .. e. P APPENDIX E SALT MARSH MICR0 ARTHROPOD P&ULATICNS Elizabeth A. McMahan Department of Zoology University of North Carolina, Chapel Hill, N.C. and Don Young Department of Enviornmental Engineering Science University of Florida, Gainesville, Fla. INTRODUCIION The salt marsh investigations at Crystal River have focused on documenting thermal effects at the community level with emphasis on the primary producers that dominate energy flow of the biological processes. But animal populations number, species compositions, and diversity are important parameters of ecosystem structure. Examination of these parameters could yield information about adaptations of consumers to elevated temperature water and suggest possible consequences to_the behavior of the marsh system as a whole. Insects are conspicuous members of the marsh ecosystem and recent studies elsewhere have indicated they are present in great numbers and the diversity of the population is high. A study was initiated in August, 1973, at Crystal River to attempt to discern the possible effects on insects and other marsh microarthropods
. exposed to thermal additions.
~
II-241
1 l 1 1 METHCDS Microarthropod Populations Insect collections were made twice during the sunner of 1973 in Juncus and Soartina marshes in b'oth the thermally affected area and control area 3. Sampling was undertaken to characterize the microarthropod populations inhabiting the various marsh types, show if thermal additions had altered the types and numbers of insects present, allow estimates of species diversity to be calcu-lated, and possibly provide data for estimating biomass and energy flow of the microarthropod populations. On August 13, under the direction of Dr. Elizabeth McMahan, ten samples of microarthropods were obtained from Juncus and Spartina marshes at Crystal River. In the thermally impacted marsh four samples from the Juncus community and two samples from the Soartina community were collected. Also two samples each of ,Tuncus and Spartina were collected from control area 3. Collections were taken with a vacuun apparatus which had been used with success previously OHcMahan, 1972, 1973). The vacuum is selective for small, slow-moving insects but may be
- better suited for quantitative sampling than sweep nets in the dense marsh vegetation.~ The vacuum was powered by a 1 HP motor and electric power was supplied by a portable generator. Attached to the l
l vacuum was a 6 foot flexible hose coupled to a 4 foot extension tube L with an expanded triangular opening. The foot portion of a woman's i nylon stocking was placed inside the vacuum and capturedthe insects II-242
w.. - w as they were-drawn inside..- Each sample of the August collections was the result of 10 minutes of continuous operation of the vacuum at low tide. Each sample was obtained from a strip through the marsh 1 meter wide and 5 meters long (5m ) . For seven minutes, the operator would go from one end of the strip to the other thrusting the tube down into the vege n. ion, sampling the bare mud and slowly drawing the tube upward through the leaves and stems of the vegetation. During the last 3 minutes, the operator would return through the strip sampling as before. After 10 minutes, the nylon stocking was removed from the vacuum and placed j l in a killing jar containing ethyl acetate. Grasshoppers avoided J the vacuun so supplemental estimates of grasshopper density were obtained simultaneously with sweep nets and by counting the I l grasshoppers which flew when the grass in a 1.0 m area was shaken vigorously. Separation of the specimens from the vegetation and debris ingested was performed with a dissecting microscope upon return to the laboratory. Most of the samples were separated at Florida, preserved in a 707 alcohol solution, and later sent to Dr. McMahan for final separation and identification to " species". Each sample was considered a unit in terms of " species" identified. Specimens were not keyed to species by comparison to a standard reference collec ti on. Because of the large numbers of insects encountered in each sample, insects were grouped into different types; each l type within a. sample was considered a species. Results of the 1 final sorting of each sample included number of orders found,
-II-243 I1 m
number of " species" per order, and the number of specimens per order and " species." Species diversity of each sample was ex-pressed several ways: number of species found per 1,000 in-dividuals, number of species divided by the square root of the number of specimens, Shannon-Weaver Diversity Index, and an eveness index (Shannon-Weaver Diversity / Maximum Shannon-Weaver Diversity). Initial sorting of the August samples revealed that the average number of specimens collected in the Spartina to be approximately 200 individuals. To insure enough specimens per sample for diversity comparisons, a second set of collections in the Spartina marshes were made on September 3, 4. Two samples each were obtained from the thermally affected and control area 3 utilizing identical techniques and equipment as in August with one exception. The time period of sampling with the vacuum was extended to 40 and 50 minutes. Collect-ing was as thorough as in August so that the increased area of marsh surface sampled was approximately proportional to the increased times of vacuuming (ie, 40 minutes = 20m2 and 2 50 minutes = 25m ). Sample sorting and identification pro-cedures were as before.
.T-tests were performed to see if significant differences in insect numbers, trophic level distribution, and diversity existed.
Results of both Spartina and Juncus thermally impacted marshes were comp. cad to corresponding data from control marshes. II-244
-~- ,2
RESULTS -~ . . . ., a . , u . . , . ,,. . , . . ~ .c . .. . , . Three aspects of the microarthropod population structure were analyzed: (1) numbers, (2) species composition, and (3) species diversity. Each of the following paragraphs is devoted to a dis-cussion of comparisons between marshes for a single population charac-teristic. Results from thermally impacted and control areas of each marsh type (Juncus and Spartina) were compared to see if the micro-arthropod population characteristic was altered by the power plant effluent. Also Juncus and Spartina marsh types were compared to see if microarthropod populations indigenous to each marsh differed. The mean number of microarthropods collected per sample in heated and unheated Juncus marshes was not statistically significantly different (Table 1 ). The difference in mean numbers of microarthropods per sample obtained between thermally affected and control Spartina marshes (Table 2) suggested that more insects were present in the thermal marsh. But because of sample-to-sample variance, t-tests revealed no statistical difference in the mean number of individuals collect.ed per sample. This was true of both the August and September ; i sampling periods. Further t-tests revealed that on August 13 signi-ficantly greater (95% confidence level) numbers of microarthropods were collected per sample from the Juncus marshes as compared to those j 1 of the Spartina - marshes. j Tables 3, 4 , and 5 summarize the microarthropod collections within each marsh type differentiated by taxonomic grouping and trophic level. Results from collections within the Jr.n us marsh (Table 3) indicated that the majority of microarthropods present were herbivores, s II-245 l 1
Table 1 Comparison of microarthropods collected from thermally impacted 13,1973. (Sampling time = and control Juncus 10 minutes, area = marsheg)on 5.0 m . August Thermally Impacted Marsh Control Marsh Sample Specimens Species Specimens Species
- 1. 664. 49. 1781. 62.
- 2. 2695. 52. 1980. 60.
- 3. 2163. 43. - -
- 4. 2224 54. - -
Mean 1956.5 49.5* 1905.5 61.* S.E. 440.5 2.4 99.5 1.0
- Asterisks denote parameters for which t-tests revealed a s,tatistically significant difference (95 % confidence level).
II-246
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Table 2 Comparison of microarthropods collected from thennally impacted and control Spartina marshes on August 3,1973 and September 3,1973. Thermally Impacted Marsh Control Marsh S ample Specimens Species Specimens Species August 13* 129. 29,
- 1. 153, 27.
- 28. 113. 22.
- 2. 249, Mean 223. 27.5 140.5 25.5 S.E. 48. 0.5 7.5 3.5 September 3
- 1. 16442.a 68. 1210.a 60.
3824.b 50. 1756.b 56. 2. Mean 10223. 59. 1573. 58. S.E. 6299. 9. 283. 2. Sample collecting time of 10 minutes; area sampled = 5 m .
# 2 Sample collecting time of 40 minutes; area sampled =20 m ,
Sample collecting time of 50 minutes; area sampled ='.5 m . l l 1 i l 11-247
Table 3 Species composition comparison by taxonomic grouping and hypothesized trophic levels of averaged microarthropod collections from thermally impacted and control Juncus marshes. Trophie level Thermally Impacted Marsh, n = 4 Control Marsh, n = 2 and Specimans/ S.E. Percent Species Speciscas/ S.E. ' Percent Species Order or group Sample of Total S amp.'.2 of Total HIrbivores Orthoptera 35.5 3.9 1, 43 77.5 19.5 4. 3 Heteroptera 89.0 18.6 5. 43 43.5 30.5 2 >4 Homoptera 1266.8 378.2 65.. 3 1037.0 209.0 55 >4 Thysanoptera 1.5 1.2 441, 1 1.5 1.5 d4-1 . I 1.8 1.5 2.5 .5 44 1 .
? Coleoptera 1.1 <c1. 2 Subtotal 1394.5 387.7 71 11.5 1162 219.5 61. 14
{l
% Detritivores oc
; Crustacea 16.3 3.2 1 >2 13.5 4.5 1, 3 1
Mites 43.8 22.9 2 4 11.5 5.5 1. >3 Collembola 55.5 33.3 3.. 2 11.0 2.5 44 1 . >l
; Diptera 147.0 13.2 8.. 13 497.0 110.0 26 . 15
,f Tricoptera 0 O. d. O. 1.0 1.0 1. 1 Subtotal 262.5 66.5 14, 21 528. 107.0 28. 23 C rnivores Spiders 27. 3.0 1. 43 79. 5.6 4* 7 Pseudoscorpions 0.3 0.3 dWL 1 1 2. 1.0 441 Hymenoptera 272.3 52.7 14 , 13 129.5 6.5 7. 15 Subtotal 299.5 53.5 15, 17 210.5 12.5 11 . 23 Total / sample 1956.5 440.5 49.5 1905.5 99.5 61. 2 Total /m 391.3 88.1 380.1 19.9 f '.t
...-- >a ... . ,, . , , , . _ _ ,~, ,, , , , , ,,,,, ,,,
- The percentage of microarthropods in each of the three trophic levels was not found to be statistically different in thermally impacted or control marshes. Spiders (carnivores) was the only group or order -
found to be statistically different between the Juncus marshes; they were more numerous in the control area. Detritivores were the numeri-cally largest trophic level grouping found in the Spartina marshes during August and September. Like the Juncus marshes, no significant difference was detected in percent composition by trophic level be - tween heated and control marshes during either sampling period. Two statistical differences were detected among the groups and orders present in the Spartina samples; greater mean numbers of crustaceans (August) and diptera (September) were present in the thermally im-pacted marsh.
\
II-249 OM-
The- pronounced increase of microarthropod numbers collected per 2 m in the'Spartina marshes, noted between August and September (Tables 4 and 5 ).- was statistically significant. T-tests showed that 2 statistically greater mean numbers of detritivores per m were present in September and thus responsible for the population gain. Detriti-vores in the control marsh were also a statistically greater percen-tage of the trophic level structure in the September sample. During August, microarthropods in Juncus and Spartina were found to have distinctly different trophic level distributions. A camparison of control area Juncus and Spartina samples revealed that the percentage contribution made by herbivores to the population total was greater (95% confidence level) in the Juncus marsh; changes in the percentage contributions of detritivores could not be proven different. In samples from the ther-mally impacted Spartina marsh, a statistically greater percentage of the populations were detritivores. All Spartina and Juncus samples from August were pooled by marsh type and the nercentage composition of herbivores and detritivores compared. T-tests showed that both the herbivore and detritivore percentage' distributions were significantly different; herbivores made up a larger percentage of the Juncus popula-tions and detritivores constituted the largest portion of the Sparrina
- populations. In addition, several orders of microarthropods in pooled Juncus and Spartina samples were found to have mean numbers which yielded statistical differences. Homoptera and Heteroptera (herbivores) and Hymenoptera (carnivore) were more numerous in the Juncus marsh. ;
Five indices of marsh microarth'ropods species diversity are sum- l l marized in Table 6. Three of the indices were used as measures of i I 2 l I
* 'l II-250 l 1 - ._ _ _ _ . . . . . . . ,, _ l
i Table . 4 s Species compositicn comparison by taxonomic grouping and hypothesized trophic levels of averaged microarthropod collections from thermally impacted and control Spartina marshes; August 13, 1973 ,
}
Thermally Impacted Marsh, n = 2 Control Marsh, n = 2 Trophic level
"" Specimens / S.E. Percent Species Specimens / S.E. Percent Species Order or group Sample of Total Sample of Total
!!erbivores 20.0 0.0 9, 1 20.0 0,0 14. 1 Orthoptera Heteroptera 10.0 00 5. 2 4 s0 2.- 0 3. 42 Homoptera 6.5 1.5 3, 2 11.0 1.0 8. 1 Thysanoptera 0.5 0.5 de l. 1 0.0 0.0 0. O
~
1.5 0.5 44 1 1 0.0 0,0 0, O Coleoptera s Subtote 38.5 1.5 17. 7 35 1 25. 4 s hDetritivores
" 25 1.0 18. A6 Crustacea 67.0 10.0 30. 4 Mites 2.5 2.5 1 1 2.5 1.5 2, 42 Collembola 5.5 5.5 2 1 6.5 1.5 5. >2 Diptera 77.0 34.0 36 8 35.5 2.5 25 6 Subtotal 152.0 52.0 69, 14 69.5 3.5 49. 16 Carnivores Spiders 26.0 7,0 12, 4 26.0 3.0 19, 3 Pseudoscorpions 1.0 0.0 d4 1, 1 0.0 00 0. 0 Hymenoptera 3.5 1.5 2s 3 10,0 2.0 7 5 Subtotal 30.5 5.5 14. 8 36 5 26. 8 Total / Sample 221,0 48.,0 27.5 140.5 7.5 25.5[
Total /m 44.2 9.6 '28.1 1.5 y
I Table 5 Species composition comparison by taxonomic grouping and hypothesized trophic levels of averaged microarthropod collections from thermally impacted and control Spartina marshes; September 3, 1973. Trophic level Thermally Impacted Marsh, n = 2 Coatrol Marsh, n = 2 and Specimens / S.E. Percent Species Order or group Sample Specimens / S.E. Percent Species of Total 3,,pg, f ,y e Herbivores Orthoptera 90.5 10.5 44 1 . 90.0 10.0 1 Heteroptera 15.0 7.0 R1s 20.5 11.5 1 Homoptera 550.5 412.5 5, 172.0 97.0 11 Thysanoptera 4.0 4.0 441 e 0.0 0.0 0 Coleoptera 2.0 1.0 4A1. 2.5 0.5 441
; { Lepidoptera 0.5 0.5 44 1 . 0.5 0.5 M1 y Subtotal 662.5 414.5 6 285.5 118.5 14 Detritivores Crustacea 255.5 152.5 3, 120.5 18.5 8 Mites 5329.5 4026.5 52, 238.0 17 0 16
! collembola 1466.0 1256.0 14 . 16.0 5.0 1
- I
- i Diptera 2421.0 424.9 24 . 784.5 231.5 52 Tricoptera 0 0 0 0.5 0.5 ' #- 1.
Psocoptera 0.5 0.5 4 El. 0.0 0.0 0. ' j Subtotal 9472. 5859 93 1159 191 77 4 1 Carnivores 54.5
~
Spiders 13.5 44 1. 37.1) 2.0 3 Pseudoscorpions 1.5 1.5 44 1 - 0.5 0.5 44 1 Hymenoptera 32.0 11.0 #1. 90.5 27.5 6 .l Subtotal 88.0 26.0 1 128 26 9 Total / Sample 10223.0 6299.0 59. 283,0 58. 1573 0 2 Total /m 491.5 334.6 69.4 4.9
. . . . , - . . , , . .. . . . . < . . . . . m. . . . .
the variety or richness of the populations: S (total species per samp1.e), s/1000 (species observed per 1000 individuals present), and S/,di (total species per sample divided by the square root of the number of individuals). Values for S/1000 were obtained from semilog plots of logarithm of numbers of individuals versus numbers of species. These figures were plotted from the sample data of Tables 1 and 2. An evenness index, In S and the Shannon-Weaver index of diversity
- s. s.
H= - (qf.) In (qf-) where si equals the number of specimens of the i th species were included to indicate the evenness of the distribution of indivi-duals among the various species and to show the interaction of rich-ness and evenness, respectively. Although all three indices suggested that more species were present in the control Spartina marshes versus the thermally impacted areas, none of the differences were significant (95% confidence level). The mean number of species per sample, . S, indicated that a significantly greater (95% confidence level) number l of species were present in the control Juncus compared to the heated ) marsh. Both S and S/1000 revealed statistically more numbers of micro-arthropods in the Juncus than in Spartina. The. evenness index, e, showed a statistically more uniform distribution of species in the Spartina marsh than in the Juncus; all other tests of e and H were insignificant. l II-253
Table 6 Indices of microarthropos species diversity in thermally impacted and control areas of Juncus and Spartina marshes. Species /1000* b D ample Total Total S//N - Number Species Individuals M1oh Y=y g g N S Juncus; August 13 Thermally Impacted 1 664 49 1.902 2.63 0.676 2 2695 52 1.002 1.41 0.357 3 2163 43 0.925 1.96 0.5211 4 2224 54 1.145 2.46 0.617 Mean i 1 S.E. 1956.5+ 49.5+ 46.5 1.244+ 2.12+ 0.543+ 49.5 2.4 0.224 0.27 0.070 Control 1 1781 .62 1.469 2.44 0.591 2 1980 '60 1.348 2.17 0.530 Mean + 1 S.E. 1905.5+ 61.0 56.0 1.409& 2.31 0.561+ 99.5 1.0 0.060 0.14 0.031 Spartina ; August 13 Thermally Impacted 1 153 27 2.183 2.05 0.622 2 249 28 1.774 2.28 0.684
.Mean 221+ 27.5+ 36.0 1.979+ 2.17+ 0.653+
48 0.5 0.204 0.12 0.031 Control 1 128 29 2.563 2.56 0.760 2 113 22 2.07 2.33 0.754 Mean i 1 S.E. 140.51 25.5 37.5 2.317+ 2.45+ 0.757+ 7.5 3.5 0.247 0.12 0.004 Spartina; September 3
-Thermally Impacted 1 16442 68 0.530 1.66 0.3934
~2 3824 50 0.809 2.00 0.511 Mean i 1 S.E. 102231 591 46.0 0.671 1.831 0.4521 6299 9 .139 0.17 0.059 Control 1 1210 ,60 1.725 2.67 0.652
,2 1756 ,56 1.336 2.35 0.584 Mean i 1 S.E. 1573 + 58+ 55.0 1.531+ 2.51+ 0.618&
283 2 0 194 0.16 0.034 a Values obtained from Figures 1, 2, and 3. b Natural logarithms (base e) used in calculations. II-254
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-.. . . ~ , . . ~. . . . . . . , , ... .. . - , . , . . . , . . . . . .,..,,,,.;,,,,,_,
FINAL REPORT to the FLORIDA POWER CORPORATION submitted by Dr. -Samuel C. Snedaker, Principal Investigator 1 Resource. Management Systems Program Institute of Food and Agricultural Sciences ! ' University of Florida ; Gainesville, Florida October,1974 4 4 7 4 11-255 o - _ _. . _ . . - , -
, <..,- ,c.,. ~ , ,
FINAL REPORT to the FLORIDA POWER CORPORATION submitted by Dr. Samuel C. Snedaker, Principal Investigator Report A Evaluations of Interactions Between a Power Generation racility and a Contiguous Estuarine Ecosystem Samuel C. Snedaker NOT COMPLETED-IN TIME FOR INCLUSION IN THIS REPORT Resource Management Systems Program Institute of Food and Agricultural Sciences University of Florida Gainesville, Florida November,1974 l l 11-257
.Es , ,. -
l .. , . . -.a . .. . . . . _ , . .;_ . . .s., . . , . . , . , , ;, .. . . . .. , , , . - -. _ . FINAL REPORT l to the FLORIDA POWER CORPORATION submitted by Dr. Samuel C. Snedaker, Principal Investigator Report B IMPINGEMENT AT THE CRYSTAL RIVER POWER < GENERATION FACILITY: A QUANTITATIVE ANALYSIS Samuel C. Snedaker I Resource Management Systems Program Institute of Food and Agricultural Sciences University of Florida Gainesville, Florida October, 1974 , i II-259 1
._i
l l l IMPINGEMENT AT THE CRYSTAL RIVER POWER GENERATION FACILITY: A QUANTITATIVE ANALYSIS INTRODUCTION The Generic Problem Power generation plants which utilize local surface water for once-through cooling must have mechanisms to protect the circulating water pumps and condensers from potential damage due to large entrained organisms, flotsam and an assortment of coastal zone debris. This pro-tection is usually achieved through the installation of such devices as turrier nets, trash racks, and fixed or traveling screens placed up-stream from the intake pungs. The large-mesh nets and/or widely-spaced bars on the trash racks successfully exclude the larger flotsam, debris, ; and aquatic organisms. As the larger fish are usually strong swimmers and therefore can escape, impingement on these devices is relatively insignificant. However, organisms and debris small enough to pass through these barriers but too large to be freely passed through the condenser tubes are impinged on the small-mesh (0.95 cm) screens. The resulting l mortality induced by impingement a.,d/or removal from the screen has l become a possible cause for concern. Whether or not the concern is i warranted depends upon both a quantitative analysis of the impingement process and the perspective from which an objective interpretation is derived. The research results described herein are based on an inten-sive study of impingement on the traveling screens at the Florida Power Corporation's Crystal River facility. The Physical Environment at Crystal River The plant site, in Citrus County, Florida, is situated 12 km (7.5 l miles) north of Crystal River on a low-energy coastline characterized l by a relatively flat topography (see figure 1). The facility is situated at the landward edge of a Juncus sp. (with spartina sp.)-dominated tidal salt marsh through which two canals cycle marine waters for cooling. I The south canal is 8.3 km-(5.2 miles) long and serves both as a cooling i intake and deep water channel for oil barges. The 2.3 km (1.4 miles) north canal discharges the warm cooling-water into the coastal estuarine area adjacent the salt marsh. At low tide the effluent is confined to the canal and discharged at the terminus. At high tide the plume is encompassed within the water mass flooding the nearshore areas. Due to the length of the south (intake) canal dike, there is little if any re-circulation of the discharge water back into the intake canal. II-260
s% , g d ., d '.;. wlTMLACOOCHEE RIVER
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y ,. .$- .w CROSS FLomicA BARGE CANAL a
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'D CRYST AL RIVER
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, 'f? f Of Figure 1. - Florida Power Corporation's Crystal River power generation facility. The intake and discharge canais are so indicated.
11-261
I ! The shallow-sloping estuarine bottom (46.4' km to the 5 fa contour) is generally coincident within the drowned karst topography of this portion of west central Florida. Variations in bottom relief are due
. to oyster bars and the cutting and filling actions of currents. The source (s) of the cooling water drawn into the intake canal, as well as the hydrodynamics of the canal itself, have been the subject of other ! Florida Power Corporation reports.
I Power Generation at the Crystal River Facility The Crystal River electrical power generation capacity is currently provided by two fossil-fueled conventional generating plants. Plant Units 1 and 2 have a combined output of 897 megawatts electrical and rely on once-through cooling with a combined flow of 640,000 gpm of seawater. These units have a designed, maximum condenser temperature of 6.1*C
- (11*F) at the above pumpin, rate. Both units are oil fired and have been in operation since July,1966 (Unit 1) and November,1969 (Unit 2).
. A nuclear power plant (Unit 3) is currently under construction and is scheduled for fuel loading in late 1974 and connercial operation in 1975. Unit 3 is-a Babcock and Wilcox pressurized water reactor having an output of 855 megawatts electrical. Once-through cooling will in-volve a pumping rate of 700,000 gpm of seawater with a maximum condenser rise of 9.4*C (17 F). o j The Circulating Water System: Barriers and Screens , Illustrated in Figure 2 is a schematic of the intake canal, barrier nets and traveling-screen assembly. Seawater is drawn down the intake canal to its eastern-nost terminus. The eight circulating pumps draw at a right angle to the canal and bring the water past one barrier net, the trash rakes and the traveling screens. The barrier net is generally parallel to and in line with the north dike of the intake canal. The cross section of the canal at this point is approximately 160 feet wide and 16 feet deep (deepest point,19 feet) with irregular, sloping sides. A 175 foot barrier net extends 8 feet down from the surface and is
- made of standard, aluminum chain-link fencing. Parallel with the net is a 12 inch oil boom to guard against accidental spillage from entering
'the. circulating water system. ~ Large debris which collects along this net and the oil boom is manually removed. The draw of water at right angles to the canal creates a large, but slow-moving counter-clockwise eddy which tends to accumulate debris along the upstream end (western f
end).of the barrier net and screens. Impingement occurs as a result of the water pressure gradient, across the screens, which is capable' of holding organisms and debris on the up-2 II-262 ( . . - . . _ - - -. - ..- ,, ,,
l
-~. .- . . . . . . .. , ,._,, _. , _ _ , , ,
stream screen surface. As the impinged material accumulates on the screens, the effective flow cross-section decreases resulting in an in-creasing water velocity through the screens due to the differences in the hydraulic heads. This has the effect of holding the impinged material more tightly additional to the screens organisms and probably which could normallyresults escape,inatthe impingement least ofN, momentarily in a lower velocity water flow. To prevent the accumulation from severely blocking the cooling water flow, the screens are designed to be " cleaned" in either an automatic or manually-initiated mode. In the automatic mode, the drop in the downstream hydraulic head is sensed and the screen-wash i operation is started. This sequence can also be initiated or stopped by a manually operated switch. During the screen-wash operation, the screens travel around the two axles, rising on the upstream side and bringing the accumulated material over the top axle. A high pressure water-jet sprays the material off the screens into sluices which drain by gravity to the sides of the screen assembly. To ensure that the impinced material is removed from the water during screen operation, the screens are fitted with " hooks" which lift the debris. Otherwise, the screens would slide in front of the debris,which tend to remain in place. The sluiced material collects in large, metal cages which are emptied at intervals of several days; the associated water drains back into the canal. Earlier Studies at Crystal River In February of 1969, the Florida Department of Natural Resources Marine Research Laboratory initiated a screenwash monitoring program which was continued until March,1971. During that period the rotating screens were being operated continuously; intermittent manual operation was initiated in March,1971, which prompted the termination of the program due to reduced sample sizes (Mountain, 1972). Collections were ~ made with a one-inch stretch-mesh, six-foot nylon bag placed at the end of the screenwash sluiceway once each month for a 24-hour period. Species abundance and sizes were recorded during each collection period. The results of the first 12 months (1969) of the monitoring program were sum-marized by Grimes (1971). The screenwash impingement record for the 1969 collections revealed that some 59 and 15 species of vertebrates and macro-invertebrates, respectively, were impinged. Seasonal patterns were evident in both species abundance and the numbers of individuals among the vertebrates. The number of species was highest in March, lowest during the suniner months and peaked again during the fall. Numbers of individuals showed a similar pattern in terms of the _ March peak and the lower numbers during the summer. However, there was an exaggerated peak during November and December. The author attri-buted this late fall / winter peak to the relatively colder water temperatures. He further suggested a mechanism whereby cold-induced lethargy is responsible E nyA organism which cannot escape from the intake canal, or become part of a resident population within the canal, may eventually become impinged on the screens. Therefore, the time at which impingement occurs may be a moot point. II-263
m for the individuals becoming more susceptible to impingement. This does not seem plausible in the absence of evidence concerning the relative-size of the population of organisms'in_ the intake during the course of cthe year; . lethargy alone could not account for the two magnitude increase in impingement. Irrespective of the reasons for the seasonal differences, the seasonal patterns are distinct in the 1969 study ~and are useful in
. interpreting the results of_ the more recent research being reported. Direct comparisons are tenuous due to the large mesh of the DNR's collection bag which may have allowed the smaller organisms and juveniles to pass through.
7 i Current Research Objectives The primary objectives of this research were.to monitor and des-cribe the kinds, number and biomass of impinged organisms and ~to interpret what effect impingement may have as an imposed population-control mechanism on the local estuarine ecosystem. These' objectives require a uniform, intensive sampling scheme designed to document the dependent variables (i.e., impinged organisms), the independent variables (e.g., season, time, tide, barge traffic, sources of organisms), and pertinent interactions (e.g., frequency of screenwash operation). The contributing i secondary objectives focus on the analyses of the data with emphases on statistical tests of significance and predictive modeling to identify the major forcing functions and the probable causes of the variations in impingement. -It is suggested that a knowledge of the impingement process may indicate simple design or operation changes in the screen-wash assembly to minimize impingement. The. secondary objectives also include research on the application of time-series (harmonic) analyses to the generic problem of impingement at coastal power-generation facilities.
'; Not to be discounted among the objectives is the contribution to our collective knowledge of the fauna of central Florida's west coast.
PROCEDURES 4 Sampling Design f
.The initial sampling design called for weekly, 24-hour collection 4
fcr a one-year period using the Unit 2 (west) sluiceway. Later -it became necessary to test the assumption that both sets of screens
- (Units 1 and 2) had equal impingement characteristics and collections
.were made'at both sluiceways during the last five weeks of the first monitoring program. The paired collections were re-instituted for a nine-week period in 1974 for validation of the sluiceway comparison of 1973'and the spring peak in impingement. The inclusive dates for the monitoring sequences were:
1 13 Aug 72 through 4 Aug 73 -- Unit 2, west
; 10 Aug 73 through 25 Aug 73 - Unit 2, west II-264 x . .. - , + ,_3-- .
y_ _ g. - e -
~ . . - , . .. ,. . . , . . , , , . , . . . . ,. , , . . , ..., 10 Aug 73 through 25 Sep 73 -- Unit 1, east 8 Feb 74 through 6 Apr 74 -- Unit 2, west 8 Feb 74 through 6 Apr 74 -- Unit 1, east The collections were made using a framed grating over the collec-ting cages at the ends of the sluiceways. The frame was covered with ; quarter-inch hardware cloth and window screening to filter organisms from the screenwash effluent; all but the small larval and planktonic forms are caught by the screening. During operation of the screens i the technical team continually removed the collected debris from the ! frame, separated out the grass, algae and flotsam, and placed all l organisms in containers for freezing. Samples were kept separate and logged by hour. Thus, a 24-hour sequence could consist of 24 discrete samples. It should be noted that the hour of collection is not neces-sarily synonymous with the hour of impingement: such would occur only when the screenwash is operating continuously. In the initial sampling design it was determined that collections should be made consistent with the normal operation of the screenwash. That is, the screens would not be operated singularly for the purpose of collecting organisms. It was recognized that " normal" operation included those times in which FPC plant personnel would manually initiate the screenwash for reasons unrelated to plant activities. In this regard, the west screens were in operation only 23% (293 hours) of the time during the 52 week sampling sequence. The results of this study are therefore stated in terms of actual plant operation and not on the basis of what might have been collected under other circum-stances. Furthermore, it should be recognized that in precise terms the collections describe what was washed off of the screens and could be a poor estimate of actual impingement. On site observations indicate that some fraction of the impinged organisms are removed, when the
-. screens are idle, by the larger predators and scavengers. Also, screen operation may capture organisms which would have, at least temporarily, escaped.
As stated, the aggregate hourly collections were frozen prior to the laboratory workup. At that time, the organisms were sorted to look-alikes, identified, number and fresh weight recorded and, on subsamples, standard length measurements were made. (Tneorginial design called for dry-weight biomass and individual measurements, but the subsequent volume of material precluded such intensive workups atotherthaninfrequentintervals.) The routine data were logged by date and hour of collection. As the 24-hour collection period ran from noon to noon of the following day, hour #1 was logged as the first hour of cpilection; the hour numbers are therefore 12 hours out of phase with standard time. Daylight Savings Time corrcctions were made in
'the analysis.
The identifications of all coninon organisms were made in-house. Unknown or questionable taxa were identified by specialists at the 11-265
c
~
~
r University of Florida and 'the Florida State Museum. Reference and voucher specimens are maintained by the Museum. At the present time only one taxon remains questionable and that is the Northern Sennet, a barracuda (species code #89), which may include specimens of the Great Barracuda, Sphyrasna barracuda. Damaged specimens were identified only to the lowest, verifiable taxonomic grouping and are so indicated by "???" or "sp." if taken to genera. The paired-comparison collections were taken, processed and recorded according to these procedures. Data for the independent variables were obtained from the appro-priate sources: tide, from a stage-recorder at the screenwash assembly; barge traffic, from shipping records; weather conditions, from on-site observations and local weather station data; water temperature, pumping rate, load, etc., from FPC plant operation records. All data were logged in date-hour matrices for identification and access. Data analyses were performed by Mr. Jun-Shen Huang under the supervision of Dr. Richard Schaeffer, both at the University of Florida's Department of Statistics. RESULTS Impingement Data Record A complete listing of all data obtained during the impingement-monitoring periods is given in Appendix B1 and is available to interested users. This listing, by species including code numbers, includes the numbers of individuals and their aggregate biomass (fresh weight) collected at the specific hours on the sequential sampling dates. Impingement Data Summaries In Appendix B2, the hourly data listing from Appendix B1 is sum-marized, providing a cursory analysis of the characteristics of im-pingement for each species. Total numbers and biomass (by species) are given for each sampling period. In addition, values for the following parameters have been computed: Percent of all species (numbers and biomass) Mean biomass per individual Date of maximum impingement Seasons of maximum and minimum impingement l Time (date) of arrival Similar sunnaries are also included for species grouped according to defined economic and habit categories. Selected summaries appear in this report to assist in the interpretation of the results. l f 11-266
._ _ ~ .
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The dates for time-of-arrival were computer-selected based on the date of first appearance in the 1972/73 screenwash record using the first week in January as the starting point. In retrospect,
.this search sequence failed to identify those species which were being impinged in January but which first appeared at some time prior to January; these dates in the summaries are therefore incorrect. A second search was made in which the first date of impingement, after the longest period of absence, was determined.
These dates are listed in Table 1 along with the species for which that date is the best estimate of the time-of-arrival. The following species, in contrast, were collected every week the screenwash was monitored in the 1972/73 period: ! Anchoa mitchitti 20 i Ogcocephalus radiatus 26 Hippocampus erectus 40 Chitomycterus schoepfi 129 Cephalopoda 136 Ca:Linectes sapidus 156 l Squitta empusa 164 l The Ten Most Abundant (Biomass) Species l Of the 164 species of vertebrates and invertebrates collected from'the screen *:ssh samplings,10 species contributed 95.61% of the i total impinged biomass. In terms of numbers of individuals, these l 10 species also accountei for 97.78% of the impinged total. The pertinent data for this group are summarized in Table 2. The species comprising the top 10 are: i % Total Biomass ! polydactylus octonemus (90) 77.20 ! ogcocephalus radiatus (26) 11.07 Chilomycterus schoepfi (129) 2.57 Callinecces sapidus (156) 1.64 Lactophrys quadricornis (125) 0.77 Ascidiaceae (164) 0.68 Lagodon rhomboides (71) 0.61 Cephalopoda(136) 0.53 Bardistla chrysura (73) 0.46 Penaeus duorarun (140) 0.07 if5T6T% In Tables 3-12, each of these 10 species is summarized according to its own impingement characteristics. Of the seven " year-round" species listed previously and these 10, four are comon: the polka-dot batfish (26), the striped burrfish (129), the blue crab (156) and squid (136). j II-267
Species of Economic Importance
.In an effort to make estimates.of the possible economic conse-quences of impingement, the 164 recorded species were grouped within one of four categories of economic importance. The species included in each are listed by category in Appendix B2. These categories are listed below along with the percent each contributed to the total impinged biomass:
% Total Biomass
, Sport fishery species 2.96 l Commercial -- edible, fish meal, ! and oil reduction 2.16 Commercial -- non-edible, orna-l mental, aquarium trade, souvenir and research 2.69 l Tiilli Of the top ten biomass-contributing species, only five are includable within the above categories: the pinfish (71), silver perch (73), pink shrimp (140), blue crab (156), and the striped burr fish (129). The Atlantic threadfin (90) was not included because evidence could not i be found to suggest an economic importance in the eastern Gulf of Mexico (Bohlke and Chaplin, 1968; Briggs, 1958; C. Gilbert and D. Beau-i mariage, pers. com.) The threadfins (Polynemidae) are found in most tropical waters about river mouths and estuaries. They are common over exposed mud and sandy shores. This family consists of approxi-mately three dozen species, and they are considered excellent food fishes. Most species grow to a length of less than 45 cm and move in
' "' large schools. The species encounterad in this study, Atlantic threadfin (Polydactylus octonsmus), is distributed from Massachusetts to Florida and throughout the Gulf of Mexico. However, there is no known commercial fishery in Florida (particularly in the northeastern Gulf) for this species. The maximum size taken by impingement was
- approximately 20 cm.
Data sumaries for the three economic categories are presented
.in Tables 13-15.
Data Analyses and Interpretation At the time this report was prepared, the imposed deadline t precluded completion of the data analyses and interpretation; this l is the subject of an addendum to be submitted. The remainder of
'this report addresses the approach being used in the analyses and provides a general overview of the entrapment-impingement-entrainment process.
Aggregation for Analysis The impingement data record.(Appendix B1) for the 1972/73/74 monitoring periods shows that 815,021 specimens were collected repre-senting 132 species of vertebrates (792,698 individuals) and 34 species II-268 a . . ~ . ..
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> + - . 4 - ofinvertebrates(22,323 individuals). The data record further shows that eaco species tends to be rather unique in terms of both numbers impinged and the periodicity of impingement. For many of the species this variation, or a portion thereof, can be explained by differences in life cycles and behavior. Although a single analysis could be performed on the entire data set, its interpretation would tend to be obscured by the cumulative variation in each of the variables. Likewise, an analysis for each species would be mechanically overwhelming and would not include those species whose sample numbers are statisti-cally small. The obvious solution would be to aggregate the 164 species into a small number of definable categories to minimize the variation between categories; that is, to partition the variation according to known or assumed sources. Thus, for analytical purposes a second suite of categories was defined based on a combination of factors describing the interaction of species' life cycles and beherior, and the major forcing functions relating to impingement. The categories selected, as well as the species included in each, reflect the many man-hours of on-site observation of the impingement process. (These considerations are described ".n detail in the next section.) The categoriesaredefinedbelow(thespeciesincludedineachonelisted in Appendix B2) and data summaries for each appear in Tables 16-23. Habit Categories: Micratory, pulsed imoinaement. No. I -- A single species fits this category. It appeared only once during the periods of intensive monitoring, but in sufficient numbers to cause a temporary shut-down in power plant operation. Grass-mat dwellers and/or trackers, No. II -- This category includes those species which live among, or are asso-ciated with, floating mats of seagrasses and algae. Impingement of thes' species is generally coincident with the appearance of these mats in tne intake canal and at the screen assemblies. Bottom dwellers, mud or sand, No. III -- This category is defined to include those species which live in or on the bottom. Most of the macroinvertebrates appearing in the impingement record are included. Large, fast-swimmina -- too and mid-water. No. IV -- These species include those organisms whose strength / size , could permit them to escape impingement and/or entrap-ment within the intake canal. Large, fast-swiming -- bottom, No. V -- These species fit the general definition of category No. IV (above), but are associated with the bottom. Included are those species with sub-terminal mouths and which feed on the bottom. Slow, wt A-swimming, No. VI -- Within this category are those species which, for the most part, tend to be sedentary and which swim slowly or in short bursts when threatened. They are subject to short periods of entrainment in the turbulent water created by barge movements and are progressively transported down the intake canal. Their inability to swim strongly for sus-tained periods may preclude swimming an escapement mechanism. II-269
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Schooling, No. VII -- These are species which, for at least a part of their life cycle, move in schools of various sizes. Impingement, therefore, involves several to numerous individuals of the same size / age class. Sessile, No. VIII -- This consists of invertebrates, generally colonial forms, which live attached to relatively hard
.substrates.
A Sumarizing Hypothesis Figure 3 is an energy circuit diagram describing the major stocks, > flows and forcing functions in the entrapment-impingement-entrainment process. The symbols are according to Odum (1971). It is presented as l a hypothesis, or as a suite of related hypotheses, for which the. on-going l analyses are designed to test. The percentages impinged (in parentheses) are estimates based on the author's judgement. The entrapment-impingement-entrainment process is described using the model as a discussion format. The source of cooling water, and the ultimate source of all organisms, lies outside of the boundaries of the intake canal. (The sources are identified by the circle in the upper left corner of Figure 3). Whereas the flow of cooling water into the intake canal, and ultimately the power plant, is proportional to the pumping rate, the movement of most organisms is controlled or limited by other functions. The primary exceptions are those organisms which, because of their planktonic sizes, are entrained in the cooling water flow. It is assumed that 100% of the individuals so entrained, beco:ne entraped in the canal, and, discounted for canal mortality, eventually enter the power plant. The numbers, kinds, and ultimate fate of these organisms are being considered by other researchers. In the l diagram, entrainment is shown to be proportional to the pumping rate and l not limited by a finite source. Included separately in the diagram is the Atlantic threadfin (90) which during one short period of time was impinged in numbers (biomass) magnitudes greater than any other species. Impingement is shown controlled by an ON-0FF switch whose frequency of operation must, in the absence of long-tenn data, be assumed to be a random event. It is further thought that 1% or less of the threadfins which enter the intake canal eventually escape. ,0nly 167 individuals of this clupeid were collected at the screen-wash at times other than the single observed event during the first week of May,1973. At intervals during a year, there are periods when masses of sea-grasses and algae enter the intake canal and eventually, into the screens. This occurs as a result of seasonal dieback, severe storms, such as hur-ricane Agnes in 1972, and uprooting or breakage by, ostensibly, commercial shrimp trawlers. These grass mats relate to impingement through two mechanisms: large mats may act as: a barrier " herding" organisms in front of it or other-wise obfuscating escapement and, by carrying with it those organisms which feed or seek refuge therein; The supposed " herding" action was deduced L 11-270
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d from the fact that relative impingement is generally alway- higher when , such mats arrive at the screens. A portion of the higher impingement ' consists of species which are normally found in association with floating l grasses and algae where they occur. These latter species have been grouped together (category No. II) and incluA for the most part such organisms as the seahorses (39,40,41), pipeft mes (42,43,44,45) and grass shrimp (143,148). Interestingly, the lwed seahorse (40) is one l of the seven species collected year-round in t.e screenwash and may ' represent a resident canal J. m lation. l
- Frequently observed during the study was the coincidence of oil-barge traffic and greater masses of grass, algae and impinged organisms.
The barge-induced canal turbulence, however, appears to have a greater influence on the slow, weak swimers (category VI) than it does on the category II organisms associated with the mats. Thus, that action, diagrammed as " canal turbulence", may have little direct effect on the impingement of grass-mat trackers and dwellers. Although the lined seahorse (40) may have a resident canal population, it is assumed that 100% of the organisms in association with a grass is impinged when the grass arrives at the screens.
. It should be' obvious by now that these three described categories '
of species are not amenable to the same kind of numerical or statistical i analysis. However, the next five groups, with certain qualification, , appear to be amenable to a ,;me-series or harmonic analysis because of re- ! f vealed relationships with seasonal, diurnal and tidal periodicities. Many of the species in these five categories show seasonal peaks (spring and fall), dawn-dusk peaks, and accelerated impingement on rising tides. Furthermore, their appearance in the intake canal, whether or not impinged, seems to be a seasonal characteristic. 4 Species which best fit the description of bottom-dwellers (category III) are thought to also include most of the species which have resident populations in the intake canal. This may reflect a common habitat pre-ference for the kinds of exposed substrates within the canal. Two species ; . in this category are among the top ten impinged in terms of biomass; the , blue crab (156) and the pink shrimp (140). With elimination of the ' Atlantic threadfin (90) from the one-year record, these two species ac-counted for 5.93% of the impinged biomass. Both the blue crab (156) and the pink shrimp (140) show seasonal fluctuations in the size of the
" resident" population; pink shrimp appeared in the screenwash on March 30th, coincident with the return migration of female blue crabs. It is thought that both species arrive at the screenwash as a result of population-dependent downstream migration; evidence is presented in Report G to show
.that blue crabs do migrate out of the intake canal. Similar evidence is
> not available for the pink shrimp. Relative population nunbers for blue crabs (156) in the intake canal were prepared from the tagging study (Report G) and included here as e Figure 4. Two foci of " bunching" are apparent: one along the canal past , the terminus of the southern dike, and the second at the downstream ter-minus of the canal near the intake structure. The former has been sug-gested to be the result of an imposed barrier (northern intake canal dike) II-272
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to the fall, northern migration. The downstream bunching at the screens may similarly reflect the eastern termination of the canal. It may not ) be unreasonable t' uggest that the latter may be a viable population supported by accuno ating organic debris and screen scavaging, and largely capable of escapement at the time of migration. The lower re-lative number along the canal could either reflect " poor habitat" or turbulent downstream displacement by barge traffic; poor habitat is the preferred hypothesis. It is estimated that for the category, consisting of all species so included, impingement may account for some 10% of the canal population j v (biomass). The seasonal seaward migration is not shown on the diagram 1 (Figure 3) as " escapement" for the term implies some peril mitigating ! against outward migration; such is not known except for those individuals, by definition, impinged. The seaward migration is diagramed as' a two-way ) work gate illustrating that " season" also controls this movement. This particular mechanism may also apply to many of the species in other cate-gories. i i Category IV includes the large, fast-swimming species associated I with the top and mid-water. Many of these are large enough to be excluded at the trash rakes and are strong enough to navigate the canal at will. Specimens in the screenwash collections are dominated by the early age classes or show evidence of trauma not necessarily related to impingement.
< It is assumed that 1% of the transitory population in the canal becomes impinged.
Similar in their respective ability to avoid impingement are the large, fast-swiming species associated with the bottom (category V). Although both categories (IV & V) are similar in terms of biomass impinged : (0.42%vs. 0.32%; Tables 19 and 20), the mean size of category V speci- ! mens is almost double (48.9 g vs. 26.1 g) those in category IV. This is l due to the dominance of relatively large rays (3,4) in the screenwash collections in addition to the many. individuals of the smaller size classes. A differential selection for the impingement of rays is suggested by their l large body surface area which would hold them tightly to the screens, pre- ' venting escapement in spite of their strength. Like the species in cate-g gory IV, impingement is assumed to be around 1% of the extant canal popu-lation. In terms of impingement, and in ignorance of possible pulses of the j Atlantic threadfin (90), three species in category VI constitute 49.20% of the impinged biomass. These are the polka-dot batfish (26) - 38.44%, striped burrfish (129) - 8.09%, and the scrawled cowfish (125) - 2.67%. j The batfish and burrfish are year-round canal residents (confirmed by canal trappings and visual observations with SCUBA). Whereas these three species are closely associated with the bottom (suggestive of another category), they are for the most part heavy-bodied and weak swimmers. 1 This is a particularly pertinent characteristic with respect to barge-induced turbulence in the intake canal and its effect on the accelerated I l l II-274
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downstream movement of these animals. In the diagram, " canal turbulence" is shown accelerating the downstream movement but some fraction is "re-turned" to the population; the remainder move some incremental distence closer to the screens. In reality, the mechanism is best considered as a continuum of these sub-circuits linked in series " pumping" these or-ganisms downstream. The net impingement resulting from this function is suggested to be 50% of the mean annual population of category VI species. As with the other categories, the presence of grass mats in the canal increases the impingement of organisms. The species which comprise category VII are common in their top-water schooling behavior not only as juveniles but also as adults. They include the clupeids (13,14,15), anchovies (18,19,20), mojarra (62-65), grunts (66,67,68), and mullet (84-87). The results from the majority of the screenwash collections suggest uut the juvenile size classes are p-the most susceptible to impingement and that impingement occurs in schcols. Whereas it is doubtful that individuals from a school would escape such circumstances, it is thought that schools in the western-end of the canal can escape. It is therefore estimated that 90% of the schools which enter the intake canal eventually become impinged but they are unable to swim against currents for relatively long distances. (The Atlantic threadfin would fit in this category if its' local presence in schools were a regular occurrence). Two of the top ten species, the pinfish (71) and the silver perch (73) are assigned to this category and collectively account for 3.72% of the impinged biomass. Category VIII includes the sessile invertebrates which have colonized the hard substrates in the 'ntake canal. The most important of these in terms of impinged biomass (2.36%) are the Ascidians (164.' Impingement is simplified in the diagram (Figure 3) and is shown to be proportionate to the size of the resident canal population. Usually, mortality among these colonial inurtebrates is not manifested as detached dead organisms; instead, the soft parts are resorbed within the colony. The large mass of Ascidians in the screenwash collections is thought to come from break-age among the massive colonies occupying such artificial substrates as the docks, intake structures and the barrier net at the eastern terminus
- of the canal. The loss to impingement is therefore a small fraction
# (i.e.,1%) of the resident canal population.
A Comment on Entrapment A presup. posed integral part of this study was the assessment of entrapment in the intake canal to determine organism mortality due, simply, to entrapment in the canal. Also, for those resident species populations such studies would allow estimates to be made of impingement, expressed as percentages of the source populations. Despite the support and personnel made available, the task failed to yield any significant data due primarily to unpredictable barge traffic aborting sampling schedules and destroying fishing gear. Also, entanglements by porpoise and sharks created much dead time. However, much was learned from the effort which will be of assistance in interpreting the analytical results of the impingement study. II-275 e
However, and in retrospect, the question of entrapment appears to be both empirically irresolvable and moot. The Atlantic threadfin (90) pulse could not be studied empirically in the cand r He % =ncy of occurrence is unknown. At best, a study could do little more than report how long it took a 10-ton school to travel the canal. Yet during the study, this single species accounted for 96% of the individuals and for 77% of the biomass impinged and forced a shut-down in plant operation. For this shock-prone clupeid, there is little distinction between entrapment and impingement.. The next four species among the top-ten rar.iang, the batfish (26), burrfish (129), blue crab (156) and cowfish (125), contributed another 16% to the impinged biomass, yet the three vertebrates (none of which have comercial or sports importance) appear to function well in the intake canal. It is doubtful that species so excellently adapted to the canal habitat could be considered entraped; certainly, impingement has not mitigated against the survival of the canal populations. The blue crab, while of comercial importance, appears to be able to migrate freely in the canal; to speak of blue crab entrap-ment would require a most precise definition of the term. Furthermore, the strong, on-shore seasonal migration could possible result in a similar percentage of impingement, irrespective of the length of the canal. Species of comercial or sports importance (other than the blue crab and the pink shrimp) are impinged in such small numbers that .a
/ impingement analysis is statistically difficult and an entrapment survey would be even more arduous and of questionable meaning. Observations during the past entrapment study suggested that the greatest portion of any canal-related mortality may be due to a high intensity of predation by large carnivores which, themselves, are not capable of being entraped or impinged under normal circumstances. Loss by predation within the canal would be extremely difficult to assess and probably impossible to interpret in terms of impact.
l Analysis and Interpretation The analysis and interpretation of the entrapment-impingement-entrainment process is continuing and is expected to be completed in several weeks. These efforts seek to accomplish the following general objectives: (1) The sumary i nformation presented in Report B and its Appendices is based on sampling estimates largely for the 1972/73, 52-week study period. In order to extrapolate to the 365-day, 2 unit totals, tests of significance between the paired screenwash samplings must be made. Ini-tial analyses (reported earlier) showed that the two screenwash assemblies behave differentia 11y with respect to the impingement of the 164 species l under consideration. l (2) Work thus far has shown that impingement, in general, can be
/ described as a function of season, time-of-day, tide and barge movements; a problem amenable to time-series analysis. An earlier estimate based on, then, incomplete data suggested that much (over 60%) of the variation i in impingement could be explained by the interaction of barge movements !
and tide. This analysis is to be performed using the completed data set. l
, II-276
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1 LITERATURE CITED B0HLKE, J.E. ~ and C.C.G. Chaplin. 1968. Fishes of the Bahamas and Adjacest Tropical Waters. Livingston Publishing Co. 771 pp. ; l BRIGGS, J.C. 19 9. A list of Florida fishes and their distribution. ' Bull.Fla.St. Museum 2(8): 223-318. GRIMES, C.B. 1971. Thermal Addition Studies of the Crystal River Stream Electric Station. Fla. Dept. of Natural Resources no. 11 53 pp. MOUNTAIN, J.A.' 1972. Further Thermal Addition Studies at Cristal River, Florida with an Annotated Checklist of Marine Fishes Collected 1969-1971. Fla. Dept. of Natural Resources no. 20 103 pp. ODUM, H.T. 1971. Environment, Power, and Society. Wiley-Interscience 317 pp. II-278
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Table 1. Time of arrival, estimated as date of first appeara ce in the screenwash. (This listing is correct and superc.' des computer estig.*es made in the data summaries.) Species Code 12 January Leiostomus zar,thurus 76 19 January Monacanthus sp. 122 26 January Sphyrna tiburo 2 Porichthys piectrodon 25 Diapterus oliathostomus 62 Nicholsina usta 83 Trinectes maculatus 117 Portunus gibbesii 153 2 February Monacanthus ciliatus 123 9 February Gymnura micrura 4 Bascanichthys scuticaria 8 Urophycia sp. 27 Strongylura marina 32 Oligoplites saurus 56 Trachinotus falcatus 60 M:mit cephalus 85 Rypsobtennius hentzi 96 16 February Brevoortia patronus 15 Strongytura notata 33 Dipiectrum formosum 47 Sciaenidae 72
'Sciaenops ocaltata 80 Mugii curema 86 Mugit trichodon 87 23 February Menticirrhus americanus 78 Bothidae 110 2 March Haemulon plumieri 67 Menticirrhus sp. 77 Neopanope texana 159 30 March Carcharhinus timbatus 1 Penaeus duorarum 140 II-279 ,
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Table 1(cont.) 5 .^oril Hippocampus sp. 39 Syngnathus Louisianae 44 Panopeus herbatii 160 13 April Anchoa hepsetus 19 Diplodus hotbrooki 70 Polydactylus octonemus 90 Menippe mercenaria 158 20 April Muraenidae 6 27 April , Cyprinodon variegatus 35 Syngnathus floridae 43 Astrapogon atutus 50 Trachinotus carolinus 59 Sphyraena borealis 89 Ancylopsetta quadrocellata 111 Atuterus schoepfi 120 Sicyonia brevirostris 141 4 May Caranx hippos 54 11 May
& pia sp. 137 18 May Hyporhamphus unifasciatus 30 25 May calamus arctifrons 69 1 June
-Opisthonema oglinum 17 Porifera 132 Penasus sp. 139 8 June Carangidae 53 Chloroscombrue chrysurus 55 22 June Synodus foetens 21 Rachycentron canadum 51 Selene vomer 57 Callinactes ornatus 155 II-280
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Table 1 (cont.) 29 June Gymnothorax nigromarginatus 7 Hippocampus sosterae 41 Echeneis naucrates 52 Eucinostomus gula 65 Cynoscion arenarius 74 Cynoscion nebulosus 75 Halichoeres bivittatus 82 Citharichtys spitopterus 112 6 July Cobiosoma robustwt 98 13 July Mycteroperca microlepis 48 Eucinostomus argenteus 64 Alpheus heterochaelis 146 Libinia dubia 162 20 July Eucinostomus sp. 63 Chasmodes saburrae 95 Perictimenes 5p. 144 10 August Polychaete 134 Xanthidae 157 17 August Clupeidae 13 Fundulus similia 36 Micrognathus crinigerus 42 Centropristia melana 46 Decapoda 138 24 August Anchoa sp. 18 Arius felis 22 Sphoeroides sp. 126 31 August. Scomberomorus maculatus 102 Anthozoa 133 Portunus 5p. 152 7 September Hacmulon sp. 66 Balistidae 119 l l II-281
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Table 1 (cont.) 14 September Harengula pensacolae 16 Strongytura timucu 34 Lutdanus griseus 61 Sphoeroides nephalus 127 Aptysia villcoxi 135 21 September Achirus lineatus 116 5 October Letharcus velifer 9 Papritus sp. 103 Prionotus 5p. 106 Pleuronectiformes 109 Symphurus plagiusa 118 Petrolisches sp. 150 Metoporhaphie calcarata 161 Squitta enpusa 163 12 October Pepriius atepidotus 104 , 19 ')ctober Petralisthes armatus 151 16 November Bairdietta chrysura 73 Micropogon undulatus 79 Monacanthus hispidus 124 23 November Dasyatis sabina 3 Prionotus tribulus 108 Lactophrys quadricornia 125 30 November Ophichthus gomesi 12 Brevoortia sp. 14 Strongytura sp. 31 Trachinotus sp. 58 i Orthopristis chryacptera 68 l BZennius 5p. '94 Scorpaena brasiliensis 105 7 December Elops saurus S Nyrophis punctatus 10 Bagre marinus 23 Menidia beryllina 37 Chaetodipterus faber 81 Sphyraena sp. 88 II-282 l~ -. - ~~.,- , - - - - - .
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- Lagodon rhomboides 71 Nugit sp. 84 Opistognathidae 91 Soleidae 115 Portunus spinimanus 154 f
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SUMMARY
l l Table 2 l TOP TEN SPECIES R ANKED BY SIOMASS (KILOS. FRESH) l 1 PERIOD TOTALS PERIOD INDIVIDUALS BIOMASS (NUMBER) (KILOS. FRESH) 1972/73 UN I T 2 782413. 4094.546 1973 UNIT 2 1299. 70.194 1973 UNIT 1 151. 47.600 1974 UNIT 2 6649. 191 699 1974 UNIT 1 2960. 79.089 TOTALS 792.173. 4412.926 i
/
1972/73 I MP I N GE MENT DESCRIP'.!ON PERCENT OF ALL SPECIES COMBINED : I ND I V ID UALS( NUMBER ) : 97.78% BI OMASS(FRESH WE IGHT ) :95.61% MEAN BIOMASS PER INDIVIDUAL : 5 23 GRAMS DATE OF MAXIMUM 24 HOUR IMPINGEMENT ON BIOMASS : MAY 4 - 5.1973 ON INDIVIDUAL : MAY 4- 5 1973 s SEASON OF MAXIMUM IMPINGEMENT ON BIOMASS : SPRING ON INDIVIDUAL : SPR I NG SEASON OF MINIMUM IMPINGEMENT ON BIOMASS : FALL ON INDIVIDUAL : FALL TIME OF ARRIVAL (DATE Of DST IMPINGEMENT) : l l II-284
DATA
SUMMARY
'- - 4 . ,, ., . . , , , .,. . , ,. Tabhe 3 00LYDACTYLUS OCTONEMUS --- POLYNEMIDAE --- PERC1F34MES NuFS IDENTIFIER : 166010503 SPEC 1ES CODE : 90 PERIDO TOTALS DEPIOD I NDIV I DJ AL S BIOMASS (NUMBEP) (KILDS. FRESH) 1972/73 UNIT 2 765363. 3306 413 1973 UNIT 2 156. 1 041 1973 UNIT 1 11. 0.090 1974 UNIT 2 O. 0.0C0 , 1974 UNIT 1 C. 0.000 3792,I TOTALS 765374. 3306.503 ~) b5, g]P }? m 1
, , { } : ..
l 1972/73 INDINGEMENT DESCRIPTION DERCENT OF ALL SPECIES COMBINED : I N D IV IOU ALS ( NUMBER ) : 95 65% B I OM A SS( FRES H WEIGHT) 177.2C% MEAN BIOMASS PER INDIVIDUAL : 4.32 GRAMS DATE OF MAXIMUM 24 HOUR IMDINGEMENT ON BIOMASS : MAY 4 - 5.1973 ON INDIVIOUAL : MAY 4 - 5.1973 SEASON OF MAXIMUM IMPINGEMENT , ON BIOMASS : SPRING ON INDIVIDUAL : SPR ING SFASON OF MINIMUM IMPINGEMENT ON B I OM AS S : FALL ON INDIVIDUAL : FALL TIME OF ARO lVAL( DATE OF FIPST IMPINGEMENT) : e
. II-285 O
OATA
SUMMARY
Table 4 - OGCOCEDHALUS PADIATUS --- OCCOCIPHALIDAE --- LOPH 11 FORMES NMFS IDENTIFIEP : 195C50207 SDECIES r.0 D E : 26 PERIOD TOTA . 4 DEPIOD INDIVIDUALS BI O, \SS (NUMBER) ( KI LJS .F RE SH) 1972/73 UNIT 2 5779. 474.272 1973 UNIT 2 317. 29.972 1973 UNIT 1 35. 3.013 1974 UNIT 2 1254. 127 108 1974 UNIT 1 G16. 58.936 TOTALS 7684 663.329 1972/73 IMPINGEMENT DESCRIPTION DECCENT OF ALL SPECIES COMBINED : INDIVIDUALS (NUMBER) : 0.72X DIOM ASS ( FRES H WE IGHT ) :11 07% MEAN HIOMASS PEP IND IV I DU AL : 82.07 GR A?t; DATF OF MIXIMUM 24 HOUR IMPINGEMENT ON BIOM ASS : MARCH 2~ 3 .1973 DN INDIVIDUAL : MARCH 2- 3 .1973 SEASON OF MAXIMUM IMPINGEMENT ON BIOMASS : WINTER ON INDIVIDUAL : WINTER SEASON OF MINIMUM I M A I NGE M'ENT ON BIOMASS : FALL ON INDIVIDJAL : FALL TIME OF ARD IV AL( DAT E OF FIRST IMPINGEMENT) : r II-286
DATA SUMMAOY , Table 5 CHILOMYCTEDUS SCHOEDFI --- D IOD'ON T I D AE --- TETR A 03ONT IF ORMES NMFS IDENTIFIER : 189C90203 SPECIES CODE : 129 PERIOD TOTALS DECIOD INDIVIDJA S BIOMASS (NUMBER) ( K I L OS , F RES H ) 1972/73 UNIT 2 822. 110.005 1973 UNIT 2 7. O.269 1973 UNIT 1 C. 0.000 1974 UNIT 2 44 7.028 1974 UNIT 1 9. 1 477 TOTALS 875. 118.S10 1972/73 IMPINGEMENT DESCRIPTION PERCENT OF ALL SPECIES COMBINED : I NDI V I DU ALS ( NU MBER ) : C.10x BIOMASS (FRESH WEIGHT) : 2 57X MFAN RIOMASS PER INDI V IDU AL : 133.83 GRAMS DATE OF MAXIMUM 24 HOUR IMPINGEMENT 2.1972 ON BIOMASS : DECEMBER 1 - ON INDIVIDUAL : DECEMBER 1 - 2 1972 SEASON OF MAX'IMUM IMAINGEMENT ON BIOMASS : WINTER ON INDIVIDUAL : WINTER SEASON OF MINIMUM IMPINGEMENT ON BIOMASS : SUMMER ON INDIVIDUAL : SUMMER T!wE OF AU R I V AL( D ATE OF FIRST IMPINGEMENT) : II-287
DATA'
SUMMARY
Table 6 C ALL INECTE S S API DUS --- PORTUNIDAE --- DECAPODA NMFS IDENTIFIER : SDECIES CODE : 156 PERIOD TOTALS PERIOD INDt VI DU AL S BIOMASS (NUMBER) (KILOS. FRESH) 1972/73 UNIT 2 1217. 70.412 1973 UNIT 2 60. A.680 1973 UNIT 1 14. 1.050 1974 UNIT 2 650. 19.081 1974 UNIT 1 135. 2.768 TOTALS 2016. 93.311 1972/73 IMPINGEMENT DESCCIATION DEDCENT OF ALL SPECIES COMBINED : . INDIVIDUALS (NUMBER) : 0.15% D I OM ASS ( FCES H WE IGHT ) : 1.64% MEAN BIOMASS PED IN31VIDUAL : 57.86 GRAMS DATE OF MAXIMUM 24 HOUR IMPINGEMENT ON BIOMASS : MAY 25-26.1973 DN INDIVIDUAL : MAY 25-26 1973 SEASON OF MAXIMUM IMPINGEMENT ON BIOMASS : SPRING ON INDIVIDUAL : SPRING SFASON CF MINIMUM IMPINGEMENT ON BIDMASS : FALL ON INDIVIDUAL : FALL TIMF OF ADC I VAL ( DATE OF FIRST I t'P I NGEM EN T ) : II-288
DATA
SUMMARY
- s ~9. . < , - - . ,
4 Table 7 L ACTOPHQYS OUADRICORNIS --- OSTRACIIDAE --- TETRA 33DNTIFORMES NMFS IDENTIFIER : 189070132 SDECIES CODE : 125 t PERIOD TOTALS ( PERIOD INDIVIDUALS BIOMASS (NUMBERI- ( K I L OS . F RES H ) 1972/73 UNIT 2 347. 33.005 ( 1973 UNIT 2 5. 1 022 1973 UNIT 1 1. 0 153 1974 UNIT 2 74 8.550 1974 UNIT 1 36. 5.079 z TOTALS 458. 46.787 i 1972/73 IMPINGEMENT DESCRIPTION i AEQCENT OF ALL SPECIES COMBINED : INDIVIDUALS (NUMBER) : C.04% B I OM ASS ( FRESH WEIGHT) : C.77% l MFAN BIOMASS DER IMDIVIDUAL : 95 12 GRAMS DATE OF MAXIMUM 24 HOUR IMPINGEMENT ON BIOMASS : FEBRUARY 16-17.1973 ON INDIVIDUAL : FEBRUARY 16-17.1973 SEASON OF MAXIMUM IMPINGEMENT ON BIOMASS : WINTER ON INDIVIDUAL : WINTER i SEASON OF MINIMUM IMPINGEMENT ON BIOMASS : FALL ON INDIVIDUAL : FALL TIME OF AQ D I V AL( D AT E OF FIRST IMDINGEMENT) : i i II-289
DATA-
SUMMARY
Table 8 (ASCIDIACEA) --- --- NMFS IDENTIFIER : SPECIES CODE : 164 PERIOD TOTALS DEnIOD INDIVID'ALS J BIOMASS (NUMBEP) ( K I L OS , F RES H ) 1972/73 UNIT 2 3. 29.247 1973 UNIT 2 c. 31 732 1973 UNIT 1 C. 42.932 1974 UNIT 2 10. 1.352 1974 UNIT I De 0 107 TOTALS 10. 73.638 197?/73 IMPINGEMENT DESCRIPTION PECCENT OF ALL SDEC IES COMBI NED : INDIVIDUALS (NUMBER) : 0.0CX BIOMASS (FRESH WEIGHT) : 0 68X DATF OF MAXIMUM 24 HOUR IMPINGEMENT ON BIOMASS : AJGUST 17-18,1973 SEASON OF M AX I MU M IMPINGEMENT ON BIOMASS : SUMMER SEASON OF MINIMUM IMPINGEMENT ' ON BIOMASS : SPRING l l TIME OF ARRIVAL (DATE OF FIRST IMPINGEMENT) : ' 6 l l II-290
..m.
DATA ' -
SUMMARY
Table 9 LAGODON GHOMDOIDES --- SPARIDAE'--- PERCIFORMES 71 NMFS IDENTIFIER : 170211601 SPECIES CODE : PERIOD TOTALS DERIOD I NDI VI DU AL S BIOMASS (NUMBER) (KILOS, FRESH) 1972/73 UNIT 2 2026. 25 929 1973 UNIT 2 10. O.257 1973 UNIT 1 1. O.150 197A UNIT 2 2C9. 0.699 197A UNIT 1 A7. 0.090 TOTALS 2283. 26.868 1972/73 IMP!NGEMENT DESC A IPT ION
, DEDCENT OF ALL SPEC 1ES COMBINED :
I ND I V I D UA LS( NUMBER ) : 0 25% BI OM ASS (FRES H WE IGHT )
- 0 . 61 X MEAN BIOMASS PER INDIVIDUAL : 12 80 GRAMS DATE OF MAXIMUM 2A HOUR IMPINGEMENT ON BIOMASS : FEBRUARY 16-17.1973 ON INDIVIDUAL : FEBRUARY 16-17.1973 SEASON OF MAXIMUM IMPINGEMENT ON BIOMASS : WINTER ON INDIVIDUAL : WINTER SEASON OF MINIMUM IMPINGEMENT 3N BIOMASS : FALL ON INDIVIDUAL : FALL TIME OF ARDIVAL(DATE OF FIRST IMDINGEMENT) :
II-291 r
f DATA'
SUMMARY
Table 10 (CEPHALOPODA) --- --- NMFS IDFNTIFIER : SDECIES CDDE : 136 PERIOD TOTALS DERIOD INDIVIDUALS BIOMASS (NUMBER) (KILOS. FRESH) 197?/73 UNIT 2 4111. 22.695 1973 UNIT 2 246. C.550 1973 UNIT 1 30. O.100 1974 UNIT 2 434 2.078 1974 UNIT 1 77. 0.501 TOTALS 4652. 25.374 197?/73 IMATNGEMENT DESCRIPTION D E S C F. N T OF ALL SPECIES COMBINED : INDIVIDUALS (NUMBE9) : C . 514 BI OM ASS ( FEES H WE IGHT ) : C.53X MEAN BIOMASS PER INDIVIDUAL : S.52 GRAMS DATE OF MAXIMUM 24 H OUR IMPINGEMENT ON BIOMASS : FEB2UARY 16-17.1973 ON INDIVIDUAL : DECEMBER 1 - 2 1972 SFASON OF MAXIMUM IMPINGEMENT ON BIOMASS : WINTE9 ON INDIVIDUAL : WINTER SEASON OF MINIMUM IMPINGEMENT ON BIOMASS : FALL ON INDIVIDUAL : SPRING TIME OF A;R IVAL( DATE OF FIRST IMPINGEMENT) : l II-292
DATA
SUMMARY
Table 11 BAIODIELLA CHRYSURA --- SCIAEN!bAE --- PERCIFORMES NMFS IDENTIFIER : 170201532 SDECIES CDDE : 73 PERIOD TOTALS PEo!OD INDIVIDUALS BIOMASS (NUMBER) (KILOS FRESH) 1972/73 UNIT 2 1364. 19.750 1973 UNIT 2 36. O.C77 1973 UNIT 1 C. 0.000 1974 UNIT 2 653. 8.319 1974 UNIT 1 43. 0.608 TOTALS 2060. 28.677 1972/73 IMPINGEMENT DESCRIPTION PECCENT OF ALL SPECIES COMBINED : I ND I V I DUA LS ( NUMBER ) : 0.17% BIOMASS (FRES H WE IGHT ) : 0.46% MEAN BIOMASS PEP INDIVIDUAL : 14.48 GRAMS DATE OF MAXIMUM 24 HOUR IMPINGEMENT ON BIOMASS : FES9UARY 16-17.1973 ON INDIVIDJAL : FEBRUARY 16-17.1973 SEASON OF MAXIMUM IMPINGEMENT ON BIOMASS : WINTER ON INDIVIDUAL : WINTER SEASON OF MINIMUM I4PINGEMENT ON BIOMASS : FALL ON INDIVIDUAL : FALL TIME OF ACRIV AL (DAT E OF FIRST IMPINGEMENT) : I i l II-293 l J
DATA- SU4 MARY ' " Table 12 DENAEUS DUORACUM --- PENAEIDAE ~--- DE C AD OD A NMFS IDENTIFIER : SPECIES CODE : 143 ESRIOD TOTALS PERIOD INDIVIDJALS BIOMASS (NUMBER) (KILOS, FRESH) 1972/73 UNIT 2 1384 2.818 1973 UNIT 2 462. 0.594 1973 UNIT 1 59. 0 112 1974 UNIT 2 3321. 17.484 1974 UNIT 1 1997. 9.523 TOTALS 6761. 29.937 1972/73 IMPINGEMENT DESCRIPTION DFQCFNT OF ALL SDECIES C OMB I NED : INDIVIDUALS (NUMBEC) : 0 17X B IOM ASS ( 74ES H WE IGHT ) : C.07% MEAN BIOMASS PEA IN3 I V I DU AL : 2.04 GRAMS' DATE OF MAXIMUM 24 HOUR IMPINGEMENT ON RIOMASS
- APRIL 27-28,1973 DN INDIVIDUAL : JULY 6 - 7,1973 SEASOfA OF MAXIMUM 14PINGEWENT ON BIOMASS : SUMMER ON INDIVIDUAL : SUMMER SEAsnN OF MINIMUM IMAINGEMENT ON BIOMASS : FALL ON INDIVIDUAL : FALL TIME OF AccIV AL( DATE OF FIRST IMDINGEMENT) :
II-294
. .,, , -, DATA
SUMMARY
Table 13 SPOR T F ISHERY SPECIES PERIOD TOTALS PERIOD INDIVIDUALS BIOMASS ( N UM BE R ) ( K I LOS .F RE SH) 1972/73 UNIT 2 12833. 126.934 1973 UNIT 2 1430. 3.456 1973 UNIT I 258. 0.800 1974 UNIT 2 4034 18.890 1974 UNIT 1 761. 5.319 TOTALS 17886. , 161 943 1972/73 IMPINGEMENT DESCRIPTION PERCENT OF ALL SPECIES COMBINED : INDIVIDUALS (NUMBER) : 1.60% BIOM ASS ( FRES H WE IGHT ) : 2 96% MEAN BI DM ASS PER IND IV I DU AL : 9 89 GRAMS DATE OF MAXIMUM 24 HOUR IMPINGEMENT ON BIOMASS : FEBRUARY 16-17 1973 DN INDIVIDUAL FEBRUARY 16-17.1973 SEASON OF MAXIMUM IMPINGEMENT ON DIOM ASS : WINTER ON INDIVIDUAL : WINTER SEASON OF MINIMUM IMPINGEMENT ON BIOMASS : FALL ON INDIVIDUAL : FALL TIME OF ARRIV AL(DATE OF F IRST IMPINGEMENT) II-295
DATA ' SUM M A'R Y Table 14 COMMERCIAL - EDIBLE. ETC. PERIOD TOTALS PERIOD INDIVIDUALS BIOMASS (NUMBERS (KILOS. FRESH) 1972/73 UNIT 2 5810. 92.594 1973 UNIT 2 630. 6.073 1973 UNIT 1 84 1.180 1974 UNIT 2 4036. .37.724 1974 UNIT 1 2172. 12 910 TOTALS 12102. 144.408 1972/73 IMPINGEMENT DESCRIPTION PERCENT OF ALL SPECIES COMBINED : I ND I V I D UALS ( NUMBER ) : 0.73% BI OMASS ( FRESH WE IGHT ) : 2 16X MEAN GIOMASS PER INDIVIDUAL : 15 94 GRAMS DATE OF MAXIMUM 24 H OUR IMPINGEMENT ON BIOMASS : MAY 25-26.1973 ON INDIVI DU AL : OCTOBER 6- 7.1972 SEASON OF MAXIMUM IWPINGEMENT ON RIONASS : SPRING ON I NDI VI DU AL : FALL SEASON OF MINIMUM IMPINGEMENT I CN BIOMASS : FALL ON INDIVIDUAL : WINTER l TIME OF ARRIV AL( DAT E OF F IRST IMPINGEMENT) :
)
\
e II-296
i DATA
SUMMARY
)
Table 15 CDMMERCIAL - NONEDIBLE. ETC. PERIOD TOTALS PERIOD INOIVIDUALS BIOMASS (NUMBER) (KILOS. FRESH) 1972/73 UNIT 2 1353. 115.409 1973 UNIT 2 17. O.315 1973 UNIT 1 3. 0.014 1974 UNIT 2 767. 10.426 1974 UNIT 1 178. 2.298 TOTALS 2301. 128 147 1972/73 IMPINGEMENT DESCRIPT ION PERCENT OF ALL SPECIES COMBINED : I ND I VID UALS ( NUMBER ) : 0 17% BIOMASS (FRESH WEIGHT) : 2 69% MEAN 01DMASS PER INDIVIDUAL : 85.30 GRAMS DATE OF MAXIMUM 24 HOUR IMPINGEMENT ON BIOMASS : DECEMBER 1 - 2 1972 ON INDIVIDUAL : DECEMBER *1 - 2 1972 SEASON OF MAXIMUM IMPINGEMENT ON BIOMASS : WINTER ON INDIVIDUAL : WINTER SEASON OF MINIMUM IMPINGEMENT ON OIOMASS : SUMMER ON INDIVIDUAL : FALL TIME OF ARRI V AL( DAT E OF F IRST IMPINGEMENT) : II-297
l l [ DAT
SUMMARY
l Table 16 - Migratory, pulsed impingement, No. 1 DOLYDACTYLUS OCTONEMUS --- POLY'NEMIDAE --- PERC1 FORMES NMFS IDENTIFIER : 166010503 ,, SPECIES CODE : 90 PE R I OD TOTALS PEPIOD INDIVI DJ AL S 810 MASS (NUMBEP) (KILOS. FRESH) 1972/73 UNIT 2 765363. 3306.413 1973 UNIT 2 156. 1.041 1973 UNIT 1 , 11. 0.090. 1974 UNIT 2 0. 0 000 1974 UNIT 1 0. 0 000 TOTALS 765374 3306.503 1972/73 IMPINGEMENT DESCRIPTION DEPCENT OF ALL SPECIES COMBINED : INDIVIDUALS (NUMBER) : 95 65% BIOMASS (FRESN WEIGHT) :77 20% MEAN BIOMASS PER IN31VIDUAL : 4.32 GRAMS DATE OF MAXIMUM 24 HOL'R IMOINGEMENT ON BIOMASS : MAY 4 - 5.1973 ON INDIVIDUAL : MAY 4 - 5 1973 SEASON OF MAXIMUM imp!NGEMENT DN BIOMASS : SPRING ON INDIVIDUAL : SPRING SFASON OF MI N I MU M IMPINGEMENT ON BIOMASS : FALL ON INDIVIDUAL : FALL
- TTME OF A4c! VAL (DATE OF FIRST IMPINGEMENT) :
11-298 m v m me o- o
. D A,T A ,.
SUMMARY
Table 17 GR A S S-M AT DWELLERS AND/OR TR ACKERS NO. 2 PERIOD TOTAL S PERIOD INDIVI DU ALS BIOMASS (NUMBER) (KILOS. FRESH) 1072/73 UNIT 2 222. 0.405 1073 UNIT 2 6. 0.018 l 1973 UNIT 1 3. 0.014 1974 UNIT 2 983. 0 921 1?7A UNIT 1 137. 0 179 TOTALS 1345. 1 519 1972/73 IMPINGEMENT DE SCR IPT ION PERCENT OF ALL SPECIES COMBINED : I NC I V I DU ALS ( NU MBER ) : 0 03X B IOM ASS ( FRES H WEIGHT) : 0 01% MEAN BICMASS PER IND IV I DU AL : 1 82 GRAMS DATE OF MAXIMUM 24 HDUR IMPINGEMENT ON BIOMASS : APRIL 27-28 1973 ON INDIVIDUAL : JUNE 29-30.1973 SEASON OF MAXIMUM IMPINGEMENT ON BIOMASS : SPRING ON INDIVIDUAL : SUMMER SEASON OF MI NI MUN IMPINGEMENT ON BIOMASS : FALL ON IN D IV I DU AL : FALL TIME OF ARR IV AL( DAT E OF F IRST IMPINGEMENT) l II-299 L.
DATA SUMM ARY ' Table 18 BOTTOM DWELLERS. MUD OR SAND NO. 3 PERIOD TOTALS PE4!OD INDI VI DUAL S j.j BIOMASS ( NU M BE R ) (KILOS. FRESH) 1972/73 UNI T 2 7264 88.609 1973 UNIT 2 1830. 8 462 1973 UNIT 1 341. 1.643 1974 UNIT 2 5720 42 651 l 1974 UNIT 1 2697. 14.512 l. TOTALS 16022. 147.415 i 4 1 1972/73 IMPINGEMENT DESCRIPTION PEACFNT OF ALL SPECIES COMBINED : I NDI VID UALS( NUMBER ) : 0.91% BI OM ASS ( FRES H WE IGHT ) : 2 07X MEAN BICMASS PER INDIVIDUAL : 12 20 GRAMS DATE OF MAXIMUM 24 HOUR IMPINGEMENT . ON BIOMASS : MAY . 25-26.1973 ON IN DIV I DUAL : JULY 6- 7.1973 SEASON OF MAXIMUM IMPINGEMENT ON BIOMASS : SPRING ON INDIVIDUAL : SUMMER SEASON OF MINIMUM IMPINGEMENT ON BIOMASS : FALL ON I NDIV I DU AL : F ALL TIME OF ARRIV AL( OAT E OF FIRST IMPINGEMENT) : II-300 w .
I DATA
SUMMARY
, Table 19 LARGE, FAST SWIMM ING = TOP A ND MID-WATER NO. 4 i
PERIOD TOT ALS PER IO D INDIVIDUALS BIOMASS r ( NUM BE R ) ( K ILOS,FRE SH) 1972/73 UNIT 2 683. 17.815 1973 UNIT 2 146. O.482 1973 UNIT 1 46. 0.060 1974 UNIT 2 62. 3.935 1974 UNIT 1 12. 3 139 TOTALS 803. 24.949 e 1972/73 IM P IN GEME NT DESCRIPTION PERCENT OF ALL SPECIES COMBINED : I NDI VID UALS( NUMBE R ) : 0 09% BIOMASS (FRESH WE IGHT ) : 0.42X MEAN BIOMASS PER I NDI V I DU AL : 26.08 GRAMS DATE OF MAXIMUN 24 HOUR IMPINGEMENT (' - ON DIONASS : DECEMBER 1 - 2,1972 ON IN DIV I DUAL : JUNE 29-30,1973 SEASON OF MAXIMUM IMPINGEMENT ON B IOM ASS : WINTER ON INDIVIDUAL : SUMMER SEASON OF MINIMUM IMPINGEMENT ON BIOMASS : SUMMER i ON I NDIV I DU AL : SPRING TIME OF ARRIV AL(DATE OF FIRST IMPINGEMENT) : . 9 I l II -301 t
l l
~ * '
' DATA SU MM ARY '
Table 20 LARGE, FAST SWIMMING - BOTT OM NO. 5 PERIOD TOTALS PERIOD INDIVI DU AL S BIOMASS (NUMBER) ( KI L CS ,F RES H) 1072/73 UNIT 2 276. 13.747 1973 UNIT 2 8. O.180 1973 UNIT 1 2. e0.021 197A UNIT 2 98. 2.121 197A UNIT 1 22. O.406 4 T O T AL S l 398. 16.295 1 l l 1972/73 I MPINGEMENT DESCRI PTION l PERCENT OF ALL SPECIES COMBINED : I N O !V IDU ALS ( NU M B ER ) : 0.03% B I O M A S S( FRE S H WEIGHT) : 0.32% WEAN BIOM ASS PER IN D I V I DUAL : 49.81 GRAMS D ATE OF M AXIMUM 24 HOUR IMPINGEMENT ON BIOM ASS : AU GU ST 20-21,1972 ON I NDI VI DU AL APRIL 20-21.1973 SEASON OF WAXIMUM IMPINGEMENT ON BIOMASS : SPRING ON IN D IV I DUAL : SPRING SEASON OF MINIMUM IMPINGEMENT ON BIOMASS : SUMMER ON INDIVIDUAL : SUMMER TIME OF ARRIVAL (DATE OF FIRST IMP!NGEMENT) : II-302 l wv~e-
DATA
SUMMARY
Table 21 SLOW. W E A K-SW IMM IN G NO. 6 PERIOD TOTALS PER IOD I ND I VI DUAL S BIOMASS ( NU M BE R I (KILOS. FRESH) 1972/73 UNIT 2 7950. 631 385 1973 U N IT 2 342. 31.306 1973 UNIT 1 36. 3.166 1974 UNIT 2 1884 149.025 1974 UNIT 1 757. 66 342 TOTALS 10627. 849.917 l 1 l l l 1972/73 IMPINGEMENT DESCRIPT ION PERCENT OF ALL SPECIES COMBINED : I NDI VIDUALS( NUMBER ) : 0 99% ; B I CM ASS ( FRES H WEIGHT) 114.74% MEAN BIOMASS PER I NDI V I DU AL : 79.42 GRAMS DATE OF MAXIMUM 24 HOUR IMPINGEMENT ON BIOMASS : MARCH 2- 3 .1973 ON IN DIV I DU AL : MARCH 2- 3 .1973 SEASON OF MAXIMUM IMPINGEMENT ON BIOMASS : WINTER l ON INDIVIDUAL : WINTER SEASON OF MINIMUM IMPINGEMENT ON BIOMASS : FALL ON I NDI V I DU AL : FALL TIME OF ARR IV AL( O AT E OF FIRST IMPINGEMENT) : i II-303
l
' D AT A SUM M AR'Y Table 22 SCHOOLING NO. 7 i
PERI OD TOT ALS PERIOD IN DIV IDUAL S BIOMASS (NUMBER) (KILOS FRESH) l 1972/73 UNIT 2 14915. 136.212 1973 UNIT 2 497. 1.197 1973 UNIT 1 45. O.423 1974 UNIT 2 2758. 14.248 1974 UNIT 1 423. 1.876 5 TOTALS 18141. 152.759 ' i 1972/73 I MP I NGE ME NT DESC RI PT I ON PE RCE NT OF ALL SPECIES COMBINED : IND I V ID UAL S( NUMBER ) : 1.864 BIOMASS (FRESH WE IG HT ) : 3 13% f MEAN BICAAi* PER INDIVIDUAL : 9.13 GRAMS ' DATE OF MAXIMUM 24 HOUR I MPI NG EME NT ON BIOM ASS : FEBRUARY 16-17,1973 ON INDIV I DU AL : F EB RU AR Y 16-17,1973 SEASON DF MAXINUM IMPINGEMENT ' ON BIOMASS : WINTER ON INDIVIDUAL : WINTER SEASON OF M IN IMUM . IMPINGEMENT ON BIOMASS : FALL . ON INDIVIDUAL : SPRING 1 TI ME OF ARRI V AL(DATE OF FIRST IMPINGEMENT) : l l II-304
l l D AT A
SUMMARY
Table 23 i SESSILE NO. 8 PER IOD TOT ALS
==
PERIOD INDI VI DU ALS BIOMASS ( NUM BE R ) (KILOS,FRESN) 1072/73 UNIT 2 30. 29.299 1973 UNIT 2 2. 31.741 1973 UNIT 1 O. 42.962 1974 UNIT 2 10. 1.352 1974 UNIT 1 O. O.107 , _ _ _ _ _ _ _ _ _ _ _ . __ 1 TOTALS 40. 73.720 1972/73 IMPINGEMENT DES CR I PT ION PERCENT OF ALL SPECIES COMBINED : l 1 I ND I VID UALS( NUMBER ) : 0.00X ' BI OMASS ( FRES H WE IGHT ) : 0 68% ME AN BI CM ASS PER IND I V I DU AL : 976.63 GRAMS D A TE OF MAXIMUM 24 NOUR IMPINGEMENT ON BIOMASS : AUGUST 17-18,1973 ON IN D IV I DU AL : OCTOBER 6- 7,1972 SEASON OF MAXIMUM IMPINGEMENT ON BIOMASS : SUMMER ON INDIVIDUAL : FALL SEASON OF MINIMUM IMPINGEMENT ON BIOMASS : SPRING 1 ON INDIVIDUAL : WINTER TIME OF ARRI V A'.( O AT E OF F IRST IMPINGEMENT) : II-305
FISH CAUGHT DURING ENTRAPMENT STUDY SPECIES NUMBER INDIVIDUALS SPECIES CODE Grass-mat dwellers and/or trackers No. II
-Hippocampus erectus 1 40 Syngnathus scovelli 4 45 Bottom dwellers, mud or sand No. III synodus foetens 3 21 Opsanus beta 6 24 Urophycia floridanus 1 28 Paractinus fasciatus 2 171 Large, fast-swiming-top and mid-water No. IV Chaetodipterus faber 3 81 Large, fast-swiming - botton No. V Dasyatis sabina 5 3 Arius fetis 1 22 Porichthys piectrodon 4 25 Centropristia melana 36 46 Diptectrum fomosum 1 47 Calamus arctifrons 56 69 Cynoscion nebulosus 1 75 Menticirrhus americanus 1 78 Micropogon undulatus 19 79 Slow, weak-swimming No. VI ogcocephatus radiatus 9 26 Monacanthus hispidus 10 124 Lactophrys quadricornia 8 125 Sphoeroides nephelus 4 128 Chitomycterus schoepfi 3 129 Schooling No. VII Eucinostomus gula 2 65 Raemulon plunieri 8 67 Orthopriatis chrysoptera 16 68 Diplodus hotbrooki 2 70 Lagadon rhanbcides 120 73 II-306
1 1 ~ ' ' ' l ACKNOWLEDGEMdNT'S The research reported herein was performed under a series of continuing contracts with the Florida Power Corporation during the period extending from 2 May 1972 through 31 December 1974. The Principal Investigator, Dr. Samuel C. Snedaker, graciously acknowledges the unrestricted support of the Corporation in behalf of the overall research objectives. Also recognized are the numerous individuals who willingly contributed in many ways to the field, laboratory and office duties. Each is listed below without regard to position or service: Clayton Adams Ellen Haitmanek Buckley Parnell Carol Alfred Brad Hartman Gregory Patrick Walter Auffenberg Marie Hartman James Peck Candace Bamford Roger Hartzog Douglas Pool ' Leslie Banks Gary Hellennan Kenneth Reid Linda Bassett Joan Hildal Joseph Rosenbaum Charles Bilgere Mark Homer Bill Seaman Ronald Browder Jun-Shen Huang William Sandilos Steve Brown Dah-Bin Kao Patricia Sawyer Walter Bunnell Deborah Karably Richard Schaeffer Lea Burns Christopher Leadon Richard Sclove I Lawrence Burns Pegene Liston Barry Sedlik David Cantlin Raymond Littell Judith Simons Albert Christie Richard Long Nancy Sinks t John Clark Joyce Lottinville Jorge Southworth Linda Clemens Bob Marsh Richard Stanford Betsy Cobb Mike Marshall Ernest Striker Stanley Coe Judy Martin Bruce Sutton Daniel Cottrell Virgil Martin Mariette Taylor Carlos Crespo Victor Mascitelli Carol Underwood l David Dorman Mike Mastandrea Melissa van Tine James Duggins Karen McAllister Robin van Tine Michael Elliot Sharon McRae Michael Veno Gary Evink James Mims Patricia Veno Barry Faske Melinda Moody Glenn Walker John Frank Gregory Morris Gary Wilburn Dennis Gilmore Patrick Morrow Philip Worley Barbara Gorrell Michael Oesterling Robert Yockey Barbara Green William Ostrand II-307
.- ,- . -.. s .
FINAL REPORT to the FLORIDA POWER CORPORATION submitted by Dr. Samuel C. Snedaker, Principal Investigator Peport u SEDIMENT COMPOSITION AND DISTRIBUTION AT CRYSTAL RIVER P0WER PLANT: EROSION VS. DEPOSITION Daniel J. Cottrell I i 1 l l , i Resource Management Systems Program ! Institute of Food and Agricultural Sciences l University of Florida I Gainesville, Florida October, 1974 c II-309
BENTHIC SUBSTRATE SURVEY Introduction Objectives of the physical substrate study at Crystal River include: (1) composition and distribution of the substrate with respect to sand, silt, clay, organic matter and carbonate; (2) comparison of sediment composition with the distri-bution and abundance of macrophytes; (3) delineation of areas which are eroding or accreting; (4) assessment of any anomalous substrate features with regard to confinement by dike structures or alteration l of circulation patterns; l (5) comparison of depositional enviro iments of the l discharge and intake areas. In addition to the substrate survey a sediment deposition study l was conducted from May 20, 1974 to September 3, 1974. Data from this ' survey are intended for use in comparing sediment burden and sedi-mentation rates between the discharge and intake areas. Lab proces-l sing is not yet completed, but included in this report are preliminary j data which will be tentatively used to delineate sedimentation patterns. Field Methods SampiIng of the 5ay sediments began in December,1973 and was conducted simultaneously with the winter quarter macrophyte sampling. Three hundred forty-one samples of the upper 5 cm of bottom sediment were obtained with a small hand-held dredge. At each sample point the depth to bedrock was determined by probing with a steel rod from a peat sampler. Water depth, time and classification by visual exam-ination were noted at each statica. Com discernible objects (e.g., dike markers) passwerebearings taken inon large, order that sample locations, calculated by triangulation, could be entered on a basemap. Each sample transect in the discharge estuary was made by following due north or due south headings so that sample points would be evenly distributed (see figures 1-3). East-west transects were made in the control area (see figure 4). Field work for the sediment deposition study was initiated on May 20, 1974. Sediment traps were constructed from 4" PVC pipe. Plexiglass discs were cemented to the bottom of the pipe and removable
" baffles" (1" PVC) were installed within the traps to increase settling II-310
efficiency. The traps were a modified design of the type used by Carter et at. (1973) and Braidech, Gehring and Klevens (1972). Ea u sediment trap was coated with marine anti-fouling paint and place? into a concrete block which anchored both the trap and a marker buoy.
..The survey began with 30 traps -- 9 in basin 1, F in basin 2, and 15 in basin 6 (see figure 5). However, due to tne gradual dis-appearance of traps in basin 2, operations were terminated there on July 25, 1974. Each trap was emptied into plastic bags, cleaned and replaced every three weeks for a period of four months. Samples were returned to the laboratory, dried and weighed.
Laboratory Methods Surface sediment samples were rinsed and then dried in large baking dishes at 700C. Each sample was then weighed, disaggregated with a wooden mortar, split to approximately 100 grams and passed through a 2 m sieve. The portion retained on the sieve was weighed and a weight percentage was calculated for particles greater than 2 m. One hundred grams of the remaining sediment (less than 2 mm) was then weighed, soaked in a 5% Calgon solution overnight, mixed and transferred to a soil cylinder for hydrometer analysis (Bouy-oucos,1962). Sand from the hydrometer analysis was sieved at half-phi intervals (Folk,1968) and grain size parameters (Folk and Ward, 1957) were calculated for each sample. Carbonate content was obtained by an acid-insoluble residue method (Maxwell, 1968). Samples were split to 10 grams, passed through a 250 micron sieve (to decrease the masking effect of shell material) and dried at 700C for 6-10 hours. Samples were then weighed to 5 grams, placed in a suitable reaction flask and 50 ml of 3N hcl were added. In general. all carbonates reacted within 1-2 hours. The samples were filtered with a Buchner funnel apparatus through pre-viously weighed filter paper and placed in a drying oven for 1-3 hours. The residue was weighed and weight loss was calculated to obtain carbonate percent by weight. Percent organic matter in the samples was determined by ashing a 1 gram sample in a tared cruicible. The samples were ashed at 5500C for about I hour. Upon cooling, the crucibles were weighed and the weight loss was converted to weight percent of organic matter in the sediment. Density calculations were intended to be determined but the sampling device was not sensitive enough to give any reasonable measure of-density. Instead, an index of substrate firmness was calculated by making a ratio of sample dry weight to the average weights of samples from the firmest substrates. The parameter is referred to as " packing", or, " relative density". II-311 7.
Results Maps, tables and figures are presented to show distributions of substrate features in the discharge and intake estuaries. The first section is concerned with physical substrate distributions. The second section presents results of the sedimentation study. Maps were compiled by sorting parameters into intervals based on frequency percentages. Map units were drawn by using both laboratory and field data. Each map will be briefly summarized. Sand-silt-clay -- Sand-silt-clay ratios for the discharge basins ranged from 66/24.8/9.2 to 96.3/2.1/1.3. Figures 7-14 are maps of sand-silt-clay distributions in basins 1 and
- 2. The substrate type in these basins is classified by Shepard (1952) as sand (80% to 100% sand). Two excep-tions to this classification occur in basin 1. These samples were taken from near the salt marsh and contained high percentages of silt, clay and organic matter. By Shepard's classification these samples are silty sands and reflect salt marsh substrate textures rather than bay sediment textures.
The highest sand percentages occur in, and near, littoral zones and the seaward side of oyster bars where tidal fluctuations and wave attack tend to winnow finer particles into deeper water. Areas within the basins with silt percentages in excess of 10% constitute ano-malous substrate features. Clay percentages seem to be lowest in littoral zones, suggesting a winnowing process. X-ray diffraction of selected samples with high percentages of clay-size particles showed no clay minerals present. Apparently most of the clay-size fraction is composed of fine, colloidal organic matter perhaps derived from Spar dna marsh peat. The highest percentages of clay were found in areas where fine organic material from the adjacent salt marsh were collecting on the substrate. Discharge basins 3, 4 and 5 are also composed of sand. sediments with some exception in basin 3. Silty sandy was found to occur here in two locations near the central and deepest portion of basin 3 (see figures 10 and 15). These areas in basin 3 are topographic depressions and act as catch basins for fine material. Sand-silt-clay percentages in the sediments of the intake basins ranged from 71.2/18.6/9.5 to 97.2/1.7/1.1. Table 1 summarizes the means for sand, silt and clay per-centages. II-312
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TABLE 1. Mean 'percenta'ges of sand, s'ilt and ciay for all basins. BASIN MEAN % SAND STD. CEV. VARIANCE LOW HIGH N_ I 1 102 88.63 4.15 17.20 66.00 96.30 2 61 89.43 3.60 12.95 78.70 96.60 3 23 86.33 6.23 38.77 69.00 94.30 4 11 86.07 4.78 22.86 78.70 93.60 5 11 88.59 6.53 42.67 73.50 96.40 6 63 88.48 3.82 14.61 74.30 96.80 7 54 84.81 4.35 18.94 71.90 93.50 8 15 89.19 4.78 '22.87 82.00 97.20 BASIN N MEAN % SILT STD. DEV. VARIANCE LOW HIGH 1 102 7.74 3.08 9.51 2.10 24.80 2 61 6.86 2.55 6.48 2.30 15.10 3 23 9.67 4.96 24.57 2.80 24.00 4 11 9.85 3.22 10.35 4.60 14.00 5 11 7.60 4.58 20.95 1.20 18.20 6 63 8.05 2.93 8.58 1.70 18.80 7 54 10.-29 3.35 11.20 3.40 18.60 i 8 15 6.99 3.52 12.42 1.70 12.80 l 1 BASIN N MEAN % CLAY STD. DEV. VARIANCE LOW HIGH 1 102 3.64 1.45 2.11 1.30 9.20 !
-2 61 3.71 1.38 1.90 1.10 6.90 l
3 23 4.00 1.55 2.45 1.90 7.80 4 11 4.30 1.86 3.45 1.80 7.50 5 11 3.81 2.02 4.10 1.20 8.30 6 63 3.47 1.46 2.12 1.20 10.40 7 54 4.89 1.49 2.22 1.90 9.50 8 15 3.82 1.50 2.25 1.10 6.40 J 11-313
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The distribution of these parameters (see figures 16-21) show finer material spreading into deeper and seaward areas. The intake basins seem to have much more exchange with each other and are not nearly as confined as basins 1 and 3 in the discharge region. Localized depressions do, however, tend to catch finer sediment.
' Organic Matter -- Possible sources of organic matter in basin sediments include salt marsh detritus, algae and seagrass dieback, plankton, fecal material and animal remains. Discharge basins average approximately 4.0% organic matter or approxi-mately 880 g/m2 (assuming S.G. = 2.23, from Carter et al. ,
1973). Means for organic matter content for the discharge basins are presented in Table 2. Maps of organic matter distributions for basins 1 through 5 (see figures 22-24) show the dominant percentage class to be 3% to 5%. Littoral zones typically contain 0-2% organic matter possibly due to removal by tidal currents, detrital feeders, oxidation and bioturbation. Isolated areas in each basin contain 6-10% organic matter. In basin 3 the central depress on is a collecting basin for organic material as are similar areas in basin 2. Basin 1, however, has a very small area of organic matter in excess of 6%. The two locations in basin I with high values occur adjacent to the salt marsh and are protected from wave attack by small oyster reefs. The distribution of organic matter in these basins is difficult to assess without more information concerning current circulation patterns, but it may suffice to say that removal of organics from the sediment may occur by resuspension and subsequent removal to low energy environments or by detritus feeders. The intake area (basins 6, 7 at 8) is rather homo-geneous in organic matter distribution. Low percentages occur in small, localized areas and one large region in basin 7 contains from 6-10% organic matter. This area appears to be a small catch basin for particulate organic matter (seefigures25and26). Table 3 compares the average percentages of organic matter in the intake basins. Carbonate Content -- Sources for CACO 3 include gastropod and pelecy-pod shell material, foramnifera, bedrock erosion or in situ destruction of bedrock by decay of organic matter, and direct precipitation from seawater. The percentages of carbonate material less than 0.25 mm (see figures 27-29) in the discharge sediments vary from 3.7 to 90.0. Sedi-ments containing less than 10% are distributed in near-shore zones. Higher carbonate percentages were obtained in areas where oyster bars and bedrock outcrops occur. 11-314
TABLE 2. Organic matter by weight percent for discharge basins. BASIN N MEAN STD. DEVIATION VARIANCE LOW HIGH 1 92 4.0 2.73 7.45 0.8 19.6 2 61 3.8 1.44 2.06 1.0 7.7 3 23 4.6 1.79 3.20 1.9 9.2 4 11 5.5 1.68 2.80 3.1 8.8 5 11 4.5 1.55 2.41 2.1 8.3 TABLE 3. Organic matter by weight percent for intake basins. BASIN ,f[ MEAN STD. DEVIATION VARIANCE LOW HIGH 6 63 4.3 1.42 2.01 1.3 8.9 7 55 5.1 1.74 3.02 1.5 10.0 8 15 5.0 2.42 5.84 2.1 10.1 TABLE 4. Percent carbonate by weight for all basins. BASIN N, MEAN STD. DEVIATION VARIANCE LOW HIGH 1 92 10.87 5.45 29.75 a3.68 40.96 2 61 17.20 11.88 141.17 4.23 90.00 3 23 22.54 9.53 90.78 8.15 49.33 4 11 26.11 8.70 75.67 13.00 41.98 5 11 26.32 7.93 62.23 13 41 42.11 , 6 63 14.74 7.89 62.87 3.47 36.31 7 55 27.29 12.39 153.44 4.88 90.00 8 13 31.71 14.97 224.13 14.63 67.50 l II-315
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Basin 3 contains a somewhat anomalous area of carbonate-in the central portion. The Gulf area also shows high percentages of carbonate and it was noted that shell material was abundant in most of the Gulf sediments. Intake basins show the same pattern of distribution as the discharge basins (see figures 30 and 31). Low percentages occur.in the littoral zone and higher percentages are found in shelly areas and regions of bedrock outcrops. A rela-tively large area of carbonate (greater than 40%) lies in the vicinity of the tip of the southernmost intake dike. This region contains a greater amc,unt of shell material and coarse particles than any other area within the study basins. Comparisons of means for each basin are listed in Table 4. Sediment Thickness (depth to bedrock) -- The thickness of unconsoli-
' dated sediment deposits was determined at each sample located in order to assess the volume of sediment overlying the local bedrock, to compare the quantity of sediment with water depths and differentiate between areas within bays which may be in the process of shoaling or scouring.
Figures 32-34 depict the distribution sediment accumulation in the discharge basins. A map of water depth in these basins from Carder and Klauswitz (1974) is provided for comparative purposes (see figures 15 and 15A). Discharge basins display a large degree of variation in sediment thickness. Some of the variation is due to the '
'~ ' local relief in the Karst topography of the underlying limestone surface. In some areas of shallow water, either bedrock-knolls outcrop or shoals have formed with thicknesses greater than 2 m. 'Other areas characteristically have thick sediments but are located in deeper waters and probably reflect normal filling. In basins 3, 4 and 5 the overburden is shallow even in water with depths of 2 m. Two areas in j basin 3 have sediment thicknesses greater than 2 m. The .
bathymetry map shows that these areas occur in or adjacent to shallow water zones and are perhaps shoaled. j The intake basins contain rather thin deposits in con- ! trast to discharge basin ~1. Most areas of thick sediment are small patches which~do not express any irregular topo-graphic feature within the basin (see figures 35 and 36). Sediment thicknesses for all basins are listed in Table 5. j ' Mean grain size -- Grain size distribution within dische.'ge basins indicates that most of the substrate is composed of fint, poorly sorted sand (0.250 mm to 0.125 m). Mean grain size
'is reported in phi units (d = -log,mm). A brief summary
' and review of grain size parameters and t!.lir significance may be found in Appendix C2. Summaries o rain eiz. l- II-316 l
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TABLE 5. 'Mean's for s'ediment thickness ~ for all basins ~ (iri~ cm.)'. BASIN N_ MEAN STD DEVIATION VARIANCE LOW HIGH l 1 102 89.22 73.64 5423.47 0.00 349 2 62 78.77 88.13 7756.85 0.00 366 3 23 52.83 67.15 4509.42 1 236 4 11 56.55 66.26 4390.67 1 192 5 11 30.36 43.72 1911.85 3 125 6 63 52.84 60.79 3695.49 4 240 7 54 28.22 46.80 2189.84 2 230 8 15 43.33 42.86 1836.81 5 152 TABLE 6. Mean values for mean grain size for all basins-(in d units). BASIN MEAN N STD. DEVIATION VARIANCE LOW HIGH 1 2587 100 .34 .12 1.26 3.64 2 2.60 67 .39 .15 1.25 3.2 3 2.73 17 .60 .36 1.61 4.0 4 2.74 11 .58 .34 1.40 3.35 5 2.23 11 .57 .32 1.40 3.23 6 2.69 63 .46 .21 1.16 3.74 7 2.56 54 .58 .34 .55 3.44 8 1.78 15. 1.01 1.02 .08 3.19 II-317
parameters for each basin are presented in Table 6. The calculated values for mean grain size have been classed at half phi intervals in order to illustrate the distributions within the study basins. Note, however, that the mean standard deviation of the estimated mean grain size is t 1.35d. The maps of mean grain size (see figures 37-39) are-intended to serve in inferring where areas of erosional or depositional processes may prevail. Basin'2 and basin 1 both contain areas where mean grain sizes of 3.0 phi to 3.5 phi delineate possible sites of deposition. Coarser particles (2.0-2.5 d) seem to , center around areas where the bedrock outcrops. These may be sites of active erosion. Basin 3 displays similar characteristics of busins 1 and 2 in that the dominant grain size lies between 2.5 and 3.0 d. Of particular interest is the area of the central basin. Here again an anomalous l feature of substrate texture exists. ! The intake basins, in terms of mean grain size, express comparable features to those of the discharge basins (see figures 40 and 41). The dominant size fraction is 2.5-3.0 d. Areas which tend to accumulate fines are confined to localities in close proximity to the spoil bank. Coarse material is generally found associated with bedrock areas and oyster bars. Sedimentation -- Calculations of sediment burden (gm/m 3/ day) and
" sedimentation" rates (gm/m2/ day) for each sediment trap are shown in Table 7. Sediment trap locations are illus-trated in Figure 5. Data collected from the four-month survey are listed in Appendix C1. The two calculations were made from weights of captured sediment since there is some question as to what parameter is measured with water column sediment samplers because lateral, surface transport is precluded and resuspension is unknown. Mean sediment burden and " sedimentation" rates are listed by sampling period and totals for the entire study in Table 8.
Maps depicting gross average sediment burden and
" sedimentation" rates for basins 1 and 6 (see figures 42-
- 45) indicate that the tidal creeks and salt marsh are supplying most of the suspended sediment to these bays.
In basin 1, high rates of " sedimentation" occur at the mouth of a small tidal creek yet the bulk of the material seems to settle out before reaching most parts of the bay. Sediment seems to disperse from the marsh and toward the canal. Some sediment is supplied from Little Rocky Creek and carried out toward Grass Island and into basin 2. l II-318 l
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I l 2 TABLE 7.- Means of g/m3 / day and g/m / day for each sediment trap. AREA trap g/m 3/ day std. error g/m2/ day std. error Discharge 4 10.10 --- 6.21 --- Discharge 7 12.71 .13 8.56 .10 Discharge 8 1.46 --- .57 --- Discharge 9 11.54 2.52 5.87 1.28 Discharge 10 --- --- --- --- Discharge 11 67.79 3.80 53.93 3.02 Discharge 12 11.93 .64 6.76 .36 Discharge 13 5.12 .48 3.54 .33 Discharge 14 8.22 1.35 5.68 .94 Discharge 15 12.19 1.29 5.87 .62 Intake 1 15.82 1.78 8.49 .96 Intake 2 15.47 2.75 3.82 .79 Intake 3 --- --- --- --- Intake 4 13.16 2.08 2.52 .63 Intake 5 15.18 1.44 2.82 .27 Intake 6 11.27 1.34 3.81 .45 Intake 7 12.32 2.43 4.78 .87 Intake 8 12.43 .86 6.10 .42 Intake 9 8.58 .20. 2.84 .19 Intake 10 6.62 .44 3.25 .21 Intake 11 4.80 1.10 .89 .21 Intake 12 7.88 .56 3.65 .26 11-319
TABLE 7. Continued ABE8. ferna n/m3/ day std. error _ g/m2/ day std. error Intake 13 2.45 .22 1.26 .11 Intake 14 4.64 .80 3.69 .64 Intake 15 4.87 .84 4.37 .75 Note: Missing values occur where the mean was calculated with only one value. A missing value in all columns indicates that the trap r:ever yielded data. N II-320
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d 3 TABLE 8: Means fon sediment burden (g/m / day) and sedimentation rate (g/m / day). Area sampling period g/ganm / day std. dev. low high Discharge 5/20 - 6/10 13.58 26.82 1.43 84.53 Intake 5/20 - 6/10 5.67 6.33 1.03 21.40 Discharge 6/10 - 7/1 19.16 26.55 3.30 58.86 Intake 6/10 - 7/1 6.27 3.29 1.69 13.08 Discharge 7/1 - 7/25 25.09 32.91 3.07 74.79 Intake 7/1 - 7/25 10.79 5.56 2.33 21.31 Discharge 7/25 - 8/15 23.33 21.43 10.10 61.05 Intake 7/25 - 8/15 14.31 6.86 6.57 25.16 Discharge 8/15 - 9/3 19.43 19.77 9.72 59.73 Intake 8/15 - 9/3 13.76 7.78 6.41 31.24 mean Area sampling period g/m / day std. dev. low hiSL h. Discharge 5/20 - 6/10 10.31 21.46 .57 67.24 Intake 5/20 - 6/10 .2.35 3.27 .20 11.48 Discharge 6/10 - 7/1 14.33 21.68 2.22 46.83 Intake 6/10 - 7/1 2.41 .92 .87 3.69 Discharge 7/1 - 7/25 19.34 26.92 1,89 59.49 Intake 7/1 - 7/25 4.43 2.35 1.20 10.12 Discharge 7/25 - 8/15 15.88 18.32 6.21 48.57 Intake 7/25 - 8/15 5.66 3.78 1.43 14.26 Discharge 8/15 - 9/3 13.46 16.73 5.50 47.52 Intake 8/15 - 9/3 5.93 2.63 2.65 10.95 l II-321
l l Dispersal patterns in the intake area are somewhat analagous to discharge patterns in that the tidal creek and salt marsh provide the source of sediment. Burden decreases with distance from shore yet the rates of deposition along the dike just west of the salt marsh show a slight increase. Sediment from the traps is in the process of being analyzed for organic matter and carbonate content. Selected samples were prepared for microscope viewing. Organic detritus was virtually unidentifiable except for l t pollen grains. The remaining fine, unrecognizable organic material had some resemblance to spartina peat. Inorganic grains included sponge spicules, foramniferas quartz grains, fine particles of limestone and fish ) scales. Some traps contained Cerithid gastropods which , were quite possibly inhabiting the traps at the time of collection. An apparent increase in the sediment burden ; occurred from July 25 to September 3. During this period i several storms battered the coast as evidenced by flotsam left at rather high elevations above the high tide swash ! i line. The increase was much more apparent in intake i traps. Evidently basin 1 is more protected by virtue of ' the discharge spoil banks. Organic detritus was observed to be more oxidized and inorganic fractions diminished with increasing distance from the salt marsh. Discussion The purpose of this discussion is to assess what combination of substrate characteristics constitute criteria for delineation of de-positional or erosional areas in the study basins. An evaluation of whether or not these processes are occurring naturally or as a result of the power generation facility operations will follow. Textural data such as sand-silt-clay ratios and grain size para-meters are indicators of sediment source and environment of deposition ! (Pettijohn,1957;~ Folk and Ward,1957; Folk,1968; Friedman,1961). ! The sandy nature of the substrate is perhaps influenced by the fact ' that the principal sources of sediment are the sandy Pleistocene formations (Pamlico and Silver Bluff). The bulk of sediment in these bays are perhaps remnants of a large sand body (such as the Pamlico) which was swept eastward from the Gulf during the last sea level ! rise (Griffin,1971). Since that time the environment of deposition i has been changed by natural accumulation of upland source material ! supplied by local rivers and streams to the bays. The area is classified as a low energy coast (Price, 1953) and consequently removal of fine sediment is minimized. Sources of fine sediment might include quartz silt and clay derived from winnowing and upland erosion of the source sands, organic floccules from salt marsh peat, and ) cominuted bedrock and shell fragments, t i r 11-322
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The highest percentages of silt (in excess of 10%) in basin 1 occur in shoaled regions of the bay where water depths are shallow, mean grain size is greater than 3.0 d, and sediment thickness ranges from 40 to 306 cm. These factors combine to indicate a depositional area where sediments are accumulating. This region lies in the central portion of basin 1 and is perhaps the product of slack cur-rents. Erosion in basin 1 is strictly limited to nearshore zones, tidal creeks and bedrock areas. Rock bottoms are characteristic of non-depositional environments and bottom scour. The littoral zone in basin 1 is principally salt marsh with small tidal creeks emptying into the basin. Clumps of peat were observed to be eroding from the marsh all along its shores. The nature of the substrate in this zone is one of fine, moderately sorted sand. Wave attack and tidal cur-rents, although minimal, still cause resuspension and subsequent removal of fine material. The fine fractions seem to accumulate or relocate in the area defined by a mean grain size greater than 3.0 A (see-figure 37). Comparison of substrates between basin 1 and basin 6 (intake) indicates that the intake experiences much more bottom scour and, in general, has a coarser mean grain size than basin 1. Accretion in basin 6 is confined to isolated areas and exchange of water and sediment with contiguous basins is less restricted than in basin 1. Carbonate content is variable, depending on salinity, amount of shell fragments and bedrock deterioration. Localities of high carbonate content seem to coincide with regions where shell material is supplied by oyster comunities and where limestone outcrops on the basin floor. The carbonate analysis was designed to account for the masking effect of coarse shell and bedrock detritus yet high values of car-bonate in shell and bedrock areas indicate that fine particles of calcium carbonate are produced by chemical and physical attrition.
" Sedimentation" in basins 1 and 6 is interesting in that the magnitude of sediment dispersed in the respactive water columns over time is virtually the same (sea Table 7). Differences occur at the source. A higher density of sediment particles are present at the mouth of the tidal creek in basin 1 than in basin 6 (see figures 42 and 44). The " sedimentation" rates at the creeks translate to 0.88 cm/yr (assume S.G. = 2.23) and 0.26 cm/yr for the gross output of tidal creeks in basin 1 and basin 6, respectively. These figures - do not account for resuspension and redeposition of sediment and are obviously somewhat high. According to these figures, approximately 80% of the load from the creeks may be deposited within a 50 m radius after entering the bays (see figures 42-45). Mean rates of "sedi-mentation" for basins 1 and 6 are 0.1710.08 cm/yr and 0.06 !
0.008 cm/yr, respectively. When the figures for rates from the tidal creeks are excluded, the mean rates of 0.08 ! 0.01 cm/yr for basin 1 and 0.05 gross " sedimentation" 0.006 become cm/yr for basin 6. The major discrepancy between these two basins is the input of sediment from their tidal creeks. In basin 1 the volume of sediment 11-323
flowing into the bay- is about 5 times greater than in basin 6
-(24.74 kg/m3/yr versus 5.77 kg/m3/yr). Explanations greater discharge of sediment into basin 1 include the existence of a steeper j_
. gradient of the discharge creek and enlargement of tha creek since the construction of the discharge canal and spoil banks. Trunca-tion of the natural drainage has led to enlargement of many small 4
creeks in the vicinity in order to handle the terrestrial run-off (M. Homer, personal communication). l Sasin 2 characteristically has a large area of thin deposits overlying the limestone bedrock. This observation holds also for intake basin 7. Both basins show comparable grain size distribu-tion with mean grain sizes of 2.6 for basin 2 and 2.56 for basin 7. Silt percentages in basin 7 are high, yet exposed bedrock indicates that the basin is subjected to periods of bottom scouring. Basii) 7 ' is also well removed from shore and probably receives most of its particulate load from basin 6, the spoil dixe and peripheral oyster communities. Basin 2 on the other hand, is less silty and closer to terrestrial sources. Sediment deposits are thicker and water depths are fairly shallow in the northern portion of the basin. In contrast, basin 7 is' deeper and does not display many topographic features such as limestone' knolls or sand bars. Bottom scour occurs in both basins and sediment accumulation is confined to small . pockets where water depths exceed 2.5 m. According to bathymetry maps of basin 2, shallow water areas between Drum and Grass Islands are associated with large bedrock knolls (see figures 32 and 15A). Grain size is generally coarser in this region and finer sediment accumulates on the western slope of the limestone outcrop (see figure 37). Basin 3 is perhaps _the most interesting locality because of some rather anomalous features. - The central portion of this basin contains silt in excess of 15% surrounded by sediments containing anywhere from 19% to 15% silt (see figure 10). This suggests that fine sediment is accumulating in this basin. Other observations such as mean grain size, % clay, % organic matter and carbonate support this inference by vfrtue of their quantity and coincidental distri-bution (see figures 38, 13, 23 and 28). It is quite possible that
' the discharge canal delivers fine particles of suspended organic detritus, silt and detrital carbonate to this area, in addition to the_ possibility that dissolved organic matter may flocculate upon reaching the more saline canal water and become suspended particu-lates. Basin 3'is also surrounded by oyster bars which tend to con-i fine sediment by limiting exchange with the Gulf. Other parts of the basin do not express these features and are most likely unaffected by the depositional process due to'a favorable current regime.
Basin 4 waters-flow to and from basin 3. Grain size distribution
- indicates that some fine material has collected in the deepest parts of the basin (see figure 39). - Silt percentages .in this portion exceed l 10% but never exceed 15%. The overburden is thin (0-20 cm) and water depths range-from 70 cm to 3.5 m. The source of these finer deposits ,
l l II-324 l
.- , - =r - - := _ :_ . :2 - - . - _ . - .
is questionable. Perhaps they have been transported from basins 2 and 3, or another possibility is that they are the product of dredging operations from the Cross Florida Barge Canal. The interpretation is conditional upon more pertinent information. Basin 5 is a large basin extending into the Gulf of Mexico. Eleven samples from the Gulf area surrounding the study basins were collected for comparative information (see figure 3). Surficial de-posits are thin in most localities, carbonate ranges from 13% to 42% and organic matter averages about 5%. One locality in particular appears to have anomalous composition. This section is adjacent to the seawardmost I oyster bar and was noted to be a topographic depression. It is atypical of all other sample localities in basin 5 and is most likely an older erosional feature of solution origin (see figures 11, 24, 29, 34 and 39). l Possible Effects Deposition and erosion are the result of the interaction of the substrate with physical processes within the estuary-bay system. Generally speaking, deposition is indicative of low energy regimes where current velocities are either attenuated by a physical barrier or cancelled by forces in opposition. Erosion represents a higher energy process which resuspends substrate sediment and transports it to a new locality. These two processes are coupled and contem-poral in that depositional sites are never far removed from sites of erosion. Figure 46 is an energy circuit diagram using Odum's (1971)
" energy language". The figure depicts the fate and interaction of new sediment with basin sediments. Results from the sediment trap survey suggest that sediment tends to disperse across the bay and per-haps into the canal. Over time, sediment may gradually drift into the canal or into basin 2. Upon entering the canal, the sediment may be transported to basin 3, where its " bowl-shaped" topography and natural barriers afford an excellent " trap" for incoming sediment.
Figure 47 presents a diagrammatic hypothesis of the interaction of organic detritus and dissolved organic matter with high salinities in the presence of turbulence. The diagram also shows the interac-tions upon organic particles and dissolved organic matter within the estuary system. Particles are oxidizing, depositing and being used as a food source for detritus feeders. Resuspension and removal to the canal may result with subsequent deposition in basin 3. II-325 > I
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.. ' , .d., ; .
** ~
Bibliography and Referer.:ss Cited Bouyoucos A. 1962. Hydrometer method improved for making particle size analysis of soils. Aaron. Jour. Braidech, T., P. Gehring and C. Klevens. 1972. Project Hypo -- an intensive study of the Lake Erie Central Basin hypolimnion and related surface water phenomena, 1972. U.S. EPA Tech. Rep. TS-05-208-24. 182 pp. Carder, K. , and R. Klausewitz. 1974. Bathymetry map of Crystal River study basins. Carter,' M.R. , L. A. Burns, T.R. Cavender, K.R. Dugger, P.L. Fore, D.B. Hicks H.L. Revells and T.W. Schmidt. 1973. Ecosystems analysis of the Big Cypress Swamp and estuaries. U.S. EPA Region IV, Surveillance and Analysis Div., South Florida Ecological Study. Emery, K.O. , and R.E. Stevenson. 1971. Estuaries and lagoons -- Treatise on marine ecology and paleoecology. Ecology 1:679. Folk, R.L. 1968. Petrology of sedimentary rocks. Hemphill's, Austin, Texas. 170 pp. Folk, R.L. , and W.C. Ward. 1957. Brazos river bar: a study of significance of grain size parameters. J. Sed. Petrology 31:3-26. Friedman, G.M. 1961. Distinguishing dune, beach and river sands. J. Sed. Petrology 31:514-29. Griffin, G.M. 1971. A survey of the marine geology, sedimentation processes and related enviror. mental factors in the coastal area near the Crystal River plant of Florida Power Corporation. Report to FPC. Maxwell, J.A. 1968. Rock and mineral analysis. Interscience Pub., New York. 584 pp. Odum, H.T. 1971. Environment, power and society. John Wiley & Sons Inc., N.Y. 331 pp. Pettijohn,F.J. 1957. Sedimentary rocks. Harper & Row. New, York. 718 pp. l l Price, W.A. 1953. The low energy coast and its new shoreline types
- on the Gulf of Mexico. IV. Congres de l' Association Interna-l tionale pour l' Etude du Quarternaire (INQUA), Rome, 8 pp.
Shepard, F.P. 1954. Nomenclature based on sand-silt-clay ra+ios. J. Sed. Petrology 24:225-34. II-326 _a r .--c
/
Tanner, W.F. 1960. Florida coastal classification. Trans. Gulf Coast Assn. Geol. Soc. 10:259-66. l. II-327 L __ ___ . . _ _ . . . . _ . . .
Figure 1. Sample locations for basins 1 and 2. 2 ns !* a . .o I o ei? *" DRUM s o
.,, p.
IS-r .;. .,. . ,, ,,*" 4. 1, u h. .i. u, u. i ., ..o O 1
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- 4. .or ,,, .=
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Figure 2. , sis ,, 678
- Sample locations l sS7 c. ,
77%h 887 s,ss for basin'3. l . , , . 678 *\ f* W% 6Y4 g 673 da g, 'e r, 670 s44 0 3 es43 645
- s /
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/ QC7 II-329
Figure 3. Sample locations in basin 3. f I ej .. d .', o z is
=
a o 'n e i g , i h 'i 'i e t o lI ii E s :, .l e 3 e : ~ (J ,,,,,,
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4 Fiqure 4A. Sample locations in ,'532 'f' 7 ^ basin 6. ,e ssi iers ::
?
s30 ep [fik ;. I624 'f5!:
. :llll .
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,,,, .iec
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I Figure 4. Sample locations in basins 7 l I and 8 :$.I:- I
;;!!!?
.: j :.:
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Basin 5 *' I f
,, gh Basin 4 g) w Basin 8 l p c-N\
r
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. r.
Basin 7 ,
/
5 / i e 3 4 a
/
c 9 e ( c;ss* ame 8 $ } 8 Qe Q I i
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,. ~ % ,s ,
7 g ',Y* i . 's.
* , Basin 2
. 4' *
,'.. 3 : /
- 6
- Basin (i ,' t o'
,' 7 \ .A
, ' Basin 1 . #co (
U I. '[ 13 2 4
,o / l .
,io 9 8 I2 i e .
f4
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- Figure S. Basin and sediment trap locations.
II-333
l^
~ . . ..
Figure 6. Sand percentages in basins 1 and 2. j .
. 1
- ii:jj
^
g . l e i0<
. ;j 90- 95 % : 5*
l
.p!
~ i:.
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p. 80- 85 % 80-85 % j$;:i 0-%% l 0 o sse: I D
- 5:!$i b
Q$ 85-90 % a o O l g O 90-95 % - s![ '::5 ' : h . '!, :t%!i l q , i5se<
,.::2.:.: k O k .l ' \
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<80 : 9 'i .
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' y;g"8!!!:! ' .
. . . ^:<:S jg;;j;::::::4:;ssss j;- 85-90 % !iA5I i'E50! . ,)!S":A5!!j . ,,( :.
<80 , = : .-
l ::sg!f;,,*^ 8 0 - 85 % '^i :0
!!S8i:
j!5 f' l 85- 90 % "E!$. - j , i@i D m g^ :- wll;;;;j;;: I 85-90 % 795 % "#*iA5 sisis { _g , 3;g- .:,
- ^!AE i g 80- 85 % . .
33 . m .it - ^' .! , 5 8 - 85 '* # 0 ii ggs wsi ;;gs: - a.: sit ~ !! ji j !^!!!ii es:l:se$.sj];;h.3.,E*%ih# ^" s i^ j-" 90 - 95 '/. ij ::
's
.,i; i ,, ..
p ., - , ;ggfmga- _,! g - g - g .
- r s ;
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- -[
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.- . S-e II-334
Figure 7. Sand percentages in basin 3. 90-95 % I 1 ed' e, k w 86 %
#' #~
- <80
;,g,
) v' 9 0- 95 %
s g) 1 s, ,
.. ..] ,
y;
\ , 785-9 '.
,h j 85-90 % /
, / ( *'&
- " %. s' h g', . \
< ,' /d "V;eg j' G
. .q
- - J b
,',~ ;.
,' % 4
/ s
-g (
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. o .
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~~
[. I ( /
/ /
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11-335
. . =
F19 Ure 8. sand percenta9es in basins 4 and S.
}'g -
.) '
2 9 . g - , u, (~ ,'. j ' p
=
g a i.
' .i n 8 ..
8 '
.u : '
3 m
' 90-95%
80 % ,
"..N--
j .. f
; D
i 85- i r c
~. 85 - ,0.,
ie
' 95 Bf- 85 % 80- 85 */. ,,
l s/ :
\
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es ' a.- **
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, 90-95 % , -
, 9h' ' '
~ s '
,. p ' ' y- a=,z, f; :
es
* % ' 'I
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u- - .- ' l l %,
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- 4. ..
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u
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- kn'h , Y , ,t ,
11-335
3: Ficure 9. Silt percentaaes in basins 1 and 2. ' y g. t p <:: -
- 6:: 0-3% "
f" 1 7-10 % 6 jg.. f':ll 3-7 % ( Mi: 3-7% 1 5F {:::!. I d3-7% ' i' f ,- 3-7 % 7-10 % 10-!5 % , s::::s l (i,'!,"
- 10 - 15 % l D g
. : .' i 0 ~
l O-3% l m; :
= 0 g >sssem:g.t y iy l 3-7 % *iti:': i;;;{
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i:12
- it
- +^;$.
lg . .. i:f 42:8:($ j,i h !
% :58!!!
$5 l@>15%
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. 54.:,
8 T *$
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l Sies :.:. ' iss:5 " ::
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-ms s iii,,,iii :
j l 10-1 "45!!jgs; '%sl[![iijin RNi$i jiiN;i:l 7-10 % 3- 7 % % :gllf. ,
$$:s gjg,,g - , g, f* ! isei!- ~ ":. '
si:ij::
- .:s l;j'5: :.:.:
[:iiisi!!ff%5f+s. j,, . "]ll .g, si:t ' QlO-15% O-3% ::!$}is*: .. 55$b5 l 10 -15 % 7-10 % . . .ss sss ' - 5!5$r s :. )). ff l 7-10% . . j:j-
; . 8:55! 0" .
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10 -15 % ::iis.ss +:
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8:$:!!$ sis.:+! h 1 0 -15 -
+#
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A 3-7 % Na' isnii'st si:iai sei!!!: sJ e, & 5!!!!! . II-337 l
- 1 1
_n
. Figure-10. Silt'per:entaqes in basin 3. ,
0-3*/ 3-7 %
; , [
cd' s 1 C' '~ 0-3% /a t" WQ % i , 57 3-7% 10 -15 % / 7-10 % 1 / h [ 3-7 % 7-10 % a "\. s
, l l
. c 3 _.
, ( "% g /' ,
b i , e g -
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g
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. 0 15 II-338 l
l l
Figure 11 S1lt percentages in basins 4 and 5. i i ( ' *
<)
9 2 a
'* en e. ..
5 ' i! 5g ' 'h Ea s; , . i g .' p* e
? .u , %
n t >l5% .' ' C t 3 -7% 80-85 % o I / 7-lO% o s. l
. ,. #~ s -'
i* 7- 10 % i ./
,0-3% ..
10 - 15 % s <"
~
3- . 3- 7 %
, i,
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* 'l r* t
?.
k <' 3 ' I ,s
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4
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~
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s . 3 g ~.'.
. %,I, , - '
Q .p -{ I;
, l
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4
. kn~ %, ,
Y , , I 11-339 I ..
. -l.
Fibure 12. Clay percentages in basins 1 and 2. ll
. I A . ,
g 6-9 %g _ I 3-6% , 3-6% '! I p l h6-9% l 6-9%
%-3% #
'~ 3 ' 0 f I l-3%
O o
- y p'i :
1 3-6 % l 1 6-3% 6 IDg :. . . , j l I- 3 %
..f;.Fi:
8-ik:::: :s i g
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y , 3' g - : 1 I* i /5 i>
^
$ N-[ : i I .: .J " hNs -
.i 3-6 % 3-6 % >
; ;?,
l
'. 3; s.
isi .. iii. l-3% -. . . : l-3 % i; ' l-3 % < g _ g ., Q q -, - : . Is I 31}'* e aMi g
, - - = -
l gM5In .aru tlEniN4de!M " s0RE , s I_a!!!$$$E
=m = # -
l )Jl*aam
-neumil 2 N ! L Y!
w g( I5
$ yigg gjgg;:gj D
?j g; g;;;
g ig II-340 s
.m-w v --
Fiqure 13. Clay percentages in basin 3.
'A l-3 %
I ,, p,; 3-6% c I I y o-g% q i-3% e s' WQ 3 -6 % % g i- 3 % o ( 5 4 s j I , [ 3-6%
'
- k u
I l e #\. 3 h l , q i i , f'd 4 T 7m.g ,,7 e%
.. q. - ,
l,
. l* ,
,o
' \
l 0 og
'i
- i&
r l g ( /
// g
.o '
f h 1 ) A I { Y II-341 A
i
^
' - t,% - Figure 14. ' Clay percentages in' basin's"4'a'nd 5. '
e. 1 O o.. l' N lj q, .. u :,. y,* ci i ,.
,e' I
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!~ 3Yo
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II-342
~~ ~
Figure 15A. Bathymetry map of basins 1 and 2. y / : .:l f ' .g; ' . q 4... I r v .5 : \l\ -
\
,i 4
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- m. 0: 6&3s:si8isiSis:46SiiiiNij!!: j$l i
- !!!:: . .. *,g;;{i.jie -
s0:0:0:tasi (after Carder and Klausewitz,1974)
- II-343
l
/
s - Figure 15. Bathymetry map of basin 3. M (after Carder and Klausewitz,1974 7 7pA 1 ; ; 3 4)
~
3 9,. - s c a
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o a
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g ... y II-345 l { +:
% ( Figure 17. Sand percentages and distribution in basins 7 and 8.
. .. A f .
~
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. .; 3 L
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< so%
C .
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a
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. v!*I' $'
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! q.- .. i a x $$$ # , 3.,~ wi:qg
'r w-' 9^< 1 S?_2=?
~
4 ll$?. %;1;g. {T N'ti..-
. 'I'. <:
- m. g in 'sn.ns 1 . 3 o.f. 7.
f
,, g .ati=
- 2 & , A.5 . .mm uom n,...o
?,."31.iii'..,r<, i.d' l pu %u a,
Q y;?,;,.i.Ydll9.
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~
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- l l .iM
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f y. :. - h"g$,.y-pA3%)C,f?f' - w: ,,,g.. v'.:,,. g ,v;;e l *: 2N% a* ;g,. -\':;. : .. qd cy ,; l
,e' [N' c'
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.....,"Gk 5 - s W; ... .
' .:'*;*f g %%i5 .
a :@:s c tt$ 3 92 8 N G 5'EI [
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4 y .:g-8%% J*?. '
% $$2 E $?
m h- m' *
- 82;&%:i **
- -2 3 2; % % 8522 ..
8 :- ,. . 3e * * * *[- g : sin
, =[
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se
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d
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c :
% %%o
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!!5f5f:!! ..
II-349
4 I
- J Figure 21. Clay percentages and distribution in basins 7 and 8. j
,g;;f5 ,.,.,.
.4 &s,,,
t~ m:. a:::
*p*!fj.
na ,. - q, * % ,,- @ ,g; ,~yd , g ;,% ,,g
, ~~ % >
iS$g s
, N I
g
% cioy 4
O l-3 %
@ 3-6 % z EB s-9%
} m >9%
i T
Fiaure 22. Percent organic matter by weight in basins 1 and 2. l O-2 % g ~ 9: hj. ' ::@i.- !@i ..s :.n:.:: .
; j .:
!$!N 6F 3-5 % i
!;;p +
l
- fSi s:
{i:j @j:j:ggg;;
. .f
;qij; I -2% i!!.;.
p.; 6-10 % 6 10 % I.. :i ' @ p I:iG*i: l
<NIE# 6-10% 6-10% 0 o I O l 3-5 % E SV.
E sp ll 0
- .5::rss:ns:wt lgj g
;!:r 1 0-2 %
if O-2 % 3g,- (!g l O-2% l d!(" g oV h. 3-5 % .
.l:fljlf.
f !.!lk l l 3-5% ( iggg;! 3[:!!!ljil!l!
$ fi
! :ggjj,!!E,,
'" % 5* '*
3-5 % I O-2 % 6!5Si . !!!!.i%- 'r : l 6-10 % ggg:::*$!@iijg E ;l;fll ls: -
,l :
- y.:j:3 '
liii@js 82:s::: sis @lm:::::
/i3" tisi ":!!!! ; 9.
l 0-2% ').g f(s::j;j
!!$i), .,jj! g:g; 3-5% j p5ad!! 3-5% Eii$3.a
- ssg! .
.' # !*gi is Jjiiss O-2% .
g:;9.:+ :s2:s:
~^
gg:.:. a (
, g;3, gjj _
..s
) :.;;::n pllj;;;
n O- 2 Y. ;;;g $,.,, , , gf lllll ;""-
,;p" ~
sij:!5i59 i49i5 >: I >lO
' '. .lll .
6-10' 6E{lg. . ? l "%!:E 4! 5!Nfjjf
.h l!hl,l.!f I "*:ssisjjgii:!jjjg ,
11-351
Figure 23. Percent,ortanic mat er in basin . , g 0-2% 6-10 % e.* cd' 4:'
~
w\ 3-5 % r
- WQ N.
- 3-5% 7
-10*/
O i
/ 1 l
3-5% #
; _5 f I
rv
/ 3-5% ,
{ u O-2%
*
- I
' A s # \ ,,,, e $ s ~
i ,' /d
- s. % .e
* == , qW , a 4
; .. s. .e
\ -c%
0 o
*a/=
{ # l l i
, c .
r , I { N' % II-352 . i
e figure 24. percent Organic matter in basin 4 m
's )
e 2 9 I 5
'* e ,{ ( .'.
y i I .. e 'il ,. 2 5, '
= i,
'I
' 'i 3 ! o 8
< .u f ii I ,e P ;;
, i J O ,,
'.ov- ,. -~. i i
.f 3- 5%
f' i . # >' l
, * ; -2 % S-fo %
0% i f 3-5%
~~ \
f ) s t **
- M
,' i.,;;.
-=. % ,, ..
s ~., . I II k ',' ja l g
. / d , /
s_. i ' k..(1.[ .> w :,/ d ..- ([h. u- o
- :_. - _ .[ .
l s, e
/g r7 '( *
/ s,
' f, %,, "!
i
's .
t ,
~
Q_Y
~
, iJ 1 .
j / i / ' a 4 ' '
. WTr?h , */ .
,t 1 11-353
,ff.!!
k? ? l' 4 Figure 25. Percent organic matter igsin6. j,sf
<r ::r
$if :
ji'?
,$r ,:;
gg % . - ts %
.e, :
A!!' f ll
!8i 3-5 % sif
-isii
$!ii
. iS!-
I
'i!.i!?
(:.: m 1::, . i 0-2 % 4 1i!h:l .hiii'
'!!?!'
's . l'l:
;j::
' ~i: !!!.
3-5 % - ~~ _{.};;f5 . y ' :
- ,;l s .
.. .,s.
( . s. I li.., ',
- . ,ifh!$5!k$:
s
.j
' WBi* sijjjj:g.g
. ;g ; ,
S5S II-354 .fi - igge:
.'.: 3:!:ir' $5l$:$5!!!: .
A___......-- _.. _ - - - r M:Ni:i3: Win 3!3ss&Oi: _- .~. . . - - . - --
Figure 26. Percent organic matter in basins 7 and 8. [ 3-5 % 6-10 %
/o 6-10 %
<D O-2% i 6-10 % : .
O- % E Mr h l'! . S
,%Be II-355 k-
. Figure 27. Percent carbonate in basins 1 and 2.
3: E I 20-30 # ~ l$ii l f9ijj!::y,.,; " W 30-40 10 - 2 0 - i T30-4 pl rg;) . 30-40 < f .
} 10-20
'.5!$ l 20-30 % #
43 0 o
- s' l g
, :+.!:j b .r! 20-30 io-2o D
.s. l 6
3 -4 q y40 <lO o A sg .sjiRj((
'isssfigil.:R
;. .jj S$isii . !!!!!!!h:.:ssss.jjll
, i. -
S !
... 5isiliiii:s:i:!:".'.'.63 h:5:
l*-S %4 l
<10
*O / i CP $$$..
. c !!!$ijjjj;j< <
' sisE: :s:0:::. . . i:. . . . . 'f is: I 20-30 is!P ss; .ss sii!!E"~ i:ii$i>s . .
si;g "'" ..!!g!!!!g<
"1 .
l: l <10 -
- i '
is 4iO ' ::i:ie!!! S <h I! I y 'W' *
,.l$!!8 .
.3
+
!$ l ...s hs -
ji:' 3:
< i:<.*$:.N
- :: :.sj{i.jps:U: . : 88. .~ :
!kh!!f! !! !
* ! [f !!f l
lS$$iI.e. :.! ffh5jh!jlfll!..... jj. -
!:i;@$$$ ! !.3Si': . i:18i5i58<3:38 fjii+:: :<< :s.. '3:3:. . s .sif:8 I ,
- . !!!!::. ;i;!N!..
f -
,s ,f ,
,..- sii:.s I
] : 4 >. .sss!I" ,;; , , , , . j - am
- - . .s 9 :
2.. ::^ ., , j __SSH #f S 3
. :J
,'..'- [
- is '- ;
bd ..
.i
. :f. .<!: , , ,: g.; /:' ::+.s ; . "- "
# E .. $ki!0s.43 "
II-356 m ** --.e.' w a se-eg_rrw w =_wy , ,
Figure 28. Percent carbonate in basin 3. l 10- 20 I O-30 30- p ..
# '~ 4 70
;,y, i l 20-30 e
b2 , 30-4 0 20-30 %
'o,
/*
20-30 # 5 # 1 . 10 - 2 0 , 8 j 10 -20 10 - 2 0 a [ ! l
, 10 - 2 0 20-3C an* ==* s 4, n i
h o
/# .
4
.. q. -
. a soo y .
0 u.*A l,* I : l %
- l f .m f a
- 0 af on l $,
L o i & :' s % s y g w g
/ / . -
( / 8 ' A i 1 4 ( { Y II-357 l
Figure 29. Percent carbonate in basins 4 and 5. I J t
) ,,
i o z ..
= ' n It o W
' Q:.. ..
;E . .;! -
t (V gi 2 8 g S F f y h l
.i $ f '
it E u , g ' E , q ' J(10-20
-- e j o.\
i' l j . 20-30 ,. j 20-30 0
- 10-20 i i i 30-40
[/ l i i
., ~l. -
t0-m .i ' . ,
- N !
,' 2 >40 ,.,
' 'h ;
'
- s
- y. - # y .,
ss l g' s" $- y~' r , Q > , , 1s a y n I . I * '
. . i ,
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s *
,5h'C: ' ~ k *R ,l'
, . >, i
/I Le w ,, l e a ,)
l
-;~. , q.
Jl.:,I fg s .
* % ,, ~ .
l'I t
- e
'M ,, [ Q
- I I ( h
( / ,f i: a < I i 1 [ - . . t ~% l II-358 a .
!.55
--k Figure . Percent carbonate in basin 6.
O W q ;.:??' 20-30 .lu!' O-10 '. pg% % 10 - 20 ..s:!! ,- f Jf9f 4D o O ao 0-1O s.
.::<:S 35!5 8 l 55 10-20 lli#
20-30 .gs 10-20 20-30 ..
!;h 4;;g !?s 3 _. 30-40 ,
$i5li Uk5 0-10 pr 10-20 d sjsf h::
.8:s 20-30 i j:;ij
% R
- Si::
.33!$ .
WiidisII O -10 .
!!!!!,(!l.;[ .
,s::.. >i;
. iU< :,- .
,' i:-
.! .I k!.! ! .
~~
.fi$i ; :-
' <:g .
j . i!!!!!S: '
- !3, ,
,. j "j.. .... ..
33
;;: ;. . .. sis
! iiii ,,gj
,i k.iEi!- !sisj: '
;j;:.gi;j I-359
~
i : ;- ..
Figure g- percent carbonate in oasins 6 and 7-20-30 l1:l l 30-40
~
10-w 10-20 20-M 3040 140 20 30 - 30-40 28 30-4 10 - 2 0 h. - 20 30
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