ML041910082

Cooling-Water System Technology Study Request for Information - Winter Flounder Mass-Balance Model

ML041910082
Person / Time
Site:	Millstone
Issue date:	06/12/2002
From:	Hicks G Dominion Nuclear Connecticut
To:	Grier J NRC/FSME, State of CT, Dept of Environmental Protection
Emch R, NRR/DRIP/RLEP, 415-1590
References
D17333, FOIA/PA-2005-0115
Download: ML041910082 (113)

Text

Dominion Nuclear Connecticut, Inc.

Millstone Power Station i Dominion-Rope Ferry Road Waterford, Cr 06385

)

June 12,2002 I'o o £$ -A o'A D137333 vlll A Mr. James Grier Supervising Sanitary Engineer Permitting, Enforcement & Remediation Division, Water Management Bureau Department of Environmental Protection 79 Elm Street Hartford, CT 06106-5127

References:

1. Email, J. Grier, Connecticut Department of Environmental Protection to P.M. Jacobson, Dominion Nuclear Connecticut, Inc., dated April 30, 2002 (10:07 AM).

2. Letter D04143, E.J. Mroczka to L. Carothers, dated October 30, 1990.

3. Letter D17249, W. Mathews to M.J. Harder, dated August 31,2001.

4. Letter C09872, M.J. Harder to F.C. Rothen, dated February 16,2000.

5. Letter D17306, G.W. Johnson to J.F. Grier, dated March 14,2002.

-6. Letter D17321, G.W. Johnson to A.J. Rocque, Jr., dated April 29,2002.

Millstone Power Station Cooling-Water System Technology Study Request for Information - Winter Flounder Mass-Balance Model

Dear Mr. Grier:

By way of an email communication (Reference 1), the Connecticut Department of Environmental Protection (DEP) requested certain information from Dominion Nuclear Connecticut, Inc. (DNC) for use by its contractor, ESSA Technologies Ltd. (ESSA), for the purposed of performing a sensitivity analysis of the larval winter flounder mass-balance model. This model was developed at Millstone Power Station (MPS) and has been in use since 1990 (Reference 2). One of the most recent presentations of this model was in the final report on the use of once-through cooling water at Millstone Power Station (MPS), entitled "An Evaluation of Selected Cooling-Water System Alternatives for Millstone Power Station", which was submitted by DNC to DEP on August 31, 2001 (Reference 3). More specifically, the mass-balance model was described and a sensitivity analysis performed by DNC personnel in Appendix B to Chapter 3 of Part II of Reference 3.

Also, please note that at the request of DEP (Reference 4) c of this model erview was performed by Dr. Eric Adams of The Massachusetts Institute of Technology. This material

' was included as Appendix C to Chapter 3 of Part 11 of Reference 3.

Per your instructions, DNC has forwarded directly to ESSA the following materials:

1. SAS (Version 8.0 for Windows) disks to be used expressly for the purpose of performing a sensitivity analysis of the larval winter flounder mass-balance model. These disks should be returned to DNC as soon as possible.

2. The SAS program and two datasets needed to obtain results of the mass-balance model for the years 1984-99 (the years analyzed in Reference 3), copied onto a compact disc.

3. To aid in ESSA's review, the program (massbal2.sas) was annotated and a separate list of variables is included, detailing their function.

Also enclosed is the initial description of the mass-balance model as first submitted to DEP in October 1990 (Reference 2). In addition, portions of five Annual Reports (1983, 1984, 1985, 1988, and 1991) on the monitoring of the marine environment of Long Island Sound at MPS are included. To facilitate the review by ESSA, only relevant portions of the chapters on winter flounder studies describing special larval studies (e.g., import-export at Niantic River mouth) that provided information leading to the development of the mass-balance model were copied.

Further included are copies of reports prepared by Drs. Joseph Crivello of the University of Connecticut and R. Bradley Moran of the University of Rhode Island on larval winter flounder stock identification studies by analysis of genetic and multi-elemental techniques, respectively, recently provided to DEP in Reference 5. These studies, which provide a direct measure of the proportion of the entrained larvae attributed to the Niantic River stock of winter flounder in 2001, were compared to findings of the mass-balance model in the latest annual report "Monitoring the Marine Environment of Long Island Sound at Millstone Power Station Waterford, Connecticut" (see pages 251-253), also recently submitted to DEP (Reference 6). A copy of relevant pages from this report is also included with this letter.

As there may be additional questions regarding these materials and to facilitate this review, DNC personnel are available to meet with representative of DEP and ESSA, if so desired. Please contact Mr. Paul Jacobson, Millstone Environmental Services at (860) 447-1791 ext. 2335 with any questions or to arrange such a meeting.

Very truly yours, DOMINION OR CONNECTICUT, INC.

- Nuclear Safety and Licensing

)

Enclosures (reports cited above only) cc (w/ all SAS materials and reports cited above):

Ian Parnell ESSA Technologies Ltd.

1. 300, 1765 West 8 ' Avenue Vancouver, BC, Canada V6J 5C6 cc (w/ reports cited above only):

Mr. Ernest Beckwith Connecticut Department of Environmental Protection Marine Fisheries Office P.O. Box 719 Old Lyme, CT 06371

)

The SAS program titled MASSBAL2.sas is a condensed and simplified version of the programs used by the Millstone Environmental Laboratory to estimate the proportion of entrained winter flounder larvae originating from the Niantic River. The simplified program combines all years (1984-1999) and provides output parameters necessary to evaluate the sensitivity of model input parameters. Model output will provide values comparable to previously reported mass-balance model outputs (e.g., Tables 38-40 of NUJSCO (2000); however, actual values will not be identical due to: 1) the use of different time periods of larval occurrence between models (simplified model is constrained to discrete period for all years), 2) the assignment of the same stage-specific proportions to missing data for all years, and 3) the assignment of the same stage-specific daily mortality rates for all years (instead of using different values each year). Table I includes a list of variable names and definitions used in the SAS program.

Table 1 Input Variable From ESSA_1 sdate sampling date wdate first day of sampling week sta sampling station, transformed to LOC (location) rep sample replicate (not needed) stage larval developmental stage (1-4) den5OO total WF larval density (noJ500 n 3 )

stden500 stage-specific density nmul -mmnl 2 stage specific densities for each 1-mm size class (not needed)

Working Variables Jden500 natural log-transformed total density (used to calculate weekly (wdate) means) cumden cumulative density, additive through season days counting variable, day of season PROC NLN Variables (Gompertz function) - also see Appendix B of Chapter 3 of Part 11 of DNC (2001)

A alpha, asymptote estimate, index of cumulative density T time, in days, of inflexion point, peak larval abundance K shape parameter pred predicted value at any point during season inflex predicted value at time T (not really needed unless you want to plot Gompertz curves)

More Working Variables group first date of 5-day sampling period ningroup stage-specific mean for each GROUP (5-day period) sumstage total mean for each GROUP stagepro stage-specific proportion (fraction of larvae represented by each developmental stage) prostl-prost4 STAGEPRO renamed for each stage, essentially turning 4 observations per GROUP (I per stage) into I observation with 4 variables Input Variables From ESSA_2 sdate sampling date year 4-bit year tvol total daily cooling water volume (x 106 m3 )

Additional Flow-related Working Variables totfiow "expanded" TVOL, daily cooling water volume (m3 )

meanflow mean daily volume by GROUP (5-day period)

Remaining variables are defined in SAS code or in winter flounder mass-balance Materials and Methods section of any recent report, or DNC (2001).

7)

l

'.;C MONITORING THE MARINE ENVIRONMENT OF LONG ISLAND SOUND AT MILLSTONE NUCLEAR POWER STATION WATERFORD, CONNECTICUT ANNUAL REPORT 1983 -

iI'

.i' Northeast Utilities Service Company March 1984

., I survey. During tagging operations, winter flounder larger than 20 cm were sexed, scales removed for aging, and length recorded to the nearest mm. A white 1.3-cm diameter disc uniquely numbered and printed with

.91 I .t information for its return was positioned on the nape of the right side of the fish and a red disc with additional information was used on the left side. A nickel pin was pushed through the musculature, cut to.

size, and its end was crimped over to connect the tags and hold them in place. Except for some specimens released specifically at the NNPS intakes, winter flounder were returned to the same location as their capture. Information requested at recapture included date, location, method of capture, length, sex, and additional scales. A reward was given to all persons returning a tag.

Ee history studies Larval stage

(%

Samples examined for winter flounder larvae were taken at the MNPS discharge (station ES, formerly designated as DIS; NUSCo 1983); at Station NB in mid-Niantic Bay (formerly NB 5); and at stations A (new in 1983), B (realignment of former station NR 1), and C (formerly NR 2) in the Niantic River (Fig. 2). Entrainment samples at EN were collected on PLANKTON ------ .

TRAWLS tISore 2. Loc.tlon olf statilos *-apled for Ivter floooder f. the trawl al.d lchthorlankteo ooitorvln proV-,.

8

Il11 II 4 days and 4 nights each week, alternating weekly at the discharge of Units 1 and 2. Approximately 400 m of water were filtered through a 1.0-m diameter, 3.6-m long, 0.333-mm mesh conical plankton net.

Additional details may be found in the Fish Ecology section.

Ichthyoplankton samples were taken in Niantic River and Bay with a 60-cm bongo sampler with 3.3-m long'nets of 0.333-mm mesh towed at 2

'knots and weighted with a 28.2-kg oceanographic depressor. Volume i filtered was determined with General Oceanics flowmeters (Model 2030) I I,:I and approximated 300 mn per sample. Single tows (one replicate I

processed) were taken both day and.night using a stepwise oblique tow pattern with equal sampling duration of 5 min in surface, midwater, and bottom strata. The length of tow line necessary to sample the mid-water and bottom strata was based on water depth and the tow line angle as

.f measured with an inclinometer and was determined by the following relationship:

i tow line length desired sampling depth/cosine of tow angle. A Tow duration was reduced to 2 min per strata at station A starting on May 28 due to net clogging by lion's mane jellyfish (Cyanea sp.). At NB, single bongo tows (both replicates processed) were made biweekly from January through March. From April through the end of the larval winter flounder season in mid-June, single bongo tows (one replicate processed) were taken'twice weekly (Monday and Thursday or Tuesday and Friday) during day and night. In the Niantic River, preliminary tows were made during the day in February at stations A, B, and C at about weekly intervals'to determine when larval winter flounder were present.

I i

From March through the disappearance of larvae at each station, single bongo tows (one replicate processed) were made twice weekly (Monday and Thursday or Tuesday and Friday) day and night.

Sampling time in the Niantic River during daylight and night was systematically varied between two daily periods (prior to 1200 and after 1200) and two nightly periods (prior to 2400 and after 2400) since the effect of time of day on collection densities was not known. No sampling was conducted 30 min before or after sunrise or sunset. The two daylight and two night sampling periods were alternated weekly.

9

Station C was the only one in the Niantic River with strong tidal currents (Marshall 1960) and the effect of tide on collection densities was not known. Therefore, sampling at station C was systematically varied over four tidal stages (high, low, mid-ebb, and mid-flood). By collecting day and night samples approximately 6 h apart on one date, two opposing tidal stages were collected (e.g., high and low). The second weekly collection trip was 3 days later at approximately the same time and collections were taken during the other two tidal stages (e.g.,

mid-flood and mid-ebb). All 16 combinations of sampling periods and tidal stages were collected during every 4-wk period at station C. Two 24-h tidal studies were conducted at station C on April 28-29 and May 8-9. Samples were collected at 2-h intervals during a 24-h period.

Tidal export and import of larvae was examined at the mouth of the Niantic River during maximum ebb and flood currents. Two ebb and flood tides were sampled on May 9 and one ebb and flood tide was sampled on May 16. Stationary tows were taken in the middle.of the channel adjacent to.the Niantic River Highway Bridge. The bongo samplers described previously were used except an additional 40 kg of weight was added as ballast to increase the vertical tow line angle. Two bongo samplers were deployed for 15 min off each side of the boat with one at mid-water and the other near bottom. Two tows were-made at each depth for a total of four replicates at each depth per tidal stage.

All ichthyoplankton samples were preserved with 10% formalin and processed in the laboratory. Samples were split to at least one-half volume and larvae identified and counted using a dissecting microscope.

Up to 50 winter flounder larvae were measured to 0.1-mm in standard length (snout tip to notochord tip). The developmental stage of each larvae measured was recorded. The five possible stages were defined as:

Stage 1. The-yolk sac was present or the eyes were not pigmented (yolk-sac larvae)

Stage 2. The eyes were pigmented, no yolk sac was present, and no fin ray development Stage 3. Fin rays were present but the left eye had not migrated to the mid-line -

10

Stage 4. The left eye had reached the. mid-line but juvenile characteristics were not present Stage 5. Transformation to juvenile was complete and intense pigmentation was present'nedr the caudal fin base Larval collection frequency and density (n/500 3n ) were used for data analyses. Collection frequency was adjusted for the number of samples at each station and sample volume. Density distribution plots were smoothed using the spline function (SAS Institute Inc. 1981).

During 1983, information was gathered on post-larval juvenile winter flounder in the Niantic River. Four stations were sampled including Sandy Point (SP), Lower River (LR), Camp O'Neill (CO), and Channel (CH) (Fig. 1). SP, CO, and LR were selected because they had good juvenile winter flounder habitat, with sandy to muddy bottoms in shallow water adjacent to eelgrass beds (Bigelow and Schroeder 1953).

Station CH was -in a slightly deeper area between stands of eelgrass and the navigation channel. Depths sampled at all stations ranged from about I to 3 m. The stations were sampled once each week from May 18 through October 12 during daylight from 2 h before to 1 h after high tide. A 1-m beam trawl which had interchangable nets of 0.8-, 1.6-,

3.2-, and 6.4 -mm bar mesh was used; the nets were changed as fish grew and became available to the next largest size. A tickler chain was added to the net for use with the three largest meshes. Three replicates were made at each station and distance of each tow was estimated by letting out a-measured line attached to a lead weight.

Tows of 40 and 50 m made initially were increased to 75 and 100 m as the number of fish decreased throughout the summer and early fall. For data analysis and calculation of CPUE, the catch at each station was adjusted to 100 m2 of bottom covered by the beam trawl.

Juveniles were measured to the nearest 0.5 mm in total length.

During the first 5 weeks of the study, standard length was also measured as many of specimens had damaged caudal fin rays and total length could not be taken. The relationship between the two was determined by a 11

this size winter flounder change from a pelagic to a benthic habitat and thus were not susceptible to the plankton sampling gear.

The mean length at each station for different developmental stages provided additional insight into larval dispersion (Table 14). Although Table 14. Mean length by stage of all measu:ed larval vinter flounder taken at stations in the Niantie River and Bay and at MNPS.

Developmental Number Yean Standard stage Station measured :Ongth (=) error I A 239 2.7 0.02 3 217 2.8 0.02 C 171 2.7 0.02 EN 29 2.9 0.10

" 11 3.1 0.10 2 A 480 3.4 0.03 B 658 3.7 0.03 C . 655 3.8 0.03 lLY 074 4.3 0.03 NB 780 4.3 0.03 3 A 64 6.5 0.11 B 342 6.4 0.05 C 646 6.4 0.04 IN 1.333 6.1 0.02 NB 605 6.4 0.03 4 A 14 6.6 0.20 1337 7.2 0.05 C 255 7.4 0.03 EN 599 7.3 0.03

,NB 210 7.6 0.05 l5 A 0 - -

3 27 7.7 0.13 C 67 7.8 0.10 E149 7.8 0.07 NE 23 8.7 0.57 Stage 2 larvae were fairly evenly distributed in Niantic River and Bay (Fig. 10), the lag in temporal occurrence in Niantic Bay (Fig. 11) was reflected in the larger mean lengths at station NB and EN. For Stages 3.

¶ to 5, the mean length was similar at all stations except NB, which had a larger mean length for Stages 4'and 5. Based on these data, it appeared that most of the dispersion from the Niantic River to Niantic Bay occurred during the Stage 2 developmental period.

Special studies Primarily Stage 3 (62% of total) and 4 (30%) winter flounder larvae were collected during the two 24-h studies at station C. No apparent i day-night relationship was found (Fig. 13). However, the bimodal cycle 39jj-

over the 24-h period suggested a tidal influence. The tidal period observed during both studies was 12 h. A harmonic regression as described by Lorda (1983) using terms of sin(hours) and cos(hours) over a 12-h period with slack ebb occurring at hours 0 and 12 and slack high at hour 6 was fit to log-transformed (n/500 m2 + 1) data (Fig. 14). The harmonic regression accounted for about 45% of the total corrected sums of squares (TCSS) with the two sampling dates combined.. Based on this model, collection densities increased on a flood tide with a peak prior to slack high and then declined during ebb tide. Analyses of covariance, with tidal effect as described by the sine-cosine function as the covariate, was used to examine sampling data and day-night effects (Table 15). An interaction term for sampling date by day-night effect accounted for less than 1% of the TCSS and was pooled with the error. -The two sampling dates were significantly different and accounted for an additional 19% of the TCSS. In agreement with the 24-h plot (Fig. 13), the day-night effect was not significant. Weinstein et al. (1980) reported that three post-larval fish taxa (spot, Atlantic croaker, and Paralichtys spp. flounders) used vertical migration in response to tides as a retention mechanism in the Cape Fear River estuary. -The day and night differences in frequency of Stages 3 and 4 larvae at stations B, NB, and EN (Fig. 10) showed that winter flounder larvae of these developmental stages were capable of vertical movements.

At station C the lack of diel differences for Stages 3 and 4 larvae suggested a modification of behavior in response to tidal currents. The vertical movement from the bottom during during a flood tide would act as a retention mechanism in the Niantic River.

Table 15. Summary of analysis of covariance for 24-h diel study with harmonic components of the tidal effect used as covariates.

Sources Sum of squares 2 of total Tidala 25.003 44.6 *b Sampling date 10.882 19.4

• Diel 1.986 . 3.5 ns Model 37.871 . 65.5 Corrected Total 56.087 -

- Includes both sine and cosine components b * - significant at p <0.05 ns - not significant 40

l 3e001

)

Ieee-300-10e-30-z 0.

Li 10-  ! APR 28-29 HAY 8 3- NIGHT I DAY I*NIGHT I I 0-0 400 800 1200 1600 2000 2400 HOLUR Figure 13. Larval winter flounder density per 500 m3 during the two 24-hr tidal studies at station C.

LOU HIGH LOW SLACK, SLACK SLACK I.

7-6-

I

?7 i Li 0F,  :

0 S

21 0 1 2 3 4 5 6 7 8 9 to II 12 "1OUR Figure 14. Larval winter flounder abundance (log density per 500 m3) for the two tidal studies conducted at station C with the line fitted from the haromic regression (log density = 5.555 - 1.158 cos(hr) +

0.832 sin (hr)).

41

The potential export or import of winter flounder larvae from the Niantic River was investigated by sampling three ebb and three flood r tides at the river mouth. Most of the larvae collected during this study were Stages 3 (45%) and 4 (48%). Many more larvae were collected during flood tide (Fig. 15). No consistent difference in collection DO M ..

2e000 see EBB FLOOD EBB FLOOD EBB FLOOD MAY9 PUt 9 MAY16 Figure 15. Frequency and collection times of larval winter flounder taken at the mouth of the Niantic River

- during maximum ebb and flood tidal

) currents.

frequency was found between mid and bottom depths. During the period of sampling, there was a net increase in the number of winter flounder larvae entering the Niantic River. The larval dispersion model for the Niantic River (Saila 1976), which assumed larvae behaved as passive particles, simulated an approximate 4% loss from the river per tidal cycle. Stage 3 and 4 larvae, which have developing or developed fins, may have used vertical movements in response to tidal currents for transport into the Niantic River from The abundance of lionts mane jellyfish (Cyanea sp.) medusae in the Niantic River samples was measured volumetrically (Fig. 16). Volumes of medusae increased at station A during late March and at station B during early May. Marshall and Hicks (1962) also found that medusae were more abundant in the upper river compared to the lower portion during May and June. A peak occurred at stations A and B during mid-May. At station C, jellyfish were most abundant in the last week of May. Although no 42

Monitoring the Marine Environment of Long Island Sound at Millstone Nuclear Power Station

- Waterford, Connecticut ANNUAL REPORT 1985 L

_ _ _ THECONNECTICUT &ICHI ANRD POWERCOMPANY lbSTtRHYASACHtSE WE TTSLCTRIC COMTN POl ( WAE PTOR ERCOMPAIP

.4PKAH(ST UtIElICS SERVCECO.PAN,

_ORTIAST NCLEAR ENERGYCOMPAsts I ENVIRONMENTAL LAB II April 1986 I

corresponding to the inflection point of the cumulative function defined by its parameters (0) and (k) as:

)j t W) = (ln i )]k .(6)

Least-squares estimates of these parameters were obtained by fitting Equation 4 to the cumulative abundance data using nonlinear regression methods (SAS Institute 1982).

Winter flounder larvae were reared in the laboratory during 1985 to orI determine developmental time and growth rate. Eggs were stripped from a female and fertilized with milt from two males. Larvae that hatched within 24 h of each other were placed in 39-1 aquaria held in a water bath. The water temperatures ranged from 4.3 to 9.1 C with a gradual increase during the holding period. Photoperiod was similar to natural conditions. Larvae were fed ad libitum rotifers (Brachionus plicatilus) and brine shrimp nauplii (Artemia salina). To examine the effect of starvation on growth, larvae in one aquarium were not fed. Known-age larvae were routinely sacrificed to obtain otoliths for aging verification and information on growth rate. Sampling frequency varied, with almost daily collections during early development to approximately biweekly during later development when the number of larvae remaining was low. Otoliths were prepared and examined in a similar manner as those collected in the field during 1984 (NUSCo 1985).

Larval import and export studies were conducted throughout complete tidal cycles on March 28, April 29, and May 28. Samples were taken hourly except between 1 h before and after slack tidal currents.

-Stationary tows were taken by mooring the boat to the Niantic River Highway Bridge in the middle of the channel. Bongo samplers with 0.202-mm mesh nets were used on March 28 and with 0.333-mm mesh nets on the other two dates. Bongo samplers were deployed off each side of the boat with one at mid-water and the other near bottom. Sampling duration varied from 6 to 15 min (depending on the current velocity) to sample approximately 100 m3 of water. Current velocity at the time of sampling was measured with a flowmeter mounted outside of the bong6 opening so that back-pressure due to net clogging would not affect the measurement.

These current velocities were used to calculate the ne.t exchange of larvae leaving and entering the river.

.10

Ebb and flood tide velocity measurements used in estimating net larval exchange may not have been comparable due to the different widths of the channel at the point of sampling. Due to the length of the

-mooring line tied to the bridge,' the actual sampling location was-approximately 10 m north of the bridge during a flood tide and approxi-

.mately 10 m south of the bridge during an ebb tide. The comparability of velocities was investigated by fitting a second order polynomial equation to the water velocity measurements over time during the three flood and ebb tidal phases sampled. The form of the equation was:

velocity (cm/sec) - at + br2 (7) where t was time in h from high slack current for an ebb tide and from low slack current for a flood tide. No intercept was used because water velocity was zero at slack currents. For both tidal phases, a dome-shaped curve was formed that started and ended at zero velocity.

The average duration in h of an ebb and flood tide was estimated by the root of the above equation (i.e., h after slack for the velocity to be zero again):

h - -2a/2b (8) where h was the duration in hours and the parameters a and b were estimated separately for ebb and flood tides with Equation 7. Also, the area under the curves (i.e., an index of the totail water volume during the sampling period) was determined by integration of Equation 7, which resulted in:

area = (a/2)(t 2 ) + (b/3)(t 3 ) (9)

Because fresh water input into the Niantic River is small, the volume of *.

water leaving the river on an ebb tide should be similar to the volume

• that enters during a flood tide. Therefore, the areas under the curves should be similar. However, the area for the flood tide was less than the ebb. The flood tide velocities were recomputed by re-estimating the parameters (a) and (b) in Equation 7 under the constraint that the area.,

for the flood tide be the same as the area for the ebb tide and using the known duration of the flood'tide. This was done by solving for a in Equation 8 for the flood-tidal phase (a = -hb) and substituting it into the area equation (9) of the ebb tidal phase where the t's'were equated to the flood duration (h). This substitution caused Equation 9 to 11

become a function of only the flood phase duration (h) and the parameter (b), so that:

area -(16)bh3 (10)

Since the area was also known, solving for (b) in the above gave a new estimate of (b); replacing this estimate in Equation 8 resulted in a new estimate of (a). The final step was the computation of the flow according to Equation 7, but using the new estimates of (a) and (b).

Post-larval Stage Information on post-larval young-of-the-year winterflounder in the Niantic River was first gathered during 1983 (NUSCo 1984). One of the four stations established then, Lower River (LR), has been sampled through 1985'(Fig. 1). The other station sampled in 1985 was located near the Waterford shoreline (station WA) and was also sampled during August and September of 1984 (NUSCo 1985). Both stations contained habitat preferred by juvenile winter flounder, with sandy to muddy bottoms in shallow water adjacent to eelgrass beds (Bigelow and Schroeder 1953). The stations-were sampled once each week from May 23 through September 19 during daylight within about 2.h before to 1 h after high tide. Depths sampled ranged from i to 2-in.

A 1-m beam trawl was used with interchangeable nets of'O.8-, 1.6-,

3.2-, and 6.4-mm bar mesh; a tickler chain was added to increase catch efficiency. Two nets of successively larger mesh were used during each sampling trip to collect the entire available size range of young. This helped to eliminate bias-in the catch as was found in 1983, when some of the older and larger specimens apparently avoided the fine-mesh net needed to capture the smallest fish (NUSCo 1984). A change to the next larger mesh in the four net sequence was made when young had grown enough to become susceptible to it. The larger meshes also reduced the amount of detritus and algae retained. Two replicates with each of the' two nets were made at both stations; the order in which the nets were deployed was chosen randomly. Distance of each tow was estimated by letting out a measured line attached to a lead weight as the net was towed. Tow length increased from 50 to 75 to 100 m as the number of fish decreased throughout the summer. For data analysis and calculation 12

Tidal Import-Export Studies Tidal import-export sampling at the mouth of the Niantic River was conducted on three dates in 1985. All winter flounder larvae collected on March 28 were Stage 1 and 2, on April 29 most (99%) were Stage 2 and iL; 3, and on May 28 Stage 3 was dominant (89%). Examination of the combined data from all dates by percent occurrence of each developmental stage p

showed that Stage 1 and 2 larvae were more abundant during ebb tides and Stage 3 and 4 during flood tides (Fig. 13). Similarly, examination by 100

-f 70-60-c, 50 .

I; a~ 40-20-10, 0

E F E F E F

't I 1 1 l 2  ! - 3  ! I 4 I DE7VEL0OPMENTAL STAGE i4 I,.,

00 9

70E 60 U

0:50 E F E F E F E F E F E F f--2 f s p- l-4 FS- - F6 -7 -q LENGTH (MM)

Figure 13. Percent occurrence of each developmental stage and 1-mm size class collected at the mouth of the Niantic River

) during ebb (E) and flood (F) tidal stages in 1985.

43

) i i

f A

MONITORING THE MARINE ENVIRONMENT OF LONG ISLAND SOUND AT MILLSTONE NUCLEAR POWER STATION WATERFORD, CONNECTICUT ANNUAL REPORT 1984 Northeast Utilities Service Company April 1985

Sampling time and frequency varied with station and season and were partly based on information from the 1983 studies described in NUSCo I (1984). At NB, single-bongo tows were. made day and night biweekly from I

January through March. From April through the end of the larval winter flounder season in mid-June, single-bongo tows were taken twice weekly during day and night. In the Niantic River, preliminary tows were made I during the day in February at stations A, B, and C at weekly intervals to determine when larval winter flounder were present. From March through the first week in April, single tows (not including additional tows to examine net extrusion) were made during the day twice weekly within 1 h of low slack tide. During the second and third weeks of April, single-bongo tows were made twice weekly day and night. The day samples were collected within 1 h of low slack tide and the night 4U, samples during the second half of a flood tide. During the remainder of CI the season until the disappearance of larvae at each station (last

-ff i -

sample taken on June 14), tows were made twice a week only at night during the second half of a flood tide. Only one collection trip was made during the weeks of March 4 and May 27 because of adverse weather I..

conditions.

II a~ 1

/

current on the collection of Niantic River wnter flounder larvae and on their import and export were examined.

Two 24-h tidal studies were conducted at station C on March 9-10 and

4) LA.

March 18-19. Samples were collected at 2-h intervals during a 24-h period. Tow durations were 6 min and paired 0.202-mm and 0.333-mm mesh nets were used. Tidal import and export studies were conducted during

..i I

two tidal cycles on April 4 and May 8. Samples were taken hourly except for 1 h before and after slack tidal currents. Stationary tows were taken in the middle of the channel adjacent to the -Niantic River Highway Bridge. Bongo samplers with 0.333-mm mesh nets were used with an additional 40 kg of weight added as ballast to increase the vertical tow line angle. Bongo samplers were deployed off each side of the boat with one at mid-water and the other near bottom. Sampling duration varied E from 6 to 15 min depending on the current velocity and approximately 100 ms of water was sampled. Current velocity at the time of sampling was measured with a flowmeter mounted outside of the bongo opening so that back-pressure due to net clogging would not effect the measurement.

7 MA <'44 M .

These current velocities were used to calculate the net exchange of larvae leaving and entering the river.

Larval data analyses were based on density per 500 ms and due to.

varying sampling frequencies data were reduced to weekly mean density.

Data from all mesh sizes and tow durations were used in calculating the weekly mean densities. For comparisons, daylight samples in 1983 from the last week of April through the end of the season were excluded.

These samples underestimated abundance because of diel behavior of the older larvae (NUSCo 1984). Daylight samples were not collected in 1984 during these weeks.

Most ichthyoplankton samples were preserved with 10% formalin.

Except for tows made to compare net extrusion between 0.202-mm and 0.333-mm mesh nets, only one of the two bongo sampler replicates was processed for Niantic River and Bay samples. Samples were split to at least one-half volume and larvae were identified and counted using a dissecting microscope. Up to 50 winter flounder larvae were measured to 0.1-mm in standard length (snout tip to notochord tip)'. The developmental stage of each larva measured was recorded and the five stages were defined as:

Stage 1. The yolk sac was present or the eyes were not pigmented (yolk-sac larvae)

Stage 2. The eyes were pigmented, no yolk sac was present, and no fin ray development Stage 3. Fin rays were present, but the left eye had not migrated to the mid-line Stage 4. The left eye had reached the mid-line, but juvenile characteristics were not present Stage 5. Transformation to juvenile was complete and intense pigmentation was present near the caudal fin base 8

CT-NiANTIC

• RIVER C COO ...  : JORDAN POINT:: ~ . COVE

L..

c NIANTIC k....;:

DAY NB NPS **f*-~

1

~NN REE PLANKTON TRAWLS

)

Figure 2. Location of stations sampled for winter flounder in the trawl and ichthyoplankton monitoring programs.

was based on water depth and the tow line angle as measured with an inclinometer and was determined by the following relationship:

tow line length = desired sampling depth/cosine of tow angle.

From February 6 through March 19, 0.202-mm and 0.333-mm mesh nets were paired on the bongo sampler and 28 samples were taken to compare net extrusion between the two meshes atthe Niantic River stations. Nets were towed for 6 min because the 0.202-mm mesh net clogged when duration was greater. After March 19, all collections were made with 0.333-mm-mesh. When time permitted, consecutive 6- and 15-min tows were made at the Niantic River stations with 0.333-mm mesh nets to compare net extrusion for the two durations (16 paired comparisons). A Wilcoxon signed-ranks test was used to compare the paired samples and test for significant differences due to mesh and tow duration. Beginning in April at stations A and B, all tows were 6 min due to clogging by Cyanea spp. hydromedusae. At station NB, 0.333-mm mesh nets-and 15-min tows were used throughout the season.

6

size-classes showed that larvae 4 mm and smaller were more abundant during an ebb tide and larvae 5 mm and larger were more abundant during a flood tide.

In order to determine if velocity measurements were comparable between ebb and flood tides, separate quadratic polynomial equations were fitted to hourly velocity measurements combined from each of the three ebb and flood tides sampled. Good fits were obtained for both ebb (R2=0.98) and flood (R2=0.97) *tide equations (Table 15). The mean Table 15. Quadratic equations used to describe ebb and flood tide velocities (cnlsec), vith estimates of tidal stage durations, integrated areas under the velocity equation curves, and final equation to adjust flood-tide velocities (see text).

Ebb Flood 2

Actual (Eq. 7 )a Vel - 52.6(t) - 7.4(t ) Vel 5.17(t) - 8.8(t 2)

Duration (Eq. 8) 6.9 h 5.8 h Area (Eq. 9) 417.3 294.1 Adjusted b velocity - Vel = 73.3(t) - 12.6(t 2 )

a Equations found on page 11.

b Based on re-computed parameter estimates o (a) and (b) from Equations 8 and 10 (pages 11 and 12).

duration of each ebb tide was about 1 h longer than the flood tide and the area under the curve for the latter was smaller than -the former.

This difference in area indicated that if the flood sampling had been conducted at the same location as ebb sampling, the flood velocities would have been higher. Therefore, the flood velocities were estimated by re-computing the parameters (a) and (b) with Equations 8 and 10 and then substituting them into Equation 7. 'The calculations of net exchange.

of larvae which follow were based on actual ebb current velocities and the adjusted flood current velocities.

Using data combined from the three sampling dates, net tidal exchange was estimated for each 1-mm size-class; the 2- and 3-mm size-classes were combined because of the low collection densities of the former. The estimates were obtained by summing the number (n/500 m 3 ) of larvae of each size-class in each hourly sample for the three sampling dates. The sum was multiplied by the estimated water velocity at the 44

time of the hourly collection. This density-velocity adjustment accounted for changes in discharge volume during the tidal cycle. Since larvae collected during an ebb tide represented a loss from the river, the density-velocity value was made negative. A harmonic regression.

equation using a 12.7-h tidal cycle (the average duration of the three tides sampled) was fitted to density-velocity values. The area under the curve for each tidal stage was estimated by numerical integration of the harmonic regression equation using 5-min increments. Net tidal exchange was expressed as the percent return of a size-class on a flood tide compared to the loss on a ebb tide (Table 16). There was a net export of 4 mm and smaller size-classes and a net import of 5 mm and larger size-classes.

Table 16. Percent return of larval winter flounder on a flood tide that were flushed from the river on an ebb tide by size class and R2 values of the harmonic regression models.

Size Percent . R2 of class (mm) return model 3 19.8 0.81 4 48.8 0.52 5 174.9 0.91 6 136.8 0.82 7 103.8 0.66 The 1985 import-export data were consistent with previous findings (NUSCo 1984, 1985). Since 1983, eight tidal cycles were sampled and these data clearly indicated a net loss of smaller larvae that lack fin ray development and have little or no locomotion. However, larger larvae with developed fin rays apparently utilized vertical migration in relation to tidal currents for passive migration back into the Niantic River. This vertical migration of larvae after fin ray development was also apparent during 24-h studies conducted in the river in 1983 (NUSCo 1984), where densities of larger larvae increased during a flood tide and decreased during an ebb tide. Vertical migration was not apparent during 24-h studies in 1984 (NUSCo 1985) since all sampling was conducted prior to fin ray development. Other researchers have also 45

reported vertical migration in early life history stages of fish. Diel movement of larval yellowtail flounder was found to increase with the size of the larvae (Smith et al. 1978). Atlantic herring larvae synchronized vertical migration with flood tides to minimize seaward transport (Fortier and Leggett 1983). Post-larval spot, Atlantic croaker, and Paralichthys spp. flounders used verical migration in response to tides as a retention mechanism (Weinstein et al. 1980).

Larval North Sea plaice demonstrated selective horizontal transport by swimming up from the bottom during flood tides and remaining near the bottom during ebb tides (Rijnsdorp et al. 1985). Most winter flounder larvae found in Niantic Bay probably were tidally flushed from the Niantic River during early developmental stages. After fin ray development, at least some of the older larvae in the bay utilized vertical migration in relation to tidal flow to reenter the river.

Those within the river demonstrated a similar behavior to remain there.

Post-larval Stage Abundance Post-larval winter flounder were collected using a 1-m beam trawl from late May through late September at stations LR and WA in the Niantic River. The standardized catch per 100 M2 at both stations peaked on June 13 and began to decline thereafter, most likely after recruitment began to be offset by mortality, and stablized by late July (Fig. 14). Although densities were more variable at WA, juveniles were more abundant there during late summer (ca. 8 per 100 mi2 ) than at LR (ca. 6 per 100 ml). This was also found in 1984 (NUSCo 1985).

A comparison of catches made from 1983 through 1985 at LR showed that although densities in 1984 were initially higher, they were similar in magnitude to 1985 by July (Fig. 15). The first 5 weeks of 1983 are not shown because the catch during that period was biased (NUSCo 1984),

but based on abundance later in the year, juveniles were probably more numerous than during the other years. Although 1983 densities were within the range of those found for 1984 and 1985 during early July, abundance in late summer was greater. More variability was evident for 1983 as only three replicate tows were taken per sampling trip rather than the four made during 1983 and 1984.

46

difference agreed well with the 17-day difference in developmental time to Stage 4 between the two years (Table 9). The estimated time from hatching to Stage 4 in 1983 and 1984 was 56 and 73 days, respectively.

This was longer than the estimated 49 and 63 days needed for growth from 3 mm to 7.5 mm in 1983 and 1984, respectively.

Although day 1 was defined at a length of 3 mm, it did not necessarily represent the date of hatching because little growth was expected during yolk-sac absorption. Cetta and Capuzzo (1982) reported that in a laboratory study total body weight of winter flounder larvae decreased during the first 2.5 weeks after hatching and after 1 week, larvae appeared to be metabolizing body-tissue following depletion of the yolk sac. Therefore, an additional 10 days may pass during yolk-sac absorption when larvae are in the 3-mm size-class. Based on the growth curves, these additional days would increase the age of a 7.5-mm larva to 59 days in 1983 and 73 days in 1984, which agreed with the estimated developmental time to reach Stage 4 of 56 days in 1983 and 73 days in 1984.

.,400000"0000Tidal Import* and Export Sampling was conducted at the Niantic River Highway Bridge on April 5 and May 8 during two tidal cycles to estimate the tidal import and export of winter flounder. On April 5, mostly Stage I and 2 larvae were collected and on May 8 the larvae were primarily Stage 3 (Fig. 16).

More Stage 1 larvae were collected during ebb rather than flood tide in April, although about 40% (1,521 per 500 m 3) of the former were collected in one sample taken near the bottom. Slightly fewer Stage 2 and 3 larvae were collected during flood tide. On May 8, similar numbers of Stage 3 larvae were collected on the two tides and most of the Stage 4 larvae were collected during the flood.

Net tidal flushing for the predominant developmental stages on each sampling date was estimated by multiplying the density (average of mid and bottom samples) by the estimated water velocity during the time of sample collection. This density adjustment accounted for changes in discharge volume during the tidal cycle. A harmonic regression equation using a 12-h tidal cycle was fit to densities adjusted for 48 FU/_JIL5

4000 APRIL 5 30a0 U

4-Z2 bIJ 2 0 a0 Cy 1 000 3 1 2 3 STAGE X 2 T IaE I EBB I - FLO 00 -

2500 MAY 8 2000 I 00 Lu U

Cr I 000 500 a

2 3 4 2 4 STAGE

- EBB , - LOODD T IDE Figure 16. Frequency of larval winter flounder by developmental stage collected at the mouth of the Niantic River during ebb and flood tides on April 5 and May 8, 1984.

49

velocity. Good fits were obtained for Stage 2 and 3 larvae on April 5 and for Stage 3 larvae on May.8 (Fig. 17). Densities of Stage 1 larvae on April 5 could not be modeled (R2=0.38) because larvae were scarce during flood tide and the one sample with a very high density was collected during ebb tide. The area under the curve for each tidal stage was assumed to be a good estimate of net flushing and the areas were approximated by numerical integration of the respective harmonic regression equations using 5-min increments. On April 5, an estimated 65 and 63% of the Stage 2 and 3 larvae, respectively, returned to the Niantic River on a flood tide. The return of a flood tide increased to 92% for Stage 3 larvae on May 8. The larval dispersion model developed for winter flounder larvae in the Niantic River used a 72% return of passive particles to the river on a flood tide (Saila 1976). This model underestimated larval retention because older larvae used flood currents to increase their return to the river.

The data for May 8 showed a net loss of Stage 3 larvae from the river during a tidal cycle.. This did not agree with, the tidal import-export studies conducted in 1983, when many more larvae were found entering the river than leaving (NUSCo 1984). In 1983, sampling was conducted on May 9 and 18 and Stage 3 (45%) and 4 (48%) larvae predominated. Although they May 8 sampling in 1984 was conducted during a similar time-period, larval development was slower this year (Table 9). Because of slower development in 1984, few Stage 4 larvae were present during the early part of May and the younger Stage 3 larvae may not have had fully developed fins. This lack of complete fin development possibly prevented the larvae from using tidal currents to-enter the river as it was postulated in 1983.

24-h Tidal Studies Two 24-h tidal studies were conducted in 1984 to examine the effect of tide on the observed abundance of-early developmental stages (Stages 1 and 2). These studies were used to most efficiently schedule sampling for winter flounder larvae of various developmental stages. The 1983 24-h sampling was conducted when Stage 3 and 4 larvae predominated and 50

I APRIL 5 STAGE 2 65 7. RETURN 20000-a 1 0000- EBB t: C.

• z X

-10000-- F!OCO

-2CD000 Exch = -1968 - 1540 cos(h) + '4174 sin(h)

R2= 0.91

- a000a-

• I I * - -

la I z & 5 7 ... a.. t ID

,I - 2

-UR

• N APRIL 5 S TAGE 3 63 % F.R.URN 2 50 0-: E= :2 0- 4 z

ul -

-2 5001- FLCCO

-5 000-:

.Exch -424 + 336 cos(h) -- 29i0 sin(h) 2 =.64

- 75 a00- .

0

• 5 6 7 a I 0 1 . 12 HOUR Figure 17. Estimated exchange of larval winter flounder at the mouth of the Niantic River for Stage 2 and 3 larvae on April 5 and Stage 3 larvae on May 8 with the line fitted from a harmonic regression model.

51

MAY 8 STAGE 3 92 % RETURN 20000,

0000EBB z

/FLOOD

-2 0000 Exch -430 + 3289 cos(h)- 14328 sin(h)

R2 - 0.74

-3a0000i 0 . 2 3 4 5 6 7 8 9 10 11 12 13 HOUR Figure 17. (Cont'd) their collection densities increased during flood tides. This was attributed to a vertical movement in relation to tidal currents, which served as an estuarine retention mechanism.

In 1984, densities of Stage 1 and 2 larvae on March 12 were unrelated to tide (Fig. 18). Although the greatest density (746 per 500 I3 ) was found during one of three low slack tidal stages sampled, the remaining collection densities ranged from approximately 100 to 300.

Collection densities evidently changed in relation to tidal stage on March 19. The greatest densities were found during an ebb tide and the lowest during a flood tide. Also, collection densities were smaller on March 12 than on March 19, as the largest ones from the first study were smaller than almost all those found a week later. A harmonic regression with a 12-h period was used in an attempt to relate changes in density to tidal stage. A satisfactory fit was achieved for Stage 1 larvae (R2 0.58), but not for Stage 2 (R2 =0.01) (Fig. 19).

The increased abundance of Stage 1 larvae found during an ebb tide on March 19 agreed with the results of the previously presented tidal import-export study on April 4, when few Stage 1 larvae returned to the 52

70 M0RCIH ;2

)

E 0

iZ U) 400 i z 1

.1a0 i-ado o n 2001 o 7 4 6  ! o 1 I: I Io 1I8 .;C 22 2-L 25 i0 POU'..

100-cOO 0 0 E

0

'0

• -~TOC En Z60' a

0 2

• 6 a 0 12 1t HCUR Figure 18. Larval winter flounder density per 500 X 3 and the time I of high and low slack tidal currents during the March 12 and 19, 1-984 24-h studies at station C.

53

6 . 3-6 . 0- L'i

. 44

. i-?4

4. FI

! . 7-II II

.ZI 8

oE 5.4-0 En 5 .1-z LA a

J 4.

a.

I HICH WLI HIGH LC V/ HIGH I

i . . 6 . .

I 2- 2 c 2 4 6 8 IC 12 26 t8 20 22 24 HOUR rII I

II Figure 19. Stage 1 larval winter flounder abundance (ln density I per 500 mi 3

) and the time of high and low slack tidal j I,

currents forthe March 19, 10,84 24-h study at station I I

C with the line fitted from a harmonic regression II (ln density = 5.39 - 0.55 cos(h) + 0.34 sin (h);

R2 = 0.58).

Niantic River on a flood tide (Fig. 16). Although the same tidal flushing study indicated a net loss of Stage.2 larvae, apparently the difference in density between ebb and flood tides at station C was not sufficient to have been detected using the harmonic regression model.

ONOMEM I' I

Post-larval Stage Abundance I

A l-m beam trawl was used at stations LR and CO in the Niantic River during 1984 to sample for young-of-the-year winter flounder following larval metamorphosis. As in 1983, dense mats of the alga Enteromorpha clathrata developed at CO and hampered sampling there beginning in mid-July. Much algae collected on the tickler chain and i

54 N

iE EAST UTILITIES General Offices

• Selden Street. Berlin. Connecticut

_KI Co_(ClICO tG T A.e pOf A CO.~

. is, . ns (tic'.

• Add~ P.O. BOX 270

' WAIIAPOWER CDV HARTFORD, CONNECTICUT 06141-0270 aAbE4ASt MXXEAss.(%G COWM (203) 665-5000

• )

October 30, 1990 D04143 Ms. Leslie Carothers, Commissioner Department.of Environmental Protection State'Office Building 165 Capitol Avenue Hartford, 'CT 06115

Dear Commissioner Carothers:

Mfllstone Nuclear Power Station Ecological Monitoring Program Northeast Utilities Service Company (NUSCO), as agent for Northeast Nuclear Energy Company (NNECO), agreed with Connecticut Department of Environmental Protection, Bureau of Water Management personnel in a meeting at Northeast.

Utilities Environmental Laboratory on September 11, 1990, to provide a report on or before October 31, 1990, describing winter flounder abundance. indices for 1990 new methods for assessing larval entrainment effects, and a progress report on the fish return sluiceway systems'at NNECO's Millstone Nuclear Power Station (MNPS). Accordingly, NUSCO hereby submits, on behalf of NNECO, updates of work completed in 1990 as follows:

I o 1990 Abundance Indices for Winter Flounder (Enclosure 1) o Mass-Balance Calculations for Assessing Production Losses due to Entrain-ment of Winter Flounder (Enclosure 2) o Progress Report on the MNPS Fish Return'Systems (Enclosure 3)

If you have any questions after reviewing this submission, please. call Dr. William C. Renfro, Director, NUSCO Environmental Programs, at (203) 665-4620.

Very truly yours, NORTHEAST UTILITIES SERVICE COMPANY As Agent for Northeast Nuclear Energy Company E.J.M ka Senior Vice President Enclosures cc: See next page oS3422 REV. 4-88

Enclosure 2 to Letter No. D04143 MASS-BALANCE CALCULATIONS FOR ASSESSING PRODUCTION LOSSES DUE TO ENTRAINMENT OF WINTER FLOUNDER MILLSTONE NUCLEAR POWER STATION NORTHEAST NUCLEAR ENERGY COMPANY NPDES PERMIT No. CT000326 Northeast Utilities Service Company PO Box 270 Hartford, Connecticut 06141-0270 October 1990

)

BACKGROUND Recent assessments of the potential impact of entrainment by Millstone Nuclear Power Station (MNPS) on the Niantic River winter flounder stock have assumed either an entrainment loss of a postulated percentage of the larvae produced in the River (NUSCO 1989, 1990) or that all winter flounder larvae entrained came from the Niantic River (Crecco and Howell 1990). Results from special studies conducted in 1988 suggested that many larvae entering Niantic Bay may not have come from the Niantic River stock. These studies consisted of 24-h sampling conducted in Twotree Island Channel and import/export sampling at the mouth of the Niantic River (NUSCO 1989). The geometric mean density of winter flounder larvae collected during a flood tide (from low to high slack current, 16 samples) during two 24-h sampling periods (April 25 and May 4, 1988) in Twotree Island Channel was 128 per 500 m3 . These larvae would pass Millstone Point and potentially enter Niantic Bay. The average volume of water passing between Millstone Point and bell buoy 4 (about 0.5 nautical miles SW of Millstone Point) is approximately 2,200 m3 /sec (NUSCO 1983). Therefore, about 13 million larvae should have entered Niantic Bay through this area during a flood tide. During a similar time period, two import/export studies (April 18 and May 2, 1988) were conducted at the mouth of the Niantic River and the geometric mean density of samples collected during an ebb tide (10 samples) was 155 per 500 M3 . With an average tidal prism volume for the Niantic River of about 2.7 x 106 M3 (Kollmeyer 1972), less than 0.9 million larvae left the river during an ebb tide. This number of larvae is equivalent to less than 7% of the larvae entering Niantic Bay between Millstone Point and bell buoy 4 during a flood tide.

Therefore, at least for this period during 1988, a majority of the winter flounder larvae entering Niantic Bay and potentially entrained came from a source(s) other than the Niantic River.

MATERIALS AND METHODS Mass-balance calculations were used to investigate whether the number of winter flounder larvae entering the Niantic Bay from the Niantic River could support the number of larvae observed in the Bay during the winter flounder larval season each year. There are three potential larval inputs to Niantic Bay: eggs hatching in the Bay, larvae flushed from the Niantic River, and larvae entering the Bay across the boundary between Millstone Point and Black Point. Due to the low numbers of yolk-sac larvae collected in Niantic Bay (NUSCO 1985-90), minimal spawning and subsequent hatching is thought to occur in Niantic Bay and, therefore, would be a negligible larval source. It is known that larvae are flushed from the Niantic River to the Bay and the number entering can be estimated from available data. Although it was demonstrated above that a large number of larvae entered Niantic Bay from Long Island Sound (LIS) in 1988 during at least a portion of the larval season, insufficient data were available to quantify this source throughout the entire larval season and for different years. Therefore, this source remains a potentially important one that needs further investigation. There are four potential losses of larvae from Niantic Bay: larvae enter the Niantic River during a flood tide, are lost due to natural mortality, entrained by MNPS, and larvae are flushed from the Bay into LIS. The number entering the Niantic River can be estimated from available data, and estimates of natural mortality and entrainment have been made, but little is known about the number of larvae flushed to LIS and this remained an unknown in the following calculation. The form of the mass balance equation was:

NBt+ 5 = (NB0)- (Ent) - (Mort) + (FromNR) - (ToNR) +/- (Source/Sink) where t = time in days NB+ 5 = number of larvae in Niantic Bay 5 days after day t (instantaneous daily' estimate)

NB1 initial number of larvae in Niantic Bay on day t (instantaneous daily estimate)

Ent = number of larvae lost from Niantic Bay due to entrainment in the condenser cooling water system (over a 5-day period)

Mort = number of larvae lost from Niantic Bay due to natural mortality (over a 5-day period)

FromNR = number of larvae flushed from the Niantic River (over a 5-day period)

ToNR = number of larvae entering the Niantic River (over a 5-day period)

Source/Sink = unknown number of larvae in Niantic Bay that flush to LIS or enter the Bay from LIS (over a 5-day period)

Solving for the unknown Source/Sink term, the equation was rearranged as:

Source/Sink - (NB+ 5 ) - (NB1) + (Ent) + (Mort) - (FromNR) + (ToNR) and because these mass-balance calculations were based on the change in the number of larvae in Niantic Bay over a 5-day period:

5-day Change = (NBt + 5) - (NBO) therefore:

Source/Sink = (5-day Change) + (Ent) + (Mort) - (FromNR) + (ToNR)

The selection of 5 days as the period of change was arbitrary and the use of different time periods should not alter the conclusions from the mass-balance calculations. Daily abundance estimates were derived from the Gompertz equation. The equation was fitted to weekly geometric mean densities (NUSCO 1990). Daily estimates for Niantic Bay (NBt and NBt + 5) were calculated from data collected at stations NB and EN combined, which represented an instantaneous daily standing stock after adjusting for the volume of Niantic Bay (about 50 x 106 m3; E. Adams, MIT, personal communications). The difference between these two estimates was the term (5-day Change).

Daily entrainment estimates were based on data collected at station EN and the actual daily volume of condenser cooling water used at MNPS. The daily entrainment estimates were summed over each 5-day period (Ent). Stage-specific mortality rates were determined by Crecco and Howell (1990) and modified to daily stage-specific mortality rates by assuming stage durations of 10 days for Stages 1, 3, and 4 larvae; and 20 days for Stage 2 larvae. The proportion of each stage collected at station EN during each 5-day period was applied to the daily standing stock for Niantic Bay (NB1) to estimate the number of larvae in each developmental stage for stage-specific mortality calculations. The daily loss due to natural mortality was summed for each 5-day period (Mort).

The 5-day input of larvae to Niantic Bay from the River (FromNR) was based on daily density estimates for station C in the river after adjusting for the rate of flushing between station C and the mouth the of River (Fig. 1). To estimate the relationship between the estimated daily density at station C and the average density of larvae leaving the River on an ebb tide, the geometric mean density of samples collected during an ebb tide for 10 import/export studies conducted at the mouth of the Niantic River during 1984,1985, and 1988 (NUSCO 1985, 1986, 1989) were compared to the estimated daily densities at station C. It appeared that less than 50% of the larvae estimated to be at station C were flushed from the river. Therefore the average density of larvae flushed from the Niantic River was estimated by the regression equation:

Average density = 18.828 + 0.458 (Daily density at station C)

This average density, the average tidal prism of 2.7 x 106 m3 (Kollmeyer 1972), and about 1.9 tidal prisms per day were used to estimate the daily flushing of larvae from the River to Niantic Bay. This daily input to the Bay was summed for each 5-day period to calculate the term (FromNR) in the mass-balance equation. The loss of larvae from Niantic Bay to the River during a flood tide (ToNR) was based on the daily density estimates for Niantic Bay (stations NB and EN

combined). A comparison of the daily estimated density for Niantc Bay to the geometric mean density of the samples collected during a flood tide for the 10 import/export studies indicated no significant relationship (Fig. 2). Because there was no apparent systematic bias in this relationship and for lack of better information, the estimated daily densities for Niantic Bay from the Gompertz equation were used to estimate daily loss after adjusting for the average tidal prism and the number of tidal prisms per day. These daily estimates of the number of larvae entering the river during a flood tide were summed over each 5-day period to calculate the term (ToNR) in the mass-balance equation.

The Source/Sink term represents the net loss from or gain to Niantic Bay of larvae from LIS during a 5-day period that is required to balance the calculation. For a net loss this term would be negative and for a net gain the term would be positive.

RESULTS AND DISCUSSION Mass-balance calculations were made for 1984 through 1989 with four of these years (1986-89) during 3-unit operation. The results of calculations for each 5-day period in 1989 are provided as an example (Table 1). During the season the value of the term (5-day Change) went from positive to negative when the estimated number of larvae in Niantic Bay started to decline during a 5-day period. In the first part of the larval season there was a net loss of larvae from Niantic Bay (negative Source/Sink term). Starting in early April the Source/Sink term became positive, indicating that larvae from other sources (LIS) were required to support the change in larval abundance or to balance the equation. During peak entrainment (rnid-April), more larvae were imported from LIS than were entrained suggesting that this was an important larval source for Niantic Bay. For each 5-day period the proportion of entrainment attributed to the Niantic River was estimated from the ratio of larvae entering the Bay from the River (FrornNR) to the total input from both sources (FromNR + Source/Sink). This proportion was applied to the total number entrained to estimate the number entrained from the Niantic River. For the 5-day periods when there was a net loss (negative Source/Sink term) or when the proportion from the river was greater than one, all larvae entrained were assumed to have originated from the Niantic River. Estimates of annual total entrainment and the annual number entrained from the Niantic River were determined by summing all 5-day periods. Based on mass-balance calculations for data collected in 1984-89, 28.2 to 65.7% of winter flounder larvae entrained by MNPS originated from the Niantic River (Table 2). Except for 1984, the total entrainment estimates based on the daily densities derived from the Gompertz function were 19 to 39% larger than those previously reported (NUSCO 1990), which were calculated from median entrainment densities. The reason for this increase was not immediately evident, but these larger annual entrainment estimates were used for the remaining calculations.

The number of each developmental stage entrained during each 5-day period was estimated based on the proportion of each stage collected at station EN during the period. By applying the proportion entrained attributed to the Niantic River (FromNR / E of FromNR and Source/Sink) the number of larvae in each stage was allocated to the two sources for each 5-day period. The annual number of larvae entrained by stage from each source was estimated by summing all 5-day periods (Fig. 3). Except for 1984, most of the Stage 3 larvae (the predominant stage entrained) originated from sources other than the Niantic River. -The estimated number of larvae entrained by stage from the River was compared to the annual abundance estimates for each larval stage in the Niantic River (Crecco and Howell 1990). The estimated percentage of the Niantic River winter flounder production that was entrained annually since 1984 ranged from about 6 to 17% (Table 3). These estimates of year-class strength reductions can be used in further impact assessment work using the stochastic population model.

CONCLUSION Mass-balance calculations were used, as an empirical analysis on available data, to estimate the proportion of the Niantic River production that was annually entrained. The results indicated that a large number bf entrained larvae were from a source or sources other than the Niantic River. A special sampling program is presently being designed for the 1991 larval winter flounder season to help verify these results.

REFERENCES CITED Crecco, V, and P. Howell. 1990. Potential effects of current larval entrainment mortality from the Millstone Nuclear Power Station on the winter flounder, Pseudopleuronecresanericanus, spawning population in the Niantic River. Mar. Fish. Div., Conn. Dept. Envir. Prot. 37 pp:

Kollmeyer, R.C. 1972. A study of the Niantic River estuary, Niantic, Connecticut. Final report phases I and II, physical aspects of Niantic River estuary. Rep. No. RDCGA 18. U.S. Coast Guard Academy, New London, CT. 78 pp.

Northeast Utilities Service Company (NUSCO). 1983. Millstone Nuclear Power Station Unit 3 environmental report. Operating license stage. Vol. 1-4.

1985. Winter flounder studies. In Monitoring the marine environment of Long Island Sound at Millstone Nuclear Power Station. Annual report, 1984. 74 pp.

____.. 1986. Winter flounder studies. In Monitoring the marine environment of Long Island Sound at Millstone Nuclear Power Station. Annual report, 1985. 69 pp.

___ 1987. Winter flounder studies. In Monitoring the marine environment of Long Island Sound at Millstone Nuclear Power Station. Summary of studies prior to Unit 3 operation.

151 pp.

1988. Winter flounder studies. Pages 149-224 in Monitoring the marine environment of Long Island Sound at Millstone Nuclear Power Station. Three-unit operational studies, 1986-1987.

___ 1989. Winter flounder studies. Pages 239-316 in Monitoring the marine environment of Long Island Sound at Millstone Nuclear Power Station. Annual report 1988.

1990. Winter flounder studies. Pages 9-77 in Monitoring the marine environment of Long Island Sound at Millstone Nuclear Power Station. Annual report 1989.

Table 1. Results of mass-balance calculations for each 5-day period in 1989.

Start of 5-day Number Loss due Number from Number to Source/Sink 5-day Change Entrained to Mortality Niantic R. Niantic R. Term Period (x 106) (x 106) (x 106) (x 106) (x 106) (x 106) 2-15 0.01 0.01 0.01 1.8 0.0 -1.8 2-20 0.0 0.0 0.0 9.2 0.0 -9.2 2-25 0.0 0.0 0.0 31A 0.0 -31.A 3-02 0.0 0.0 0.0 62.0 0.0 -62.0 3-07 0.0 0.0 0.0 82.8 0.0 -82.8 3-12 0.0 0.0 0.0 85.3 0.0 -852 3-17 0.3 0.0 0.0 74.2 0.1 73.7 3-22 1.4 0.3 0.3 57.9 0.6 -55.3 3-27 3.7 2.7 1.2 42.2 2.1 -32.6 4-01 5.8. 11.1 3.7 29.5 5.0 -3.8 4-06 6.1 21.4 4.3 20.1 8.7 20.4 4-11 4.3 21.5 7.1 13.6 11.9 31.2 4-16 1.6 26.0 7A 9.2 13.7 39.6 4-21 -09 24.1 6.3 6.3 13.9 37.2 4-26 -25 19.6 63 4.3 12.8 31.9 5-01 -3.2 17.2 5.3 3.1 11.1 27.2 5-06 -3.2 12.3 4.0 2.3 9.1 19.9 5-11 -29 7.4 3.0 1.8 7.2 12.9 5-16 -25 3.5 2.3 1.5 5.6 7.4 5-21 -2.0 2.3 1.8 1.3 4.2 5.1 5-26 -15 1.8 1.3 1.1 3.2 3.6 5-31 -12 1.2 1.0 1.1 2.4 2.3 6-05 -0.9 1.0 0.7 1.0 1.7 1.5 6-10 -0.7 0.6 0.5 1.0 1.3 0:8 6-15 -05 OA 0.0 0.9 0.9 -0.1 6-20 -OA 0.3 0.0 0.9 0.7 -0.3

'Due to rounding zero values represent numbers under 50,000 larvae.

Table 2. Larval winter flounder estimates of total.entrainment, number of larvae entrained from the Niantic River, and the percentage of total entrainment attributed to the Niantic River for 1984-89 based on mass-balance calculations.

Niantic River  % Entrainment Total Entrainment Larval Entrainment Attributed to Year (X 106 ) (X 106 )

• the Niantic River 1984 87.8 57.7 65.7 1985 82.6 43.2 52.3 1986 130.1 51.4 39.5 1987 171.8 66.8 38.9 1988 192.0 60.8 31.7 1989 . 174.8 49.3 28.2

Table 3. Estimated abundance of winter flounder larvae in the Niantic River and the number and percentage of the production entrained from the Niantic River by developmental stage for 1984-89. The number of larvae from the Niantic River was based on mass-balance calculations.

Niantic River' Entrainment from Developmental Abundance Niantic River  % of the Stage (x 106) (x 106) Production 1984 Stage 1 3096 0.3 <0.1 Stage 2 743 24.8 3.3 Stage 3 364 26.5 7.3 Stage 4 255 6.1 2.4 Total 57.7b 13.0 1985 Stage I 4071 4.0 0.1 Stage 2 977 22.4 23 Stage 3 479 14.3 3.0 Stage 4 335 1.2 0.3 Total 41.9 5.7 1986 Stage 1 2696 1.2 <0.1 Stage 2 755 11.9 1.6 Stage 3 392 25.9 6.6 Stage 4 275 8A 3.1 Total 47.4 11.3 1987 Stage 1 3281 1.1 <0.1 Stage 2 919 21A 2.3 Stage 3 478 38.5 8.1 Stage 4 334 4.4 1.3 Total 65.4 11.7 1988 Stage I 5352 4.7 0.1 Stage 2 803 12.5 1.6 Stage 3 289 39.0 13.5 Stage 4 208 3.1 1.5 Total 59.3 16.7 1989 Stage I 4421 3.6 0.1 Stage 2 619 15.6 2.5 Stage 3 204 27.6 13.5 Stage 4 137 1.7 1.2 Total 48.5 17.3

'Abundance estimates are from Creeco and Howell (1990).

bSome total entrainment estimates may differ slightly from Table 2 due to rounding error.

1000 ' .

ME 0

800 -

0 600 X .

400 2'

.0 r= <0.94 200' p = 0.00i C) y = 18.828 + 0.458 x Z.

0 0 N 1000 2000

.Niantic River Station C Density (500 nil)

Fig. 1. Comparison of winter flounder larval densities collected during an ebb tide at the mouth of the Nianiic River and corresponding daily density estimates at station C in the Niantic River from the Gompertz function.

n FE 400 300 1 im 0

0 200 - . 0 va 0 .

0 U 100 -

C. .

z 0 .4.

0 100 200 '300 3

Niantic Bay Density (500 m )

Fig. 2. Comparison of winter flounder larval densities collected during a flood tide at the mouth of the Niantic River and corresponding daily density estimates in Niantic Bay from the Gompertz function.

IJI

. II..

1984 30 I--

CDC 20 c

._9 10 o Niantic River C I Other Source hi 0

1 2 3 4 1985 30 CD 0 20

-o

._~

c 10 o Niantic River Ct w 10 Other Source 1 2 3 4 1986 60 CDo 50

. X 5-40 30 0)

.Vc 01Niantic River 20 C 10 El Other Source a , ...

1 2 3 4 Developmental Stage Fig. 3. Estimated number of winterflounder larvae entrained by developmental stage from the Niantic River and other source(s) based on mass-balance calculations.

. . I I 1987 80 -

cDoC)

'- I) 60 -

CD0 c

40 -

o Niantic River F

.c 20 -

1E Other Source 0 .4 1 2 3 4 1988 120 CD 0 100 80 60 Li-q a Niantic River 40 b

c ED Other Source 1 2 3 4 1989 80 wCD

'1-4 60 40 C o Niantic River 20 C El Other Source 0

1 2 3 4 Developmental Stage Fig. 3. Cont'd.

)

Report to Millstone Environmental Laboratory. Ecological Advisory Committee

-Analysisof winter flounder'Larvae BY br. J. Crivello: University :of Corinecticut. Storrs, CT 2.12.02 This is a report of the: activities of the second year of a project designed to determine the most likely source population for winter flounder larvae'entrained by the Millstone Power Station. Staff scientists at the Environmental Laboratory, Millstone Power Station, Waterford, CT, provided samples. Larvae were collected from the Ni6ntic River, Thames River and an area due west of the Connecticut River, mostly off Westbrook (Figure 1). These areas were known to be, or adjacent to winter flounder nursery locations inLong Island Soun'd (LIS), and were

• near the Millstone Station,. Larvae samplfts were staged according to criteria presented in NUSCO (2000). Stage 1(yolk-sac) '&2 (pre-flexion) winter flounder larvae were collected'with a bongo net sampler with a 202-tim mesh net at variable depths from February thro~u"h April 2001. Larvae were sorted on board the sampling vessel and placed in 70% ethanol. -Atotal of 164 Stage 16 2 larvae' were collected from the Niantic River, 174 from the Thames River area and 198 from the

Westbrook area (Table 1).

gadAtlantic Ocean Niantic River Thames River Connecticut River Millstone Nuclear , -.

' Power Station' I

x _. ' . ".: Long Island Sound

• s.ox WestbrooN .

Figure 1. Approximate locations in eastern Long Island Sound (>) where larval winter flounder were collected for genetic st0c'k identification studies during 2001.

Larvae were also collected, using a 333-micron mesh net,'from seawater entrained at the Millstone Power Station from March June 2001. Larval samples collected oThrough during this time period were stratified so as to provide an accurate cross-section of larvae-entrained by the Station W~*, , -

(i.e., the maximal number of sample were collected during those dates when it was known that the maximal number of larvae are entrained in the Station). A total of 1067 stage 2, stage 3 (flexion) and stage 4 (pre-metamorphosing) entrainment larvae were collected (Table 2).

Table 1. Spawning Stock collection sites and number of larvae processed Collection site Date Number and stage Total Niantic River 2.27.01 35 - stage I 25 - stage 2 3.14.01 31 - stage 1 19 - stage 2 3.28.01 19 - stage 1 35-stage 2 164 Thames River 3.03.01 12 - stage 1 44 - stage 2 3.11.01 19 - stage 1 42 - stage 2 3.18.01 12 - stage 1 45 - stage 2 174 Westbrook 4.05.01 30- stage I 50 - stage 2 4.16.01 24- stage 1 34 stage 2 4.26.01 6 - stage 1 3 - stage 2 51 - stage 3 198 536 Table 2. Entrained larvae collection dates & amounts and number of larvae processed Collection bates Number and stage Total Collection bates Number and stage Total 3.28.01 14 - stage 2 14 5.14.01 - 28 - stage 2 4.06.01 4 - stage 2 66 - stage 3 7 - stage 3 11 10 - stage 4 104

• 4.09.01 45 - stage 2 5.21.01 43 - stage 3 34 - stage 3 79 20 - stage 4 63 4.16.01 47 - stage 2 5.29.01 41 - stage 3 95 - stage 3 142 10 - stage 4 51-4.23.01 14 - stage 2 6.04.01 15 - stage 3 176 - stage 3 190 19 - stage 4 34 4.30.01 18 - stage 2 6.11.01 29 - stage 4 29 160 - stage 3 178 6.18.01 18 -stage 4 18 5.07.01 29 - stage 2 1067 104 - stage 3 21 - stage 4 154

Following metamorphosing and settlement, juvenile winter flounder (10-71 mmn) were collected on June 22d and September. 18 of 2000 and July 3' and September 24'h of 2001 with a 1-meter beam trawl at two locations in the Ni'antic River (Figure 2; LR and WA); Juveniles were placed in 70% ethanol and then transferred to the lablfor analysis. A small piece of muscle tissue was used to isolate genomic DNA from each juvenile (Table 3).:

,Nianic

, . . \ ~~Rivurld.

-N 1 km'L~w 0I mi Nantic

.ay C.

Figure 2. Approximate locations in the Niantic River (LR and WA) where age-0 juvenile winter.

flounder were collected for genetic stock identification studies during 2000 and 2001.

.Table 3. Age-O juvenile collection dates and number processed ...

Collection"Site Date 'Number Collection Site, ate -Number Total (Niantic River) (Niantic River)

LR 6.22.00 57 WA, 6.22.00 35 92.-

9.18.00 30 . 9.18.00 35. . 65.

7.03.01 ' 70

, 7.0301 78

. 148

'- 9 24 0; " 45 . , ','

1 - . .

9.24.01' 18 ; '.'63 . -, -,--. :,

• *' - . * . t .

. ,1 .;, - - . 0 I ', -,' '. ' *

. - ,. .

• a: . . = . , - , - ..................................................... i .

C

Genetic analysis Genomic tNA was extracted from each sample by the method of Kaplan et aJ. (2001) from each larva and juvenile muscle sample. Genomic DNA was quantified with Pico Greent (Molecular Probes, Inc.) and comparison to a DNA standard curve. Stage I larvae provided 75-lOOng of genomic DNA that was sufficient for analysis of 6 microsatellite loci. Stage 2 through 4 larvae and age-o juveniles gave large amounts of genomic DNA.

To analyze each microsatellite loci, 10ng of genomic DNA was added to a solution containing 10mM Tris, 50mM KCI, 2.5mM MgCl 2 , 0.2mM dNTPs, 0.2 1tM forward and reverse primers to a final 101d volume. The forward primer was covalently modified with a t2, 03, or D4 fluorescent tag (Research Genetics Inc. Huntsville, Alabama). The sequence of primers is included in Table 4 as well as the PCR conditions for each primer set. Primer sequences were a kind gift from Susan Douglas and Doug Cook (McGowan & Reith, 1999).

After PCR, the samples were precipitated by addition of 2R1 3M NaAcetate pH 5, 2 tlIof a 1mg/ml glycogen solution and 50%d of absolute ethanol. The samples were frozen at -70'C for ten minutes and then spun at 30,000xg for 15 minutes. The supernatant was discarded and each sample washed with 7 5 td of 70% ethanol. The samples were dried and re-suspended in 301t1 of formamide that contained a 60-400 bp D>NA standard labeled with a D1-fluorescent tag (Beckman Instruments, Pal Alto, CA). The samples were then analyzed on the Beckman Seq-2000T h Capillary Electrophoresis System (frag3 protocol). Microsatellite products were identified by size with an accuracy of 0.25 bp by comparison to standards. Table 4 contains the size ranges and number of alleles for each loci.

Statistical analysis Statistical analyses of data were performed using PopGene (available as shareware at http://www.ualberta.ca/-fyeh/) and the NeuroShell' Classifier neural net software (Ward Systems Inc, Frederick, MD). Pop~ene calculated expected heterozygosities as well as an estimate of FIs (Cockerham and Weir, 1986). Tests for conformity to Hardy-Weinberg equilibrium were calculated using a Markov chain method. Tests for allele frequency differences were calculated using Fisher's exact test with pair-wise comparison of all samples at all loci that were then combined across loci. Genetic differences were also calculated.

The NteuroShellTM Classifier neural net software was used to assign entrained larvae to likely source locations. This software makes no assumptions about genetic differences among populations and builds an algorithm (i.e., a neural network) that best differ'entiates differences among the populations. This neural network is then applied to the entrained data. The network is trained on a file (i.e., the training file) that contains the genetic information about larvae collected f rom the three source areas.

Control experiments to determine the accuracy and resolving power of this approach were carried out in the following manner. A validation experiment was carried out in which the network was trained on one-half of the training sets and then used to classify the other half of each training set. This was repeated 100 times by randomly selecting which samples were included in the training set and which were classified. Through these experiments a mean error rate confidence value was generated. Then the network was trained on the complete training sets (TNN). In a second set of control experiments, the source location of each larva within the training groups was randomized (n=100). The randomized training sets were used to develop networks that were applied to entrained samples (RNN).

Af ter the control experiments were carried out; the TNN was' used to classify all entrained larvae and juveniles to the most likely geographical source. The TNN generated a confidence value for the classification of each unknown sample from 0-1.0. Samples were assigned to a geographical source population if confidence value exceeded 0.75. A confide~nce level of'0.75was chosen for the following reasons: 1)this confidence level would be at least 3 times as great as the next high confidence value and 2) it represents the lowest confidence value wiith e'rror less than 5%

(determined by.multiple classification of the samesample).'In some cases, 'the TNN could not asign a sample to a source area with'0,75 confidence but was able to determine that'the'sample did not

'belong to a specific:source population (less than 0.05 confidence); If the assignedconfidence value was the some or similar for all three source populations the som'ple wa sasssigned to an unknown group. This gave 7 possible groups: Niantic River, Thames River, Westbrook' (Connecticu't River),

not-Niantic River, not-Thames River, noi-Westbrook or'an i'nknown location '

Results: , .' '

A major goal of this year's effort was to increase the number of identified alleles, to increase the number of larvae in the source populations and to make the collection of entrained larvae represent with the overall entrainment (i.e.; the greatest number of analyzed entrained larvae should come from the date in which the greatest number of larvae are entrained by the.

plant)

-These objectives were meet with an increase of 30Y% in the number of source population larvae (536 in 2001'vs:. 423 in 2000). The number of entrained larvae also increased by 3-fold (1067 in.2001 vs. 360 in 2000) and the collection of larvae peaked during late April usually when the greatest numbers of larvae are entrained at the plant, although in 2001, entrained larvae were also abundant in May (DNC, in preparation). The number of identifiable alleles increased from 29 in

.2000 to 135 alleles in 2001, thereby increasing the resolving power of the analysis.

Table 4. Primers and PCR conditions, icrosotellite sizes, and number of alleles.

Loci Primer Sequence Product Annealing rc Allele Number

. - .: .length (bp)

P157 D2-AGTGCAACAACAGATTCCAG(+)93-195 500C 40 GCAGAATGAGTGAAATGTGG(-)

P159 t3-GTGT6GAG&TCAATGC(+)85-209 :530 C 11 GGAGCATCATTCATACAC(-)

A441 .. D2-CAACT&T&GGTATGTG6CCTG(+) .89-213 55 0C .. ' '-- 25 GT6TCA6CACTGTGC1TAAACC(-).

D34 b4-GCCTGGTCTCATTGTGTTCC(+)89-315 550 Ci 27 A&GTTAAATGATTTCCTGAAGCTG(-)

I29 D3-GCTTCGGTTACACCTTTGC(+)91-223 - 550C  : -4 AGGACAGTGAGGATGTCCG(-'. . -

J42 D4-CACAAACTCAAGATGTTGCG(+) .95-185 :55C - ' - 28 AAGCTCACTGGAAAATAATACCC(-) -

D2, D3 & D4 refer to fluorescent tags on 'the forward primer. ' .'

-. , b . . . -;. .,,...,.

Individual larvae could have 12 possible products (2 for each primer set) if each locus was heterozygous or one if the locus is homozygous (to a minimum of 6 products). The source populations were examined by POPGENE statistical package. In Table 5, the relevant characteristics of each microsatellite loci are provided. The p value refers to the likelihood that the loci obey Hardy-Weinberg rules (a p value >0.05 suggests that it does not). Loci p15 9 and I29 don't always obey Hard-Weinberg rules suggesting that they might be inbred but the Frs values don't suggest that the loci are inbred. The Het0 bs values refer to the heterozygosity of the loci among the tested samples. The heterozygosity varied from about 10-80%, which is typical for microsatellite loci. Five out of the 6 loci were very heterozygotic (thereby increasing their resolving power) while one (I29) was not very heterozygotic. In the future, it may be worthwhile to substitute a different marker than the I29 to increase resolving power. It is interesting to note that on the basis of the heterozygosities, the Thames River larvae were less heterozygotic than the Niantic or Westbrook. The Westbrook larvae were the most genetically diverse and may reflect more than one population as these larvae were collected in the open waters of LIS rather than within a specific estuary.

Table 5. Summary statistics for 6 microsatellite loci surveyed in winter flounder.

Population Microsatellite Loci P157 P159 A441 134 I29 J42 Niantic P value 0.0000 0.2798 0.0000 0.0000 0.2759 0.0000 Het~bs 0.7481 0.3926 0.6000 0.7185 0.0667 0.5333 N 148 148 148 148 148 148 Fis 0.1485 -0.0515 0.3151 0.1823 -0.0345 0.3597 Thames P value 0.0000 0.9817 0.0000 0.0000 0.0000 0.0000 HettbS 0.8129 0.0719 0.5971 0.5972 0.1000 0.3669 N. 154 154 154 154 154 - -- 154 Fis 0.0937 -0.0281 0.3263 0.2985 0.1078 0.5927 Westbrook P value 0.0000 0.8865 0.0000 0.0000 0.1594 0.0000 Het0 b5 0.7744 0.2359 0.6821 0.4974 0.0103 0.3538 N 195 195 195 195 195 195 Frs -0.0062 -0.0572 0.2133 0.4256 -0.0052 0.5716 P values indicate the probability of conformity to Hardy-Weinberg expectations by the Chi-squared method. N is the sample size.

The next comparison was to see how distinct the source populations were from each other.

This is determined through the FST (Fisher's statistic), which Is a numerical measurement of the genetic difference, with values greater than 0.05 considered to be significantly genetically distinct and values between 0.025 and 0.05 considered to show less significant but potentially important genetic differences. Table 6 has the results for 2000 A 2001. It is interesting to note that the Niantic River population is distinct from the Thames &'Connecticut River area populations in both years. The Thames River larvae are also distinct from the Plum Bank and Westbrook larvae. This

genetic.differentiation is geographically linked; i.e., those source populations that most geographically distinct are the most genetically distinct The other interesting' point isthat the genetic differences were relatively similar over the last two years, suggesting a temporal stability.

Table 6. The genetic difference between training groups.

FST FST 2001 2000 Vs. Thames Westbrook Thames Plum Bank Niantic 0.0385 0.0571 0.0384 0.0518 Thames ---- 0.0545 - 0.0425 '

Westbrook ' -

The NeuroShell neu'ral network classifying program was then trained on the files 'containing the genetic differences between larvae collected in the Thames, Niantic and Connecticut Rivers.;

Control experiments were carried out in the following manner. Initially, the neural network was trained on half of the larva from each training area and then used to classify the other half of larva from the same area. Secondly,'the order of the samples within the training set(s) was randomized but the correct source location was maintained, Thirdly, both the order and source6of the: larva in the training set was randomized. -These controls demonstrated that this approach had at least 98.57w accuracy in classifying unknown larvae to one of the spawning areas. Samples were-assigned to a geographical nursery pojulation if their probability exceeded 0.75. A confidence level of 0.75 was chosen for the following reasons: 1)this confidence level would be at least 3 times as' great as the next high confidence value and 2) it represents the lowest confidence value with error less than 5%(determined by 'multiple classification of the same samples with ne'ural networks). In some cases, the network could not assign asample to a nursery area but was able' to determine that the sample did not belong tooa specific nursery population (essentially less than 5% confidence). If the assignment confidence was the same for all 3-nursery populations the sample was assigned to an -

unknown group. This gave 7 possible groups: Niantic River, Thames River, Westbrook (Connecticut River), not-Niantic River, not-Thames River, not-Westbrook or an unknown location.

Itis clear from Table 7 that there were very few larvae that coul iot _ be assigned to one of the 1' 6 groups (essentially not from any of the tested source areas). The greatest number of entrained larvae came from the Westbrook area (34a/0) and approximately equal number classified to the'other spawning stocks (Niantic Piver 24/s, Thames River 21%). Peak entrainment of Niantic.River larvae was in mid-April. Peak entrainment of Thames River larvae was in late May,-

early June, while peak entrainment of Westbrook larvae occurred in early May at the same time of peak entrainment into the Power Station'(Table 7).

Table 7. Classification of larvae knoWntnurs'ery areas using thetraingd ntane networka eto fentrained Classification (values.are expresed as percentage'of'total)'- :?'i Niantic -. ,Thames il West--.f;. Not' Not' -

River River brook Niantic Tames West-1 known River River ' .Brook Collection Date 3.28.01 46.2 7,7 15.4 .' 23.1 0 7.7 4.09.01 14.6 29.2 ,34.8. 6.7" 7.9 3.4 4.16.01 29.5 22.7 25.0'. 6.1 6.1 ' 9.1.. 1.5,,

4.23.01 35.6 23.3 21.7 5.0 2.2 11.7 0.6 4.30.01 27.2 15.4.. 33.3 '8.0 9.9 4.3 ' 1.9, 50701 -. 16.2 .. 14.0.- 51.5 9.6- 5.9-- .1.5- ,zC4. 1.5 51401- . 170,

.2 - 5,13 5.14 457

'46V-- 9.

-4.6 3.i4 5.21.01:, ' 21.7;- 304. '319. .- 10.1 0- 4.3 "' 1.4 5.28.01-. 188. ,29.2 292 . .4.2' 10.4 2.1 6.3 6.04.01 6.9 -24.1, '48.3 17.2. - 34 -0

'6.11.01- 18.5. 18.5 -370 18.5 . 7.4 .0 0 6.17.01 i 23:i ;38.5 7 7.7 -i.7 715.4 0,,,

V. of all- - 24.1 21.0'- 33.5l "'$` 8.1 ' '5.8 1.8 ' '5.71 sampled larvae , .- '.

Classification'to one' of the known sp'awningareas required 'at easta 0.75.cnfidence. Classificationa to the. not-spawning area'columns required. that one'of th e s aassified as having . -

<0*05tconfidence of being thespawning' area for that Iarsvae.t The cn was for"'

larvae thatfhad equal confidence'to belogto' any of the spawning'groups.

'Juveniles thatwere'olected in 2000A&2001 ron'the Niantic River' were'compared to the tested spawning stocks (Tabje 8). Once again, very, T __Juveniies could not; be assigned.to one of the t six groups. There was no signifaicatdiffei'ence in? the classification of,the juveniles collected in'.",

early'or late summer of both 'e'ars.' LR station, located ne the mouth of the river had initially -'

fewer juveniles classified to th eNidntic spawning stock-inJuhe 2000 than the WA site that isz' -  : i

more upriver.'However'lessdifferen c'ewasseen';tem 20 0orin2001. 'Thegreat' majorietyb-'

- of juvnieswere' cla'sifie'd t'i theRiver Niintic' andWest rook areas and'not tothe .Thme R'iver . I ;

Also of interest'was the size of juveniles assigned to source populations, iLe., were larger juveniles produced within the Niantic River as opposed to smaller fish entering the River from other areas. A one-way analysis of variance indicated no significant difference in the juvenile size by year, month, and station except in September 2000 at the lower river site, where juveniles originating from Westbrook were significantly larger (mean of 43 mm) than those from the Niantic (36 mm) or Thames Rivers (35 mm).

.4

Table 8. Classification of juvenile winter flounder fo nursery areas using the trained neural networks.'

Classification (values are expressed as percentage of total)

- June, Septeml

ber June,` September' June; Sept'ember June. September

' 2000 2000I ' 2000' - 2000 2001'2 '2001 2001 ' 2001 LR LR WA -WA ' LR - WA, "WA Niantic 21 23 51 . 26- .20 28 16 :17.

River Thames: 11 10 .11, 29 24 9 1;3.. 3 . '. . 1l '

River: .;

West :4Q0 37 17 ' 37 27 36 -44 33

-Brook  ; -.

Not' . 5 10 0 0 -16 5 16 6 Niantic . 7 .

. . I I.

Not .14 -:7.' -11  !-0 .4 . *17-5.

9 .17 -

. 1 . -

Thames Not  ; 13 66 9..9-I. , 5 . ,.

.2 :-: .11- -.

West Brook Unknown -2 0.- ' 3 3' 0 0;' 6 Conclusions A Discussion:

Previous work suggests that there are discrete breeding stocks of winter flounder, based on morphometric, meristic, tagging studies' and 6ther factors (Pearcy'1962a, 1962b, Ae`rry et al."

1965). Work over the past few decades by the' Connicticut Department of -Environmental Protection has suggested that 'distinct spawning and nursery areas for winter flounde'r exist within LIS (Howell et al., 1999). One such nursery area is iMthe Niantic River that is nearby'o othe Millstone.

Power Station. In general, marine fish show less genetic differentiation than freshwater or -

anadromous fishes since marine environments are less fragmented than freshwater environments-*

(Carvalho, 1994; Ward et al., 1994).-Marine organisms with a planktonic phaselhove a high potential 7a:

for physically and biologically mediated dispersal. Nonetheless, evidence does suggest that larval retention (Jordan et al., 2000), cohort fidelity (Sinclair 1988), geographical structures and impediments (Ruzzante et al., 1998) and natal homing instincts (Nielsen ett al., 1999) may limit gene flow. Marine species such as cod, hake, herring and squid have previously shown little genetic' population differentiation by allozyme markers and thought to be homogeneous over large '

geographical ranges. Recent examination with microsatellite loci has'revealed fine levels of -

population structure (Bentzen'et al., 1996; O'Connell et al., 1998, Lundy et al, 1999,-Shawet al.,

1999)..

Microsatellite loci form a class of highly polymorphic and informative regionsdf, chromosomal DNA that have found great usage for studies of intra-specific population structures, as well as hybridization evehts, linkage mapping, paternity testing and pedigree analysis (Hughes4&

Queller et al., 1993, Roy et. al., 1994, towling et. al., 1997). Although statistically -significant:,.

genetic differences do not always have biological significance (Waples 1998)-they can playoan-

important role in,fishery.hanagenentm issues or in instances of efforts to recover commercial ,,,J .

fishing industries.

• uring normal Station operations, cooling water,withdrawn byethe Station causes the entrainment and deth of jiIons of winter floun de orIae. issue of plant impact due to winter.

flounder larval entrainm'ent has been addressed by populationidynamic modeling (Lorda'et al.,

2000).

This modeling has;focused onthe Niantic River winter flounder stock and among the information required is an estimate of the annual reproductive output removed by entrainment; This fraction was determined using an indirect metho'd.(the mass-balance model). However, the present genetic analysis provides a more direct quantitative estimate of entrainment loss by source population.

Thus; larvae in early developmental stages were collected from areas known to be near spawning:

grounds. The young stage 1 2 larvae appear to have limited geographical dispersal and hence likely

• retain genetic differences Comparison of, genetic'differences between these groups demonstrates a relatively high degree of difference (Nei's genetic difference >0.05). This genetic differentiation"'

• is geographically based with the greatest difference seen between the Westbrook and the Thames River source areas that are separated by 20.5 miles. Though only separated by 5 miles, the Thamnes" and, Niantic River source areds had relatively substantial genetic separation between them (Nei's .

genetic difference = 0.036), suggesting that one or more factors might be limiting gene flow.

The:

same genetic differences were seen in larvae collected in 2000, suggesting a temporal stability tof these genetic differences.

There is no apparent geographical or physical barrier to gene flow between these areas so

-natal homing instincts or selective pressures may be responsible.-'

These differences were sufficient to provide'the resolution to assign entrained larvae or older, settled juveniles to the tested populations. Many different approaches have been used to assign individuals of unknown origin to populations based on the genetic distance between individuals and populations (e.g neighbor-joining trees, Estoup et al., 1998, likelihood of the multi-locus genotype and Bayesion.

Cornuet etoa.--, 1999).'A key component 'of any of these approaches is th'atthey have theability tole.

correctly. assign individduals, but a i'm n drawb'ack is that if the origin of the individual is not represented in the reference populations'most 'mthods will stifl designate a wrong iopulation of, i; .-- 0 origin (6ornuet et'aL', 1999). Maany, approaches 6re based on two explicit assumptiohs that all loci areat equilibrium and 't. linkge eqiuilibrium. Other constraints'are the levelsof' rardy-Weinberg differentiaticn between tested populations: the ability to sample all, orvirtually all of-the '.' -.

potentially contributing stocks, theteiporal s tabilit ohe microsatellite markers and a large9.6:'i) l pr9en tonppcaios sample size that. contains re'-etation ellitcherkerand n for all donor populations (Letchir and King 1'999; Smous'ei et al., 1990). Newe'r apiproachis have attempted to- overcome these limitations (egi Bayesian)'andol

- i maximizing the accuracy of 'assignment' depends in part on the FST values, poulation sizes and loci6':i

number;. The largedifferences in FTvalues amongJ ested reference populations in this work,*'

coupled with large popsu ation 'ver'je 150.individuais) hi(on and ioci with large numbers of alkl&')

(135) should allow for th6'maximal'6ccuriacy iniassigninent to reference populations. It is clear that we have not sampled from all of the possible'd6nor'stocks in LIS or surrounding areas, but on a smaller geographical range across'which all stocks can be sampled adeq uately minimizesfocusing .'

this' "

• problem.

Recently, 'several investigators havebe-iin to use non-supervisedo artificia 'eubal  :

networks (ANN or'NN't'adigs iiindiv'idualstwo;popuiations based on geeticdifferences (Bross I-  :

et al.,- 1999;.' 2001 -WU Catherine'&2000): ese neural networks'are trained on populations with.' a'a. -

known genetic' differences and' thinbaplied. to dnkhvwn individuals. Neural networks make no

'prior' assumptions-about.'theX haraeristics of-the training sets and develop olgorithm's that maximize its

ability to correctly identify unknown individuals to populations. These ANN hove been used in awide,'

( range of areas including assessments of fish abundance and spatial occupancies (Brosse et. al.,

1999):

The TNN used in this work was trained on microsateflite data generated from the populations found in the Niantic, Thames and Westbrook areas. To test the accuracy of this approach for correct assignment of individuals to populations, confidence values were generated and classification was compared to neural networks trained on randomized (and incorrect) training, sets (i.e., the RNNs). The RNNs lost all ability to classify individuals and classification was' essentially random. The TNNs classified individuals with high accuracy. A confidence value below 0.75 was the lowest confidence used to assign an individual to a source population. Even when the TNN could not assign an individual to a specific population with at least 0.75 confidence,'it was capable of determining that an individudlwas not from a specific population ('0.05 confidence).

When the TNN was applied to the entrained larvae and collected juveniles, the assignments, namely

'~

that not all of the entrained larvae were from the Niantic River stock, are in agreement'with other approaches (e.g., mass-balance model based on larval dispersal). Previous mass-balance approaches (NUSCO, 2000) indicated that during 1984-98, about 12% to 59% of 'thentrainedlarvae were from the Niontic River with 'along term average of 25./4-that is in agreement with the'riesults seen here (24.17.). Previous work has also suggested that larval entrainment from the Niantic River area is fhighest earlier in spring. This likely occurs because this area is closest to the Station and larvae displaced from'the River make up a greater' propbrtion of all dlrvae found in Niontic Bay. As the season progresses more larvae from other sourtes are transported by tidal currents into this area and locally produced larvae are less dominan* Large assignments were made to the tested population that lies 15 miles to the west near the Connecticut River. The Thames River, which is 5 miles to the east, contributed for fewer larvae. This suggests that currents and tidal flow

( - transport winter flounder larvae in April and May predominantly from a west-to-east direction. This is supported by the fact that the contribution of the Thames River population is also highest June.

The assignment of larvae to'the Westbrook (i.e., Connecticut River) area reaches apeak in mid-May, when the contribution of larvae from the Niantic River has reached a nadir. The peak entrainment in the Station occurs in late April & early May when the contribution from the Westbrook area is greatest.

Over 80%/ of -the larvae could be definitively assigned to one of the tested populations'with at least a 0.75 confidence value. Of the remaining 207O, the TNN could determine'that they did not belong to' one of the populations and the confidence'values were roughly divided between the remaining two. There were very few larvae (2%) that could not be assigned to the tested populations or were known not to have come from a specific population.

This approach is also able to classify the most likel 'source population of young-of-the-year juvenile flounder. Though only the genetic differences between larvae collected in 2001 w'ere used in the TNN, we had previously characterized larvae in 2000 and found the'genetic differences between the source populations to be almost identical as they were in 2001.'Juvenile flo"under of the 2000 & 2001 year class that were collected in July and September of each year from two-sites in the Niantic River were then assigned to the tested populations with the TNN. The lower river site had initially a smaller proportion of juveniles assigned to the Niantic River than themid-river :

site, where there were more juveniles resulting from the Thames River. Also, there were substantial numbers of juvenile flounder from the Westbrook are-that were captured in thie Niontic River.QOverall, in 2001, 21% of the juveniles were classified as of Niantic River origin, 15% from the

( '- Thames River, 25% from the Westbrook area and the source of 28% of the juveniles 'could not be

determined.These results clearly demonstrate that.thobu'the st'age 1 lar1va'e found inup-river spawning areashave su stantialgenetic differences with loaraefrohmother spawninn areasthe young-of -the-year that settle in the Niantic River are from a wide geographic area.,

aIn terms of fisheries management. this 'approach allowsfor the estimation of the impact of commercial operation (i.e., the Power Station)' on specific flounder spowning.

groups and also allows for the direct linkage between a flounder spawning stock and recruitmentto juveniles.

these factors are critical components of any'fishery management pln that attempts Both of ,

to maintarin a

- - coinrcilly~-viable winter, flounder population in LIS. '

Future experiments: . ..

If A*s' ex t ' res,_

cont W.,' 'in;iu.>ed.

If these experiments were continued for anot her ,I'would recommend that we do6.

so at the same level of, effort as this year.. Collection fbr'a'additionail'year will1allow us--..'

to ~well eterminethe variaL ance in the genetic diffeiseric bet een the spawning population.

nce as astheyvariance in tie &trainment of. 1arvae If. this~!;ora o iformtion is correlated, populations",iit with hydrodynamic information (tides, currents, spring astc.ndapplied to,

,, current plant- oas,,then it' might be possibli'to pre'ict the entrainment from'.

^,- s ' spawning areas in future years ,with a high lev$el ofconfidenc4& "'

With information.from a third year;' it will be,'possible todetermine Ne, the effeciveI.-

adult spawning population in the different river.areas.' Ne refes to the amount of ..

,, adults that contribute the genes to 957.4 of the population and is a us'eful valiuefor. -

fishery management issues and identifies the number of females producing

. fou~nd in each river system.'

the larvae

References:

4 t -

• 4 , *;

. 4f , ,*,_,,

Bentzen, P.. C.T.-Taggart, t.E.; Ruzzante and D.Cook. 1996.'Micro.sateliit'polymorphism the population structure of Atlantic and

. cod (Gadu5 morhua ) intheJ. Nothwst '. Atlantic. Can. Fish. .- -

Aquat. Sci., 53:2706-2721. .- .i- , .-, 7 Berry. R., S.Salia, S.and t. Horton. 1965. Growth studies of wintei flounder,

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94:259-362. ., r-Brosse, S. J.F., Guegan,.J.N.,; T uienq and:S. Lek 1999. The use of'reural net'iorks to,;'

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Brosse, S. J.L. Giraudel and S.Lek:'2001. Utilization of nonr-suoervisid neural principal component analysis to'study fish assemblages. Ecol. Model. 146'159A166. networks-and ;`'

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.populatons. Ann. Hum. Genet. 50:271-81... ' 4 -

-- Cornuet, JM. Piry, S.- Luikart, . Estoup. A.and M.Solignac. 1999. New methods employing multilocus genotypes to'select.or exclude populations as otrigins ofrndiduals 2 ,- .. ~ ~

Genetics, 153:1989 2000.-'.-"~,.-4-- -  ; 4 - ; .1 ;j s .- - -A - --- 4

- . . . ,DNC 2002,. In preparation: Winter Flounder Studies. Monitoring the marine Long Island Sound at Millstonne Nuclezar Power'Station, environment'of' .

tWterford. CT. 'Annual Report 2001. -

Dominion Nuclear ConnecticutI&c -'` - -: - . ' , i-

Dowling, T.E., R.E.; Broughton, and B.D. DeMarais. 1997. Significant role for historical effects in the evolution of reproductive isolation: Evidence from patterns of introgression between the cyprinid fishes, Luxilus cornutusand Luxilus chrysocephalus. -Evolution, 51:1574-1583.

Estoup, A., K.Gharbi and M. SanCristobal. 1998: Parentage assignment using microsatellites' in turbot (Scophthalmus maximus) and rainbow trout (Oncorhynchusmykiss) hatchery populations.

Can. J. Fish. Aquat. Sci., 55:715-25 -;p Howell, P.T., D.R. Molnar and R.B. Harris. 1999. Juvenile winter flounder distribution by habitat type. Estuaries, 22:1090-1095.

'Hughes,';C.R. and D.C. Queller. 1993. Detection of highly polymorphic 'microsatellite loci in a species with little allozyme polymorphism: Mol. Ecol., 2:131-137; Jordan, R.C., A.M.. Gospodarek,^E.T., Schultz' R.K., Cowen, and K.Lwiza. 2000.

Spatial and temporal growth rate variation of bay anchovyo(Ancloa mitchili) larvae in the mid Hudson River Estuary. Estuaries; 23:683-689.

Kaplan, L.A.E., J. Leamon and J. F. Crivello. 2001. The development of a rapid and sensitive, high-through-put protocol for RNA-DNA ratio analysis. J. Aquat. Animal Health, 13:246-256.

Letcher, B.H. and T.L. King. 1999. Targeted stock identification using multilocus genotype familyprinting'. Fish. Res., 43:99-111.

Lorda. E., D.J., Danila and J.D. Miller. 2000. Application of a population dynamics model to the probabilistic assessment of cooling water intake effects of Millstone Nuclear Power Station (Waterford, CT) on a nearby winter flounder spawning stock. Environ. Sci. Pol.,

3:5471-5482.

Lundy, C.J., P.. Moran, C., Rico, R.S., Milner, and G.M. Hewitt. 1999 Macrogeographical population differentiation in oceanic environments: a case study of European hake (Merluccius merluccius), a commercially important fish. Mol. Ecol., 8:1889-1898 '

McGowan, C.and M.E. Reith. 1999. Polymorphic microsatellite markers for (Hippoglossus hippoglossus. Molecular Ecology, 8:1761-63.

Atlantic Halibut, Nielsen, E.E., M.M., Hansen and V. Loeschcke. 1999. Genetic variation in time and space:

Microsatellite analysis of extinct and extant populations of Atlantic salmon.

Evolution, 53:261-268.

NUSCO. 2000. Winter flounder studies. Monitoring the marine environment of Long Island Sound at Millstone Nuclear Power Station, Waterford, CT. Annual Report 1999. Northeast Utilities Service Company, pp. 9-111.

O'Connell, M., M.C., Dillon, J.M., Wright, P., Bentzen, S., Merkouris and J. Seeb.

1998.

Genetic structuring among Alaskan Pacific herring populations identified using microsatellite variation. J. Fish Biol., 53:150-163.

Pearcy, W.G. 1962a. Ecology of an estuarine population of winter flounder, Pseuopleuronectesamericanus(Waldbaum). II. Distribution and dynamics of larvae. Bull. Bingham Oceanogr. Coll. 18:16-37.

Pearcy, W.G. 1962b Ecology of an estuarine population of winter flounder, Pseuopleuronectesamericanus(Waldbaum). III. Distribution, abundance, growth, and production of juveniles, survival of larvae and juveniles. Bull. Bingham Oceanogr. Coll. 18:39-64.

Roy, K.and D. Jablonski, and J.W. Valentine. 1994. Eastern Pacific molluscan provinces and latitudinal diversity gradient: No evidence for 'Rapoport's rule". Proc. Nati. Acad.

Sci. USA.,

91:8871-8874.

Ruzzante, D.E., C.T., Taggart and D.Cook. 1998. A nuclear DNA basis for shelf-and bank-scale population structure in Northwest Atlantic cod (6adusmorhua): Labrador to Georges Bank.

Mol. Ecol., 7:1663-1680.

)'

ShakleeJO.B. and P. Bentien. 1998. Genetic identification of stoks of marine fish and:

shellfish. Bull. Mar. Sci. 62:589-621" ' -

Shaw, P.W.; andnCt, Turan, Wright, J. O'ConellM.'and 6.R.'Carvalho.1999.

Microsatellite DNAf analysis of; population structu're, in Atlntic rring ( c th ,,iwt dire comparison to allozyme and mtDNA RFLP an'alys-es. Heredity' 83:490-499.^

'Sinclair, M 1988. Marine populations. An essay on population regulationi and speciation.:In:

Recruitment. of Fish in Oceanography., Volume 1,Washington Sea Grat, Seattle' WA, 252 pp."

Smouse, P.E., R.S., Waples and J.A.Tworek. 1990. A genetic-mixture canalysis for use with incomplete source population data. Can. J Fis_.'Aquat. Sci.,47:620-634.

Waples, R.. 1998. Separating the' Wheat From'the Chaff Patterns of Genetic Differentiation in High Gene Flow Species. J. Hered.; 89:438-450.'- '

Wrd, R.D., M., Woodwark and DO.F.'Skibinski. 1994; A comparison of genetic diversity leyels in marine, freshwater, and anadromous fishes. J. Fish Biol., 44:213-232:

I II

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Monitoring the Marine Environment of Long Island Sound at Millstone Nuclear Power Station 1991 Annual Report i

f.

Northeast Utilities Environmental Laboratory.

L April 24, 1992 Waterford, Connecticut

0 01 ' M-I i ml MILLSTONE PT.

C0 I BL PT.

Fig. 3. Location of stations sampled for larval winter flounder during 1991.

using a single GO flowrneter mounted in the center of pearance of larvae at each station, tows were made at each bongo opening. The sampler was towed at night during the second half of a flood tide. From approximately 2 knots using a stepwise oblique tow 1983 through 1990, sampling was conducted 2 days a pattern, with equal sampling time at surface, mid- week. In 1991, sampling was reduced to I day a week depth; and near bottom. The length of tow line neces- (NUSCO 1991a). At NB, single day and night tows sary to sample the mid-water and bottom strata was were made every two weeks during February and at determined by water depth and tow-line angle measured least once a week from March through the end of the with an inclinometer. The nets were towed for 6 larval winter flounder season. During 1991, all day minutes at stations A, B, and C (filtering about 120 collections in March were made during a flood tide and n3 ) and 15 minutes at station NB (filtering about 300 in April and May all night collections were taken m3 ). One of the duplicate samples from the bongo during a flood tide. Jellyfish medusae at the three sampler was retained for laboratory processing. river stations were removed (1-cm mesh sieve) from The larval winter flounder sampling schedule for the samples and measured volumetrically to the near-Niantic River and Bay was based on knowledge gained gomlm during previous years and was designed to increase data Three additional stations in Niantic Bay were sam-collection efficiency while minimizing sampling pled during 1991 to deternine larval winter flounder biases (NUSCO 1987). Larval sampling at the three abundance and spatial distribution relative to tidal Niantic River stations usually started in mid-February. currents. Station RM was located south of the mouth From then through the end of March, daytime tows of the Niantic River, MP west of Millstone Point, were conducted within 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> of low slack tide. and BL east of Black Point (Fig. 3). Six-minute During the remainder of the season, until the disap- stepwise oblique tows were made with the bongo 12 Monitoring Studies, 1991 j mY1 i AZ-MoAJfIJ 7Ai I

sampler described above. tSampling was conducted A 202-lm mesh net was attached to a net ring within within one hour fromrthe time of maximum ebb and the net chamber. Seawater was filtered though the flood tidal currents twice a week from March through net, which removed larvae, and exited through the May. Collections were made during daylight in bottom of the net chamber via a 7.7-cm hose connect-March with 202-Itm mesh nets and during night-time ed to a gasoline-powered pump (Pacer Pumps, Model in April and May with 333-ltm mesh nets. For SE3SLL). Water volume was measured with an station MP, neither ebb nor flood samples collected electronic in-line flowmeter (Omega Engineering, on March 8 onda lod

s. Inc.) located in the pump discharge pipe; flow rate and anrig 991, the vertical distrbution of yo total sample volume were registered on a remote (Stage 1) winter flounder larvae in the Niantic River readout box. Thepump capacity was about I m3 per was determined using a pump sampler (Fig. 4). The minute and total sample volume ranged from about 5 sampler was designed to collect larvae from discrete to 10 m3 . During sampling, the research vessel was depths -and remove them before they passed through anchored from both the bow and stern to prevent the pump, which would have destroyed yolk-sac movement; this stability was particularly important winter flounder larvae. The intake of the sampler while sampling at the sediment-water interface. A consisted of four 103-cm diameter inlets connected to total of 12 sets of samples were collected during a 15A-cm hose; the inlet openings were perpendicular February and March at the three Niantic River stations to the bottom. The intake could be raised and lowered (Fig. 3). Each set consisted of collections at the to sample discrete depths. The 15.4-cm hose was surface, mid-depth, near bottom (approximately 0.3 m connected to the top of the net chamber located aboard above the bottom), and at the sediment-water interface.

the research vessel. The net chamber was fabricated Five sets of samples were collected at station A, six at from fiberglass and had a diameter of 0.6 m, was I m B. and only I at C. Station C was located in the deep, and was designed to withstand a perfect vacuum. navigational channel, where strong tidal currents made sampling difficult Net Chamber Discharge I ntake t

Fig- 4. Schematic of the pump sampler used to collect winter flounder larvae in the Niantic River during 1991.

Winter Flounder 13

-U

years in both the river and bay, except for the river in with paired ebb and flood tidal stage collections tak.

1988. Dates of peak abundance for older larvae were during times of maximum tidal current; collections i similar in both the river and bay and because those for station NB were made only during a flood tide..

Stage 2 larvae differed considerably, this suggested comparison of abundances based on the a parametc that most larvae were probably flushed from the river from the Gompertz function (Eq. 2) indicated larg during Stage 2 of development differences between ebb and flood collections at th Previously, it was shown that water temperature three new stations (Table 15). Two distinct group' may affect the rate of development for winter flounder were evident on the basis of abundance. Larvae were larvae, where growth and development were positively most abundant for RM-flood, MP-flood, and BL-cbl' related to temperature (NUSCO 1991b). The warmer collections, with ca values ranging from 42t than normal water temperature during the larval season 5s322. Similarly, lowest abundances were found for in 1991 (Table 6) and the early peaks of Stage 3 and 4 RM-ebb, MP-ebb, and BL-flood, with a values rangi larvae in the river and bay during 1991 suggested a ing from 1,865 to 2,124. The NB-flood collections relationship between water temperature and the rate of were also within this lower abundance range. The larval development The mean March-April water 95% confidence interval indicated good precision of temperature in the bay (determined from a continuous the abundance estimates, except for both ebb and flood recorder in the intakes of Units I and 2) in 1991 was collections at station RM. The low of precision in 6.8 0 C (95% CI of 6.5-7.21C), the highest of the estimating the other two parameters (p and Kc)was preceding 15 years (1976-90), which had a mean of also evident for RM. Many of the samples collected, 5.10 C (95% Cl of 5.0-5.2C). Buckley et al. (1990) atRM had heavy detrital loads, particularly during ebb reported that egg incubation time was inversely related collections, which may have affected the quality of to water temperature during oocyte maturation and egg sample processing.

incubation. The early peaks of Stage I and 2 larvae in Abundance curves were constructed based on the the river during 1990 was related to higher than aver- Gompertz density function (Eq. 3) to examine tempo

- age February water temperatures (NUSCO 1991b). ral abundance at each bay station (Fig. 14). Due to The average February 1991 water temperature (4.80 C the low precision of parameter estimates for station 95% Cl of 4.64.9C) was even higher than found for RM, only limited interpretations were made concern-1990 (43 0 C: 95% Cl of 4.14.5oC), but the dates of ing temporal changes at this location. The estimated peak abundance for Stage I and 2 were near the aver- abundance for RM-flood collections began to exceed age for the 9-year period. Based on the results from RM-ebb in early March and continued throughout the

• } field data, it appeared that water temperature affects season. MP-flood abundance was greater than P-ebb larval developmental rates, but its effects on oocyte starting on March 23. In contrast, BL-ebb abundance' Op m ,ation and egg incubation rates was not clear. exceeded BL-flood beginning on April 5. The shape During 1991, a special sampling program was of the abundance curves and density estimates were, conducted in Niantic Bay to examine larval winter similar for MP-ebb, BL-flood. and NB-flood (Fig. 5).

flounder temporal and spatial distribution and abun- Since tidal current patterns in Niantic Bay culd'

-1 dance relative to tidal stage. Three new stations (RM, affect larval abundance, the examination of these.

MP, and BL) were sampled from March through May patterns may provide some insight into the differences TABLE 15. Larval winter flounder abundances and 95% conifdence intervals for ebb and flood tide collections at statons NB, RM. MP, and lBL as esuimated by the et parameter from the Gonpen function.

Station Ebb Flood

£. 1.39 (1,829-1,950)

RM 2.124 (948-3,299) S,141 (2.374-7.908)

Id? 1.865 (1,683-2.044) 4.225 (3.464.4,986) lL 5,322 (4,719-5.924) 1,962 (1,688-2,236)

B Ebbtide wasnot sampled.

40 Monitoring Studies, 1991 R evs

FEB 15 MAR 27 MAY6 JUN 15 FEB 15 MAR 27 MAY6 JUN 15 1800. BL 500. NB 1600. 450 I' 400 I j E 350 I cc 300 I 0.

I c 25 0 80o- I I F200 I

600. I z 150 W

40D - 100 200-FEB 15 MAR 27 MAY 6 JUN 15 FEB 15 MAR 27 MAY 6 JUN 15 EBB FLOOD Fig. 14. Abumdance curves estimated from the Gompert density function for larval winter flounder during an ebb and flood tidal stages at staions RM. MP. BL. and NB in 1991.

in density estimates between ebb and flood collections current drogue studies were conducted during 1991 to at the various sations. Hydrodynamic modeling has verify the model simulations (see the Niantic Bay Provided simulations of tidal currents in Niantic Bay Current Studies section in this report). Based on the during maximum ebb and flood currents (NUSCO hydrodynamic model simulations and verification with 1976: Figs. 4.2-2 and 4.2-4). In addition, several current drogues, generalized current flow patterns were Winter Flounder 41

BL-FLOOD ies at station NB showed no tidal-related differences in winter flounder larval abundance (NUSCO 1989a).

Developmental stage-specific abundances were compared at stations RM, W. and BL on the basis of cumulative weekly geometric means, an approxima-tion for the ca parameter in the Gompertz function (Fig. 17). Stage 1 larvae were most abundant at station RM, with the Niantic River the most probable source of this early developmental stage. The abun-dance of Stage 2 was more homogenous in the bay, except for RM-ebb collections. Stage 3 abundance was much greater than Stage 2 and collections by tidal stage indicated that more were entering the bay from LIS (MP-flood and BL-ebb) than were being flushed out of the bay to LIS (MP-ebb and BL-flood). A similar pattern at stations MW and BL was evident for Stage 4 larvae.

FEB 15 MAR 27 MAY 6 JUN 15 The results of this special bay-wide sampling in 1991, taking into account tidal circulation patterns, Fig. 15. Comparison of abundance curves estimated from provided some insight into the sources of winter the Gompertz density function for larval winter flounder flounder larvae in Niantic Bay. Early in the larval during selected tidal stages at stations MP, BL, and NB. season the primary source appeared to be the Niantic River, but as the season progressed the major source J

prepared for maximum ebb and flood currents (Fig. was LIS. Because this change in sources occurred 16). During maximum flood current some of the later in the season, these older larvae could have origi-water mass flowing westward south of Millstone nated from spawning stocks both east and west of the Point enters Niantic Bay, flowing north by the MNPS Niantic Bay and transported by tidally currents to the intakes and towards the Niantic River mouth. The Millstone area.

remaining water mass continues westward until being wnn deflected towards the southwest by Black Point.

During maximum ebb current, some of the water Development and growth mass flowing eastward south of Black Point enters Niantic Bay and flows to the northeast The flow then The length-frequency distribution for each stage has turns to the southeast, passes MPS intakes, and remained fairly consistent since developmental stage exits the Niantic Bay to the east. determination began in 1983 (NUSCO 1987, 1988c, The circulation patterns and differences in larval 1989a, 1990a, 1991b). Stage-specific length-abundance between ebb and flood tides at stations MW frequency distributions by 0.5-mm size-classes in and BL indicated that as the larval season progressed 1991 showed a separation in predominant size-classes into April, large numbers of larvae entered Niantic for the first four developmental stages (Fig. 18). j Bay from LIS. Collections with the greatest larval Stage I larvae were primarily in the 2.5 to 3.5-mm abundance were MP-flood and BL-ebb. In both collec- size-classes (96%), Stage 2 were 3.0 to 4.0 mm .

tions, the primary source of water entering the bay (84%), Stage 3 were 4.5 to 7.5 mm (82%). and Stage was from LIS. In contrast, the lowest larval densities 4 were 7.0 to 9.0 mm (87%). These consistent re-occurred during MP-ebb and BL-flood collections. For sults from year to year indicated that developmental:

these collections the water sampled had entered from stage and length of larval winter flounder were closely LIS, but had flowed across the bay and most likely related. This agreed with laboratory studies on larval mixed with bay water, possibly diluting the greater winter flounder which showed that there were positive -

densities of larvae entering from US. The abundance correlations between growth and developmental rates .

during NB-flood collections were similar to BL-flood (Chambers and Leggett 1987; Chambers et al. 1988). *^

and MP-ebb (Fig. 15), suggesting a similar dilution This relationship allowed for the estimation of devel-of LIS water in the bay. Previous 24-hour tidal stud- opmental stage from length-frequency data.

42 Monitoring Studies, 1991

N 0

FLOOD "I EBB

.4 iig- 16. Generalized current patterns in Niantic Bay during maximum flood and ebb curent, adapted from hydrodynamic I odel simulations (NUSCO 1976: Figs. 4.2-2 and 4.24).

.Nianlic Bay during 1991. Also shown arc larval winter flounder sampling locations in WinterFlounder 43

rr 600. STAGE 1 350- STAGE 2 f.'

500S 300-C) -

"k' X

z Z 250-  :-X:

o 400.

.i 0 'i' z z m D tD 200- I

< 300.

w 200.

E 100' 100. so .

H 50 -

U-. I. I I I Ir - r -

TIDE E F E F E F TIDE E F E F E F STATION RM MP BL STATION RM MP BL 5000- STAGE 3 450. STAGE 4 4500- 400.

wU4000 tu 350-U 0 2

35000 a 300-2 H.

Co 200 250 -

I 200 -

P2000 I . I111- I-

[1;5 H Hl H

'S:

I ) 1000 ...... 0 100:-

! 500 TIDE I

n I I I I I I 50l TIDE n_.

-I I I I I I I E F E F E F E F E F E F-STATION RM MP BL STATION RM MP BL Fig. 17. Cumulative density by developmental stage for larval winter flounder collected during ebb and flood tidal sta stations RM, MP, and BL in 1991.

The length-frequency distributions of larvae (all 85% of the larvae in the bay during 1991 were in stages combined) collected in the Niantic River (sta- 4.0-mm and larger size-classes. The slight increeas tions A, B, and C combined) were quite different than frequency for the larger size-classes in the rivver for Niantic Bay (stations EN and NB combined) in been apparent in some previous years (NUSCO 19 1991 (Fig. 19). The differences in size-class distribu- 1988c, 1989a, 1991b) and was additional eviden ce I tion between the two areas were similar to previous some older larvae were imported to the river. lCC findings reported in NUSCO (1987, 1988c, 1989a, Length-frequency data from entrainment colic 1990a, 1991b) and consistent with the spatial distribu- (station EN) were used to estimate larval Ncta don of developmental stages (Figs. 11 and 12). flounder growth rates for Niantic Bay; these dat:

Smaller size-classes predominated in the river during examined because a 16-year time-series was ava ilal 1991, which had about 70% of the larvae in the 3.5- Weekly mean lengths during a season formed i mm and smaller size-classes. In contrast, more than moid-shaped curve (NUSCO 1988c). The lin 44 Monitoring Studies, 1991

Monitoring the Marine Environment of Long Island Sound at Millstone Nuclear Power Station 1988 Annual Report.

Northeast Utilities Environmental Laboratory (f*

i

• 1 April .19, 1989 Waterford, Connecticut

have been classified into various length and sex groupings, depending upon the year; at minimum, all fish caught can be classified as smaller or larger than 15 cm. Since 1977, the sex and reproductive Niontic condition of the larger winter flounder have been determined either by observing eggs or milt or by River the presence (males) or absence (females) of ctenii on the caudal peduncle scales of the left side (Smigielski 1975). Fish larger than 15 cm (1977-82) or 20 cm (1983-88) were marked with a number or letter made by a brass brand cooled in liquid nitrogen and were then released. The mark was changed weekly and fish recaptured were noted and remarked with the brand desig-naiinig the current week of sampling.

North Larval winter flounder Winter flounder larvae have been routinely sampled in Niantic River at stations A, 1, and C since 1983, and in Niantic Day at ND since 1979 and at I-N (entrainment sampling) since 1976 (Fig. 3). In addition, special studies were con-ducted during 1988 at the mbuth of the Niantic River to examine larval export-import; 24-h sam-pling was conducted in. mid-Niantic Bay and Twotrcc Island channel to examine possible tidal and dicl larval behavior; and a comparison of entrainment sampling densities was made at the discharges of Units I, 2, and 3. The export-import studies'and the 24-h sampling studies are described below. 'T1he comparison of entrainment sampling densities among the units was presented in the Fish Ecology Section of this report.

Collections in the river and at ND were made with a 60-cm bongo sampler with 3.3-m long nets Fig. 2. Location orstations sampled for winter flounder towed at approximately 2 knots and weighted during the spawning season in the Niantic River during with a 28.2-kg oceanographic depressor. Volume 1988. of water filtered was determined using a single General Oceanics (GO) flowmeter (model 2030) mounted in the center of each bongo opening. A containers aboard the survey vessel before pro- itepwise oblique tow pattern was used with equal cessing. At least 200 randomly selected fish were sampling time at surface, mid-depth, and near measured to the nearest 0.1 cm in total length bottom. The length of tow line necessary to during each week of the survey in all years. Since sample the mid-water and bottom strata was 1983, all winter flounder larger than 20 cm have based on water depth and tow-line angle measured been 'Measured and sexed. Fish not measured with an inclinometer. Winter flounder larvae Winter Flounder Studies 241 I[VI 4,ra7 1.hck me fSd

NORTH 1 KU 0 ' ' m NLANVMC BAY 0

NB T1 IAA.

L4 b II 4

Fig I l.ocation orstations sampled for larval winter founder in 1988.

entrained by MNPS wcre collccted at Units I upon plant operations (number of circulating and 2 discharge (station EN) using a gantry system pumps). All ichthyoplankton samples were pre-to deploy a 1.0 x 3.6-m plankton net. Four GO served with 10% formalin. At the three river flowmetcrs were positioned in the mouth of the stations, jellyfish medusae were sieved (1-cm net to account for horizontal and vertical flow mesh) from the sample and measured volumetri-variation; sample volume was determined by av- cally (ml).

eraging the four volume estimates from the flowmeters. During the larval winter flounder season, sam-pling time and frequency varied by station and All sampling at EN was conducted with month. At EN, two replicate samples were taken 333-rim mesh nets. On the bongo sampler, during both daylight and at night once per week 202-jim mesh nets were used from February 23 in February and June, and during four days and through the last week of March and 333-jim mesh nights per week from March through May. Single

• nets during the remainder of the season. The bongo tows were made during the day and night bongo sampler was towed for 6 min at stations at ND) biweekly ini February and at least once a A, B, and C (filtering about 120 in3 ) and for 15 week in March through the end of the larval rmin at station ND (filtering about 300 in 3 ). Gen- winter flounder season. Sampling in the Niantic erally, the net was de~loyed at EN for 5 to 6 min River did not start in 1988 until February 23 (filtering about 400(m ), but this varied depending because of ice. From the start of sampling through 242 Monitoring Studies, 19R8

the end of March, single daytime tows at each station were made twice weekly within an hour l

I Post-larvalage-O and age-] winter flounder of low slack tide. During the first three weeks of April, single day and night bongo tows were made Annual surveys of post-larval young-twice weekly. Day samples were collected within of-the-year winter flounder in the Niantic River an hour of low slack tide and night samples during began in 1983.(NUSCO 1987a). Station LR has the second half of a flood tide. During the re- been sampled every year and WA since late 1984 mainder of the season, until the disappearance of (Fig. 4). Two Niantic Bay stations (RM and larvae at each station, tows were made twice a BP) were established in 1988. Each station was week only at night during the second half of a sampled weekly from late May through late Sep-flood tide. This sampling scheme, based on in- tember during daylight from about 2 hours2.314815e-5 days <br />5.555556e-4 hours <br />3.306878e-6 weeks <br />7.61e-7 months <br /> before

- formation from previous years, was designed to to 1 hour1.157407e-5 days <br />2.777778e-4 hours <br />1.653439e-6 weeks <br />3.805e-7 months <br /> after high tide. Sampling ceased at the increase efficiency in data gathering and reduce Niantic Bay stations in September when few or sampling biases (NUSCO 1987a). no young were present.

Larval export-import studies were conducted at the mouth of the Niantic River in 1988 on A I-m beam trawl with interchangeable nets March 24, April 18, May 2, May 10, and May of 0.8-, 1.6-, 3.2-, and 6.4-mm bar mesh was used

17. Stationary tows were taken by mooring the to catch age-0 winter flounder. Two tickler chains boat to the Niantic River Highway Bridge in the were added in late June of 1983 to increase catch middle of the channel. During a complete tidal efficiency, because older and larger young appar-cycle, samples were taken hourly except from I ently were able to avoid the net without them hour before to I hour after slack tidal currents. (NUSCO 1987a). In 1983, triplicate tows were A bongo sampler with 202-pm mesh nets was made using nets of increasing larger mesh as fish used on March 24; 333-pm mesh nets were used grew during the season. Since 1984, two nets of on the other four dates. The bongo sampler was successively larger mesh have been used during deployed off the side of the boat and was lowered each sampling trip to collect the entire available and raised between the surface and near bottom size range of young. A change to the next larger continuously during the sampling period. Sam- mesh in the four-nct sequence was made when pling duration varied from 6to 15 min (depending fish had grown enough to become susceptible to velocity of tidal currents) to sample approximately it; the larger meshes reduced the amount of 100 m of water. detritus and algae retained. Two replicates with each of the two nets were made at all stations, Two'24-h studies were conducted to examine deploying them in a random order. Distance was

• diel and tidal effects on sample density at stations estimated by letting out a measured line attached NB and TT on April 25-26 and May 4-5 (Fig. to a lead weight as the net was towed at about 3). At both stations, samples were collected ap- 25 m per.min. Tow length was increased from proximately every 2'hours intervals through the 50 to 75 and to 100 m as the number of fish two 24-h periods. Tow durations were 15 min decreased throughout the summer.

using a bongo sampler with 505-pm mesh nets.

I Stepwise oblique tows were made to sample An abundance index of juvenile winter floun-equally at the surface, mid-depths, and near bot- der during fall and winter was calculated by using tom. catches from the trawl monitoring program; field sampling methodology is detailed in the Fish Ecology section of this report. Because data on juvenile fish abundance were available from about May of their birth year into April of the following year, juvenile indices were referred to as age-0 or Winter Flounder Studies 243

TABLE 9. Estimated dates or peak abundance or larval wnter flounder for each developmental stage in the Niantic River and Bay.

Year Stage I Stage 2 Stage 3 Stage 4 Nptian River 1983 Mar S Mar 15 Apr 18 May I 1984 Mar 7 Mar 9 Apr 26 May 19 1985 Mar 12 Mar 16 Apr 28 May 15 1986 Feb 26 Mar 7 Apr 23 May 12 1987 Mar 10 Mar IS Apr 22 May 9 1988 Feb 29 Mar 9 Apr 6. May 'I LNiantic Ba 1983 Apr 7 Apr 24 May 10 1984 Apr 8 May 4 May 25 1985

• Apr I Apr 28 May 18 1986 Apr 6 Apr 29 May 12 1987 Apr 5 Apr 25 May 16 1988 Mar 24 Apr 23 May 10 Predation may affect larval abundance and (1962) also reported that jellyfish were more abun-there are numerous accounts of jellyfish being dant in the upper river. In addition, laboratory predators of fish larvae. - Several species of studies have shown that winter flounder larvae hydromedusae and the scyphomedusa, Aurelia which contacted the tentacles of the lion's mane awuita, prey upon herring larvae (Arai and Hay jellyfish were stunned and ultimately died, even 1982; Moller 1984), and laboratory studies with if not consumed by the medusa (NUmSCO 1988a).

cod, plaice, and herring have shown that the cap- Similar to 1985 and 1987, jellyfish abundance at ture success by A. aurita increased with medusal station A in 1988 was relatively low when com-size (Bailey and Batty 1984). Evidence of a causal pared to 1983, 1984, and 1986 (Fig. 15). Coinci-predator-prey relationship on larvae Of two Eu- dent with the low jellyfish abundances in 1985 ropean flatfishes (Pleuronectes platessa and and 1988 were the highest abundances of Stage 2 Plalichthysfiesus)by A. auriltaand the ctenophore, larvae at station A (Fig. 13). Although few Stage Pleurobrachiapileus, was reported by van der 2 larvae were taken at station A in 1987, their Veer (1985). Pearcy (1962) stated that Sarsia abundance was low at all stations, thus obsuring tubulosa medusae were important predators of any observation on the effects of predation. No larval winter flounder in the Mystic River, CT, causal predator-prey relationship in the Niantic and had greatest impact on younger, less mobile River has been established, but there is strong individuals. Crawford and Carey (1985) reported circumstantial evidence that the lion's mane jel-large numbers of the moon jelly (A. aurata) in lyfish may be an important source of mortality Point Judith Pond, RI and felt that they were a for winter flounder larvae.

significant predator of larval winter flounder.

(

Medusae of the the lion's mane jellyfish (Cyanea Sampling was conducted over 24-h periods on sp.), prevalent in collections at station A, were April 25 and May 4, 1988 at stations NB and TI suspected of being an important predator of larval to examine the effects of tidal stage and day-night winter flounder in the upper portion of the Niantic collection on the sample density of winter flounder River (NUSCO 1987a). Marshall and Hicks larvae. These sampling dates were selected fK 272 Monitoring Studies, 1988 Qs'-*

1984 E

0 En t.

U.1 I

i 4

J I

I

. ' 51987 I-15FEB 01 MAR 15MAR 29AAR 12APR 26APR 1OMAY 24MAY j

DATE Fig. 15. Weekly mean volume (L per 500 m3 ) of C.yanea sp. medusae collected at station A in thl Niantic River from 1983 through 1988.

to provide opposing tidal stages during the same sities at station 1' were lower than at NB, larval time of day to discriminate between possible diel densities in Twotree Island Channel generally ex-and tidal responses of larvae. Stage 3 larvae dom- ceeded 100 per 500 m3 , suggesting that there were inated the collections (95%) at both stations for large numbers of winter flounder larvae through-the two dates. There was a large variation in out LIS at this time of the season. Most likely, sample densities during both sampling dates (Fig. some of the large numbers of larvae found in LIS 16).. In general, densities were greater at night in the proximity of Millstone Point could have than during daylight and there was no apparent originated from other spawning grounds and were tidal influence on collection densities. Larval den- tidally tranported into the area.

sities were significantly (p < 0.025) greater at NB for both dates combined and for each date Tidal export-import sampling was previously seperately, tested with the Wilcoxon's signed-rank conducted at the mouth of the Niantic River test (Sokal and Rohlf 1969) by pairing the samples (NUSCO 1987a) to estimate the net loss of winter collected within the same 2-h intervals at NB and flounder larvae from the river, and in 1988 five T1. The seawater flow through Twotree Island additional studies were conducted to verify earlier Channel is large, and sample densities from station results. Sampling dates during 1988 were spaced TT are probably more representive of larval winter over most of the larval winter flounder season to flounder abundance found in LIS than collections collect various developmental stages and size-taken in Niantic Bay because of the proximity of classes. On March 24, a majority of the larvae station NB to the Niantic River. Although den- collected were Stages I and 2 (89%); Stage 3 was Winter Flounder Studies 273

500 -

ND MPR 25 ,

. 400 L 300 a .200 ,,.% . .

100 E E F E F E NIGHT I DAYUIGHT ... I NIGHT I1 2 3 4 0- LS -- -- HS -- - -LS- HS

,.5--.I.

tLS DEVELOPUENTAL STAGE

... . .,I .,, _ I . X,,

0 3 6 9 12 15 18 21 24 27 HOUR 90

, L

.. 6f 2 3 4 5 e 7 B cm LENGTH (MM)

I ig. 17. Percent occurrence by each developmental stage and 1-mm size-class of winter flounder larvae cot-Iecced at the mouth of the Niantic River during ebb (E) and flood (F:) tidal stages in 1988.

0 3 6 9 12 15 18 21 24 27 HOUR Fig. 16. Larval winter flounder densities (number per mm largc were more abundant during a flood 500 m ) during two 24-h sampling periods at stations tide. Similar results were found in previous stud-NB and "T in 1988 including the periods when night ies, except that the 5-mm sizc-class was more and daylight samples were collected and the time or abundant during flood tide (NUJSCO 1987a).

low slack (LS) and high slack (t IS) tides. I lours is the time from the start or sampling on each date. lTo determine if velocity measurements were comparable between ebb and flood tides, separate quadratic polynomial equations were fit to the dominant on April 18 (68%) and May 2.92%); hourly velocity measurements combined from and Stages 3 and 4 dominated on May 10 (92%) each of the live ebb and flood tides sampled.

and May 17 (100%). For the five dates, the Goo~d fits were obtained with R2 values exceeding mean length ranged from 3.3 mm on March 24 0.95 for both equations. The mean ebb duration to 6.8 mm on May 17. Examination of the per- was 6.7 h and flood duration was 5.7 h. The centage of each developmental stage for the com- area under the curve for the flood tide (307.8) bined data from all five dates showed that larvae was smaller than for the ebb tide (414.4), indicating of Stages I and 2 were more abundant during ebb that flood velocities were low due to sampling tides and those of Stages 3 and 4 during flood location. To make ebb and flood velocities com-tides (Fig. 17). Also, an examination by size-class parable, the flood velocities were estimated using showed that larvae 5 mm and smaller were more a technique presented in NfUSCO (1986a). These abundant .during an ebb tide, where as, larvae 6 results were similar to those from previous studies 274 Monitoring Studies, 1988

(NUSCO 1987a). The calculations of net larval 1988, but a net gain (percent return of 131.8) in exchange, which follow, were based on actual ebb the earlier studies. This difference suggested that current velocities and the adjusted flood current the 5-mm size-class was the size at which the velocities. transition from net loss to gain occurred and their relative abundance in relation to tidal stage may Using data combined from the five sampling vary annually.

dates, net tidal exchange was estimated for each 1-nmn size-class: The estimates were obtained by This change from a net loss of larvae from averaging the number of larvae per 500 mn3 of the river to a net gain as they get older has been each size-class during each hourly sample for the attributed in the past to larval behavior with ver-five sampling dates. The average was multiplied tical migration in the water column as a retention by the estimated water velocity at the time of the mechanism (NUSCO 1987a). This behavior ap-hourly collection. This density-velocity adjust- pears to become evident at the time of fin ray mient accounted for changes in discharge volume development, which allowed for better locomotion during the tidal cycle. Because larvae collected ability. Other researchers have also reported ver-during an ebb tide represented a loss from the tical migrations in early life history stages of fish.

river, the density-velocity value was made negative. Did movements of larval yellowtail flounder A harmonic regression equation using a 12.4-h (Limandaferriuginea)were found to increase with tidal cycle (the average duration of the five tides larval size (Smith et al. 1978). Atlantic herring sampled) was fit to density-velocity values. The (Clupea harengw) larvae synchronize vertical mi-area under. the curve for each tidal stage was es- gration with flood tides to minimize seaward trans-timated by numerical integration of the regression port (Fortier and Leggett 1983). Post-larval spot equation using 5-min increments. Net tidal ex- (Leiosiomus xanihurus), Atlantic croaker change was expressed as the percent return of a (Micropogoniasundulanus), and Paralichthysspp.

size-class on a flood tide compared to loss on an flounders use vertical migration in response to ebb tide (Table 10). The harmonic regressions tides as a retention mechanism (Weinstein et al.

could not be satisfactorily fit to the 2- and 8-mm 1980). Larval North Sea plaice demonstrated se-size-class data since the model sums of squares lective horizontal transport by swimming up from did not account for a significant (p = 0.05) amount the bottom during flood tides and remaining near of the total corrected sums of squares. Ihe results the bottom during ebb tides (RMinsdorp et al.

showed a net export of 5 mm and smaller size- 1985). Vertical migration by larval winter flounder classes and a net import of 6 mm and larger in relation to tidal stage was a plausible explana-size-classes. These results were similar to those tion for the results of the export-import studies.

of previous studies (NUSCO 1987a), except that However, an alternative hypothesis was that dur-there was a net loss of the 5-mm size-class in ing the latter portion of the larval season large numbers of winter flounder larvae were tidally transported into Niantic Bay from other spawning TABLE 10. Estimated percent return or larval winter areas and the larval density in the bay exceeded flounder on a flood tide that were flushed from the river on an ebb tide presented by size-class with R2 that of the river. Therefore, more larvae were values of the harmonic regression models. present during a flood tide than an ebb. Several Size Percent R2 or research projects are presently underway to ex-amine this alternative hypothesis.

class (mm) return model 3 27.0 0.60 rowth and development 4 28.0 0.61 5 55.0 0.70 Examination of the length-frequency distribu-6 164.2 0.60 tion of larvae collected in 1988 showed a separa-7 314.9 0.78 tion between the fiust three developmental stages Winter Flounder Studies 275

FINAL REPORT Larval Winter F lounder Stock Identification Using Microel.ements:.Year 2001 Studies SUBMiTTED-TO:-

Dr. Milan-Keser

. Dominiion Nuclear.ConnecticutInc.

Millst4Dne Environmental Laboratory Waterford,-CT 06385 ;

I PREPARED BY:

7 Dr. S. Bradley Moran

.Associate-Professor I .t Graduate School of Oceanography University of Rhode Island I

.Narragansett, RI, 02882-1197-ruaryf t7_ 2 0 February 7! -2.002 :

C-

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EXECUTIVEj

SUMMARY

aid The goal of this project was to assets the degree to -which winter flounder larvae are entrained from major local sources into the Millstone Nuclear P,ow'er Station-(MNPS).

Thestrategy-,-,'involve the us"e, and fu development of a method usling in iv new multi-elementali-tra6er' "'i'di idual winter f rounder larvae and established statistical analysis and neural network techniques. The emphasis was on multi-elemental analysis of individual larva e as this was of primary importance in tracking the origin of larvae from JIMMY local sources into the-Mil 'stone-'Plant. Winter flobnder larvae -(primarily stage 2) were collected during March-April, 2001, from the-ViAntic and Thames Rivers, off Westbrook, and7Plum,Bank:, (old:"-Sabr66k)"-.".,Winter flounder e Millstone Plant were larvae (stage--_2,-._4):I_ entrained into'2::`th`-'

ana yzed rom mid-Ar;ril to mid-May.

also collected and 1 Ei Samples were digested in a cleanroom laboratory and analyzed using inductively coupled plasma mass spectrometry (ICP-MS).

A total of 247 individual winter larvae (stages 1-4) and 10 blanks were. analyzed fok.`!II.'e1ements (2827 data points).

Statii.-tical analysis -of these multi-elemental. data using multivariate ayer neural network classifier indicate that.7a'r-e-'lative y' 11-percentage ( 20%) of wintej:,-rrf1ounder--l'6rvae 'en i by the MNPS originate f rom their.. Mi:antic-'Rive4r. keisiiits` from this study further suggest that_,rthd.VS`e m ef6-6ii S of icro m t is a promising

'new tool for stock identification of the early life history stages of winter 'f lounder and possibly other species, ticularl when combined with independent techniques such as microsatellite DNA small-

2

r INTRODUCTION -

The population of the winter-flounder local to the Niantic River -is potentially affected by 'the operation of. the

.,Millstone Nuclear Power: Station (MNPS), mainly by the entrainment-of larvae through the cooling-water,.systems of the operating units '(NUEL Annual Report, 1997). Since 1976, there.have been extensive-studies of the life history and population dynamics of this -important sport and commercial species-. It. is now clear' that 'a key goal is to: assign

. individual entrained larvae, to 'one of several stocks of

• larval winter flounder: in this region. This requires a

- unique tracer, or "fingerprintv',--of the individual larva.

A recent report entitled "Stock Identification Research Directions for the Northeast Fisheries Science Center5 ' by the NEFSC Stock Identification Working Gx'oup (January 10, 2000) provides an *excellent' sumary of current research.

needs and some practical- applications related to marine.

stock identification problems.- An important objective .in applied fishery management of some species is the ability to l assign individuals to one of several of stocks in a given.-

l region., Substantial effort has already been focused on microsatellite DNA analysis,-and'the potential of DNA marker analysis is recogni zed. 'However, we -suggest that the approach described herein -also provides a unique and practical method Jfor identifying -source(s) of early life history stages of species, su'ch as'the- winter flounder, which returh.,with -high fidelity 'to riverine-estuarine spawning areas that retain their early life history stages.

The approach conducted in 'this' study was to use trace tu. elements incorporated in whole winter flounder larvae-as a 3

. - l  :

tracer of the local environmental conditions,;which- were assumed.to be unique for each spawning stock. The use of microelemental dataa-to delineate -fish2 stocks'"has' bleen

-increasingly utilized via analysis of. otoli'thsr using highly sensitive' laser ablation inductively y coupl'ed u , ,

pIasma mass

,sm : .m-atssA-spectrometry (e.g. ,Secor, et, al.,. 1995;- Thresher et al.

31999).' The' key: advantage, in. analyzinhg 'whole -larvae, however,' is that it is.not- necessaryj-:to',.1remove 'a specific tissue 'component, .such -as -,the.'otolfith'.-which' adds significantly to the time involved in"'sample .processing.

Implicit in'the whole larval analysis approach used'in' this study' -is that- the trace element(s)rare recorded Iin the larvae; tissue, and;.we suggest. that- tEiis'" is "most likely within the l'arval otolith and other boney tissues.

Thi's project expands-. on,,the initial.'studies Icondtucted in 2000 (Moran, 2000;,.Saila and Lorda,.2000)"i Our whole larvae analysis technique.and.established'.statistical anad neural network'based classification techniques-.were used to assess the' degree to 'which winter flounder larvae-were entrained into the MNPS from major -local sources'.' '-

T S initial' studies conducted by. the P1?with assistance from Drs. Saila and Lorda,-,.suggested that 'a-felatively sm'aiY peicenltage '(<20%) of winter.,flounder.larva&6eint'rainead by the MNPS originate 'from. the.Niantic River<. (Moran- 200C;' Saila

• 3 and Lorda, 2000). ,Thedetails of the statisticalananeural netwwork methodologies used are similar'to those'p roose9d by

• Saila(1 998) Based.onour initial preliminary resUts, we suggested that this. ,was" a successful 'fi'r'st-step, in the

_I

.t  !. _- i -

development of a capability to determine a wide range of trace elements in individual winter flound6er^'larvae.

4r_J U_*jv .

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. In this report are the results-from a more detailed study,

( conducted' in 2001, and its application to the problem of larval entrainment by. the MNPS. Results from this study further suggest that the use of microelemental analysis .of whole larvae, rather than the otoliths, is a promising tool-for stock identification of the.early life history stages of w4inter flounder and other species,: particularly' when

.:c'ombined with- independent techniques such as microsatellite DNA data analysis.

OBJECTIVES The overreaching objective of.this project was to further

.develop "the use of a new technique to assess the degree6to' which early life history stages of winter'flounder larvae are entrained into the MNPS using a combination of a new multi-elemental tracer approach and established'statistical aAd neural network classification techniques. This multi-elemental approach is a first attempt at' developing an empirical chemical tracer. technique to: assign -individual larvae to one of several- stocks. The .details -of. the statistical and neural network methodologies to be applied

. in this proposal are very.similar.to those proposed by Saila (1998)'.'

A total of 247 winter flounder larvae samples were'collected from Narch-May, 2001, in conjunction-with the ongoing Millstone Environmental Laboratory sampling operations.:

Samples were analyzed for, a .suite o .- trace elements 'by inductively coupled plasma mass spectrometry (ICP-MS)'.'

These data were then forwarded to Drs. Lorda-and Saila for statistical analysis and interpretation. This work provides complementary information to independent stock 5 .

-ident fication. 'techniques, -specifically the use-, of microsatellite DNA analysis on larval samples being conducted ,concurrentlyiby Dr. J. Cri'vello at the University of Connecticut.-

The following.. pr6vides a;'more detailed description of the previous. work- and current research strategy, including procedures.used-, for-;sample collection and analysis, followed by results, data analysis, and conclusions.'

PROPOSED WORK1 of I

A proposal was submitted'to'the MNPS in-January, 2001, which outlined the- following wo'rk: to be completed. The. proposed work was-to utilize! the' recently developed multi-elemental analytical-and, statistical 'methods' (oran, 2000; Saila and Lorda,. 2000) for' stock tidentificat'ion of the early life history stages of winter f lounder and other species. ..It was.

proposed that.the- application of this'technique could be, used, toprovide-used,, evidence-regarding to di the sourcess oE oflra larval: I entrained at, the.MNPS.'- This' involved collection of samples-,

of winter,'flounder;.Jlarvae' froum the Niantic and Thames^0 44, Rivers, and west-of -the'CdnnecEicut River off Westbrook, andy Plum Bank (Old Saybrook), and entrained larvae from MNPS.

The.primary.purpose.of the Year 2000 Study was,. to developE' and assess the feasibility ofthis' technique asIa tool-fori'-

stock identifi cation.-In order to fully develop this method, -

we *proposed .the following work for 2001 to improver-'

confidence .in -the.,use of these multi-elemental and data-'..!

analysis-ftechniques.i-.

,,  : .. . -,  ; .. ,c

. . -' - 3 ' -. .

_

• 6 ' ..- - .v-I- I . '. V _

1) Increase Samyle-Size: The larval sample-size collected

• K during the Year 2000 study ranged from approximately 10-20 larvae.per river (Moran, 2000). Moreover, the least number of larvae were collected from the primary river, the'Niantic River. Furthermore, only 5-10 entrained larvae were

. analyzed -for each collection period. We' proposed that a total.of approximately '150. larvae from -the three rivers sampled in this work be obtained in order to better establishthe initial conditions ("training sets-) required for data analysis. After discussions with' Millstone personnel, we further proposed that a sample' size 'of approximately 100-150 individual entrained larvae be collected over several weeks in spring 2001-in-order to provide-.a more robust statistical analysis of these data.

Based on these recommendations, 'the total'number-of samples

. to be analyzed increased.from approximately 100 larvae in

Year 2000 to 247 larvae in Year-2001.

2) Specific Elements: A primary objective of the' Year 2000 study was to assess the feasibility of this multi-elemental technique. For this reason,, we analyzed each larvae for 30 elements. It became apparent that a smaller number of elements may provide sufficient information to 'conduct a statistically robust stock identification'.- Specifically,'

based on results contained in the 2000.Final Report '(Moran,

'2000; Saila and, Lorda, 2000), we proposed' to focus on.a.

number of key elements (Co, Ni, Cu, Mo,Ba, Ce, Nd, Sm. Gd, Au, and.Pb), shown to provide the.best: discrimination in the

.'Year 2000 study.

Details, of. the proposed work, including sample collection','

sample processing, elemental: analysiss and- statistical

<e -a 7

I r 11

- I I , - -_ 17. _, , - _: !, . ,

-1 , __! - . . - I . _. -

4 analysis, .have been- documented--(Moran', 2000; Saila and Lorda, 2000) and aresummarized below.-

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SAMPLE COLLECTION.-.

The proposed work involved collection-of a total "of 247 samples (105 population samplesland 142 'ent-rainment sampl'es) from the aforementioned, locations. early March 2001 to mid-May, 2001. -.Samples;coflectedwere~winter flounder larvae, of which fresh larvae (stage 1 and 2).'were targeted'in the spring.

At all times,!>samples.were collected iusing clean techniques to avoid contamination from e'xternal sources. Samples were collected using cleanttechniques tcavoid contamination-from external sources-.l. Source-area larval samples were collected using a 60-cm bongo sampiler,: 'towed'6-8-minutes near the bottom. Contents of both replicates were rinsed with seawater into a .5-gallon plastib'bucket. '

A.,sub-sample. (ca.,1'.1L).-.was tray onboard.-.Individuals placed in 4 'apl'exiglass. sorting were' sorted ^ad removed using a

.- 1g:

plastic pipette-. and-- .tr3ansferred into' a spotting glass

, !5S; containing ;,de-ionized,: water.. Individuial larvae were j; separated from zooplankton'"using aplastic pipette and."  : t8.. 0 transferred, to' a-! final.,-spot glass containing deionized  ; .!S Milli-Q water.---- Individual- larva e were 'the'n transferred; using.teflon-forcepse to- an -acid-cleaned'vi'al- (ca. 2- mLL,'

4 capped, and stored frozen until further processing in the' 't, *?

t !J T cleanroom laboratory. Entrainment samples were taken at the,.

.t power. plant.,) discharges' using methods' outlined in' NUSC9O,

, f .'>i' (1997). Laboratory-processing was the same as for field  :' '\

collected larvae. .

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SAMPLE-PROCESSING,.

Samples were thawed and processed using a total microwave

. digestion technique, which was adapted from a method originally developed in the PI's laboratory'for elemental analysis of, marine. particulate matter and sediment (Pike,

.1998; Pike and Moran, 2001).' Samples were processed in a clean room laboratory 'to' reduce possible sample contamination from 'external sources (e.g., dust).

Individual larvae were transferred from sample collection vials to a teflon bomb using an acid-cleaned pipette.

Collection vials were'rinsed with 2% ultrapure (sub-boiling distilled) HNO3 . -Approximately 1 mL of concentrated HN03 and HF-was added to each sample in the bomb and then digested in a microwave oven at low heat for 45 seconds.

Digested samples were then subjected 'to' mild'heat overnight

. to ensure total digestion of the larvae.' The final digested solutions *were clear 'and devoid of any Visible particle matter, indicating total digestion of-the sample.

. Samples.were then'evaporated to dryness-in a clean -hood and further evaporated two more times'using 2% ultrapure HNO3.

Samples in 2% *HNO, were transferred to preweighed, acid-

cleaned vials and then weighed. Proceduial' blanks. were prepared using the same 'digestion procedures as for the larval sample analyses. ' -

SAMPLE ANALYSIS A key technical advantage of the project involved the use of inductively coupled plasma mass.spectrometry (ICP-MS)J. The rapid, multi-element 'capability,.-and high'sensiti;-ity of ICP-MS provided a powerful method for quantifying a wide

range of trace metals in the larval samples- Digested samples were analyzed for simultaneous determination of Co, Ni, Cu, Mo, Ba, Ce, Nd, Sm, Gd, Au, and Pb using a VG PlasmaQuad ExCell ICPMS. Matrix matched, multi-element standards were prepared using SPEX high purity standards.

Instrument drift was monitored throughout the analysis.

Quality control is based on analysis of certified reference materials (MESS-2, MESS-4, BCSS, PACS) (Pike, 1998; Pike and Moran, 2001).

Data reduction was conducted off-line. Linear regression calibration curves were prepared for each element and applied to all samples analyzed. Elemental concentrations in larvae are reported as ng element per individual larva.

It is worth noting that an alternative and/or complementary method could be developed to analyze the otoliths of individual winter flounder larvae using LA-ICPMS. This technique has the advantages of the multi-elemental analysis afforded by ICP-MS plus the ability to ablate, with a high degree of precision and accuracy, solid surfaces using a high-powered laser. Indeed, the use of LA-ICPMS is receiving increased application to fishery source identification and it is increasingly being recognized as a viable method for identifying source(s) of early life history stages *of a number of fish species -(Secor et al-.,

1995; Thresher et al., 1999; Yoshinaga et al., 2000; Zdanowicz, 2001). The minimum target spot size is 5 pm, which is well within the approximate 50-100 wm size of a winter flounder larval otolith. The use of LA-ICPMS would also reduce sources of external contamination, as a solid surface is analyzed and would avoid the need for sample 10

ri digestion and preconcentration, which is prone to. sample contamination.

RESULTS Results from the. elemental analysis of winter flounder larvae, are listed in the attached Tables (Tables 1-10). .A total of, 247 individual winter larvae and 10 blanks were analyzed for 1i elements, :resulting in a total of 2827 data points. In addition', results from the statistical analysis of these data, and a comparison with the 2001 microsatellite:

. DNA entrainment' results (Crivello,' 2002, in preparation),

are-presented in Tables 11-13.'

STATISTICAL ANALYSIS Statistical and .neural network based classification of winter flounder larvae -

The microelemental-data listed in'Tables 1-10 were analyzed using statistical techniques -and neural -network methodologies for classification." The ultimate goal was to assign an individual. winter flounder la'rva to one of a number of predetermined groups.' This type of problem. is termed classification, and it is important in many areas of science. A common classification tool', the linear discriminant' function, has desirable properties and was explored initially'L(Saila, 1999). The linear discriminant .

function can be, considered as a form of Bayes rule that applies. when the measurement'-:vector comes from a multivariate normal distribution when all'groups'are assumed to have identical covariance matrices. Tf the' covariance matrices were not equal, this-.leads to a quadratic form of 11

the discriminant function. The above approaches were also combined with an artificial intelligence tool; namely, a three-layer neural network classifier (NeuroShell Easy Classifier').

The microelemental data sets from the four known larval sources (Tables 1-4) were consolidated into a single "Rtraining data setw and the sources Plum Bank (PB) and Westbrook (WB), geographically undistinguishable, were pooled together as a single WB location. Screening statistical analyses were conducted on this training, data set prior to the final discrimination analysis. The screening process involved the following steps carried out with the SAS computer programs:

1) All data sets were first screened for negative concentrations (changed to zeroes) and for unusually large concentrations likely resulting from sample contamination. The latter were removed and replaced with the mean concentration of that particular microelement in the specific location where the abnormal data was found.

In a final- step prior to Any subsequent analysis, the' data were subjected to logarithmic transformation (i.e.,

log,(x+ll) to reduce the disparity of scales among the eleven microelements.

2) Linear correlation analyses were conducted to establish whether larval size was related-to the concentrations of the eleven microelements; the results showed significant correlation for some- large larvae. It was concluded that a few larvae larger than 6.5 mm should be excluded prior to the discrimination analysis (see below). 1

3) Multiple means comparisons of microelemental concentrations among the three sources-were conducted for each of' the eleven chemical elements in an attempt to lselect onlyelements with significant mean concentration differences. Since no significant differences among

-sources could be found for any, of' the- microelements, it was decided to use all of them- in all subsequent discrimination analyses.,

.l no me tg' Elie.

Given that some of the data were clearly not meeti the

. requirements of normality and homogeneity of variance for

• standard parametric statistical analysis, only nonparanretric discriminant methods were applied.' In 'the icase' of "the training data sets (i.e.,. from larvae.of known.sources),' the

. best discrimination results were obtained with a K-nearest-

. neighbor method with a parameter K=2 chosen because i: gave' the.best cross-vpalidated estimate of the error rate. This same method' with K=2 was subsequently used to identify possible larvalsources in the Entrainment data sets ('ables-5-10)., for'which actual sources were unknown.- The screening step. #l above'was applied,to-the raw entrainment'da-ta prior to the discrimination analysis. A second.nonparametric discriminant function based.on a kernel method using kernel' density estimates with unequal bandwidth.was. applied to both' training and the-entrainment data.sets.with no discernible' improvement of the discrimination results...

A totally different classification method applied tso the h above.-data '.1was based on a three-layer neural-network classifier algorithm (NeuroShell Easy Classifier>) recrsiring no assumptions for the data. This class of algorithms use the information content, in the data regardless 'of

> distribution, scales, or units. The specific algori'tl'z. used 13

was from the computer program t "Neuro-Shell Classifier" developed by Ward Systems Group, Inc., (www.wardsystems.com) widely used in medical and pharmaceutical research.

Results from the analysis of the training set data using a nonparametric discriminant function with K=2 (Table 11) indicated 76-81% of larvae matched the source regions. By comparison, analysis of the training set data using a three-layer neural network model indicated 84-93% classification sensitivity (Table 12). Thus, considering just the training set data, these classification results were satisfactory.

When applied to the entrained larvae samples (Table 13), the nonparametric discriminant function with K=2 suggests a classification of 4%, 0% and 66% to the Niantic and Thames Rivers and off Westbrook, respectively, and 30% to other sources not classified, based on the training set data provided. Using this classification model with kernal density estimates with equal bandwidth, the classification results were 14% Niantic, 5% Thames, 80% Westbrook, and 0%

to other sources. The entrainment analysis results obtained using the neural network classifier ranged from 10 to 20%

Niantic, 2 to 4% Thames, 33 to 61% Westbrook, and 15 to 55%

to other sources, using a cut-off probability of 0.65 and 0.5, respectively. This compares with preliminary results of the neural network analysis of the 2001 microsatellite DNA data (Crivello, 2002, In preparation) of about 24%

Niantic, 22% Thames, 35% Westbrook, and 19% to other sources (Table 13).

It is encouraging that the microelemental and microsatellite DNA results suggest a similar classification probability to the Niantic River; namely, 10-20%. Also, the 33%

14

4 classification to Westbrook (0.65 cut-off) and 15%.to other'.

sources (0.5 cutoff) '*is! consistent with the miicrosatellite DNA results. However, using the heural network analysis classifier, the microelemental data suggests a relatively low percentage assigned to.'the Thames' River compared to thei

'microsatellite EDNA data., This -result is unusual,. and apparently inconsistent 'with the known tidal circulation pattern in. this region that .is' expected to ,deliver significant quantities of -larvae from the Thames River to the Millstone Plant.

One possible explanation may 'be that the elemental

. composition of the larvae -assigned-to othler sources may.have been similar'to the Thames River elemental composition, at least in 2001, thereby complicating the classification.

Supporting 'this suggestion i's the fact' that elemental concentrations in the larvae in Year 2001 were extremely low, making it more difficult- to distinguish between geographical In -sources.

this. regard, examination of, additional elemental data (above the 11 'elements examined) from the larvae analyzed';'in 2001may provide further.

information.

In addition to 'using a neural network for classifying individualwinter flounder larvae -into 'known groups, an effort' was also made.to utilize an unsupervised clustering.

method to.,estimate the optimum 'number of-groups in a data set 'without any a priori information about the actual number..

of groups in the data.. The purpose':ofthis work was to be.

able to obtain a grouping from'.'sample data without any other information'. The specific.fuzzy clustering method used in this'study is described in Kaufmann-and Rousseeuw (1990).

0," ". ' ' '., ..............

15 ,_. .1..

The fuzzy clustering method was applied to the training set for microelements, but no information on individual larval sources was provided. Fuzzy clustering was applied to these data under the assumption of 2,3,4,5 and 6 groups. It was observed that the clustering into 3 groups provided the best grouping, based on Dunn's partition coefficient. This confirmed that the unsupervised clustering method appeared to work in a satisfactory manner with training set data by providing a similar partitioning of the individuals.

However, the attempt to separate the entrainment data set into groups was not successful. It appeared that these data were more variable to the extent that this particular clustering algorithm could not effectively distinguish groups.

Further efforts to use other unsupervised clustering methods were undertaken. An approach to fuzzy clustering first described by Marsili-Libelli (1989) was developed and tested. This uses a fuzzy partition algorithm, and fuzzy partition efficiency was measured by a normalized partition entropy. It has been indicated by the above author that the normalized partition entropy corresponds to a maximization of the likelihood that a given data set X may indeed contain C subsets with homogeneous features. Our program utilizes algorithm 1 of- Marsili-Libelli and normalized partition entropy. It was applied to an entrainment sample which consisted of N = 113 observations with 11 variables per observation. It was found that -the optimum number of clusters was three with an optimal entropy index of 0.0213576. The results from this unsupervised algorithm suggest that the entrainment data analyzed consists of three distinct groups of winter founder larvae. This corresponds with a familiar finding of three groups for the training 16

I*I

'I set. The results of this analysis for the...entrainment samples suiggest that these larvae also consist of three C~I. distinct groups, which are.-assumed to correspond to the training set.samples. However, there is no valid procedure for comparing these results with the neural net predictions because the assignment methods differ. This analysis also indicated, that only one individual larva of the 113

-individuals was classified '-as 'unknown by virtue of a calculated possibility 'of.,membership in any group of less than the 0.65..

- bit I IRelationship between-microelemental composition and'total lencrth of winter flounder larvae

. Total length measurements were. made for a sample of the training set larvae prior to analysis of their whole body microelemental composition .by- ICPMS. The' purpose. was determine.whether or-not there'is-a significant functional relationship between size-' of sampled larvae and microelemental composition- and, if a significant relationship was found, to provide advice as to how 4it should be.treated. -

Initially, a Pearson: product' moment correlation was calculated between larval size of all sampled larvae and 'a suite of the eleven elements analyzed. That is, all sampled..

sites were combined -and correlated-'with each' individual element. The results of Ethis analysis 'indicated no statistically., significant-correlation -for eight of he, eleven elements.. -The three -elements for which low (but statistically signifiicant) correlation's' were obtained in this manner were Cu, Mo and Pb. -

17

A further careful analysis of the relation between size and quantities of these elements was then made. This was done using an automated curve fitting program which fitted a series of 105 single term functions with intercepts to the data regarding the above elements. This curve fitting procedure assured that the best fitting equation based on a r2 and F statistic values was selected in each application.

It was decided to test whether the initial correlations for the three elements listed as significant were affected by merging all samples prior to analysis. Therefore, separate analyses were conducted for establishing relations between size and composition for each sample site (namely Ni'antic River, Thames River, and Westbrook) versus each element (namely Cu, Mo, Pb).

The results of this work are summarized as follows. No significant relationship between size and'concentration of any of the three elements was found for the Niantic River data. No significant relationship between the concentration of the three elements and larval size were found for the Thames River data. However, a significant functional relationship was found between Cu and size for the Westbrook sample data. This significant relationship was eliminated by truncating the individual larval size at 7 mm.

A one-way analysis of variance (ANOVA) clearly indicated that the average size of Westbrook larvae was greater than the Niantic or Thames River larvae. Similarly, it was found that a significant relation between Mo and size occurred when all Westbrook data were utilized. This relationship was eliminated by truncating the sample larvae at 6.5 mm.

No significant relation between Pb concentration and size was found for Westbrook larvae. In summary, no significant 18

1, relation between larval size and microelemental concentration is expected if the size of the largest larvae.

used for classification using microelements can be limited as indicated above.

CONCLUSIONS

1) Based on a three-layer neural network analysis, a relatively small..percentage (10-20%) of larvae entrained into the. Millstone! Power. Station were from'the Niantic River for the period analyzed in March-May, 2001.

2)'The classification of 10-20% of entrained larvae to the Niantic River based on the microelemental data is in reasonable agreement with preliminary microsatellite DNA results (about 24%) for this sampling year.

3) Analysis of the microelemental data suggests a greater classification probability to Westbrook (Connecticut River area) and other (nonclassified) sources and a relatively smaller classification probability--to the Thames River than determined when using 'the microsatellite DNA and a neural network classification model.

4) Results from-an unsupervised fuzzy clustering algorithm (Marsili-Libelli, 1989) suggest that the entrainment data analyzed consists of three distinct groups of winter founder larvae. This corresponds with a familiar finding of three groups for the training set. Results of this analysis for the entrainment samples suggest that these larvae also consist of three distinct groups, which are assumed to correspond to the training set samples.

19

. I

.,5) No significant, relation between larva I ssize,. -and

. r ,e .~.a, microelemental.. concentration is expected if the size of

,the largest larvae used for classific' Ration using microelements can be limited to <6.5 mm.

DATA PRESENTATIONS AND PUBLICATIONS m

t~~~~~~~~ -< - m _ 1 ! ------ i f - a -~~~~ttm~ - - - , .1 I- - - ^ ^ 4 unis worx was made atr cne,.2uul A pre.lnr.naRy presenuaLionf'o-I MillstoneEnvironmental Advisory Council Meeting, June12-14,' 2001. . These1>.results will be used to prepare a 16

... I manuscript for submission to a peer-reviewed scientific journal. ,

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(I 11 REFERENCES Hampshire, J.B. and B.A. Pearlmutter (1990) Equivalence proofs for multilayer perceptron classifiers, and 'the Bayesian discrimination function. In: Proceedings of the 1990 Connectionist Summer School. Morgan Kaufmann..

Kaufmann, L. and P.J.. Rousseeuw (1990) Finding groups in data. John'Wiley and Sons,' NY..

Marsili-Libelli, S. (1989) Fuzzy clustering of ecological data. Coenoses 4(2),95-106. -

Moran, S.B. (2000) Tracking.The Origin of Winter Flounder Larvae Near The Millstone Nuclear Power Plant, Using Multi-Elemental Analysis Techniques. Final Report to the Northeast Utilities Environmental Laboratory. -

Nigrin, A. (1993) Neural networks for pattern recognition.

The MIT' Press, Cambridge,'MA. ^

NEFSC Stock Identification Working Group Report (2000) Stock identification research directions for the northeast fisheries science center.- Northeast Fisheries Science Center, January 10. -

Northeast Utilities Service Company (NUSCO), (1997)-

Monitoring the Marine :Environment of Long Island Sound at Millstone. Nuclear Power Station, 'Waterford, Connecticut.

pp. 258.

Ce s.

21 -

Pike, S.M. (1998) Atmospheric Deposition and water Column Fluxes of Tracer Metals in the Gulf of Maine.'---M.Sc.

Thesis, Graduate' School off oceanography, University off Rhode Island, pp. 200. .-. ' ';l "EPike, S.M.' x-id'S.B. Moran (2001) Trace'elements-in aerosol and precipitation at New castle, N.H.,- U.S.A.' Atmospheric Environmjent 35/19, 3361-3366

- '-Saila'S'.B. (1998) Some methodologies- ^related. tbo,: stock identification with social reference to studying spawning fidelity in Atlantic bluefin tuna.'. pp'.. 201-205, In: 'J.S.

.-Beckett; ed. -Procedings of the ICCAT Tuna Symposium,

'PartI.

Saila, S.B' (1999) Neural networks. in. lassifying biological 4;..iv.~; 1 . >.,,,,,,

e,,'

populations (manuscript in preparation).

0 . ,: .-..-

,.-.' f -'" -' .- ~ - - . ¶ i Saila, S. and E. Lorda (2000). Larval winter flounder stock identification using microelements.: .1Firs -year (2000).

- ,analysiand preliminary results. to-;th'eN orteast

,Report.

Utilities.Environmental Laboratory.

Secor et' al. (1995) Can otolith. microchemjistry' cart patterns- of migration and habitat, utilization' in

anadromous fishes. Journal of Experimental'Biology and Ecology 192, 15-33.

.; t r  ! I:

Thresher et'-aA" '(1999) ElementalcompositionSof otoliths a1 stock delineator in fishes.: Fisheries-Re.search43 3, 165-20 4 - '

22.

-4 7 _ - - .

Yoshinaga, J., A. Nakama, M. AMorita and J.S. Edmonds (2000)

F Fish otolith reference material for quality assurance.of

'C chemical analyses. MarineiChemistry, 69, 91-97.

Zdanowicz, V. (2001) Elemental composition of fish otoliths:

results of a laboratory intercomparison exercise.

Northeast Fisheries Science Center Reference Document 01-13, 92 p.

I.

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LIST, OF,' TABLES -A

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Table 1- 2001 Thames River Training Sets (ng element- per

4" individual larva).

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Table 2 -- 2001 Plum Bank Training -Sets, (ng element per

'individual larva) .'-

Table 3 - 2001 Niantic River Training Sets (ng element per individual larva).

Table 4 - 2001 Westbrook Training Sets (ng element per individual larva).

Table 5 - 2001 Blanks (ng element per individual larvae).

Table 6 - 2001 Entrainment Data Set#1 z(ng element per individual larva).

Table 7 - 2001 Entrainment Data Set#2 (ng element per SI individual larva).

Table 8 - 2001 Entrainment Data Set#3 (ng element per individual larva).

Table 9 - 2001 Entrainment Data Set#4 (ng element per individual larva).

Table 10 - 2001 Entrainment Data Set#5 (ng element per individual larva).

I Table 11 - 2001 nonparametric discriminant function with J -11 I-IP K=2, training data. -

- I I  ;, '. "  !

24 -

Table 12 - 2001 NeuroShell Easy Classifiers', training data.

(S Table 13 - 2001 'micro-elemental and microsatellite .DNA

.entrainment data analysis results summary. -

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Table 1 - 2001 Thames River Training Sets - Final (ng element per Individual larvae).

Il I Sample L (mm) Co :Ni i Mo Ba Ce Nd Sm Gd Au Pb ;i TR 1.1 5.0 0.1390 1.3444 0.9447 0.0251 0.0792 '0.0076 0.0162 0.0045 0.0090 0.0004 0.3026 I.Jol TR 1-2 5.2 0.1194 1.7318 1.0334 0.0273 0.1552 -0.0503 0.0038 0.0024 0.0088 0.0009 0.2594 TR 1-3 4.5 0.1169 1.6668 1.7761 0.0313 0.0117 -0.0,534 0.0038 0.0027 0.0088 0.0003 0.2460 TR 1.5 5.9 0.1008 1.4890 0.5281 0.0251 0.0377 -0.0488 .0.0010 0.0013 0.0083 0.0004 0.2606 TR 1-8 5.2 0.1175 1.4890 1.6902. 0.0280 0.0756 -0.0465 0.0040 0.0012 0.0084 0.0002 0.6621 TR 1-10 5.1 0.1254 1.5849 1.4081 0.0404 0.0939 -0.0453 0.0057. 0.0022 0.0082 -0.0001 0.5360 TR 1-12 6.0 0.1040 1.4259 1.1633 0.0139 0.1864 -0.0424 0.0016 0.0033 0.0090 0.0003, 0.4?348.

TR 1-13 6.3 0.1925 30.0135 4.2337 0.0247 0.1980 -0.0455 0.0026 0.0015 ,.0081 0.0002 0.4572 TA 1-16 6.3 0.1187 1:4901 1.6802. 0.0254 0.0625 -0.0129 0.0250 0.0064 0.0109 0.0002 0.4329 TR 2.1 3.7 0.1222 1.4376 1.4468 0.0394 0.0196 .0.0472 0.0028 0.0013 0.0074 0.0002 '0.3562 TR2-2 4.4 0.5298 1.8676 2.5503 0.0378 0.0688 -0.0539 0.0016 0.0014' 0.0084 0.0001 0.3039 TR 2-8 4.2 0.0994 1.4815 0.8764 0.0281 -0.0600 -0.0382 0.0005 0.0010 0.0080 -0.0002 1.2616 TR 2:10 4.4 0.1046 1.5700 1.1101 0.0240 0.1251 -0.0166 0.0213 0.0056 0.p099 -0.0001 ;0.2636 TR 2-12 5.7 0.1124 1.3607 1.3206 0.0154 1.4766 -0.0335 0.0098 0.0028 0.0087 0.0002 0.5252 TR 2-13 4.0 0.0888 1.2825 0.4836 0.0245 0.3887 -0.0451 0.0015 0.0018 0.0070 0.0000 02748 TR 2-15 4.0 0.1043 1,3597 0.9913 .0.0142 -0.0069 -0.0524 -0.0004 0.0006 0.0081 -0.0001 0.2617 TR 2.17. 4.3 0.1296 .1.8169 13.2825 0.0158 0.3319 -0.0611 0.0010 0.0019 0.0094 0.0001 0.2592 TR 2-19 3.8 0.1237 1.7218 0.4951 0.0185 .0.0089 -0.0245 0.0190 0.0056 0.0115 0.0001 0.2222 TR 2-21 4.1 0.1011 1.4755 0.5293 0.0154 -0.0802 .0.0485 0.0010 0.0013 0.0075 0.0004 0.2862 TR 2-23 3.5 0.1332 1.7117 1.1399 0.0106 0.0038 -0.0487 0.0038 0.0005 0.0081 -0.0001 0.4555, TR 3.1' 6.6 0.1390 1.9800 0.8324 0.0194 0.3472 -0.0565 0.0022 0.0024 0.0093 0.0008 0.,3398 TR 3.2 4.0. 0.4550 2.0086 4.3136 0.2797 50.6500 -0.0435 0.0031 . 0.0024 0.0074 0.0003 1.3052 TR 3-3 5.8 0.1376 1.7764 1.5069 0.0573 0.2197 .0.0095 0.0250 0.0070 0.0107 0:0013 0.4764j TR 3-5 6.0 0.1363 1.56;80 2.2406 0.0387 0.3258 -0.0461- 0.0027 0.0018 000082 0.0006 0.4796W, TR 3.9 7.0 0.0935 1.3S87 1.0608 0.0172 0.1572 -0.0406 0.0025 0.0015 0.0065 0.0000 0 3945 TR 3-10 5.9 0.1185 1.7867 1.2492 0.0151 0.1744 -0.0553 0.0039 0.0017 0.0089 0.0001 0.5276 TR 3-11 4.2 0.1189 1.8878 3.1296 0.0268 0.0671 -0.0192 0.0169 0.0063 -0.0100 0.0000 0.8047.,.

TR 3-12 6.8 0.1366 2.8612 128.3488 p.0201 0.0730 -0.0491 0.0038 0.0017 0.0080 -0.0001 6.2705S TR 3-13 7.2 0.1703 1.6959 2.3467 0.0462 0.1315 *0.0270 0.0043 0.0016 0.0077 0.0003 0.6571:.

TR 3-16 5.5 0.1389 1.6726 1.6060 0.0469 0.0993 *0.0565 0.0007 0.0011 0.0087 .0.0003 0.4323-TR 3-18 4.5 o.io75 1.5162 1.0140 0.0101 -0.0705 *0.0520 *0.00f2 0.0007 0.0072 .0.0001 0.26757 TR 3-19 5.2 0.1200 1.5413 0.4695 0.0220 0.2289 0.1662 0.1033 0.0209 0.0143 -0.0002 0.25147',

ave 0.1455 2.'5305 5.8376 0.0339 1.7363 -0.0347 0.0092 0.0031 0.0088 0.0002 0.6334'

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% I Table 2 - 2001 Plum Bank Tralning Sets - Final (nq element per Individual Sample' L (mm) larvae).

Co Nl ' ' u 'Mo i.B&'

PB 1-1 ' Ce. - Nd Sm- Gd 0.0969 1.3033" 0.7948 0.0135 Au Pb PB 1 -0.0342 .0.0388 '0.0036 ,0.0014

.0.1106 1.7347' 1;1347 '0.01'71 0.0070 :0.0002 0.2128 PB 1.3 -0.0709 -0.0467: 0.0018 0.0012 0.1001 1.3078' i.0859 0.0159 0.0073 0.0000 0.2488 PB 1.5 0.0663 -0.0449 0.0000A0.0008 4.5 0.0986 1.8605 1.9064 0.0891 ,0.0069 0.0006 0.1959 0.0768 -0.0152 0.0177 0.0044 0.0091 0.0001 6.3767 I

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Table 3 . 2001 Niantic River Training Sets- Final (nq element per individual larvae).

Sample L (mm) Co Ni Cu Mo Ba Ce Nd Sm Gd Au Pb NR 1-B' 0.2451 1.3744 2.5457 0.0153 0.0423 -0.0439 0.0016 0.0015 0.0066 0.0000 0.3735 NR 1-1 0.0684 1.1326 1.1570 0.0094 0.0837 -0.0447 0.0014 0.0011 0.0065 0.0001 0.4091 NR 1-2 0.0835 1.2046 1.5271 0.2002 0.4942 -0.0428 0.0002 0.0010 0.0058 0.0000 0.2970 NR 1-3 0.0855 1.3475 2.1260 0,0123 0.0151 -0.0392 0.0022 0.0017 0.0060 0.0000 0.4028 NR 1.4 0.0722 1.0878 1.4269 0.0222 0.0448 -0.0138 0.0190 0.0048 0.0077 0.0001 0.8208 NR 1-5 0.0821 1.1555 1.0586 0.0170 -0.0289 *0.0411 0.0028 0.0008 0.0062 0.0001 0.2157 NR 1.6 . 0.0582 1.0601 0.3457 0.0106 -0.0335 -0,0432 0.0015 0.0011 0.0065 0.0000 0.2671 NR 1.7 - 0.0723 1.1010 1.4235 0.0105 0.0680 -0.0390 '0.0006 0.001,6 0.0058 -0.0,001 0.3205 NR 1-8(1) 0.0686 1.1710 0.3713 0.0110 -0.0737 -0.0508 -0.0001 0.0007 0.0070 0.0003 0.1572 NR 1-8(2) 0.5696 1.6274 0.8075 0.0419 0.1356 0.0059 0.0285: 0.0087 0.0096 0.0004 1.2417 NR 1-9 0.0775 1.1846 0.3127 0.0099 0.0747 -0.0252 0.0104 0.0030 0.0066 -0.0001 0.4807 NR 1-10 0.0748 8.2519 0.7264 0.0118 -0.0481 -0.0367 0.0054 0.0014 0.0060 0.0001 0.3160 NR 1.11 0.0920 1.7764 0.4936 0.0143 0.0351 -0.0378 0.0337 0.0062,. 0.0092 -0.0001 0.1896 NR 1-12 0.0626 1.1582 0.6173 0.0168 -0.0100 -0.0377 0.0040 0.0022 0.0067 0.0017 0.2071, NR 1-13 0.0804 1.3843 2.1719 0.0201 0.2380 0.0341 0.1900 .0.0380 0.0198 0.0000 0.2819 NR 2-1 3.3 0.0537 1.3016 1.27,21 0.0267 0.2610 -0.0274 0.0056 0.0010 0.0049 0.0003 0.4332 NR 2-3 3.4 0.0700 0.9912 0.5777 0.0178 -0.0598 -0.0473 0.0011 0.0011. 0.0064 0.0000 0.2284 NR 2-4 3.6 0.0695 1.2572 0.8089 0.0291 0.0153 -0.0432 0.0034 0.0017 0.0074 0.0000 0.5500 NR2-5 3.7 0.0880 1.1924 0.5219. 0.0622 0.2897 -0.0215 0.0157 0.0052' 0.0083 0.0000 0.3159 NR 2-6 3.4 0.0609 1.1137 0.7206 0.0244 -0.0357 -0.0462 0.0015 0.0018' 0.0075 -0.0001 0.2097 NR 2-7 4.1 0.0624 1.4511 1.4067 0.1341 0.1412 -0.0317 0.0053 0.0023 0.0061 0.0002 0.6724 NR2-11 . 3.1 0.0541 0.9366 0.8568 0.0146 0.0262, -0.0308 0.0078' 0.0024 0.0057 0.0002 0.2987 NR 2-13 3.8 0.0622 0.9974 0.3796 0.0126 -0.0480 -0.0414 0.0044 0.0012 0.0061 0.0000 0.2164 NR2-15 3.9 0.0816 1.0848- 1.2730 0.0157 0.0688 -0.0179 0.0123 '0.0042 0.0070 0.0000 0.1950 NR2-17 3.9 0.1158 1.0729 0.7285 0.0173 0.1301 -0.0222 0.0042 0.0019 0.0045 0.0001 0.4845 NR 2-18 3.6 0.1068 26.4528 0.7761 0.0152 0.0352 -0.0392 0.0021 0.0011 0.0065 0.0000 0.3852 NR 2-19 3.9 0.0960 2.2577 0.6668 0.0142 0.0956 -0.0468' 0.0002 0.0017 0.0067 0.0001 0.2504, NR2-21 3.5 0.0962 1.9687 4.7716 0.0160 -0.0044 -0.0485 0.0006 -0.0011;- O.O73;' '0.0001 0.3020 NR2-22 4.1 0.1075 1.8808 )0.9179 ... 0.0158 ...0.2420-0.7O-';79.'.0143 ' 0.0040 0.0085 0.0001 0.19,93 NR 2-23 3.8- 01 128-; 1.8889 0.0141 0.,9,93.2 0.0480 0.0012; 0.010. 0.0075:0.0002,01381 00.7257,,

NR 3 1 ' 4.2 0.10473,1.9586!'t' 0.9304' 0.021 6 Q. 73-0. -0.0409:,,0.0003 0,'

001 0 : 0.0061 O.OOQI;.1 O.3053, NR32'V 3.9 0.0929 J.6320"0.5567'- 0.0691,. O.I065 ,-0.0101>'.0.0207j,<'b 0.0057 0;.0077- .0009 0.4151 NR 33' 3.9 0 14489,2.9343-' 0.9257j0.0378 -0.04-46 0,0451 0.0012;:,0.0004 0.0067- 0,0005.3.7244 NR38 6A 0'1679-77198 1.7419_ 0.2241- 59.192.00.02l8 0.0141 '0.0030 0.0073 0.0001 1.2400

, 0 G 41 0.0030

f-N NR 3.9 5.2 0.1052 1.6 908 0.6592 0.0158 0.1155 -0.0428 0.01005 0.0013 0.0063 0.0003 0.1523 NR 3-10 3.3 0.1629 2.6 263 2.6247 0.0671 2.1659 0.0290 0.0 190 0.0047 0.0078 0.0913 1.6093 NR 3-11 3.1 0.1349 3.1 007 1.4608 0.0269 -0.0196 -0.0373 0.0w014 0.0017 0.0066 0.0077 0.3259 NR 3-12 3.3 0.1070 2.3 502 0.8718 0.0259 0.1773 -0.0149 0.0 149 0.0032 0.0071 0.0004 0.5127 NR 3-15 3.9 0.2005 3.9 186 1.0098 0.0170 0.0362 -0.0569 0.0'020 0.0027 0.0092 0.0001 0.3463 NR 3-16 4 0.0780 0.9 344 1.8608 0.0139 -0.0257. -0.0357 0,.01058 0.0021 0.0085 0.0006 0.2517 NR 3.19 3.8 0.1864 3.0 805 1.8895 0.0440 0.0509 -0.0102 0.0 145 0.0031 0.0081 0.0324 0.3367 NR 3-22 3.2 0.1213 1.7552 0.2791 0.0164 -0.0484 -0.0213 0.0 06i 0.0007- 0.0064 0.0006 0.1718 ave

--- 0.1105 2.5 135 .1.1506 0.0341 0.1451 -0.0308 '0.0 114 .0.0032 0.0072; 0.0035 0.4822 t

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sample L (mm) Co NI Cu Mo Ba Ce' Nd Sm Gd - Au Pb WB 1-1 0.1696 1.7655 5.2662 0.0301 0.1671 *0.0359' 0.0036 0.0008 0.0067 0.0005 0.4482 WB 1-2 3.8 0.1496 1.6548 2.0446 0.0230 0,0242 '-0.0514 0.0017 0.0008 0.0078 0.0001 0.3177 WB 1-3 0.1204 1.7602 2.9598 0.0302 0.0568 -0.0483 0.0051 0.0016 0.0085 0.0001 0.4284 WB 1.4 4.7 0,1293 1.7936 2.8666 0.0251 -0.0351 -0.0538 0.0025 0.0015 0.0085 -0.0003 0.3620 WB 1-6 0.1318 1.7587 1.3767 0.0776 2.4710 .0.0217 0.0193- 0.0075 0.0095 0.0001 0.7674 WB 1.9 5.1 0.1077 1.5767 1.5222' 0.0342 0.0847 -0.0501 0.0037 0.0017 0.0083 0.0009 0.4301 WB 1-10 4.9 0.0981 1.4346 1.9411 0.0459 .0.0711 -0.0559 0.0015 0.00.14 0.0083 0.0002 0.3315 WS 1-12 0.1326 1.5012 4.4052 0.0519 0.4078 -0.0270 0.0297 0.0092 0.0105 0.0008 1,3719 WB 1-14 0.0918-' 1.1760 1.0631 0.0233 0.1584 -0.0198 0.0213 0.0054 0.0092 0.0003 0.3007 WB 1-15 0.1057 1.4736 1.9432 0.0503 0.0212 -0.0474 0.0032 0.0024 0.0075 0.0004 0.6330 WB 1-16 0.0932 1.3268 0.7492 0.0225 -0.0894 -0.0584 -0.0014 0.0007 0.0077 0.0012 0.1566 I

WB 1-18 0.0881 1.2260 1.3028 0.0244 -0.0917 -0.0570 -0.0003 0.0014 0.0075 0.0003 0.6037 WB 1-19 0.1054 1.3213 1.2277 0.0302 0.0900 -0.0146 0.0204 0.0045 0.4t106 0.0009 0.4304 WB 2-1 5.1 0.1045 1.4094 0.9638 0.0337 0.1724 -0.0146 0.0280 0.0053 0.0094 0.0004 0.4568 W2-2 4.6 0.0902 1.2779 5.4085 0.0186 -0.0030 -0.0519 0.0011 0.0009 0.0070 0.0005 1.5512 WB2-3 8.5 0.0997 1.3644 1.6147: 1.2158 0.0121 -0.0532 0.0030 0.0014 0.0088 0.0007 0.3840 WB2-4 3.3 0.9785 5.6027 33.8724 0.0364 0.7140 -0.0376 0.0110 0.0020 0.0082 0.0011 2.8002 WB 2-5 4 0.0999 1.4073 1.3001 0.0221 0.0442 -0.0224 0.0160 0.0057 0.0099 -0.0001 0.9193 WB 2-6 7 0.0812 1.2998 0.9833 0.0217 -0.0800 -0.0473 0.0025 0.0011 0.0084 0.0008 0.2704 WB 2-11 4.1 0.0843 1.4457 0.8778 0.0115 0.2635 -0.0454 0.0030 0.0020 0.0070 -0.0001 0.3814.

WB 2-12 5.3 0.0908 1.6721 1.0465 0.0207 -0.0176 -0.0561 0.0017 0.0016 0.0077 0.0000 1.2668 WB 2-17 6.4 0.0823 1.2270 0.8963 0.0235 0.0501 -0.0195 0.0159- 0.0069 0.0085 0.0010 0.2891 WB 2 19 3.8 0.0768 1 5966 0.8836 0.0171 0.0040 0,0380 0.0044 0.0028 0.0066 0.0002 0.4124 WB 2-20 4 0.1017 1.4189 - 0.5173 0.0117 0.1056 0.0605 0.0004 0.0013 0.0085 0.0001 1.3464 WB 2-22 3.7 0.0841 1.5088 1.0476 0.0240 0.0151 -0.0501 0.0040 0.0009 0.0084,0.0001)',' 0.28Z5 WB-2-24 3.2 0.0822 1.4212 1.0833 0.0213 0.0090 0.0259 0.0158 00060 00092 0.00010.3558 ave. 0.1377 1.6316 3.04475 0.0749 0.1776 0040930.0083 0.003'0 008, 0.0004" 0.665g

_t

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d, I J Table 5 - 2001 Blanks - Final (nO)

Sample L (mm) Co NI Cu Mo Ba Ce .Nd Sm Gd - Au. Pb WB 1-8 blank 0.1181 1.6484 1.6455 0.0385 0.0011 -0.0548 0.0010 0.0021 0.0079 0.0001 0.2384 WB 1-17 blank O.1057 1.3449 0.7993 0.0786 -0.0699 -0.0614 -0.0012 0.0009 0.0083 -0.0003 0.1887 WB2-7 blank 0.1166 1.2893 1.0701 0.0087 :0.0112 -0.0574 -0.0016 0.0010 0.0081 0.0000 0.1967 WB 2-21 blank 0.0737 1.2292 0.5899 0.0147 -0.1020 -0.0517 :0.0015 0.0011 0.0076 -0.0002 0.4116 TR 1.7 blank 0.1063 1.4900 0.7528 0.0447 0.2625 -0.0121 0.0158 0.0052 0.0091 0.0001 0.2702 TR 2-7 blank 0.1258 1.7212 1:4245 0.0216 0.0986 -0.0465 0.0066 0.0018 0.0085 -0.0003 0.4819 TR 3-7 blank 0.1439 1.9334 2.1143 0.0185 0.0933 -0.0385 0.0016 0.0022 0.0090 -0.0001 0.7061 PB 1.4 blank 0.0961 1.3236 0.8949. 0.0137 *0.0659 -0.0498 0.0029 0.0015 0.0077 0.0003 0.2849 NR2-B blank 0.1007 1.5774 3.9013 0.0467 0.4748 -0.0254 0.0094 0.0022 0.0069 0.0002 1.5361 NR 3-7 blank 0.1839 2.9743 1.7334 0.0477 0.3999 -0.0190 0.0207 0.0072 0.0097 .0.0001 0.3542 I I

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.I Table 6 - Entrainment Data Set#l 2001 (ng element per individual larvae)

Sample L(mm) Co NI Mo- Ba Ce Nd Sm Gd Au Pb E. 5.1 0.15819 2.05172 2.22951 0.03067 0.21725 0.04160 0.02386 0.00378 0.00373 0.00107 0.44537 E-1.3 5.5 0.14184 2.19115 1.11147 0.03585 0.09050 0.00791 0.00773 0.00042 0.00212 0.00100 0.24883 E 1.5 7.9 0.17157 2.44778 1.6957-3 0.04198 0.28152 0.00726 0.01174 0.00163 0.00304 0.00063 0.62617 E-1-7 5.9 0.16942 2.27804 2.28706 0.05831 0.19938 0.00434 0.00752 0.00122 '0.00393 0.00102 1.00446 E-1-10 6.1 0.16976 2.06295 1.44320 0.03581 0.21933 0.00274 0.00887 0.00263 0.00504 0.00080 0.39518 E-1-12 6.7 0.17582 2.61985 2.1641'3 0.03622 0.33308 0.00039 0.01430 0.00285 0.00219 0.00134 0.61087 E-1-14 7.4 0.18167' 2.16159 1.93820 0.02921 0.15308 0.03893 0.05018 0.01042 0.01057 0.00110 4.05547 E.1-15 6.3 0.15104 1.91826 1.25366 0.03785 0.25804 0.00517 0.00862 0.00095. 0.00109 0.00091 0.32369 E-1-17 - 0.16871 2.09755 1.42483 0.03598 0.15433 0.05498 o.04646 0.00733 0.01166, 0.00184 0.23743 E-1-18 7.6 0.21899. 2.69575 3.84433 0.07893 1.33961 0.04021 0.03475 0.00684 0.00655 0.00155 1.61172 19 6.3 0.20837 2,24818 1.79228 0.09210 0.90045 0.02886 0.02736 0.00619 0.00592 0.00093. 0.78210 E-1-21 6.2 0.16364 2.30369 1.86131 0.04335 0.26847 -0.00371 0.00969 0.00156 0.00114 0.00145 0.90566 E 1-22 4.6 0.16893 2.00815 3.01516 0.03363 0.18447 -0.00300 0.00747 0.00110 .0.00215 0.00112 0.55090 E-1-23 7.5 0.26252 3.19659 32.68435 0.10094 5.46504 0.12400 0.07072 0.01221 0.01376 0.00500 12.42337 E-1-26 7 0.59761 2.36908 1.98863 0.06344 0.31054 0.02024 0.00797 0.00048 0.00173 0.00195 0.97689 E-1 -27 6.2 0.19032 2.20163 2.14498 0:06615 0.27883 0.00593 0.02533 0.00211 0.00390 0.00140 0.60230 E-1 -28 7.5 0.20004 2.05886 2.30398 0.07998 1.03620 1.09828 0.04954 0.00303 0.02274 0.00196 0.65391 E-1.30 5.7 0.14392 1.87516 1.24434 0.04120 0.11899 -0.00554 0.00177 -0.00027 -0.00026 0.00076 0.31901 E-1-31 7.3 0.19436 2.24819 3.69603 0.06847 0.39621 0.03186 0.02872 0.00597 0.00660 0.00102 0.57131 E-1-32 7.3 0.18214 2.33535 2.22416 0.05160 0.34582 0.00293 0.06186 0.00173 0.00250 0.00173 0,95553 E*1-33 6.8 0.15728 2.00790 2.17079 0.06215 0.24696 .0.00406 0.00442 0.00074 0.00088 0.00163 0.64578 7 _. .,- .. .rr+-

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a /-"IN, Table 7 - Entralnment Data Set #2 2001 (no element ner Individual larvao)

Sample L (mm) Co NI Cu Mo Ba Ce Nd Sm Gd Au Pb E-2-1 5 0.19662 2.49865 3.10124 0.14564 0.39073 0.05254 0.04107 0.00658 ).00647 0.00213 0.62525 E-2-4 4 0.15594 1.96560 2.46015 0.04024 0.14179 -0.00187 0.00708 0.00077 0.00157 0.00071 0.35947 E-2-5 5 0.15187 1.71863 1.82327 0.05337 0.21441 -0.00145 0.01035 0.00074 0.00017 0.00173 0.54007 E-2-8 5 0.20701 2.06539 1.63504 0.08188 0.77767 0.05521 0.0,3544 0.00797 0.00748 0.00163 0.53261 E-2-9 4.9 0.15932 1.95531 1.91838 0.04339 0.24928 0.00672 0.00739 0.00122 0.00090 0.00083 0.99301 E-2-10 5.9 0.18322 1.96448 2.95921 0.04,406 0.42909 0.01988 0.01897 0.00473 0.00364 0.00075 0.59582 E-2-11 6.6 0.19170 1.96245 2.63159 0.06313 1.08401 0.05681 0.03945 0.00746 0.00432 0.00130 0.64059 E-2-13 3.9 0.84429 2.54818 4.'98538 0.11151 4.38614 0.00116 0.00924 0.00138 ).p01 12 0.00637 2.26569 E.2-14 4.4 0.34108 2.03798 7.18580 0.14350 0.42944 0.03774 0.03096 0.00723 0.00520 0.00242, 6.86795 E-2-16 3.9 0.17833 1.91206 1.55564 0.18275 0.36140 -0.00582 0.00647. 0.001.11 0.00083 0.00120; 0.60285 E-2-19 4.8 -0.21292 1.83034 '1.08226 '0.04815 0.59197' -0.00541 0.00319 0.00032 ,.00026 0.00052 0.59429 E-2-22 4.3 .0.13381 1.68634 0.79148 0.03666 0.10711 -0.00479 .0.00638 0.00030 0.00025 0.00090 0.20017

'E-2-23 .4.9 0.13506 1.75004 1.31920'0.03'169 0.15013' 0.03063 0.02378 0.00424 0.00306 0.00042 0.26255 E-2-25 5.1 0.17020, :2.11568 1.97913 0.06918 0.36721 -0.02257 0.01873 0.00485 0.00183 0.00084 0.93584 E-2-26 5 0.16778 12.25062 1.98922 0.04316 0.71962 0.02436, 0.02143 0.00326 0.00129 0.70224 E-2.28 3.9 0.12851 .1.76270 -0.75368 0.03629 0.14509. '0.00114 0.00779 6.'00093 0.00018 0.00078 . 0.23064 E-2-29 - 6 .0.17053 2.43800 2.732i7'0;1 1294 0.35599' 0.00139 0.02098 0.00562 0.00238 0.00232 0.39500 0.01798a E-2'31 5.6 0.17043 2.02240 1.3'8159 0.06468' 0.57042 '0.07074 0.05817 3.01 551- 0.00108 *0.34523 E-2-32 5.5 0.15020 .1.89426 1.37457 0.04944 0.46573 0.05455 0.03836 0.00604 D.00509 0.00131 0.64030 E-2-34 '5.9 ,0.15550 2.04965 1.34170 0.05304 0.17498 ,-0.00228 0.01106 0.001158' 0.00116 0.00079 -0.28241 E42.36 4.3 0.13453 1.76331 2.40144 0.04466 0.23260 0.21593 0.01644 3.00199 0.00110 0.30352 E-2-37 6.6 0.15000 1.83213 2.81486 0.07867 0.42147 0.00609 0,01224 0.00259 0.00036 0.00181 ,0;43561 E-2-3U '3 0.13157 l .92339 1.73271 0.03324 0.18158 '0.60798 0.03669 0.06489 3.01432' 0.00066', 181.71422 E-2-39 ;5'. 0.15506 1.63113 .1.91585 0.07092 0.21928 0.01095 0.00792 0.00252 0.00261 0.00140 0.63774

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Table 8 - Entrainmient Data Set#3 2001 (no lmn e ESa mie 5m m ndvda ave Co. Ni C M O E31 53 01468 2.01712 1.36251 0.05107 Ba ' eNdSGdA 0.710I 41 -0047d.'06 0.0 12 u Pb 2-- . .39 .81 0 0 04 0.01 137 0.81 783

.9815 0,04423 E-3-3 5,7 0.14149 1.74418 2.4210OQ 0.05573 0.24898 -0.00701 0.00676 0.00078 *0.00052 0.00191 0.65272 E-3-6 0.09947 -0.01044 0.00435 0.00001 7 0 18097 2.05871 4.03474 0.07943 -0 00106 0.00170 0.28756 E-3-8 0.46052 0.08117 0.04690 0.00978 0.00935 6.2 0.18238 1.93193 1.67647 0.05361 0.00264 0.93663 E-3-1 1 6 0.14141 -000775 0.00617 0.00118 0 16021 2.03924 1.65727 0.06612 -000140 0.00128 0.65075.

E-3-13 1 00641 0.03,601' 0.03372 0.00529 3.5 0 15774 2.10124 1. 16524 .0.04306 0.00529 0.00368 0.47976

0. 14956 0.00049 0.00492 0.00145

-31 52 01992.18728 2.16280. 0.05538 0.00004 0.00081 0.35220 2-3 0.41324 0.02651 0.03098 0.00412 6 1 0 17982. 2 36576 1.77837: 0.00151 0072-1.25820~

E-3-20 64 0. 15843, 2.06476 1. 60O4%.5980 0.'06 153 0 29878 0 051.18

'"0.8

_0009'.,.~-04~

2-33.21' 6."8 23921,4.003 045000780063QOs

.0.21113 2 1338 3.2851710-08003'0734 0048 008 1142 E 3-22,! .246 .34 0.00174 '~0 00082 '01.00 .88 62 0 12674: 1.741487 2.53244:0.07597 0.00479 016 000241 0.607,10.

E-~~ 66 0 16805- 2. 03355-, 1.97330O:0.080O74 0 95 05~0.00594 :O000o70 &0120008048214.

0 573..001648- 0.02105 :0.00319 E- .- 4 . 5 4 0 5 6 118079 7Q*Q595 0.00257 190.001-5 0 53523~'~

E-3-26 6 1 0. 13046' 1.85588 023069 0.039 21 0.028.15 '0 .00557 1981:. 0.05939; 0 54 0 00498 0.000 6 0.44226e :

1E-3.2 6.6 0 '13834 .1. 9 5084,i.50896' 0.06002- 04.0001.0007 E-3.30' - 6.8 0.29887. 0 01963~- 0.0,1235 0.02`007 0001 95 .29 028012, 2396946560.094503 0.000740813 E-3.31- 5.7 0.16d8'3'7'. .2.87955. 1.6;5542 0.06919'0.20590 162425,- 0. 1170, .0.073671, 0.0 1439; 00104', P' 0.001 80 2.27 89 7..

'-00 07?20,O091'0024 0000.09 .292 E.. -774 1 . . 2 4 8 9 1 3 0 0 O 0 7 2 1 0 0 0 3 *0 0 2 0. .

E-3-32 . 4.8 0 2 0 0 0 0 4 0.69 10 0.11 71 6037r.1 4,85 1 .;4 12 4 3700 58 107137'0 00 9 O0.0047 0 01 7020 0 ' .2 2 5

-:1 1,11'. - ...

-. 11 I I .00.3- .8.,

E-3-33 7~~.2 61

~

O45, . ,Q37,;.75:!1965

.O.102.Q0052-0011 E6 3 69---1. 4 "' 098 340

6. 0 . ,-~0.0 71,19.:24 057 O.2 17C '-O O 30',,O 0-096~O.69 012 V"6 .df7~ 0 000 4., .00 4 - 981 -,.

E-3 5.7 ,11',2273 357 . , .O~

4 0,5 -

0, 29.,O'0 6 -- .01 E - -1 R 6 7~ .1 6 7 -00 10 03 7 ,-,' -- 95 4 6 6 .5 9 4 7 I 0 . 1 57.o

'7 ,'qij'

'IC I ~-,~ 1..

00 . 0

'-N I .

P Al q.

Table 9 - Entrainment Data Set#4 2001 (ng element per Individual larvae)

, RJ Sample L(mm) Co NI Mo Ba Ce . Nd Sm Gd Au Pb I E-4-1 7.7 0.28437 1.86187 1.62875 0.10233 0.57385 0.04712 0.03330 0.00783 0.00665 0.00088 0.42485 E-4-2 8.2 0.24109 1.88275 1.59764 0.08390 0.32206 0.00859 0.01397 0.00371 0.00170 0.00169 0.22398 E-4-3 8.5 0.14324 1.61789 1.67873 0.07473 0.59013 0.12197 0.07430 0.01304 0.01404 0.00128 0.25116 E-4-5 6.2 0.14938 1.68891 46.94319 0.06930 0.82521 0.03263: 0.03317 0.00626 0.00409 0.00073 .0.48745 E-4-6 6.5 3.49811 3.77235 1.52351 0.06760 0.64156 0.01493 0.01702 0.00422 0.00341 0.00140 0.30839 E-4-7 6.1 0.13335 1.90361 1.51262 0.05695 0.41039 0.04892 0.04416 0.00829 0.00606 0.00147 0.50138 6.8 0.11685 1.52143 3.34680 0.05275 0.28044 0.01406 0.01979 0.00379 0.00177 0.00103 0.26290 E-4-9 6 0.14683 1.82079 1.52332 0.05216 0.58977 0.02064 0.02238 0.00466 0.00179 0.00122 0.30874 E-4-11 6.2 0;14536 1.54225 1.05411 0.04692 0.77377 0.06610 0.04970 0.00950 0.00793 0.00054 0.28807 E-4-12 9.5 0.14740 1.76253 2.33106 0.10184 0.36238 0.00539 0.01659 0.00262 0.00136 0.00176 0.42377 E-4-13 6.2 0.15035 1.58502 1.58555 0.05847 1.40191 0.08716 0.05997 0,01243 0.01157 0.00200 0.48301 E-4-14 8.8 0.15875 1.59667 2.04410 0.06987 0.807.12,.0.06368. '0.05302;'O..191 :0.0086i4 0.00081 0.33899 E-4-1 5

• 6.5 0.17424 1.83807 3.40693 0.06975 0.38524 ,-0.00468: 0.00624'.'6.30 . 0.00300015 0.001'03 0.35909 E-4 .9 ~'6.7 0.13554' 0. 1.68262 6 ;2.15168 2.1568 0.07726 0.77506 0.03852 0.04i'SO 0.00756 0.00580 -0.00130! 0.50832 E-4-17 0.15439 '2.13520 2.76837 0.09723 0.95818 0.11026 0.09899 0.02367,.0.02906 0.00247 0.53395 E-4 8.1 0.31301 1.86703 3.55295 0.05920.' 070221 0.16443 0.11222 0.02377 0.01890.00177 0.34247 E-4-19 8.8 0.14624 2.00692 1.83147 0.-15480 0.44704 0.00724 '0;01394 '-0.00207 0.00033 0.00300 0.29308

.E-4.20 7.4 0.31621 2.48819 1.79147 0.20362 0.91153 0.01406 r0.01756 0.0021 0.00095. 0.00107 0.46270 E-4 7.9 0.17457 1.82303 .1.75424 0.07451 0.50408 0.02162 ;0.02058 0.00360 0.00086. 0.00076' 0.37808 E-4-24 ' 4.9. 0.13314 1.84537 0.80391 0.04238 0.15410 ,0.00190 0.00992 0.00164 0.000350.00043 0..20574 E-4.25 - 6.7 0.13010,1.82165 .0.95591 0.04167 0.25405 '0.03234 '0.02687 0'.00'563 0.00444 0.00046' 0.50583 E-4-26 - 6.8 *O 14819 2.4 1106 4.37959 0.10709 0.54043 0.05183 0.04062 6.00642 0.00440 0.00075; 0.67774 E-4-28 6.4 0.12249 1.64156 1.41786, 0.05385 i.13i93 0.08781 0.02544 0.00387 0.00466 0,00031 j0.36448 E-4.30 - - 6.4- 0.12903 1.67768 1.53805 0.06425 0.44983 0;00079 0.01406 '0;00309-,0.0008'4 0.00179 :0.28018

.. i . . .

.I I A I ..

I.

I -. . .

. , . , .. ,, s . , .

Table 10 - Entrainment Data Set#5 2001 (ng element per Individual larvae)

Sample L(mm) Co Nl -a Mo Ba Ce Nd Sm Gd Au Pb E-5-1 7.3 0.1354 1.5668 2.0217 0.0773 0.3635 0.0089 0.0160 0.0029 0.0005 0.0016 0.6591 E-5-2 7.4 0.1669 1.8641 5.0387 0.1027 0.9504 0.0649 0.0480 0.0110 0.0078 0.0023 1.0204 E-5-3 5.5 0.1106 1.4430 0.9640 0.0441 0.1962 -0.0063 0.0034 0.0012 -0.0002 0.0008 0.3584 E-5-4 7.5 0.1457 1.5339 1.6873 0.0828 0.3068 0.0601 0,0442 0.0033 0.0047 0.0007 0.5709 E-5-5 8.5 0.1395 1.5387 2.3544' 0.0863 0.2498 0.0055 0:0116 0.0026 0.0003 0.0011 0.4583 E6-56 8 0.1428 1.5434 1.9686'0.0940 0.2306 -0.0101 0.0045 0.0004 -0.0012 0.0010 0.4056 E-5-7 0.1209 1.5820 0.7705 0.0454 0.1556 0.0277 0.0218 0.0044 0.0025 0.0004 0.2843 E-58 7.5 0.1790 1.5-129 2.0325'0.1095 0.2699 -0.0020 0.0109 0.0013 -0.0007, 0.0009-;0.5223.-..;

E5-9 6.6 0.1181 1.4381 2.6291 0.0751 0.2543 0.0040 .. 0.0171,0.0021' 0.0010`0.0010-.:0.5010.

E-5-11 0.1,108,-;1.4120 .1.2P87,0.0628 0.1381"'-'0.0082 0.0044--,i0.0001',:.'0.12",..0004 0.2824 '

,I-512 7.7 0.1 362 1.7489. 2.0714..0 .1029 0.4263 0.0387 O0.0320i-0.00568' 0.006 0.0010,0.5625 5-13 ,'7.8 "0.1210 ,8682,0.0901 0.2440, 1.6197 0.0002. 0.0155" 0;01 -0.0010 '0.0020,-0.6892

'E-5-14

' 5.1 I 0.14,92.,1.8915i.1.7584 0.0557 0.2438,0.0092, .O18,,i 0.0028 'Q.00,0001 0,06.1.0619 E-5-15 5.3 0.1884 1.7268 1.2027 0.0526 0.0934 *-0.01.15,0,.0020i,,0.00,12' 0.0016,,0.0003',.0.2400,-

E-5-16 ;9 00.1670 1.6166;2.7409 0.1114 0.3299 0.0052 0.0086-',0.0017 -0.0012 '0.O0018 0.5691:1 E-518 0.1200 '1 798206998'0.04544' 00570" 0.0097T-0 0029.0002 0014 '0.004 0.2251 E 519 8 0.1769,- 1.6903'1.9549 00996 0.3!78'0.0023 0.0160 0.0019,0.0005 00009 .0.8143.,

E 5 20 5.5 0 2883 1.7893 1.0769 0 0939:0.4012 0.0041 0.0171 0.0032 '0b0002, 0.0010 0.3274 E 5-21 0.1200 1 5684 i1,0.254 0.0603.0.0790'0 0052 00047 OOOV -00017 0.0006 .0.2902 ,,,

E 5 22 3.8 01629'2'0134.2.3027 0.0593 0.2304- -0.0588 ,0.0277-0.0076'8 000701 09013.1 0308 524 78 0147322785 1.6516 0.06180.2798 0.0061 00152 0'.0016 00019 00012 -14240 E ,2'4,'n3:

-7 E;-M-.8-,

O. ,;, .473 .2 8 ,1 l/

s 01 , ,  ;

_. ' ,:' : , ,  :. ' 1'  ;' ' '  : ' < ;'

Table 11 - 2001 nonparametic discririnant function with K=2, traininq data Source ' WB- Other- - " Total

R  ;-' 32 ': -- -- .4 . 2 4 42 76.2% 9.5% 4.8% 9.5% 100%

TR 0 23 6 3 32 0.0% 71.9% 18.8% 9.4% i ,1,00%

WB 2 3 35 3 43 4.7% 7.0% " 81.4% 7.0% 100%

Total 34 30 *43 -' '117 29.1%- - - 25.6% 36.8% 8.5% 100%

I.I

Table 12 - 2001 NeuroShell Easy ClassifieJ!' traiinhg'l ata i;- M Source

_ NR-actual TR-actual" WB;-actual Total A

- fNR-clasifiedas  : 39 - 2 6 47 TR-clasified as 2 27 1 30 WB-clasified as ' 1 3 36 40 Total 42, 32 :. 43 117 Sensitivity 92.9% 4.4. 83.7%,

-.44

1. I A.+

.m 4 I

Table 13 - 2001 micro-elemental and DNA entrainment data analysis results summary Source NR TR WB Other Total

- Nonparametric discriminant function 5 0 74 34 113 with K=2, entrainment data 4.4% 0.0% 65.5% 30.1% 100%

Nonparametric discriminant function 16 6 91 0 113

£ with kernal density estimates 14.2% 5.3% 80.5% *0.0% 100%

with equal bandwidth NeuroShell Easy Classifierm 12 2 37 62 113 entrainment data, cut-off = 0.65 10.6% 1.8% 32.7% 54.9% 100%

NeuroShell Easy ClassifierWm 23 4 69 17 113 entrainment data, cut-off = 0.5 20.4% 3.5% 61.1% 15.0% 100%

'236 203 Nuclear DNA 260 368 1067 NeuroShell Easy Classifier" 24.4% 22.1% 34.5% 1 9.0% 100%