Juvenile Sportfish Monitoring in Florida Bay, Everglades National Park

Transcription

1 Juvenile Sportfish Monitoring in Florida Bay, Everglades National Park Christopher R. Kelble Joan Browder Allyn Powell I. Introduction The spotted seatrout, Cynoscion nebulosus, is an important recreational sportfish in Florida Bay and spends its entire life history within the Bay (Rutherford et al., 1989). The distribution of Cynoscion nebulosus varies in response to salinity conditions in the western and central portions of the bay (Thayer et al., 1999). Western Florida Bay is excellent habitat for juvenile spotted seatrout (Thayer et al., 1987; Thayer and Chester, 1989), whereas the northcentral part of the bay is less suitable. In , seatrout distributions were limited primarily to the western portion of the bay and absent from the north-central part of the bay, where hypersaline conditions prevailed. During , when hypersaline conditions in the northcentral area of the bay were rare or absent, the spotted seatrout juveniles expanded into the northcentral part of the bay (Thayer et al., 1999). Hypersaline conditions are characteristic of the north-central sub-region of Florida Bay (Orlando et al.1997, Kelble et al. 2007), although this could be alleviated with increased freshwater inflow (Lee et al. 2008), as the few periods of exceptionally high rainfall beginning in 1994 demonstrated. Despite hypersalinity, Powell (2003) reported substantial numbers of spotted seatrout larvae in Whipray Basin from that only translated into significant juvenile spotted seatrout populations in this sub-region in 1994 and 1995 during the period of relatively low salinities. Seagrass habitat is another variable in Florida Bay that may affect the abundance and distribution of juvenile spotted seatrout. A major die-off of dense stands of turtle grass, Thalassia testudinum occurred in the late 1980s (Fourqurean and Robblee, 1999). Plans to restore the Everglades include increasing freshwater flows to Florida Bay within the next few decades. Increased freshwater flows can have potential positive and negative impacts on spotted seatrout populations. At low salinities, the planktonic eggs of spotted seatrout sink to the bottom and are not viable (Alshuth and Gilmore, 1994; Holt and Holt, 2002), but increased freshwater flows can alleviate hypersaline conditions and allow an expanded distribution of the early life stages of spotted seatrout into the north-central part of the bay (Thayer et al., 1999). There will be indirect effects as well, because the altered freshwater flows will modify the current seagrass distributions and species composition. This project is a component of the RECOVER Monitoring and Assessment Plan of the Comprehensive Everglades Restoration Program. The objectives of this year s efforts were to: (1) develop reference conditions from pre-monitoring and Assessment Plan data ( ; ) that can be used as a baseline to evaluate trends in juvenile spotted seatrout populations, and, as an exercise, compare data with Monitoring and Assessment Plan (MAP) data sets ( ); (2) develop a juvenile abundance index (mean density and frequency of occurrence) and determine if annual differences in abundance occur among areas in the Bay; (3) examine the

2 relationship between juvenile spotted seatrout abundance and salinity and use this analysis to gain insights into the potential response of spotted seatrout to CERP; and (4) determine the salinity preference for other juvenile sportfish in Florida Bay. II. Methods Observational Data The four sub-regions (Fig.1) in which spotted seatrout are monitored were selected based upon 2 criteria: 1) juvenile spotted seatrout were previously collected in the sub-region according to historical data; and 2) the sub-region is likely to be affected by water management changes associated with CERP. Each sub-region was divided into cells (macrocells) measuring 1800 m on a side, which were further divided into four smaller cells (microcells). Hence, there were four potential sampling sites per macrocell. Macrocells were randomly selected within each subregion and a microcell (900 m on a side) was then randomly selected within the randomly selected macrocell. A sample was collected at the center of this microcell. Because of the presence of shallow mud banks, islands, and variable tides, numerous macrocells contained less than four trawlable microcells. If a microcell was not suitable for trawling, another microcell within the macrocell was randomly chosen. If there were no suitable microcells within a macrocell, we randomly selected an alternate macrocell. There are 50 trawlable macrocells in the West sub-region, 23 in Rankin, 19 in Whipray, and 20 in Crocodile Dragover (Fig. 1). The sampling scheme followed from 2004 through 2008 was weighted by the number of trawlable sites per sub-region; therefore the initial (through 2008) total number of samples to be collected annually (ca. 360) were distributed among areas as follows: 156 samples per year in the West, 84 in Rankin, 60 in both Whipray and Crocodile Dragover. A modified sampling distribution based on an updated power analysis began in This new distribution collects 492 samples with 120 collected in the West, 138 collected in Rankin, 114 collected in Whipray and 120 collected in Crocodile Dragover. Sampling is conducted monthly during the peak abundance of juvenile spotted seatrout (June through November). An equal number of samples was scheduled for collection each month from each sub-region, 20 in the West, 23 in Rankin, 19 in Whipray and 20 in Crocodile Dragover (Powell et al., 2007). However, this equal spacing did not occur each year due to unforeseen circumstances. In 2004, funding did not become available until August and a hurricane truncated sampling in September. In 2005, sampling was not performed in August, September, and only partially in October due to hurricanes. We sampled intensively in November 2005 in an attempt to reach our annual sampling goal. Sampling from 2006 through 2009 was as planned as we have been able to minimize the impact of adverse weather and funding delays. Juvenile spotted seatrout sampling was conducted with an otter trawl. The trawl has a 3.4 m head rope, 3.8 m foot rope equipped with a 3 mm galvanized tickler chain, 6 mm mesh in the body, and a 3 mm tailbag. The mouth opening has an effective width of 2.1 m. The trawl was towed at a speed of approximately 2.0 m s -1 for 2 min (to sample an area of about 500 m 2 ), unless the net was clogged with detritus. If the net became clogged the sample would be counted if the tow was longer than a minute or redone if the clog occurred prior to 1 minute. In , a

3 floating marker was deployed at the beginning and end of each tow and the distance between buoys measured using GPS technology (Garmin 76 and Garmin Mapper software). In 2008 we modified this scheme, recording a waypoint in the GPS at the beginning and end of each tow to more accurately calculate the tow distance and bearing. The distance towed (calculated from the GPS waypoint) was multiplied by the mouth opening of the net to calculate the area sampled in a tow. Density (number of fish 1000 m -2 ) was used as an index of abundance. Spotted seatrout >100mm standard length were excluded from the analysis, because previous work determined that they are not efficiently captured by the sampling gear. Although juvenile spotted seatrout were the main target of our sampling, we also identified and counted other species of sportfish caught in the tows. Figure 1. Location of all potential sampling stations by sub-region in Florida Bay. Symbols are centered in the macrocell that is 1800 m on a side. Temperature and salinity were measured with a Hydrolab Scout 2 Water Quality Data System and a H20 or a SeaBird Model 21 thermosalinograph at each tow. Seagrass abundance was quantified by conducting triplicate Braun-Blanquet 0.25 m 2 quadrats at both endpoints and the midpoint of each tow. The Braun-Blanquet data included measurements of algal abundance. A non-parametric, Mann-Whitney U-test (Sokal and Rohlf, 1981) with = 0.05 was used to test differences in spotted seatrout densities and seagrass densities among years and areas.

4 III. Results and Discussion Establishing Juvenile Spotted Seatrout Reference Conditions Pre-MAP data ( ; 1994 through 2000) were used to establish reference conditions for evaluating juvenile spotted seatrout performance measures. Methods for the collection of these historical data are detailed in Thayer et al. (1987); Thayer and Chester (1989); and Powell et al. (2007). Historical data used were in concordance with the sampling design for the on-going MAP juvenile spotted seatrout monitoring program (Fig. 1). Hence, only data from June through November at stations that coincided with the RECOVER/MAP monitoring program were included, providing 164 collections. Because sampling during the period of interest (June- November) sometimes occurred during two annual periods (e.g., ) we reported both years (Fig. 7). After CERP implementation, all pre-implementation data (historical and MAP) can be combined to develop more comprehensive reference guidelines and performance measures. Reference guidelines are subject to climatic conditions and natural variability during the pre-implementation sampling, and the factors that limit the distribution of a species must be understood and examined in the context of potential changes due to restoration efforts. Quinn and Dunham (1983) proposed four strong generalizations (that are not mutually exclusive) that cause distributional limits: (1) physiological limits that affect survival; (2) lack of recruitment in certain areas; (3) limits set by competition; and (4) limits set by predation. Water management changes could induce physiological limits if activities result in mesosaline or hypersaline conditions that affect egg, larval and juvenile spotted seatrout survival (Powell, 2003). The influences of CERP activities on recruitment, competition, or predation will be difficult to discern, and these factors could influence spotted seatrout abundance and distribution; therefore, we recommend evaluating long-term trends rather than abundance indices and distributional data for individual years. We apply statistical methodologies to help identify biological and environmental variables that influence juvenile spotted seatrout population abundances. Monitoring Results: September 2004-November 2009 Data from the 12 years in which juvenile spotted seatrout abundance has been quantified has a high degree of variability (Fig. 2). However, there appear to be high and low years of juvenile spotted seatrout abundance within each region. Many years have similar low abundances and frequencies of occurrence within each sub-region. There are also years in which the abundance and frequency of occurrence are elevated compared to these low-population years. In the west sub-region, four ( , 1999, 2000 and 2006) of the 12 years had elevated spotted seatrout populations as indicated by the frequency of occurrence being nearly double the observations during the low-population years. In Rankin, the break between high-population and low-population years is not as pronounced. Instead, there are five low-population years ( , 2004, 2007, 2008 and 2009), three moderate-population years ( , 1999 and 2005), and four high-population years (1996, , 2000 and 2005). In Whipray there are six high-population years (1995, 1996, 1997, 2005, 2006 and 2007) and in Crocodile

5 Dragover there is only 1 (1999). Figure 2. Abundance (number 1000 m -2 + standard error) as a bar chart with each error bar representing the standard error and frequency of occurrence as a scatter plot for juvenile spotted seatrout by area and year in Florida Bay. Values in parentheses indicate the number of stations sampled. However, there were significant differences in sample size between years and the data from the pre-map surveys prior to 2004 all had n<15. Thus, the pre-map data may not well define the juvenile spotted seatrout population; therefore, these data were combined to provide a pre-map reference condition in all further analyses.

6 Table 1. Summary of Mann-Whitney U-test p-values comparing spotted seatrout monitoring abundances between years within sub-regions. Arrows indicate the direction of a significant increase or decrease in values [i.e. the pre-map ( ) spotted seatrout density in the west was significantly greater than all other years, except 2006 which it was significantly less than].

7 Figure 3. Abundance (number 1000 m -2 + standard error) as a bar chart with each error bar representing the standard error and frequency of occurrence as a scatter plot for juvenile spotted seatrout by area and year in Florida Bay. Values in parentheses indicate the number of stations sampled. Data from are combined. In the west sub-region, both the pre-map period and 2006 had significantly higher abundances of juvenile spotted seatrout than other years (Table 1 and Figure 3). Abundance was significantly higher in 2006 than in the pre-map period, and 2006 also had the highest frequency of occurrence (0.51). The only difference among the low-population years was that 2007 was significantly greater than In Rankin, the pre-map period, 2005, and 2006 all had significantly greater juvenile spotted seatrout abundances than the low-population years of 2004, 2007, 2008 and However, there were numerous differences within high-population and low-population years in Rankin. Juvenile spotted seatrout abundance was significantly higher in 2005 than in Both 2004 and 2007 had significantly greater juvenile spotted seatrout abundances than 2008,

8 and 2007 was also significantly greater than 2009 (Fig. 3, Table 1). In Whipray, the pre-map data had a large degree of variability and did not fit into either the high-population or low-population bin. The high-population years of 2005, 2006, and 2007 had significantly greater juvenile spotted seatrout abundances than the low-population years of 2004, 2008 and The only significant difference within classifications was that abundance was greater in 2006 than 2005 and 2007 (Fig. 3, Table 1). In Crocodile Dragover, the high-population years of 2004, 2005 and 2007 had significantly greater juvenile spotted seatrout abundances than the low-population years of 2006, 2008 and 2009 (Fig. 3, Table 1). Spotted seatrout abundance and frequency of occurrence (numbers1000 m -2 ) were low in 2004, relative to other years, in all areas except Crocodile Dragover. Abundances were high in 2005 and 2006 in all areas except in the west in 2005 and in Crocodile Dragover in In 2007, abundance was high in Whipray and Crocodile Dragover in the central Bay; whereas abundance was low in the west and Rankin sub-regions. In 2008 and 2009, juvenile spotted seatrout populations were low throughout the Bay (Fig. 3, Table 1). Figure 4. Mean salinities at time of tow and standard deviations by area and year. Mean salinities in the West sub-region during the sampling period were moderate and comparable to the pre-map record. Salinities were slightly depressed in the fall of

9 2005 following the passage of hurricanes (Fig. 5). Although immediately after the hurricanes the two lowest mean monthly salinities were recorded, these values were still greater than 31, confirming the previously documented influence of Gulf of Mexico waters on western Florida Bay salinity patterns (Kelble et al. 2007). Salinity increased in 2007 to a mean of 39.3 and increased still further in 2008 to a mean of 41.3 when a regional drought was more widespread and the nearshore Gulf of Mexico was also hypersaline (Ortner et al. 2008). Mean monthly salinities in 2008 began much higher than previous records, but by October had receded to within the historical record (Fig. 5). The annual salinity in the west sub-region for 2009 (38.8) was still hypersaline and the third highest on record. Figure 5. Monthly mean values of salinity in each sub-region for all years of the MAP effort. Mean sample-year salinities for Rankin increased substantially from 2006 to 2008 before decreasing, but remaining elevated in 2009 (Fig. 4). The mean salinity in Rankin in 2008 was 44.1, more than four-times greater than the second highest salinity of 40.0 observed in Mean monthly salinities in 2007 were relatively high during the first four months of sampling (June-September), and considerably lower in the latter sampling period. In 2008, salinities were the highest on record from June through August and by the end of the sampling season had returned to be within their historical range. The monthly mean salinities were lower in 2009, but followed the same approximate pattern as 2008 (Fig. 5). Overall, higher salinities in the Rankin sub-region co-occurred with decreased juvenile spotted seatrout abundance, as was observed in 2007, 2008 and Salinity patterns of Rankin and Whipray appeared similar, likely because both sub-

10 regions have long residence times and a greater tendency towards hypersaline conditions. In Whipray, salinities began increasing after 2005, took a big jump in 2008, and decreased in 2009 (Fig. 9). In 2008, salinities in Whipray were the highest on record for this study with a mean greater than 43. In 2009, salinities decreased, but remained hypersaline. The years with hypersaline annual mean salinities correspond to the low-population years, suggesting a strong relationship between hypersalinity and low juvenile spotted seatrout populations in Whipray. Overall, salinity patterns in Crocodile Dragover were slightly lower and more variable than in Whipray, reflecting the direct freshwater runoff that this sub-region sometimes receives (Fig. 4). However, two of the three high-population years, 2005 and 2007, corresponded with the lowest annual mean salinities in this sub-region. The monthly salinity means in all years decreased from June through November (Fig. 5). Figure 6. Monthly mean values of salinity in each sub-region for all years of the MAP effort. Monthly patterns of juvenile spotted seatrout frequency of occurrence were highly variable in the West sub-region (Fig. 6). The lone commonality was a decrease in November for all years that likely reflects the end of the spotted seatrout spawning-season. In 2009, the frequency of occurrence of juvenile spotted seatrout peaked in July and decreased to 0 by September, representing an earlier peak and decline than other years. In the Rankin sub-region, juvenile spotted seatrout densities and frequencies of occurrence have been declining since Spotted seatrout were collected at 44% of the stations in 2005, 20% in 2006, 6% in 2007, 0% in 2008, and 0.7% in The peak in spotted

11 seatrout collections in 2005 mostly occurred in October and November after the passage of Hurricanes Katrina, Rita, and Wilma over Florida Bay and coincident with the lowest salinities observed in Rankin (Fig. 5 and 6). In 2007, juvenile spotted seatrout were not collected in three (July, August, October) of the six months (June through November) sampled; whereas, in 2006 they were collected every month. Densities of juvenile spotted seatrout observed in Rankin in 2007, 2008 and 2009 mirrored those observed in Crocodile Dragover; an area where spotted seatrout are rarely collected. Only one juvenile spotted seatrout was collected in Whipray Basin in 2008, continuing a decline from the peak in abundance and frequency of occurrence observed in 2006 (Table 1, Fig. 3). In 2009, four juvenile spotted seatrout were collected in Whipray; however, the sampling effort in the area was nearly double that of previous years. Thus 2009 was still a lowpopulation year. The peak in juvenile spotted seatrout was observed in October, reproducing the late season peak observed in 2004 and Density and frequency of occurrence in Whipray remained higher than Rankin for the third consecutive year, despite close spatial proximity (Fig. 1). The relatively low juvenile abundance observed in Whipray is perplexing, because spotted seatrout larvae have been consistently collected there at relatively high densities (Powell, 2003). In Crocodile Dragover, an area that represents their eastern most distribution in Florida Bay, juvenile spotted seatrout were rarely collected. They generally occur at <10% of the stations sampled (Fig. 3). They were never collected in 2006 or In 2009, the year we increased the sampling intensity in the area, a single juvenile was collected in July (Fig. 6). Surprisingly, in 2007, spotted seatrout were collected at slightly higher densities and occurred at a greater frequency in Crocodile Dragover than in the Rankin sub-region. Notable increases in spotted seatrout densities in north-central Florida Bay occurred in the fall of 2005, following a considerable salinity decrease as a result of hurricanes (Fig. 8). Densities of ca. 10 juvenile spotted seatrout 1000 m -2 in the Rankin in October 2005 were the second highest mean densities we observed in Florida Bay, only surpassed by mean densities in the West area in 2006 (Fig.8). Spotted Seatrout Reference Body Condition Beginning in September 2007, all juvenile spotted seatrout were measured to obtain lengths and weights. From these values, we derived an index of body condition based upon the coefficient, q, determined by a relationship that assumes weight is proportional to length cubed. (1) We found no correlation in a preliminary examination to determine if body condition varied with salinity (Fig. 7). But we know have a reference for determining if restoration activities result in a change in the body condition of juvenile spotted seatrout. The lack of a correlation with salinity may help us determine which of the above mentioned four population control mechanisms is responsible for the small population of juvenile spotted seatrout during hypersaline periods in Florida Bay.

12 Figure 7. Depicted are a histogram of q, an index of body condition, and scatter-plot of q versus salinity showing no significant relationship. Spotted Seatrout Distribution and Abundance Relative to Salinity (Potential Restoration Effects) To examine the impact of salinity on the juvenile spotted seatrout population the data were binned into salinity categories, each with a range of 5. Bins with fewer than five observations were omitted, due to the inability of such a small sample size to capture the observed variability. The data on the seatrout population was expressed as three abundance metrics: 1) frequency of occurrence (i.e. the percent of tows with at least 1 juvenile spotted seatrout); 2) the concentration of seatrout when present (# per 1000 m -2 ); and 3) density (# per 1000 m -2 ) for all observations. When the data were examined as a whole, but delineated by sub-region and divided into salinity bins, there was a significant inverse linear relationship between salinity and frequency of occurrence (F 1,26 = 6.93, p = 0.014). Only in the West sub-region were juvenile spotted seatrout observed at salinities greater than 50. Bay-wide there were also significant inverse relationships of salinity with concentration (i.e., average number, where present; F 1,26 = 10.5, p = 0.003), and density with salinity (F 1,26 = 5.00, p = 0.034). Examining the data within each sub-region showed that all of the sub-regions had at least one aspect of the juvenile spotted seatrout population with a significant inverse linear relationship with salinity. In the west sub-region, concentration was the only abundance metric inversely correlated with salinity. These results suggest that the frequency of samples with juvenile spotted seatrout present does not vary with salinity; however, the concentration when they are present decreases significantly with increasing salinity. In Rankin and Crocodile Dragover, both the frequency of occurrence and concentration were inversely correlated with salinity. Thus, the concentration of juvenile spotted seatrout observed and the frequency of samples that capture juvenile spotted seatrout both decrease with increasing salinity. In Whipray, the frequency of occurrence and density were significantly inversely related to salinity (Fig. 8).

13 Figure 8. Scatter plots depict the correlation of the juvenile spotted seatrout population to salinity within each sub-region. The black boxes are frequency of occurrence, the blue diamonds are concentration and the red circles are delta-density. Only significant linear regressions are depicted. A Generalized Linear Model (GLM) was developed to examine the influence of salinity, temperature, and seagrass biomass on the juvenile spotted seatrout distribution. Based on AIC, the best model for predicting juvenile spotted seatrout density included all three potential explanatory variables (water temperature, salinity, and seagrass biomass). Estimated juvenile spotted seatrout density increased with increasing temperature, decreased with increasing salinity, and increased but saturated with greater seagrass biomass (Fig. 11). The effect of temperature is likely confounded by the seasonality of spotted seatrout spawning, which results in peak juvenile abundances from June to November when temperatures are higher. A refined GLM should attempt to normalize the temperature to seasonal variations and better explore how deviations from normal temperatures affect the juvenile spotted seatrout distribution. The effect of seagrass shows an increase from the lower quartile to the second quartile ( % of observations). Above the median, the effect of seagrass is insignificant as the slope of this relationship is near zero (Fig. 9). Thus, the GLM suggests that juvenile spotted seatrout have low densities in areas devoid of seagrass or with sparse seagrass blades. However, as long as the area has seagrass, the seagrass biomass is irrelevant. The GLM suggests that, of the three variables, salinity has the most pronounced effect on juvenile spotted seatrout distributions. The GLM results show that at salinities less than 33, there is typically a density just below 1 juvenile spotted seatrout per 1000 m -2 and a lot of variability in observations; however at salinities greater than 39.5 there is less than 1 juvenile spotted seatrout per 1000 m -2 and little variability.

14 Figure 9. Estimates of seatrout density from the delta-lognormal GLM with bins defined by quartiles. A logistic regression was employed to quantify the impact of various environmental parameters on juvenile spotted seatrout frequency of occurrence. This abundance metric was selected principally because the power analysis found much more power to detect changes in frequency of occurrence versus mean density for the same number of samples based on the observed population distribution of juvenile spotted seatrout. The multiple logistic regression calculated significant dependencies on salinity, temperature, and depth. The dependency on depth and temperature could be a result of the tight correlation of these two variables. For simplicity the relationship of juvenile spotted seatrout habitat suitability with temperature and salinity is presented (Fig. 10). This relationship shows several important aspects. First juvenile spotted seatrout are unlikely to be observed at temperatures below 20 C, reflecting the seasonal spawning cycle. In hypersaline waters, juvenile spotted seatrout are only found in areas with

15 moderate temperatures. Overall, this probability plot shows that juvenile spotted seatrout prefer low salinity and moderate temperatures. To further investigate the impact of salinity on the logistic regression the probability of juvenile spotted seatrout observation was plotted against salinity. This showed a significant inverse linear relationship, further supporting the observational data. The relationship was more pronounced when the confounding effects of temperature and depth were removed (Fig. 11). Figure 10. Index of habitat suitability for juvenile spotted seatrout across the range of salinity and temperatures in Florida Bay extracted from logistic regression. Figure 11. These scatter-plots depict the correlation between the probability of occurrence for juvenile spotted seatrout and salinity from both the raw logistic regression (left panel) and the regression with the confounding effects of temperature and depth removed (right panel). These findings all concur that hypersalinity is negatively correlated with juvenile spotted seatrout densities in Florida Bay. Therefore, if CERP accomplishes its interim goal of reducing the magnitude, duration and spatial extent of hypersalinity events, it should have a beneficial impact on the juvenile spotted seatrout population in Florida Bay, unless salinities become so low during spawning time that egg buoyancy and viability would be compromised. However, salinity decreases are not expected to be drastic enough to compromise egg viability. Increasing the juvenile population is likely to increase the adult population, which is an important

16 recreational fishery stock within Florida Bay. Relationship of other Sportfish to Salinity Beginning in 2009, we expanded the project to collect information on other sportfish species within Florida Bay. As yet, we have only a single year of information for many of these species. However, a smaller subset of these species has been enumerated since MAP sampling began in 2004 (Table 2). We investigated the relationship between the diversity of these species with salinity and the salinity preferences of several of the more common and fisheries-relevant species. Table 2. Salinity ranges and means with confidence intervals and sample size (n) for the 23 species that have been enumerated since the project s inception in The diversity of sportfish taxa (defined by table 2) observed in the bay showed a significant dependence on salinity (Fig. 12). The tows in which no sportfish were observed had significantly higher salinities than the overall salinity distribution (t=-3.05, p=0.002). Tows in which 1, 2, or 3 taxa were observed had significantly lower salinities than tows where no sportfish were observed. There were no significant differences in salinity for tows with greater than 3 sportfish taxa observed; however, there does visually appear to be a restricted salinity distribution at higher diversities.

17 Figure 12. Box and whisker plot depicting the salinity range for the number of sportfish taxa observed in a tow (e.g. the second box and whisker plot from the left depicts the salinity range for tows where 0 of the 23 sportfish taxa were observed). All Values is the range of all salinity values observed. Data includes all MAP observations ( ). All Values is the range of all salinity values observed. The central line is the median, the box depicts the range of lower to upper quartile, the whiskers demark the minimum and maximum of non-outlier values, and the circles depict the outliers.

18 Figure 13. Box and whisker plot depicting the range of salinity values within which the identified sportfish species was observed. All is the range of all salinity values observed. Data includes all MAP observations ( ). The central line is the median, the box depicts the range of lower to upper quartile, the whiskers demark the minimum and maximum of non-outlier values, and the circles depict the outliers. The salinity preferences of each sportfish taxa contributes to the overall diversity, but can also contribute to the temporal and spatial distribution of the taxa. To examine species salinity preference we used a subset of the sportfish taxa presented in table 2 that focused on species with larger sample sizes and economic relevance. There was not a large range in mean salinities for these taxa (Fig. 13), but there were some significant salinity trends. First, the upper quartile for all taxa, except sheepshead, was less than the upper quartile for all salinity values despite there being approximately an order of magnitude larger sample size for all salinity values. This large

19 sample size would constrict the quartile range. This suggests that these taxa are less commonly found in the hypersaline conditions. Moreover, three taxa (Atlantic spadefish, spotted seatrout and great barracuda) had salinity distributions that were significantly less than the overall salinity distribution, =0.05. This suggests that if CERP is successful at mitigating hypersalinity, these taxa should become more common, and the diversity of sportfish will likely increase. IV. Lessons Learned Based upon the results of the first 5 years of sampling and the power analyses we optimized our sampling protocol. The power analyses suggested we collect the following number of samples per year in each sub-region: 90 samples in the west, 138 samples in Rankin, 114 samples in Whipray and 120 samples in Crocodile. However, we were uncomfortable with the dramatic reduction in sampling effort for the west sub-region where the vast majority of the juvenile spotted seatrout population is located and there is a large degree of variability. Thus, starting in 2009, we collected 120 samples in the west sub-region, 138 samples in Rankin, 114 samples in Whipray and 120 samples in Crocodile. This new sampling regime required the collection of 492 samples per year, up 132 samples from the old sampling regime. The new sampling regime improved our ability to estimate the juvenile spotted seatrout population in the central areas of the bay, where the population is often low, but where the greatest change from CERP may occur. To allow for this expansion in juvenile spotted seatrout sampling without any increased cost, we altered the methodology for collecting seagrass data. The GLM analysis showed only a minor dependency on seagrass and this occurred when seagrass biomass increased from the lowest to second quartile. In other words, the only significant effect of seagrass appears to occur when seagrass is sparse or non-existent which reduces the concentration of juvenile spotted seatrout. Based upon this finding, we sampled seagrass via estimation of percent cover of each species using a 0.5 m 2 quadrant at 5 points along the tow-line. This sampling methodology will likely still allow for the determination of seagrass abundance at the resolution necessary to examine and account for its affect on juvenile spotted seatrout. Furthermore, this methodology improves the disparity between sampling scales by two orders of magnitude for the trawl and the seagrass sampling. This disparity was cited in previous reviews of our reports as a weakness in sampling protocol. We did not report on seagrasses in this report, because the switch to the new sampling methodology restricted our ability to use the old data beyond examining frequency of occurrence. Although, this parameter is likely of great importance to juvenile spotted seatrout, we opted to wait until next year when we have 2-years of data collected with the new methodology. The same is true for examination of the samples in which all species were enumerated, which also began in Preliminary results suggest great value will come from these additional samples. V. Acknowledgements This program has greatly benefitted from the efforts of field and laboratory technicians, specifically Joseph Contillo, Patrick Cope, Mike Lacroix, Lloyd Moore and Mike Greene. Kyle

20 Shertzer developed the General Linear Model. Joseph E. Serafy provided invaluable guidance and thoughtful conversation with both the implementation of the logistic regression and binomial power analysis. VI. References Alshuth, S., and R. G. Gilmore, Jr Salinity and temperature tolerance limits for larval spotted seatrout, Cynoscion nebulosus C. (Pisces: Sciaenidae). Int. Coun. Explor. Sea, Coun. Meet. Pap., ICES-CM-1994/L: 17, 19 p. Chester, A. J., and G. W. Thayer Distribution of spotted seatrout (Cynoscion nebulosus) and gray snapper (Lutjanusgriseus) juveniles in seagrass habitats of western Florida Bay. Bull Mar. 46: Fourqurean, J. W., and M. B. Robblee Florida Bay: a history of recent ecological changes. Estuaries 22: Hall, M. O., M. J. Durako, J. W. Fourwurean, and J. C. Zieman.1999.Decadal change in seagrass distribution and abundance in Florida Bay.Estuaries 22: Hemminga, M. A., and C. M. Duarte Seagrass ecology. Holt, G. J., and S. A. Holt Effects of variable salinity on reproduction and early life stages of spotted seatrout. In Biology of the spotted seatrout (S. Bortone, ed.), p CRC Press, Wash., DC. Kelble, C.R., E.M. Johns,W.K. Nuttle, T.N. Lee, R.H. Smith, and P.B. Ortner Salinity patterns of Florida Bay. Estuarine Coastal and Shelf Science 71: Lee, T.N., N. Melo, E. Johns, C. Kelble, R.H. Smith, and P. Ortner On water renewal and salinity variability in the northeast subregion of Florida Bay. Bulletin of Marine Science 82: Orlando, S. P., Jr., M. B. Robblee, and C. J. Klein Salinity characteristics of Florida Bay: a review of the archived data set ( ). National Oceanic and Atmospheric Administration, Office of Ocean ResourcesConservation and Assessments, Silver Spring, Maryland, 33 p. Ortner, P.B., E.M. Johns, and C.R. Kelble Final Report to USACoE: Water Quality, Salinity and Circulation Monitoring in the CERP/Southern Estuaries Module Domain. Porch, C. E., A.B. Powell, and L. Settle Power Analysis for Detecting Trends in Juvenile Spotted Seatrout Abundance in Florida Bay. NOAA Technical Memorandum NMFS- SEFSC-526, 12 p. Powell, A. B Larval abundance and distribution, and spawning habits of spotted seatrout, Cynoscion nebulosus, in Florida Bay, Everglades National Park, Florida. Fish. Bull.101: Powell, A. B., G. W. Thayer, M. Lacroix, and R. Cheshire Juvenile and small resident fishes of Florida Bay, a critical habitat in the Everglades National Park, Florida. NOAA Professional Paper NMFS 6, 210 p. Quinn, J. F., and A. E. Dunham On hypothesis testing in ecology and evolution. Amer. Nat. 122: Rutherford, E. S., T. W. Schmidt, and J. T. Tilmant Early life history of spotted seatrout (Cynoscion nebulosus) and gray snapper (Lutjanusgriseus) in Florida Bay, Everglades National Park, Florida. Bull. Mar. Sci. 44:49-64.

21 Sokal, R. R., and F. J. Rohlf Biometry, 2nd ed. W. H. Freeman and Company, San Francisco, CA, 859 p. Thayer, G. W. and A. J. Chester Distribution and abundance of fishes among basin and channel habitats in Florida Bay. Bull. Mar. Sci. 44: Thayer, G. W., A. B. Powell, and D. E. Hoss Composition of larval, juvenile and small adult fishes relative to changes in environmental conditions in Florida Bay. Estuaries 22: Thayer, G. W., W. F. Hettler, Jr., A. J. Chester, D. R. Colby, and P. J. McElhaney Distribution and abundance of fish communities among selected estuarine and marine habitats in Everglades National Park. South Florida Research Center Rep. SFRC-87/02. Everglades National Park, South Florida Research Center, Homestead, Florida. Zieman, J. C., J. W. Fourqurean, and R. L. Iverson Distribution, abundance and productivity of seagrasses and macroalgae in Florida Bay. Bull. Mar. Sci. 44: