Relationship between Habitat and Sport Fish Populations over a 20-Year Period at West Lake Tohopekaliga, Florida

North American Journal of Fisheries Management 26:124 133, 2006 Ó Copyright by the American Fisheries Society 2006 DOI: 10.1577/M04-191.1 [Article] Relationship between Habitat and Sport Fish Populations over a 20-Year Period at West Lake Tohopekaliga, Florida KIMBERLY I. BONVECHIO* Florida Fish and Wildlife Conservation Commission, Eustis Fisheries Research Laboratory, 601 West Woodward Avenue, Eustis, Florida 32726, USA TIMOTHY F. BONVECHIO Florida Fish and Wildlife Conservation Commission, Kissimmee Fisheries Field Office, 1601 Scottys Road, Kissimmee, Florida 34744, USA Abstract. Relationships between environmental variables and sport fish population parameters were investigated for West Lake Tohopekaliga from 1983 to 2002. Through time, the lake has undergone a process of cultural oligotrophication as indicated by reductions in nutrient and chlorophyll-a concentrations because of improvements in wastewater treatment and the establishment of hydrilla Hydrilla verticillata in the system. With this decline in trophic state, angler catch and catch rate increased for largemouth bass Micropterus salmoides, but harvest and harvest rate decreased for black crappie Pomoxis nigromaculatus. Furthermore, the angler base of the lake shifted almost exclusively to those fishing for largemouth bass. Although angling effort for largemouth bass has increased through time with reductions in trophic state, angling effort for black crappies and sunfish species Lepomis spp. has declined. The growth of largemouth bass less than age 5 has also declined since the late 1980s, and the proportion of memorable-sized fish in electrofishing catches decreased with decreases in total phosphorus. Areal coverage of hydrilla varied dramatically throughout this 20-year period, and angler catch rate of largemouth bass as well as angler harvest rate of black crappies were positively correlated with hydrilla coverage. We believe the current level of nutrients and intermediate levels of vegetation (20 40%) should be maintained to balance the needs of both the angling and nonangling communities and to maximize the economic potential of the lake. Changes in habitat and water quality can influence sport fish populations in lakes and reservoirs (Colle and Shireman 1980; Buynak et al. 1991; Bettoli et al. 1992; Bachmann et al. 1996; Hoyer and Canfield 1996; Maceina et al. 1996; Wrenn et al. 1996). Increasing aquatic macrophyte coverage can be beneficial to sport fish populations by increasing diversity, abundance, and standing crop of invertebrate prey species and reducing their vulnerability to predation at small sizes (Crowder and Cooper 1982; Moxley and Langford 1985; Wiley et al. 1984; Dewey et al. 1997). Increased abundance of age-0 largemouth bass Micropterus salmoides was detected at hydrilla coverages up to 91% at Lochloosa Lake and up to 75% at Orange Lake, both lakes in Florida (Tate et al. 2003). However, excessive vegetation coverage can result in reduced growth (Crowder and Cooper 1982; Bettoli et al. 1992) and condition (Colle and Shireman 1980) of some sport fish species and has been related to reduced feeding efficiency (Savino and Stein 1982, 1989a, 1989b; Bettoli et al. 1992). Other studies have found that changes in habitat complexity can lead to changes in * Corresponding author: kim.bonvechio@myfwc.com Received November 8, 2004; accepted September 27, 2005 Published online January 16, 2006 behavior of some sport fish and prey species (Savino and Stein 1982, 1989a, 1989b; Hosn and Downing 1994; Dewey et al. 1997; Sammons et al. 2003). In addition to the influences of aquatic vegetation, changes in water quality have been correlated with sport fish abundance, biomass, and growth (Kautz 1982; Buynak et al. 1991; DiCenzo et al. 1995; Hoyer and Canfield 1996; Maceina et al. 1996; Allen et al. 1999). For example, Hoyer and Canfield (1996) found that growth of age-1 and age-2 largemouth bass was positively correlated with total phosphorus, chlorophyll a, and total organic nitrogen concentrations. Although the abundance of young-of-year largemouth bass (,160 mm) was not significantly correlated with any water-quality parameters, a negative relationship was detected between abundance of subadult (161 240 mm) largemouth bass and concentrations of chlorophyll a, total phosphorus, and nitrogen (Hoyer and Canfield 1996). In a study of 32 Alabama reservoirs, increased chlorophyll-a concentration had little impact on angler catch or harvest rate of black crappie Pomoxis nigromaculatus and black bass Micropterus spp., but growth of these species increased with trophic state (Maceina et al. 1996). Buynak et al. (1991) attributed increases in the growth of largemouth bass and the standing crop of largemouth bass and prey 124

HABITAT AND SPORT FISH POPULATIONS 125 species at Kentucky and Barkley lakes, Kentucky, to increases in productivity. Aside from their biological effects, changes in habitat structure and water quality may have sociological ramifications. For example, although catch rate and the number of harvestable-sized largemouth bass were unaffected by large increases in hydrilla Hydrilla verticillata coverage at Orange Lake, Florida, the angling effort declined, which resulted in an economic loss of 90% to that fishery (Colle et al. 1987). Furthermore, user groups other than anglers may be adversely affected by excessive plant coverage. At Lake Guntersville, Alabama, estimates of annual visits and mean economic value were highest for anglers at high plant coverage (30 50%) but were highest for nonangler groups at low plant coverage (.;10%; Henderson 1996). As a result of Henderson (1996) s study, a plant coverage of 20% was determined to be optimal because it maximized the net economic value by incorporating both angler and nonangler uses. Maceina et al. (1996) suggested that a chlorophylla concentration between 10 and 15 mg/l should be targeted in Alabama reservoirs to balance the fishery impacts attributable to reduced trophic state and the aesthetic attraction of clear water to other recreational users. Similar guidelines have also been proposed for total phosphorus concentration (Ney 1996). From 1983 to 2002, West Lake Tohopekaliga, Florida, experienced large fluctuations in water quality and habitat caused, in part, by anthropogenic activities. Before 1982, three wastewater treatment plants discharged secondary effluent containing high concentrations of nitrogen and phosphorus into the lake and its tributaries, which resulted in the subsequent deterioration of water quality (James et al. 1994; Williams 2001). However, by 1988, all wastewater treatment plant effluent was diverted from the lake, and wet retention ponds were used to treat stormwater runoff (James et al. 1994). These actions greatly reduced nutrient loading and improved water-quality conditions (James et al. 1994; Williams 2001). In the mid-1990s, the exotic plant hydrilla also became established and, despite numerous chemical treatments, has dominated the plant community for many years. Given these large fluctuations in water quality and habitat at West Lake Tohopekaliga, we conducted an analysis of long-term data to identify the primary factors related to changes observed in the sport fish populations and fisheries during this 20-year period and to evaluate what changes might occur with future nutrient and aquatic plant management actions. For this study, the primary objectives were to (1) evaluate the temporal trends in environmental parameters (e.g., chlorophyll-a concentration and hydrilla coverage), sport fish population parameters (e.g., growth and size structure), and creel statistics (e.g., angler effort and success rate); and (2) investigate the relationships between these environmental and sport fish parameters over the 20-year period. Study Site West Lake Tohopekaliga is a 7,612-ha, shallow, eutrophic natural lake (Kautz 1982) located in the central Florida town of Kissimmee in Osceola County. The lake supports a wide variety of outdoor recreation, including a high-profile largemouth bass sport fishery, subsistence fisheries (e.g., bream Lepomis sp.), hunting opportunities (e.g., the ring-necked duck Aythya collaris), wildlife viewing (e.g., nature tours and bird watching), and other nonconsumptive uses (e.g., kayaking). Annual water level fluctuations are regulated via two water-control structures: S-59, which controls flow into West Lake Tohopekaliga from East Lake Tohopekaliga, and S-61, which controls flow out of West Lake Tohopekaliga to the South. Annual water-level fluctuations are regulated at approximately 1 m by the South Florida Water Management District with higher water levels maintained during the winter months and lower water levels during the summer months. Methods Field sampling. Water quality parameters were measured four times each year by Florida Fish and Wildlife Conservation Commission (FWC) personnel. Surface water samples were obtained at two open-water sites, one located in the south portion and the other in the north portion of the lake. Total organic nitrogen (mg/l) was measured by the Kjeldahl method, total phosphorus (PO 4 ; mg/l) by the stannous chloride method, and chlorophyll-a concentration (mg/l) by the ethanol extraction method (APHA 1985). Secchi depth (m) was also recorded for each site. Hydrilla coverage was estimated each fall by Florida Department of Environmental Protection (FDEP) personnel by using a fathometer, which, aside from providing depth data, can be used to depict bottom structure (e.g., vegetation). Multiple transects were run across sections of the lake, and data were collected from the boat-mounted fathometer and from periodic vegetation samples. These data were then analyzed to determine lake-wide bottom coverage of hydrilla (E. Harris, FDEP, personal communication). Hydrilla treatments were conducted at various times throughout each year from 1993 to 2002 with fluridone (1-methyl-3-phenyl-5-[3-(trifluoromethyl)phenyl]-4[1H]-pyridinone) (E. Harris, FDEP, unpublished data). Treatments were usually conducted once or twice a year, except for 1996 and 1997, during

126 BONVECHIO AND BONVECHIO which the lake was treated three times. Approximately 243-1872 ha, or 3 25%, of the lake was treated each time with Sonar SRP (pelleted formula containing 5% fluridone), Sonar A.S. (liquid formula containing 47.1% fluridone), or both (E. Harris, FDEP, unpublished data). Roving angler creel surveys using nonuniform probability sampling (Malvestuto et al. 1978) were conducted each fall (August to November) from 1983 to 2002. West Lake Tohopekaliga was split into three sections corresponding to the northern, middle, and southern portions of the lake, and all sections were sampled each creel day. The fall creel season consisted of six 2-week periods during which three weekdays and two weekend days were chosen at random and sampled. Probabilities were chosen based on fishing patterns during AM (sunrise to midday) and PM (midday to sunset) on weekdays and weekends. A probability of 0.5 was assigned to all weekday creels irrespective of time period, but a probability of 0.6 was assigned to weekend PM creels and 0.4 to weekend AM creels. Approximately 6 h was spent on the water for each creel day, 2 h being allocated to each section. Time period (AM or PM) and the order of the sections sampled were chosen at random for each day. Instantaneous angler counts were conducted either at the start of the section creel or 1 h after, and this procedure was chosen at random for each section and day. All creel analyses were performed by the Creel Analysis Version 1.0 computer program (Connor and Sheaffer 2000), which uses roving-survey catch-rate estimators reported by Pollock et al. (1994, 1997), Jones et al. (1995), and Hoenig et al. (1997). Total catch, effort, and catch rate estimates were obtained for largemouth bass; harvest, effort, and harvest rate were obtained for black crappies and sunfish species (bluegill Lepomis macrochirus and redear sunfish L. microlophus). Catch and harvest rates for a given species or group were determined from anglers who were targeting that specific species or group (i.e., data about incidental catches were not included). Each spring (February to April) from 1985 to 2002, largemouth bass populations were sampled by electrofishing. A total of six fixed littoral sites, distributed around the lake, were sampled for 20 min each during night hours, and all largemouth bass collected were measured for total length (TL) to the nearest millimeter. Each site was sampled once in 1985 and 1986 and from 1988 to 1992; twice from 1996 to 2000 and in 2002; three times in 1993 and 2001; four times in 1995; and five times in 1994. The frequency of sampling was dependent on other sampling objectives unrelated to this study. Additional electrofishing was conducted in littoral areas during the spring in 1987, 1992, 2001, and 2002 to obtain a representative age sample for largemouth bass. Generally, 5 to 10 fish per centimeter group were killed for age determination, but larger sizes (.550 mm) were not subsampled effectively in 1992, so ages corresponding to these size groups (.age 6) were discarded from the analysis for all years. In the laboratory, sagittal otoliths were removed, the fish were weighed and measured for TL, and gender was determined by visually examining the gonads. Otoliths were either sectioned along the dorsoventral plane and mounted on a glass slide or broken through the core region and mounted in clay. Otoliths were then examined with a light microscope or fiberoptic light and assessed for age by two independent readers. If a discrepancy occurred, a third reader was used, but if the discrepancy could not be resolved, that fish was eliminated from the age dataset. Statistical analysis of temporal trends. Kendall s tau correlation procedure was used to assess temporal trends in the data. Habitat variables used in this analysis include mean chlorophyll-a concentration (mg/l; CHLA), annual mean Secchi depth (m; SECCHI), annual mean total organic nitrogen concentration (mg/l; TON), annual mean total phosphorus concentration (TP [PO 4 ]; mg/l), and hydrilla coverage (%; HYDR). The fish variables varied by species. For largemouth bass, variables included angler effort (h; LMBE), catch (all fish and by size-group number of fish; LMBC), catch success (fish/h; LMBCR), electrofishing catch per effort (all fish and by size-group fish/h; LMB CPE), mean total length of age-1 fish (mm; TLAGE1); and relative stock density of quality fish (.305 mm TL; PSD), preferred fish (.381 mm TL; RSD-P), and memorable-sized (.508 mm TL; RSD-M) fish in the electrofishing sample. Relative stock density calculations were done as described in Anderson and Neumann (1996). For black crappies and sunfish species, the variables included angler effort (h; BLCE and SFE, respectively), harvest (no. fish; BLCH and SFH), and harvest success (fish/h; BLCHR and SFHR). We used a ¼ 0.05 for all temporal analyses. Statistical analysis of fish habitat relationships. To investigate the relationship between fish and habitat variables, we used stepwise linear regression. If needed, the variables were transformed to linearize the relationship or normalize the response variable. Multicollinearity was assessed by calculating the variance inflation factor (VIF) values. If VIF values were less than 10, multicollinearity was considered low. The independent variables for these analyses were CHLA, SECCHI, TON, TP, and HYDR. The response variables varied by species. For largemouth bass, they included LMBE, LMBC for all fish and by size-group,

HABITAT AND SPORT FISH POPULATIONS 127 LMBCR, LMB CPE for all fish and by size-group, TLAGE1, PSD, RSD-P, and RSD-M. For black crappies and sunfish species, they included effort (BLCE, SFE), harvest (BLCH, SFH), and harvest success (BLCHR, SFHR), which were the only data available for these species. Because of concerns about low power often associated with long-term datasets containing highly variable parameters, we used a ¼ 0.10 for all regression analyses (Peterman 1990). We used several methods to investigate the growth of largemouth bass. For years for which age and growth data were available (1987, 1992, 2001, 2002), we calculated mean TL at age by using an age length key (DeVries and Frie 1996) because calculating these values from a subsample may be biased (Bettoli and Miranda 2001). A modified analysis of variance (ANOVA) was then used to compare mean TL at age with the Statistical Analysis Systems (SAS) computer program (Larson 1992). This ANOVA allows for the comparison of data when only summary statistics are available (i.e., mean, standard deviation, sample size), as is the case for unbiased estimates of mean length at age. Mean length-at-age comparisons were made for the whole sample as well as separately for each sex. An a of 0.05 was used for all comparisons. We also fit a von Bertalanffy growth curve to the mean length-atage data to determine the average time for fish to reach harvestable size (i.e., 356 mm; Ricker 1975). To further investigate the relationship between the growth of age- 1 fish and habitat, we constructed length frequency distributions and considered all fish within the first mode of the length frequency to be age 1 (DeVries and Frie 1996; Allen et al. 2003; Tate et al. 2003). We then computed the mean TL of these individuals for each year and assessed the relationship between mean TL and habitat variables using a stepwise linear regression procedure as previously described. All years for which the first mode could not be identified were excluded from the analysis. Results Temporal Trends West Lake Tohopekaliga experienced large shifts in habitat during this 20-year period (Table 1; Figure 1). Hydrilla coverage ranged from 0 to 83% and showed peaks in coverage in 1994 and 2002 during the study period. Annual means for TON, TP, and CHLA fell in the ranges 0.9 3.2 mg/l, 0.06 0.35 mg PO 4 /L, and 9 91 mg/l, respectively, and exhibited a declining trend through time (Kendall s tau b; r ¼ 0.512 to 0.706; P 0.002; Table 1). Annual mean Secchi depth, which ranged from 0.5 to 1.2 m, increased through time (Kendall s tau b; r ¼ 0.734; P, 0.001); it was negatively correlated with CHLA (r ¼ 0.859; P, 0.001) and positively correlated with log 10 HYDR (r ¼ 0.854; P, 0.001). Chlorophyll-a concentration was highly correlated with log 10 HYDR (r ¼ 0.751; P, 0.001), TON (r ¼ 0.907; P, 0.001), and TP (r ¼ 0.849; P, 0.001). During this same time period, West Lake Tohopekaliga also experienced shifts in the sport fish population and fishery (Table 1). Significant positive trends through time included angler catch rate for largemouth bass (Kendall s tau b; r ¼ 0.688; P, 0.001) and angler catch of all (r ¼ 0.684; P, 0.001) and subharvestable-sized (,356 mm TL) fish (r ¼ 0.527; P ¼ 0.024). Negative trends were observed for black crappie angler effort and harvest (Kendall s tau b; r ¼ 0.558 to 0.547; P, 0.001). All other fish variables did not depict a significant linear temporal trend during this period at a ¼ 0.05. Fish Habitat Relationships Regression models relating water quality variables to creel estimates are summarized in Table 2. Largemouth bass angler catch of all fish and subharvestable-sized fish and angling effort were negatively related to either CHLA or log 10 CHLA. Likewise, largemouth bass angler catch rate has increased through time as log 10 TON decreased and HYDR increased in the system. These two factors alone accounted for 93% of the variation in catch rate. Although a positive relationship was also detected for black crappie harvest rate and HYDR, other creel estimates indicated a decline with decreasing nutrient levels. Sunfish angling effort and black crappie harvest, harvest rate, and angling effort decreased with TON and TP levels. Thus, these species fisheries have shown a decline consistent with trophic status. Electrofishing data for largemouth bass were also used to assess abundance and size structure shifts during this period (Tables 1, 2). Electrofishing catch rates of all and subharvestable-sized (,356 mm TL) bass were not significantly related to any habitat variables or creel estimates (P. 0.10). The relative stock density of quality (.305 mm TL) and preferred (.381 mm TL) sized fish were also not related to observed changes in CHLA, TON, TP, HYDR, or SECCHI (P. 0.10). Relative stock density of memorable-sized (.508 mm TL) fish, however, was positively related to TP, which explained 44% of the variation (Table 2). Although these data suggest that the overall size structure did not shift significantly, the proportion of large individuals in the population declined with changes in trophic state. Growth of largemouth bass was first assessed with a modified ANOVA (Larson 1992) to compare mean length at age across years. Mean TL values varied

128 BONVECHIO AND BONVECHIO TABLE 1. Summary statistics for habitat and fish species data collected at West Lake Tohopekaliga, Florida, from 1983 to 2002. Angler effort is measured in hours, catch and harvest rates in fish per hour, and catch in numbers of fish. The following abbreviations are used: PSD ¼ proportional stock density, RSD-P ¼ relative stock density of preferred-sized fish (.381 mm TL), and RSD-M ¼ relative stock density of memorable-sized fish (.508 mm); all three variables are percentages. A plus sign in the trend column indicates a significant (P, 0.05) increasing trend, a minus sign a significant decreasing trend, and the letters ns no significant trend (asterisks denote marginal significance [0.05, P, 0.06]). Variable Median Range Years Trend Habitat Hydrilla coverage (%) 13 0 83 1983 2002 þ Conductivity (ls/cm) 162 134 216 1983 2002 ns Secchi depth (m) 0.8 0.5 1.2 1983 2002 þ Total organic nitrogen concentration (mg/l) 1.3 0.9 2.6 1983 2002 Total phosphorus concentration (mg/l) 0.12 0.06 0.35 1983 2002 Chlorophyll-a concentration (mg/l) 36 9 91 1983 2002 Largemouth bass Angler effort 30,289 19,493 57,851 1983 2002 ns* Angler catch rate 0.53 0.16 1.11 1983 2002 þ Total angler catch 15,482 4,533 49,995 1983 2002 þ Angler catch of subharvestable fish a 11,604 7,505 22,735 1992 2002 þ Electrofishing catch rate 58 34 98 1985, 1986, 1988 2002 ns Electrofishing catch rate of subharvestable fish a 42 20 88 1985, 1986, 1988 2002 ns Total length of age-1 fish (mm) 159 139 185 1985, 1986, 1988 1995, 1997, 1998, 2000 2002 ns PSD 66 18 81 1985, 1986, 1988 2002 ns RSD-P 22 1 40 1985, 1986, 1988 2002 ns RSD-M 5 0 11 1985, 1986, 1988 2002 ns* Black crappies Angler effort 11,148 2,985 42,162 1983 2002 Angler harvest rate 1.5 0.9 2.0 1983 2002 ns Angler harvest 18,106 3,917 77,650 1983 2002 Sunfish species Angler effort 10,670 6,319 37,477 1983 2002 ns Angler harvest rate 2.8 1.6 3.8 1983 2002 ns Angler harvest 28,826 10,452 137,373 1983 2002 ns a Fish, 356 mm TL. among years, with means of fish younger than age 5 significantly higher for those collected in 1987 than those collected in other years (P, 0.05; Table 3). However, for all years other than 1987, mean TL of these age-classes were similar (P. 0.05; Table 3). This trend was generally similar among sexes, but fish greater than age 4 were not analyzed because of low sample sizes in some years. A von Bertalanffy growth curve was also fit to mean length-at-age data of the whole sample as well as individually for each sex. The average time for fish to reach harvestable size (356 mm TL) ranged from 3.1 to 3.6 years for all fish, from 2.8 to 3.3 years for females and from 3.2 to 3.9 years for males (Table 3). These data suggest that growth declined through time at West Lake Tohopekaliga as nutrient concentration decreased. Discussion Temporal Trends From 1983 to 2002, West Lake Tohopekaliga experienced large-scale changes in habitat and water quality, which may have impacted its valuable sport fishery. Ney (1996) coined the phrase cultural oligotrophication, which refers to the phenomenon of decreasing nutrient concentrations in lakes and waterways as a result of human activities. Since the late 1980s, West Lake Tohopekaliga has been undergoing this process with a continued decline in nutrient and chlorophyll-a concentrations, first as the result of improvements with wastewater treatment and secondly with the establishment of hydrilla in the system. According to Forsberg and Ryding (1980), the threshold value separating eutrophic and hypereutrophic lakes is 100 mg/l for total phosphorus (or 0.3 mg PO 4 /L) and 40 mg/l for chlorophyll-a concentration. Thus, using the criteria established by Forsberg and Ryding (1980), West Lake Tohopekaliga experienced a shift in trophic state within the last 20 years from hypereutrophic in the late 1980s to approaching mesotrophic towards the end of the time series. In addition to changes in water quality, hydrilla coverage varied widely, ranging from 0 to 83%, throughout the study period. Many sport fish population and creel parameters

HABITAT AND SPORT FISH POPULATIONS 129 FIGURE 1. Time series indicating annual mean chlorophyll-a concentration (CHLA), coverage of hydrilla (HYDR), angler catch rate (LMBCR), and electrofishing catch per unit effort (LMB CPE) of largemouth bass from 1983 to 2002. exhibited significant temporal trends during this study period. A declining trend was detected for black crappie angler effort and harvest, whereas largemouth bass angler success and catch displayed an increasing trend. Our analyses found that large-scale environmental changes observed at West Lake Tohopekaliga were correlated to trends in the sport fish population and fishery. Future efforts should consider possible implications of these changes, as will be discussed, when managing for multiple species and users in order to maximize the lake s economic potential. Fish Habitat Relationships Growth and size structure of largemouth bass shifted during the 20-year period at West Lake Tohopekaliga. Maceina et al. (1996) found that anglers caught smaller largemouth bass in oligomesotrophic lakes as compared to eutrophic lakes. This coincided with observed increases in the growth rate and condition of black crappies and largemouth bass in higher trophic reservoirs (Maceina et al. 1996). A higher proportion of larger fish was also found to be indicative of TABLE 2. Regression results for fish variables calculated from data collected at West Lake Tohopekaliga, Florida, from 1983 to 2002. Variable codes represent angler catch (number of fish; LMBC), angler catch of subharvestable-sized (,356 mm TL) fish (number of fish; LMBCS), catch rate (fish/h; LMBCR), angling effort (h; LMBE) for largemouth bass; harvest (number of fish; BLCH), harvest rate (fish/h; BLCHR), and angling effort (h; BLCE) for black crappies; angling effort (h; SFE) for sunfish species; relative stock density of memorable-sized (.508 mm TL) largemouth bass (%; RSD-M); mean total length of age-1 largemouth bass in the electrofishing sample (mm; TLAGE1); chlorophyll-a concentration (mg/l; CHLA); total organic nitrogen concentration (mg/l; TON); total phosphorus concentration (mg/l; TP); and areal coverage of hydrilla (%; HYDR). Regression R 2 df F-statistic P-value N LMBC ¼ 91,894 46,698(log 10 CHLA) 0.78 1, 18 63.43,0.001 20 LMBCS ¼ 29,199 561(CHLA) 0.78 1, 9 31.01,0.001 11 LMBCR ¼ 0.534 þ 0.508(HYDR) 0.820(log 10 TON) 0.93 2, 17 111.86,0.001 20 LMBE ¼ 86,102 34,446(log 10 CHLA) 0.49 1, 18 17.43,0.001 20 BLCH ¼ 5,299 þ 120,607(TP) 0.33 1, 18 8.86 0.008 20 BLCHR ¼ 1.075 þ 0.886(HYDR) þ 1.200(log 10 TON) 0.34 2, 17 4.37 0.029 20 BLCE ¼ 38,120 þ 28,107(log 10 TP) 0.44 1, 18 14.35 0.001 20 SFE ¼ 6,440 þ 38,262(TP) 0.31 1, 18 6.18 0.023 20 RSD-M ¼ 1.526 þ 25.758(TP) 0.44 1, 16 12.63 0.003 17 TLAGE1 ¼ 146.049 þ 111.336(TP) 0.19 1, 12 3.14 0.100 15

130 BONVECHIO AND BONVECHIO TABLE 3. Mean total length at age 6 SD for largemouth bass collected at West Lake Tohopekaliga, Florida, in 1987, 1992, 2001, and 2002. The number of individuals in the sample (in parentheses) and time for fish to reach harvestable size (356 mm TL; THARV) are also provided. For each age, common letters indicate no significant difference between years according to a modified ANOVA (Larson 1992) with a ¼ 0.05. Age Group Year 1 2 3 4 5 6 THARV (years) All 1987 173 6 31 z 309 6 28 z 360 6 26 z 407 6 37 z 427 6 58 z 457 6 54 z 3.1 (220) (219) (219) (116) (89) (116) 1992 159 6 29 y 280 6 29 y 324 6 30 y 363 6 36 x 442 6 54 z 441 6 11 xy 3.4 (78) (90) (39) (123) (7) (9) 2001 159 6 20 y 250 6 34 x 327 6 53 y 376 6 54 y 425 6 66 yz 421 6 66 x 3.6 (264) (200) (189) (54) (34) (25) 2002 157 6 22 y 257 6 30 x 325 6 28 y 375 6 46 y 411 6 63 y 443 6 53 y 3.9 (62) (114) (148) (88) (28) (35) Female 1987 166 6 32 z 317 6 30 z 375 6 17 z 428 6 25 z 2.8 (80) (121) (117) (69) 1992 156 6 25 z 285 6 29 y 335 6 43 xy 373 6 45 x 3.1 (43) (40) (15) (43) 2001 161 6 20 z 242 6 27 x 321 6 63 x 409 6 59 y 3.3 (164) (159) (112) (26) 2002 158 6 22 z 250 6 29 x 337 6 31 y 429 6 31 z 3.1 (33) (71) (53) (26) Male 1987 177 6 32 z 300 6 30 z 342 6 17 z 377 6 25 z 3.2 (140) (98) (102) (48) 1992 163 6 25 y 276 6 29 y 317 6 43 x 358 6 45 y 3.7 (35) (50) (24) (81) 2001 157 6 20 xy 278 6 42 y 334 6 33 y 344 6 18 x 3.8 (99) (41) (78) (28) 2002 155 6 21 x 268 6 30 y 319 6 24 x 352 6 29 xy 3.9 (29) (43) (95) (61) increasing trophic state for largemouth bass collected from 65 Florida lakes (Bachmann et al. 1996). These observations were supported by the results of this study. The catch of subharvestable-sized (,356 mm TL) fish increased with decreasing chlorophyll-a concentration, and the proportion of large fish in the electrofishing catches, as indexed by RSD of memorable-sized (.508 mm TL) fish, decreased as total phosphorus decreased. Furthermore, the growth of largemouth bass was higher in 1987 when the lake was hypereutrophic. In the late 1980s, females and males, on average, took 2.8 and 3.2 years, respectively, to reach harvestable size, but in following years, they required 3.1 3.3 and 3.7 3.9 years, respectively; thus, it took as much as 6 to 8 months longer for the fish to reach harvestable size in the latter part of the study period than in the 1987 sample. Changes in hydrilla coverage may also have impacted the growth of largemouth bass. Several studies have indicated that excessive levels of aquatic plants result in decreased growth of largemouth bass (Bettoli et al. 1992; Hoyer and Canfield 1996; Wrenn et al. 1996). For example, Wrenn et al. (1996) found that fish younger than age 4 exhibited decreased growth when the surface area of aquatic plants exceeded 20%. When all submersed vegetation was removed by grass carp Ctenopharyngodon idella at Lake Conroe, Texas, age-0 largemouth bass switched to piscivory earlier than when the lake had a 40% areal coverage of plants. As a result, these age-0 fish exhibited faster growth when vegetation coverage was decreased (Bettoli et al. 1992). With the onset of large stands of hydrilla in West Lake Tohopekaliga, largemouth bass growth probably would have decreased even further than it did, but factors such as increased angler effort for the species may have offset this. Although it is difficult to separate out the effects of hydrilla and water quality, we believe both of these factors probably interacted together to influence the growth of largemouth bass. Several studies have attempted to relate sport fish biomass and abundance with changes in trophic state (Kautz 1982; Yurk and Ney 1989; Downing et al. 1990; Bachmann et al. 1996) and aquatic macrophyte coverage (Moxley and Langford 1985; Colle et al. 1987; Hoyer and Canfield 1996; Maceina 1996; Wrenn et al. 1996). The results of such studies are often inconsistent. Kautz (1982) investigated the relationship between sport fish density and biomass and trophic state indicators in 22 Florida lakes. Although species were not separated out, Kautz (1982) indicated that density and biomass of sport fish were maximized when total nitrogen concentration was 1.2 mg/l and chlorophyll-a concentration was 11.0 mg/l. However, Bachmann et al. (1996), in a study of 65 Florida lakes, found that total fish biomass and the biomass of most

HABITAT AND SPORT FISH POPULATIONS 131 sport fish species were positively correlated with these two variables over their entire range (0.08 3.79 mg/l and 1 241 mg/l, respectively). Likewise, Colle et al. (1987) found that hydrilla had minimal impact on the abundance of harvestable-sized bass or black crappies at Orange Lake, Florida, but Maceina et al. (1996), using Hoyer and Canfield (1996) s published data, suggested that coverage of aquatic macrophytes may play a significant role in predicting the density of harvestable-sized bass in larger systems. At West Lake Tohopekaliga, we found that creel statistics were significantly related to habitat variables for some sport fish species. Angler catch rate of largemouth bass and angler harvest rate of black crappies were positively related to hydrilla coverage across years. Although total angler harvest and harvest rate of black crappies were also positively correlated with TP or TON concentration, largemouth bass catch and catch rate declined with increases in several trophic state indicators. These results indicate that characteristics of the sport fishery shifted during this period and were correlated with nutrient concentrations and hydrilla coverage, but whether our observations were indicative of increased abundance or the result of other factors is unknown (see below). The lack of a relationship between electrofishing and angler catch rates for largemouth bass causes uncertainty in our conclusions. This result indicates that either one or both methods yielded poor indicators of largemouth bass population abundance at West Lake Tohopekaliga. The catchability of this species by both methods electrofishing and angling probably shifted during this time series as large changes in aquatic plant coverage and water quality occurred. Annual chlorophyll-a concentration experienced a 10- fold difference and Secchi depth decreased by approximately 0.5 m during this period, coincident with lowered nutrient levels and changes in hydrilla coverage. These factors probably influenced electrofishing efficiency and subsequently the electrofishing catch rate (Reynolds 1996; McInerny and Cross 2000). Bailey and Austen (2002) found that the catchability of different species by electrofishing may be influenced by the presence of vegetation. For example, a 2.3-fold decrease in the catchability of 30-cm largemouth bass is predicted when macrophyte coverage increased from 0 to 50%. Thus, our ability to detect changes in largemouth bass abundance, as indexed by electrofishing catch rate, was probably limited, given the shifts in hydrilla coverage and water quality at West Lake Tohopekaliga. It is also plausible that largemouth bass abundance was not influenced by observed changes in hydrilla coverage or trophic state. Angling success improved without a corresponding increase in electrofishing CPE, which could occur if angling success were related to factors other than fish abundance. Our results may indicate that changes in the angler catch and harvest rates for largemouth bass and black crappies were related, in part, to changes in fish behavior (e.g., Savino and Stein 1982, 1989a, 1989b; Sammons et al. 2003) that may make them more vulnerable to angling. Also, sociological shifts within the angling community (e.g., adoption of new techniques to target fish in heavily vegetated areas) and advances in technology (e.g., boat motors more capable of running through vegetation) over the -year period may have influenced creel estimates. Therefore, given the inconsistent results obtained from creel and electrofishing sampling, we could not conclude that sport fish abundance changed through time. The user base at West Lake Tohopekaliga shifted during this study period as the lake became less eutrophic. During this time period, the percentage of effort for largemouth bass increased. Angling effort for largemouth bass has accounted for 31% to 82% of the total angling effort, the larger values being associated with lower chlorophyll-a concentrations (r ¼ 0.722; P, 0.001). Although angling effort for largemouth bass increased with decreasing chlorophyll-a concentration, angling effort for sunfish species and black crappies has declined with decreased TP concentration. When evaluating the value of a lake, one should also consider nonconsumptive users, such as recreational boaters and wildlife viewers. A balance must be reached between nonconsumptive users, who tend to prefer clear water, and anglers, who benefit from highly productive situations (Maceina et al. 1996; Ney 1996). For example, water users perception of acceptable TP concentration was estimated to be around 40 lg/l, but sport fish standing stock generally peaks at TP concentrations above 100 lg/l (Ney 1996). The potential for user conflict over lake trophic status exists, and a compromise between water clarity and fish production may be critical (Ney 1996). Intermediate levels of coverage may also be desirable to maintain or enhance the multifunctional use of the lake. Unlike what was reported by Colle et al. (1987) for Orange Lake, the infestation of hydrilla in West Lake Tohopekaliga did not negatively affect largemouth bass angler effort or catch. Other angler groups (e.g., black crappies), however, and nonconsumptive user groups were probably affected. Henderson (1996) found that plant coverages of 20% and a mix of angler and nonangler use provided the maximum optimal economic value at Lake Guntersville, Alabama. Colle et al. (1987) also found that increased hydrilla resulted in the almost complete loss

132 BONVECHIO AND BONVECHIO of the sunfish and black crappie fisheries, even though catch rates were the same or higher than in previous years. Thus, to maximize fishing opportunities for the diversity of angler groups utilizing West Lake Tohopekaliga, we recommend that intermediate vegetation coverage (20 40%) be sustained when possible. Acknowledgments We thank the many FWC personnel and volunteers who gathered and entered data during this 20-year period, including D. Arwood, J. Buntz, R. Hujik, M. Hulon, A. Landrum, K. McDaniel, M. Mann, E. Moyer, T. Penfield, J. Sweatman, and countless others. We would also like to thank the current FWC Kissimmee Chain of Lakes project leader, T. Coughlin, and former leaders, M. Hulon, M. Mann, and E. Moyer, for their efforts in maintaining this data series. M. Allen, W. Porak, and S. Sammons provided helpful comments during the preparation of this manuscript. References Allen, M. S., K. I. Tugend, and M. J. Mann. 2003. 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HABITAT AND SPORT FISH POPULATIONS 133 Conference Southeastern Association of Fish and Wildlife Agencies 34(1980):67 80. Larson, D. A. 1992. Analysis of variance with just summary statistics as input. American Statistician 46:151 152. Maceina, M. J. 1996. Largemouth bass abundance and aquatic vegetation in Florida lakes: an alternative interpretation. Journal of Aquatic Plant Management 34:43 47. Maceina, M. J., D. R. Bayne, A. S. Hendricks, W. C. Reeves, W. P. Black, and V. J. DiCenzo. 1996. Compatibility between water clarity and quality black bass and crappie fisheries in Alabama. Pages 296 305 in L. E. Miranda and D. R. DeVries editors. Multidimensional approaches to reservoir fisheries management. American Fisheries Society, Symposium 16, Bethesda, Maryland. Malvestuto, S. P., W. D. Davies, and W. L. Shelton. 1978. An evaluation of the roving creel survey with nonuniform probability sampling. Transactions of the American Fisheries Society 107:255 262. McInerny, M. C., and T. K. Cross. 2000. Effects of sampling time, intraspecific density, and environmental variables on electrofishing catch per effort of largemouth bass in Minnesota lakes. North American Journal of Fisheries Management 20:328 336. Moxley, D. J., and F. H. Langford. 1985. Beneficial effects of hydrilla on two eutrophic lakes in central Florida. Proceedings of the Annual Conference Southeastern Association of Fish and Wildlife Agencies 36(1982):280 286. Ney, J. J. 1996. Oligotrophication and its discontents: effects of reduced nutrient loading on reservoir fisheries. Pages 285 295 in L. E. Miranda and D. R. DeVries editors. Multidimensional approaches to reservoir fisheries management. American Fisheries Society, Symposium 16, Bethesda, Maryland. Peterman, R. M. 1990. Statistical power analysis can improve fisheries research and management. Canadian Journal of Fisheries and Aquatic Sciences 47:2 15. Pollock, K. H., C. M. Jones, and T. L. Brown. 1994. Angler survey methods and their application in fisheries management. American Fisheries Society, Special Publication 25, Bethesda, Maryland. Pollock, K. H., J. M. Hoenig, C. M. Jones, D. S. Robson, and C. J. Greene. 1997. Catch rate estimation for roving and access point surveys. North American Journal of Fisheries Management 17:11 19. Reynolds, J. B. 1996. Electrofishing. Pages 221 253 in B. R. Murphy and D. W. Willis editors. Fisheries techniques, 2nd edition. American Fisheries Society, Bethesda, Maryland. Ricker, W. E. 1975. Computation and interpretation of biological statistics of fish populations. Department of the Environment, Fisheries and Marine Science, Bulletin 191, Ottawa, Canada. Sammons, S. M., M. J. Maceina, and D. G. Partridge. 2003. Changes in behavior, movement, and home ranges of largemouth bass following large-scale hydrilla removal in Lake Seminole, Georgia. Journal of Aquatic Plant Management 41:31 38. Savino, J. F., and R. A. Stein. 1982. Predator prey interaction between largemouth bass and bluegills as influenced by simulated, submersed vegetation. Transactions of the American Fisheries Society 111:255 266. Savino, J. F., and R. A. Stein. 1989a. Behavioral interactions between fish predators and their prey: effects of plant density. Animal Behavior 37:311 321. Savino, J. F., and R. A. Stein. 1989b. Behavior of fish predators and their prey: habitat choice between open water and dense vegetation. Environmental Biology of Fishes 24:287 293. Tate, W. B., M. S. Allen, R. A. Myers, and J. Estes. 2003. Relation of age-0 largemouth bass abundance to hydrilla coverage and water levels at Lakes Lochloosa and Orange, Florida. North American Journal of Fisheries Management 23:251 257. Wiley, M. J., R. W. Gorden, S. W. Waite, and T. Powless. 1984. The relationship between aquatic macrophytes and sport fish production in Illinois ponds: a simple model. North American Journal of Fisheries Management 4:111 119. Williams, V. P. 2001. Effects of point-source removal on lake water quality: a case history of Lake Tohopekaliga, Florida. Lake and Reservoir Management 17:315 329. Wrenn, W. B., D. R. Lowery, M. J. Maceina, and W. C. Reeves. 1996. Relationships between largemouth bass and aquatic plants in Guntersville Reservoir, Alabama. Pages 382 393 in L. E. Miranda and D. R. DeVries editors. Multidimensional approaches to reservoir fisheries management. American Fisheries Society, Symposium 16, Bethesda, Maryland. Yurk, J. J., and J. J. Ney. 1989. Phosphorus fish community biomass relationships in southern Appalachian reservoirs: can lakes be too clean for fish? Lake and Reservoir Management 5:83 90.

North American Journal of Fisheries Management 26, 2006 Ó Copyright by the American Fisheries Society 2006 DOI: 10.1577/M04-191e.1 ERRATUM Erratum: Relationship between Habitat and Sport Fish Populations over a 20-Year Period at West Lake Tohopekaliga, Florida Kimberly I. Bonvechio and Timothy F. Bonvechio Volume 26(1), February 2006: 124 133. Page 128. In Table 1, total phosphorus concentrations should be measured in mg PO 4 /L, and total chlorophyll-a concentrations in lg/l. The sentence in the middle of the right column should read as follows: According to Forsberg and Ryding (1980), the threshold value separating euthropic and hypereutrophic lakes is 100 lg/l for total phosphorus (or 0.3 mg PO 4 /L) and 40 lg/l for chlorophyll-a concentration. In all other instances in the article, chlorophyll-a concentrations should be expressed as lg/l.