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Diet Composition and Growth Rates of Black Crappie Pomoxis nigromaculatus Relative to Benthic Food Availability at Three...


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DIET COMPOSITION AND GROWTH RATES OF BLACK CRAPPIE Pomoxis nigromaculatus RELATIVE TO BENTHIC FOOD AVAILABILITY AT THREE FLORIDA LAKES By M. TRAVIS TUTEN A THESIS PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE UNIVERSITY OF FLORIDA 2007 1

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2007 M. Travis Tuten 2

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To my family, who are the meaning of life. 3

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ACKNOWLEDGMENTS I would like to thank Micheal S. Allen, Chuck E. Cichra, Marty M. Hale, and Gary L. Warren for serving as members of my supervisory committee. The various help and knowledge that each of them individually provided was instrumental and will be influential in my future. I am especially appreciative of the long list of people who provided help in the field, laboratory, and office including Holly Alred, Anne Cichra, Gina DelPizzo, Kevin Dockendorf, Mike Duncan, Tracy Ferring, Darrie Hohlt, Cory Keller, Cara Miller, Eric Nagid, Summer Pardo, Tracy Peters, Eric Porak, Marina Post, Tracey Smith, Andy Strickland, Will Strong, Loanna Torrance, and David Ziesk. Without them, I would still have my eyes at a scope and be wishing for the last sample. I would also like to send a special thanks to Howard Jelks and Daryl Parkyn for their help and advice on data analysis. Funding for this project was provided by the Florida Fish and Wildlife Conservation Commission. I am thankful to Jim Estes and Dick Krause for providing extra means to accelerate this project and also to Eric Nagid for going to bat for me to get more help. The most important piece of this puzzle is my family. I am grateful to my Mom and Dad, who provided the foundation of my life. It is comforting to know that I have supportive parents who have always been there. Della is my greatest catch. I am thankful for the way she puts up with me and giving me an extra push every now and then. I look forward to our future together raising Eli and any other little Tuten we may be blessed with. 4

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TABLE OF CONTENTS page ACKNOWLEDGMENTS ...............................................................................................................4 LIST OF TABLES ...........................................................................................................................6 LIST OF FIGURES .........................................................................................................................7 ABSTRACT .....................................................................................................................................8 INTRODUCTION .........................................................................................................................10 METHODS ....................................................................................................................................14 Study Lakes ............................................................................................................................14 Black Crappie Collection ........................................................................................................14 Process of Fish and Stomachs .................................................................................................15 Age Estimation .......................................................................................................................16 Macroinvertebrate Collection and Processing ........................................................................17 Data Analysis ..........................................................................................................................18 Population Abundance and Size Structure ......................................................................18 Age and Growth Comparisons ........................................................................................19 Diet Comparisons ............................................................................................................20 Macroinvertebrate Density Comparisons ........................................................................23 Ponar-Diet Comparisons .................................................................................................24 RESULTS ......................................................................................................................................27 DISCUSSION ................................................................................................................................63 MANAGEMENT IMPLICATIONS .............................................................................................73 LIST OF REFERENCES ...............................................................................................................74 BIOGRAPHICAL SKETCH .........................................................................................................84 5

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LIST OF TABLES Table page 1 Mean water quality parameters for Lakes Lochloosa, Marian, and Monroe. ....................37 2 List of types and common names of prey used to numerically and gravimetrically describe black crappie diet contents. .................................................................................38 3 Four major prey categories used in the MANOVA procedure and the individual prey items included in each category. ........................................................................................39 4 Otter trawl capture and collection data for black crappie at Lakes Lochloosa, Marian, and Monroe during each sampling period. ........................................................................40 5 Linear, Gompertz, and von Bertalanffy growth functions of black crappie at Lakes Lochloosa, Marian, and Monroe based on the collected total length at age data. .............43 6 Number of black crappie stomachs examined for diet contents, number of empty stomachs observed, and number of stomachs with 100 % digested material in each of the three study lakes. ..........................................................................................................44 7 Mean percent weight values of dominant prey types in the Insect and Macrocrustacean prey categories found in black crappie diets at Lakes Lochloosa, Marian, and Monroe. ..........................................................................................................46 8 Mean densities (number/m) of taxa collected with petite Ponars in each period at Lakes Lochloosa, Marian, and Monroe. 2 ............................................................................47 9 Simplified Morisita index values of similarity for various taxa comparing density found with petite Ponars to the total number found in black crappie diets through all sampling periods. ...............................................................................................................49 6

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LIST OF FIGURES Figure page 1 General locations of Lochloosa Lake, Lake Marian, and Lake Monroe in the state of Florida. ...............................................................................................................................50 2 Relative length frequencies of black crappie > 110 mm TL captured with otter trawls at Lakes Lochloosa, Marian, and Monroe. ........................................................................51 3 Residuals of the expected total length at age values from the observed total length at age values when using von Bertalanffy growth models. ...................................................52 4 Mean total length at age of black crappie at Lakes Lochloosa, Marian, and Monroe using their respective von Bertalanffy growth model. .......................................................53 5 Mean percent of total diet weight of microcrustaceans for black crappie at Lakes Lochloosa, Marian, and Monroe during sampling periods for all size classes. .................54 6 Mean percent of total diet weight of insects for black crappie at Lakes Lochloosa, Marian, and Monroe during sampling periods for all size classes. ....................................55 7 Mean percent of total diet weight of macrocrustaceans for black crappie at Lakes Lochloosa, Marian, and Monroe during sampling periods for all size classes. .................56 8 Mean percent of total diet weight of fish for black crappie at Lakes Lochloosa, Marian, and Monroe during sampling periods for all size classes. ....................................57 9 Mean percent total weight of major prey types in the diets of black crappie for all size classes at Lakes Lochloosa, Marian, and Monroe. .....................................................58 10 Mean Manly's values indicating selection of prey taxa by black crappie in all size classes at Lakes Lochloosa, Marian, and Monroe during all sampling periods. ...............59 11 Mean Chironomidae larvae, Chaoboridae larvae, Diptera pupae, and Mysidacea densities collected with petite Ponars and mean numbers found in black crappie stomachs for all size classes at Lakes Lochloosa, Marian, and Monroe during all sampling periods. ...............................................................................................................61 7

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Abstract of Thesis Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Master of Science DIET COMPOSITION AND GROWTH RATES OF BLACK CRAPPIE Pomoxis nigromaculatus RELATIVE TO BENTHIC FOOD AVAILABILITY AT THREE FLORIDA LAKES By M. Travis Tuten May 2007 Chair: Chuck E. Cichra Cochair: Micheal S. Allen Major: Fisher ies and Aquatic Sciences Factors influencing black crappie growth are an important research need for management of black crappie fisheries. I evaluated the diets and growth of black crappie in relation to benthic food availability and population structures (e.g., abundance) among three Florida systems: Lakes Lochloosa, Marian, and Monroe. The simplified Morisita index was used to measure similarity of diet contents (i.e., mean numbers) relative to benthic macroinvertebrate densities throughout sampling periods. Manlys index of selectivity was used to measure selective predation by black crappie for benthic prey taxa. Black crappie at Lake Monroe obtained the largest size at age, whereas Lake Marian had the smallest size at age. Lake Marian had the highest abundances of black crappie based on otter trawl mean catch per unit effort data and Lochloosa Lake had the lowest abundance. Manlys index of selectivity resulted in two major trends. Black crappie at Lakes Lochloosa and Marian were consistently selective of Diptera pupae, whereas black crappie at Lake Monroe were consistently selective of Mysidacea Americamysis almyra. Differences in prey availability and prey selection were influential in producing differences in the diet composition and ontogenetic diet shifts of black crappie among the three study lakes. Results were variable for different taxa, but indicated that benthic prey availability can influence 8

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consumption rates of prey items by black crappie, particularly for more utilized taxa. The diet, prey availability, and black crappie population structure differences among lakes likely contributed to the variation in population growth rates. 9

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INTRODUCTION Black crappie Pomoxis nigromaculatus support important recreational fisheries in Florida including 22% of the states freshwater anglers and more than 5.8 million days of annual fishing effort (U.S. Department of Interior 2001). Factors that influence growth and abundance of black crappie are thus important to the management of black crappie fisheries. Understanding how black crappie growth rates are related to diet composition and benthic food availability is an important research need for management of black crappie fisheries. The diets of both black crappie and white crappie P. annularis are well documented. In Florida alone, food items found in black crappie diets have included crustacean zooplankton, such as cladocera and copepoda; diptera larvae, pupae and adults, particularly Chironomidae and Chaoboridae; Palaemonetes and Mysidopsis shrimp; and various fishes, especially shads Dorosoma spp. (Chable 1947; Reid 1949; Huish 1957; Ager 1975). Keast (1968) and Hanson and Quadri (1979) found that diets of black crappie did not vary greatly throughout their distribution. Conversely, Mathur and Robbins (1971) suggested that differences in feeding habits among populations of white crappie were due to differences in food availability at those water bodies. Ontogenetic diet shifts from zooplankton to aquatic insects to fish occur in many fishes including Eurasian perch Perca fluviatilis (Hjelm et al. 2000), yellow perch Perca flavescens (Keast 1977), walleye Sander vitreus (Galarowicz et al. 2006), largemouth bass Micropterus salmoides (Keast and Eadie 1985; Olson 1996; Garcia-Berthou 2002), and northern pike Esox lucius (Frost 1954). Diet shifts occur as a result of morphological changes (i.e., larger gape width), which allow fish to utilize larger food items (McCormick 1998; Hjelm et al. 2000). It is optimal for individuals to select prey items that maximize the net energy gain, which typically are the larger items available (Mittelbach 1981). Higher quality foods can produce faster growth 10

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(Buijse and Houthuijzen 1992; Frankiewicz et al. 1996), which allows the transition to the next larger prey item (Frankiewicz et al. 1996; Olson 1996), alters resource competition (Keast and Eadie 1985), and allows piscivorous fish to maintain or obtain a size advantage over prey fish (Timmons et al. 1980; Keast and Eadie 1985; Olson 1996). Olson (1996) found that largemouth bass with faster growth rates in the invertebrate-feeding stage became piscivorous significantly faster than fish with slower growth rates at the same stage. An increase in growth also influences recruitment by limiting mortality (Post et al. 1998; Olson 1996) and reducing risk of predation (Frankiewicz et al. 1996; Post et al. 1998). Applegate et al. (1967) attributed the growth rates of juvenile largemouth bass at one Arkansas reservoir to be twice as fast as those at another Arkansas reservoir because of greater availability and consumption of midge larvae between the diet shift from zooplankton to fish. At one Florida lake, Wicker and Johnson (1987) found that periods of high mortality of age-0 largemouth bass occurred directly after periods when low fish prey: predator biomass ratios occurred. Juvenile black crappie exhibit shifts from primarily zooplankton to a combination of zooplankton and macroinvertebrates at about 65 to 100 mm TL (Reid 1949; Keast 1968; Tucker 1972; Pine and Allen 2001; Dockendorf and Allen 2005). Fish become a common prey item when crappies Pomoxis spp. attain a TL of 140 to 200 mm (Keast 1968; Ellison 1984; OBrien et al. 1984; Schramm et. al. 1985; Muoneke et al. 1992; Mittelbach and Persson 1998). Crappies will continue to feed on zooplankton when they are greater than 150 mm TL (Muoneke et al. 1992) and have been found to feed on fish when as small as 60 mm TL (Reid 1949; Huish 1957). However, it is important for crappies to shift their diet to optimize growth and survival. For example, Muoneke et al. (1992) credited the reduced growth of white crappie at an Oklahoma reservoir to their inability to become piscivorous at 150 mm TL. Dockendorf and Allen (2005) 11

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found larger age-0 black crappie at one Florida lake, which had a higher frequency of fish in their diets, in comparison to two other Florida populations. Ellison (1984) found lower growth and survival rates of black crappie feeding as insectivores and planktivores than for white crappie that had switched to a fish diet at the same Nebraska lake, particularly after the crappie reached 200 mm TL. Seasonal and monthly trends of crappie diets have been analyzed in numerous studies (Pearse 1918; Dendy 1946; Reid 1949; Ball and Kilambi 1972; Mathur 1972; Liao et al. 2002). Fish become a more important, if not the most important, part of the crappie diet in the summer and/or fall months. Ball and Kilambi (1972) found crappie diets to be 92% fish in the summer months at an Arkansas reservoir. In the spring, fall, and winter seasons, fish were consumed to a lesser degree, and benthic insects, annelids, and crustaceans increased in importance. Likewise, Dendy (1946) found a high proportion of aquatic insects and zooplankton in adult black crappie diets in the spring and early summer, but fish dominated the diets in the late summer and fall at a Tennessee reservoir. Reid (1949) also found a Florida black crappie population to feed largely on fish in the summer and fall. The foods consumed during the summer are considered the most important on a yearly basis, because this is when much of the annual growth occurs and energy requirements are the highest (Ball and Kilambi 1972; Ellison 1984). At Lake George, Florida, Huish (1953) found that black crappie made most of their annual growth from April through November. Lochloosa Lake, Florida, had a successful black crappie fishery prior to 1992, when fishing effort and harvest dropped significantly (Hujik et al. 2002). For five years, the fishery showed no signs of improvement and consequently, the Florida Fish and Wildlife Conservation Commission (FWC) stocked more than 500,000 advanced fingerling (100 mm 150 mm TL) 12

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black crappie from 1997 to 2001. Hujik et al. (2002) found that angler effort and harvest were 30% and 85% lower, respectively, for the post-stocking period (1997-2002) when compared to the pre-stocking period (1988-1996). Catch curve analysis estimated 93% total annual mortality of black crappie > age-1 in 1999 and 71% in 2001 (Hujik et al. 2002). Although 71% total annual mortality is comparable to the average of other crappie populations in the U.S. compiled by Allen and Miranda (1995) and Allen et al. (1998), the 93% estimate is on the upper range of those reported. Because exploitation was apparently low since stocking began, natural mortality was suspected to be the primary component of total annual mortality. This led to the question of whether food availability at Lochloosa Lake was limiting the growth and survival of black crappie larger than 200 mm total length (TL), which is also the approximate age and length that crappie are recruited into sport fisheries (Schramm et al. 1985; Larson et al. 1991; Miranda and Dorr 2000). I compared diets and benthic food availability of black crappie at Lochloosa Lake with that of two other Florida lakes, that supported successful black crappie fisheries. I evaluated the diets of black crappie > 110 mm TL at three Florida lakes in comparison to the benthic macroinvertebrate availability within these lakes. My objectives were to (1) compare differences in diets among size groups of black crappie within each lake, (2) compare differences in diets across size groups among the three lakes, (3) relate diets to benthic food availability, and (4) evaluate trends between diet composition and fish growth rates among the three lakes. 13

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METHODS Study Lakes Lakes Lochloosa, Marian, and Monroe were the study lakes for this research (Figure 1). Lakes Lochloosa and Marian are hypereutrophic and Lake Monroe is eutrophic, according to average chlorophyll a concentrations sampled between 1993 and 2002, as classified by Forsburg and Ryding (1980; Table 1). These lakes were selected because of the differences in their black crappie population characteristics. Lochloosa Lake is a 2,310-ha lake in eastern Alachua County and the fishery characteristics were described above. Lake Marian is a 2,323-ha lake located in southern Osceola County. It was listed as one of FWCs top-ten black crappie lakes of 2003 and is known for producing high recreational catches of black crappie, although it is not known for catches of large black crappie (Hale and Alred 2003). Lake Monroe is a 3,808-ha lake located in Seminole and Volusia counties. It was also listed as one of FWCs 2003 top-ten black crappie lakes (Hale and Alred 2003) and is known for producing large black crappie. There was a 304-mm minimum length limit on the black crappie fishery at Lake Monroe from 1998 to 2005. Black Crappie Collection Otter trawls have frequently been used as a method for sampling black crappie at Florida water bodies (Huish 1953; Ager 1975; Schramm et al. 1985; Allen et al. 1999; Pine 2000). Huish (1957) used shrimp trawls to collect bluegill Lepomis macrochirus, readear sunfish Lepomis microlophus, and black crappie at Lake George, Florida as early as 1950 because commercial seines did not catch fish < 152 mm TL effectively. Similarly, Allen et al. (1999) found otter trawls to be preferred over trap nets for sampling black crappie due to a larger size range of fish caught, reduced sampling effort required, precision of catch per effort, and reduced sampling expenses. 14

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Otter trawls (4.6 m mouth, 4.9 m long, 38.1 mm stretch mesh body, and 31.8 mm stretch mesh bag) were used to collect black crappie from each lake during the study. Sample periods included August, October, and December of 2002 and February, April, June, August, and October of 2003. A minimum of three trawls were pulled at each lake during each period. During each period, the first three or four trawls in Lakes Monroe and Marian were pulled at separate fixed sites. Trawls pulled at Lochloosa Lake were scattered throughout the lake, because Lochloosa Lake was sampled much more intensively than the other systems (below). Time length of the trawls was adjusted based on catch. Black crappie were measured to the nearest mm TL. I attempted to collect 10 fish in each of four size classes from Lakes Marian and Monroe and 30 fish in each of four size classes from Lochloosa Lake during each sampling period. The size classes include (1) 110 149, (2) 150 189, (3) 190 229, and (4) > 230 mm TL. The fish collected for stomach analysis were immediately stored on ice to reduce the likelihood of regurgitation (Doxtater 1963), and then taken to the laboratory. Fish that could not be immediately processed at the laboratory were frozen for later analysis. Processing of Fish and Stomachs At the laboratory, each fish was measured to the nearest mm TL, weighed to the nearest gram, and the sagittal otoliths were removed. The stomach and hindgut of each fish were removed from the esophagus to the anal opening. The stomach was placed into a labeled jar with 10% buffered formalin acetate for preservation. Formalin was eventually replaced by 95% ethanol, prior to stomach content analysis. A dissecting microscope was used when sorting through the contents of the stomachs. Individual food items were categorized (Table 2) and counted for each taxonomic group. When contents were partially digested, countable parts such as eyes and head capsules were counted to obtain consumption estimates of those items. For example, two diptera pupae eyes made up one 15

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individual. All remaining unidentifiable contents were placed together and categorized as unidentified digested material. Each category was wet weighed to the nearest 10 -4 g. Stomachs and hindguts, that were completely full of small digested parts (e.g., Diptera eyes), were subsampled to reduce sampling time. All larger items (e.g., fish, Palaemonetes, etc.) were separated from the bulk of the contents, identified, counted, and weighed. The remaining diet contents were stirred and visually divided into quarter sections, using one section as the subsample. The contents of the subsample were categorized, counted, and weighed. The remaining portion of the sample was placed together and wet weighed to the nearest 10 -4 g. Results were used to extrapolate the remainder of the sample. Age Estimation Numerous studies have validated the use of otoliths for accurate age assessments for crappies (Schramm and Doerzbacher 1982; Hammers and Miranda 1991; Ross et al. 2005). Whole views of otoliths were read for aging. If three or more rings were found, one otolith from each fish was sectioned transversely from the ventral to dorsal gradient using a South Bay Technology, Inc. low-speed diamond-wheel saw. Two sections, 0.5 mm wide, were cut from each sectioned otolith. The sections were mounted on a labeled glass slide using Thermo Shandon Synthetic Mountant with the inner-nucleus side facing up. Two independent readers aged each fish using a dissecting microscope. The age-class of the fish was equal to the number of rings if the collection date was in the latter half of the year. However, the age-class of a fish, collected in the first half of the year, was equal to the number of rings if a new ring had recently formed at the margin, or the number of rings plus one if a new ring had not yet formed at the margin. Any disagreement in age-class between readers was reexamined, and if conflict remained, a third reader was used. If no agreement could be reached with a third reader, that fish was not used in the analyses. 16

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Based on an observation of peak hatch dates of black crappie at the north Florida Lake Wauberg, between mid-March and mid-April (Pine and Allen 2001), the hatch date of all fish in this study was set at March 1 st A March 1 st hatch date could act as a midpoint for the possible earlier spawning periods of black crappie in the more southern lakes of Marian and Monroe and the later spawning period of the north Florida Lochloosa Lake, which is latitudinally equivalent to Lake Wauberg. An age of each fish was then set based on the proportion of the year that occurred between March 1 st and the collection date. Macroinvertebrate Collection and Processing Benthic macroinvertebrates were sampled at eight fixed sites in each lake using a petite Ponar during each sampling period from December 2002 to October 2003. The sites were selected based on substrate types and locations that corresponded with the trawl sites. The contents of each sample were sieved through a 300-um mesh bucket and preserved in a labeled jar with 95% denatured ethanol. The petite Ponar (15.24 cm long and 15.24 cm wide) is a smaller version of the Ponar grab designed by Powers and Robertson (1967). Ponars have been compared with other forms of benthic samplers (Flannagan 1970; Hudson 1970; Howmiller 1971; Elliott and Drake 1981) and across a variety of substrate types (Nalepa et al. 1988; Int Panis et al. 1995). The reliability of the various samplers for adequate assessment of benthic community structure and abundance depends on the sediment type (Flannagan 1970; Hudson 1970; Howmiller 1971; Elliott and Drake 1981; Int Paris et al. 1995). In studies where three or more grabs were compared, the Ponar has been found to be the most adequate benthic sampler among a range of substrate types (Flannagan 1970; Hudson 1970; Elliot and Drake 1981). A dissecting microscope was used when sorting through the samples. If the contents included a large quantity of sand, a sugar solution flotation procedure described by Anderson 17

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(1959) was used to reduce processing time. If the content of a Ponar was large, a fixed fraction of the sample was processed. Contents were poured into a pan and stirred to form a homogeneous sample and weighed. A proportion of the sample based on weight, was removed from the pan and used as a subsample. Proportions used as subsamples included 0.50, 0.25 and 0.125, depending on the total sample volume. Macroinvertebrates contained in the subsample were removed, identified taxonomically, and counted. Subsample data were used to estimate total sample contents. Data Analysis Population Abundance and Size Structure Mean catch per unit of effort (CPUE) values were used as an index to compare crappie population relative abundance among the three lakes. Black crappie were classified into four size groups (Size classes 2, 3, 4, and all fish) and mean CPUE values were calculated for each lake and sampling period. A one-way ANOVA was used to compare mean log transformed CPUE values among lakes for each group. Values of CPUE were log (X + 1) transformed to improve the homogeneity of variances. The least squares means (LSMEANS) procedure was used to determine differences between lakes when ANOVAs were significant (SAS Institute 1997). I assumed that mean CPUE values were proportional to the population densities (Hubert 1996). Size structure of black crappie > 110 mm TL, captured with otter trawls at each of the three lakes, was expressed with a length frequency histogram for the last four sampling periods. A chi-square test was used to determine if the proportion of black crappie among the four size classes was homogeneous among lakes. 18

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Age and Growth Comparisons Ages of black crappie, collected from the three lakes, were used to make inferences about the age structure of black crappie at each lake. Fish ages and total lengths were used to fit linear, von Bertalanffy (VBGM) and Gompertz growth models for each lake. Residuals of the observed versus predicted total lengths were plotted against the predicted values to evaluate the fit of the three models for each lake. A variance ratio test was used to assess differences in the models and choose the best-fit model for the data in the form of 2df21df1MSEMSEF where MSE 1 and MSE 2 are the mean squared errors obtained by using separate growth models for the same lake, with degrees of freedom df 1 and df 2, respectively. The larger MSE was used as the numerator and F was compared to an F-statistic at P = 0.05. A significant result meant the model used to receive MSE 2 had a better fit to the data. After comparisons among all three models were made, the one that best fit the data was used to estimate mean TL at age for each lake. The likelihood ratio test described by Kimura (1980) and Haddon (2001) was used to compare growth curves among the three lakes using the VBGM ottkteLL1 where L t is the mean length at age t, L is the asymptotic maximum length, k is the growth rate coefficient determining how quickly L is obtained, and t o is the hypothetical age when length is equal to zero. The likelihood ratio test compares two or more non-linear equations by first treating them as separate populations and then combining all observations as if they were from the same population to make a new growth curve with new values for parameters k, t o and L 19

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Cerrato (1990) suggested using the likelihood ratio test over three other tests when comparing VBGMs because of more accurate and reliable results. This test uses a chi-square statistic to see if the combined curve residual sum of squares is significantly different from the sum of the residual sum of squares for each model separately as RRSRRSLnNk2 where k is the degrees of freedom (equal to the number of parameters fixed), N is the total number of observations used, RRS is the total residual sum of squares derived from fitting the curves together, and RRS is the total residual sum of squares derived from fitting all curves separately. This analysis tested the hypothesis that the quality of fit was not significantly different for a combined model versus separate models. To test the hypotheses that parameters (i.e., L and k) of the growth curves were different, I fitted the VBGM for each lake using only the value of the parameter in question, obtained from the combined equation. A chi-square statistic was calculated again for each hypothesis (L values are different, etc.) where RRS is the total residual sum of squares derived from fitting the curves with one of the parameter constraints and RRS is the same total residual sum of squares derived from fitting all curves separately with no constraints. Likelihood ratio tests were then used to make pair-wise comparisons among the three lakes using the same procedures as above. Diet Comparisons Mean percent weights of prey categories were used to compare diet compositions of black crappie. Percent weights were calculated as jiiWtWtWt100% 20

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where Wt i is the weight of category i found in a stomach and Wt j is the total weight of all categories found in that stomach. Empty stomachs and stomachs which contained nothing but unidentified digested material were not included in the analysis for %Wt Unidentifiable digested material was not included for the summation of Wt j because it would distort the description of the identifiable prey categories. Weights of partially digested items were not projected into whole weights for two reasons. First, this would require substantial extrapolation. Second, individual species or life stages within a particular prey category (e.g., Chironomidae larvae) might be far different in size. Thus, predicted weights would not be accurate without further identification or classification. Percent composition by weight of dietary items provides an idea of the relative importance of various food types to the nutrition of fish (Bowen 1996). However, Liao et al. (2001) found percent weight indices to overemphasize the importance of larger prey taxa. Diet compositions of black crappie were compared using multivariate analysis of variance (MANOVA). Crow (1979) suggested the use of a MANOVA for diet comparisons when it was desirable to test for differences in more than one prey species because it simultaneously evaluates multiple prey categories, whereas a series of univariate ANOVAs on separate prey variables may not reveal among-group differences. Individual %Wts of each category were arcsine-transformed to normalize the data (Kleinbaum et al. 1998; Zar 1999). The arcsine-transformed %Wts of prey categories were pooled into four major categories (Table 3) based on taxonomy, size, and previous published findings about shifts in crappie diets. Mean arcsine-transformed %Wts of the major categories were then calculated for each group. A three-way MANOVA was used to evaluate if mean arcsine-transformed percent composition by weight of the four major prey categories in the stomach contents varied with lake, period, and size class. A 21

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significant interaction of the treatments lead to univariate F tests by analysis of variance (ANOVA), to expose which prey categories were responsible for the interaction. Significant interactions of the ANOVAs were explained graphically and by comparisons of the treatment means using the LSMEANS procedure adjusted for the Tukey-Kramer multiple comparison test (SAS Institute 1997). To evaluate diet shifts with fish size among the three lakes, the %Wt data for all periods were pooled for each size class at each lake. Comparisons of ontogenetic diet shifts were made by two-way ANOVAs, using the mean arcsine-transformed values for %Wt of the major diet categories as the dependent variable, with lake, size class, and the interaction of these variables as factors. The LSMEANS procedure adjusted for Tukey-Kramer was used to separate the means if the ANOVA was significant (SAS Institute 1997). I used an index of stomach fullness to evaluate total prey weight standardized for fish size among lakes with the equation %1001NWeighttandardWetTotalFishSetWeightchContentWTotalStomaIFNiiii where i is an individual observation in a set of N total fish. The total stomach content wet weight included all material found in a stomach. An index of fullness is a useful measurement of diet because it is relative to fish size (Hyslop 1980). Standard wet weights based on individual total lengths were used in the IF equation because of differences of the length-weight relationships among the three lakes. Standard weights were taken from a standard weight equation by using the logarithmic transformations of the pooled length-weight data, in the form )TL(log)Wt(log1010 ba 22

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where Wt is weight, TL is total length, a is the y-axis intercept, and b is the slope of the equation. Because the sample sizes of length-weight data were not equal among the three lakes, the sample size for each lake in the pooled data was limited to the number of observations in the smallest sample by randomly selecting data from the lakes with larger samples. This procedure provided a length-weight relationship that was weighted equally for all lakes. The standard weight equation was ).TL(log246.3458.5)Wt(log1010 Average total stomach content weights were then compared with one-way and two-way ANOVAs using mean log-transformed IF values as the dependent variable and lake, size class, and the interaction as factors. The individual IF observations were log (X + 1) transformed to homogenize the variances. The LSMEANS procedure adjusted for the Tukey-Kramer multiple comparison test (SAS Institute 1997) was used to compare mean IF values between lakes, size classes, and lakes for each size class. Macroinvertebrate Density Comparisons Estimated densities of the macroinvertebrate taxa used in selectivity and similarity indices were compared among lakes by one of two methods. Chironomidae larvae densities were log (X + 1) transformed and ANOVAs were used for each sample period using lakes as the treatments and the log-transformed Chironomidae larvae densities as the variables. If a significant difference was found, the LSMEANS procedure adjusted for Tukeys multiple comparison test (SAS Institute 1997) was used to compare values between lakes to determine the difference(s). Comparisons among lake mean densities of the other macroinvertebrate taxa were made with a Kruskal-Wallis test because of the non-normal structure of the data, even after transformations were conducted. If significant differences were found, nonparametric multiple comparisons for 23

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data with tied ranks (i.e., Dunn test) were made to locate where differences occurred (Zar 1999). Mysidacea and Isopoda (i.e., Suborder Anthuridea) were not included in this analysis because they were only found at Lake Monroe. Ponar-Diet Comparisons Between-lake comparisons of mean %Wt, mean number, and/or occurrence of prey taxa in black crappie diets were used to express how density differences of macroinvertebrate taxa between lakes could influence black crappie diets. Mean number of prey items was calculated as nNoNoii where No i is the total number of prey taxa i found in stomachs from a group of n total fish. Occurrence was considered as presence of a prey item in black crappie diets. Selective feeding of black crappie on benthic macroinvertebrates at each lake was measured using Manlys index of preference for each size class in six sampling periods. The sampling periods included December of 2002 and February, April, June, August, and October of 2003. Manly et al. (1972) originally developed the index, which was later refined by Chesson (1978). Manlys estimates were calculated for individual black crappie as mjjjiiinrnr11 where i is Manlys (preference index) for prey type i, r i and r j is the proportion of prey type i and j in the diet (number of individuals), n i and n j is the proportion of prey type i and j in the environment (petite Ponar density), and j is an individual prey type out of m possible prey types. Mean Manlys estimates were calculated for each size class in each sampling period by 24

PAGE 25

KKii1 where i is one observation out of a total of K observations made for that group. Inferences of prey selection were made using mi1 as an indication level where values greater than, equal to, and less than i indicate preference, no selection, and avoidance of that prey item, respectively. Taxa used in Manlys indices include Chironomidae larvae, Chaoboridae larvae, Ceratopogonidae larvae, Diptera pupae, Ephemeroptera larvae, Trichoptera larvae, Amphipoda, Isopoda, Hydracarina, and Mysidacea. These taxa were chosen because they were represented in both the benthic grabs and black crappie diets. These taxa could also be effectively sampled with the benthic grabs and would be available for black crappie consumption. Individual taxa were not included in Manlys estimates for periods or lakes when they were not observed in the benthic grabs or diets. Consumption of a particular resource is considered selective when the relative proportion of that resource in the diet is greater than the relative proportion available in the environment (Chesson 1978). The simplified Morisita index of similarity was used to measure similarity of diet contents (i.e., mean numbers) relative to benthic densities for individual taxa throughout sampling periods for each lake. Taxa and sampling periods included in similarity indices were the same used in the selectivity indices. Horn (1966) suggested this version to ignore cases where negative numbers would appear in Morisitas original function. The simplified Morisita index is in the form of kjkikjijikijHNNNXNXXXC2222//2 25

PAGE 26

where C H is the simplified Morisita index of similarity, X ij and X ik are the numbers of individuals from sampling period i in sample j and sample k, N j is the total number of individuals in sample j, N k is the total number of individuals in sample k, j represents diets, and k represents petite Ponars. Values of the index range from 0 (no similarity) to 1 (complete similarity). 26

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RESULTS Catch rates of black crappie with otter trawls varied widely among lakes (Table 4). One-way ANOVAs resulted in significant differences of mean log-transformed CPUE values among lakes for each group (all P < 0.0029). Lake Marian had the highest CPUE value for all groups of black crappie (LSMEANS procedure; all P < 0.0001) and required the least amount of effort (total trawls = 37; total minutes = 108) to collect the desired number of individuals for diet analyses. Individual tow times of each trawl at Lake Marian were reduced because of the extremely high catch rates. Mean CPUE values did not differ significantly for size classes 2 (P = 0.3453) and 3 (P = 0.6457) black crappie between Lakes Lochloosa and Monroe, but Lochloosa Lake had the lowest mean CPUE for size class 4 (P < 0.0001) and all black crappie (P = 0.0119). Thus, Lochloosa Lake required the greatest amount of effort (total trawls = 186; total minutes = 1080) to collect enough specimens for diet analysis. Length frequency distributions also differed among the three sampling lakes (Figure 2). Chi square tests between lakes and size classes were significant for each period tested (all P < 0.0001), indicating that black crappie at Lakes Lochloosa and Monroe had higher proportions in size class 1 compared to Lake Marian. Lake Marian consistently had a higher proportion of black crappie in size class 3 compared to Lakes Lochloosa and Monroe (Figure 2). Lochloosa Lake generally had the lowest proportion of black crappie in the largest size class, whereas Lakes Marian and Monroe were comparable (Figure 2). A total of 1,351 black crappie were used for age and growth comparisons. Lakes Lochloosa, Marian, and Monroe had sample sizes of 734, 317, and 300, respectively. Lochloosa Lake had the greatest percent of black crappie collected < age 1 (75.1 %) and the lowest percent of black crappie > age 2, with only one observation as high as age 6. Lake Marian had both the 27

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oldest individual black crappie observed (age 11) and the highest percentage of black crappie collected > age 2 (56.4 %). The oldest black crappie collected at Lake Monroe were age 8. Linear, Gompertz and VBGM growth models (Table 5) were developed using the age at length data for the three lakes. Variance ratio tests resulted in significantly lower MSE values obtained from the Gompertz growth model and VBGM when compared to the linear growth model for all three lakes (all P < 0.0005). There was no significant difference found in the variance between the Gompertz growth model and VBGM for any of the study lakes (all P > 0.39). The residual plots of the VBGMs expected versus observed TL at age values (Figure 3) were uniformly distributed, which supports the use of this function. The VBGMs were chosen to estimate mean TL at age of black crappie for each lake and were used to plot the expected growth curves (Figure 4). The likelihood ratio test used to compare the VBGMs among the three lakes was significant ( 2 = 212.3; df = 3; P < 0.0001), indicating that at least one curve was significantly different from at least one of the other two curves. Tests of the individual parameters L and k of the three growth models were also significant at P < 0.05, indicating that the parameter being tested was significantly different in at least one of the growth models. Pairwise comparisons between the three growth curves showed that each model was significantly different from the other at P < 0.0001. Lake Monroe had a significantly higher L than Lochloosa Lake ( 2 = 5.21; df = 1; P = 0.0357), which had a significantly higher L than Lake Marian ( 2 = 4.41; df = 1; P = 0.0225). The estimate of k was higher at Lochloosa Lake than for Lakes Marian ( 2 = 7.73; df = 1; P = 0.0054) and Monroe ( 2 = 6.48; df = 1; P = 0.0109), but k did not differ significantly between the latter two lakes ( 2 = 0.18; df = 1; P = 0.6695). Thus, growth 28

PAGE 29

rates varied among populations with Lake Monroe having the largest mean TL-at-age, Lochloosa intermediate, and Lake Marian the lowest size-at-age. A total of 1,047 black crappie stomachs were examined for diet contents (Table 6). Lakes Lochloosa, Marian, and Monroe had sample sizes of 431, 317, and 299, respectively. There were 48 (4.6 %) empty stomachs and 49 (4.7 %) stomachs that contained nothing but unidentifiable digested material, which were not included in the mean %Wt analysis. Diets varied widely among lakes, size groups, and periods. The arcsine-transformed mean %Wt of major prey categories in black crappie diets was significantly different due to the lake, size class, and period interaction (MANOVA, Wilks Lambda: F 164, 3399 = 2.45, P < 0.0001). Univariate ANOVAs of the four major prey categories revealed significant three-way interactions for microcrustaceans (F 41, 855 = 4.06, P < 0.0001), insects (F 41, 855 = 2.29, P < 0.0001), macrocrustaceans (F 41, 855 = 1.55, P = 0.0157), and fish (F 41, 855 = 2.99, P < 0.0001). Thus, all of the major prey categories were responsible for the significant three-way interaction found in the MANOVA (Figures 5-8), which caused inconsistent differences for the importance of the major prey categories throughout the sampling periods, lakes, and size classes. For example, the mean arcsine-transformed %Wt value of microcrustaceans of size class 1 black crappie diets collected from Lochloosa Lake during October 2003 was higher than Lake Marian (Tukey-Kramer test; P = 0.0094), whereas Lake Monroe was not significantly different from Lochloosa Lake (P = 0.0631) or Lake Marian (P = 1.000). During this same sampling period, there was no significant difference of the mean arsine-transformed %Wt values of microcrustaceans between any of the lakes for size class 4 fish (all P = 1.000). When considering size class 1 in February 2003, the mean arcsine-transformed %Wt value of Lochloosa Lake was significantly smaller than both Lake Marian (P < 0.0001) and Lake Monroe 29

PAGE 30

(P < 0.0001), whereas there was no difference between Lake Marian and Lake Monroe (P = 0.9999). Thus, the diet composition expressed as mean %Wt for all the major prey categories (i.e., microcrustaceans, insects, macrocrustaceans, and fish) exhibited inconsistent differences among periods, size classes, and lakes. Two seasonal trends of major diet categories were evident in black crappie diets at all three study lakes (Figures 5-8). Microcrustaceans were a more important component of the diets during the winter (December and February) and were least important during the summer (June and August), with spring (April) and fall (October) varying depending on the lake and size class (Figure 5). No seasonal trends among lakes were evident in the mean %Wt values obtained for insects and macrocrustaceans in black crappie diets because of high variation of those values among the periods, size groups, and lakes (Figures 6 and 7). Fish prey generally increased in black crappie diets from the spring to the fall, whereas it was less important during the winter (Figure 8). This was more noticeable in the smaller size classes of fish, which had lower mean %Wt values of fish throughout the seasons than the larger size classes. Ontogenetic diet shifts of black crappie were evident at each lake (Figure 9). In general, mean %Wt values of microcrustaceans decreased and fish increased as crappie increased in size in each lake. There was no lake-size class interaction for mean arcsine-transformed %Wt values for microcrustaceans (ANOVA: F 6, 938 = 1.05, P = 0.3891) or fish (F 6, 938 = 0.20, P = 0.9762), which is supported by the parallelism present among lake values through all size classes (Figure 9). However, trends in the values for insects and macrocrustaceans were different among lakes as black crappie increased in size. A significant lake-size class interaction was found for the insect (F 6, 938 = 2.19, P = 0.0419) and macrocrustacean (F 6, 938 = 5.67, P < 0.0001) categories, which was due to the lack of parallelism across lakes and size classes, particularly for 30

PAGE 31

macrocrustaceans (Figure 9). Insect values obtained in size class 4 black crappie from Lochloosa Lake were significantly lower than in size classes 1, 2, and 3 (Tukey-Kramer test, all P < 0.003) and insect values in size class 4 black crappie from Lake Marian were significantly lower than those in size classes 1 and 3 (all P < 0.05). However, there were no significant differences between any size classes in the insect values from Lake Monroe (all P > 0.05). Lake Monroe macrocrustacean values were significantly lower for size class 4 than size classes 1, 2, and 3 (all P < 0.0005), whereas there were no differences in macrocrustacean values found between any of the size classes for Lochloosa Lake or Lake Marian (all P > 0.05). When comparing insect and macrocrustacean values between lakes for individual size groups, Lochloosa Lake and Lake Marian had no significant differences (all P > 0.05). When compared to Lake Monroe, these two lakes had significantly higher values of insects (all P < 0.01) for all size classes except size class 4 and significantly lower values of macrocrustaceans (all P < 0.0001) for every size class. Hence, differences in ontogenetic diet shifts of black crappie between lakes were due to the intermediate sized prey categories (insects and macrocrustaceans) rather than microcrustaceans or fish. There were four prey types that made up the majority of the %Wt values of the insect and macrocrustacean prey categories (Table 7). These included Chironomidae larvae, Chaoboridae larvae, Diptera pupae, and Mysidacea. Chironomidae larvae was a highly consumed prey type by black crappie in size classes 1, 2, and 3 among all systems. However, there were differences in the %Wt values of Chaoboridae larvae, Diptera pupae, and Mysidacea among lakes. While black crappie at Lochloosa Lake preyed highly upon Diptera pupae and black crappie at Lake Marian preyed highly upon Diptera pupae and Chaoboridae larvae, these two prey types were not highly utilized by black crappie at Lake Monroe. This resulted in higher %Wt values of the 31

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insect category at Lakes Lochloosa and Marian relative to Lake Monroe. Black crappie at Lake Monroe instead utilized the additional resource of Mysidacea (i.e., Americamysis almyra) as a prey item, which caused the macrocrustacean category %Wt values to be much larger than what was found in the other two systems. Diet shifts of the insect and macrocrustacean prey categories occurred when the %Wt values were consistently higher throughout size classes within a system. Therefore, differences in the utilization of Chaoboridae larvae, Diptera pupae, and Mysidacea by black crappie among systems led to the differences in ontogenetic diets shifts among systems. There was not a significant lake-size class interaction found for the mean log (X + 1)-transformed total stomach content IF values (ANOVA; F 6, 935 = 1.36, P = 0.2293). Tukey-Kramer multiple comparison tests resulted in no significant differences (all P > 0.05) found between lakes for any size class, implying that total consumption expressed as a function of fish weight was similar across all lakes for each size class. The main effects showed significant differences of the IF values for both lakes (F 2, 935 = 5.87, P = 0.0029) and size classes (F 3, 935 = 7.63, P < 0.0001). Tukey-Kramer multiple comparison tests resulted in greater IF values at Lakes Lochloosa and Marian compared with Lake Monroe (both P < 0.008), whereas the prior two lakes IF values were not significantly different from each other (P = 0.9797). Size class 1 black crappie IF values were greater when compared to size classes 3 (P = 0.0001) and 4 (P = 0.0006), and greater than size class 2 IF values by a marginal significance (P = 0.0579). There were no differences found in the IF values among size classes 2, 3, and 4 (all P > 0.30). Thus, black crappie at Lakes Lochloosa and Marian consumed a greater amount (i.e., weight) of total prey when expressed as a function of fish weight then black crappie at Lake Monroe. Also, 32

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size class 1 black crappie had larger diets in proportion to fish weight compared to larger size classes of black crappie. Differences in densities of benthic macroinvertebrates among lakes were significant for four taxa including Chironomidae larvae, Chaoboridae larvae, Amphipoda, and Hydracarina. Mean densities of all taxa are listed in Table 8. Chironomidae larvae densities were significantly different among lakes in December 2002 (ANOVA; F 2, 21 = 6.30, P = 0.0072) and marginally significant in February 2003 (F 2, 21 = 3.31, P = 0.0563). Differences occurred due to higher densities of Chironomidae larvae at Lochloosa Lake than at Lake Monroe for December (Tukey test; q = 4.9855; df = 21, 3; P = 0.0055) and February (q = 3.6146; df = 21, 3; P = 0.0465). Differences among lakes for Chaoboridae larvae and Hydracarina densities were found in all periods (Kruskal-Wallis test; all H C s > H 0.05, 8, 8, 8 = 5.805), except the February 2003 Hydracarina values (H C = 4.062; df = 8, 8, 8; P > 0.05). Lake Marian had higher densities of Chaoboridae larvae when compared to Lake Monroe for each sample period (Dunn test; all Qs > Q 0.05, 3 = 2.394). Chaoboridae densities at Lochloosa Lake were greater than those at Lake Monroe during April (Q = 2.856; df = 3; 0.01< P < 0.02) and June (Q = 3.246; df = 3; 0.001< P < 0.005) and lower than those at Lake Marian during August (Q = 2.766; df = 3; 0.01< P < 0.02) and October (Q = 2.799; df = 3; 0.01 < P < 0.02). Lake Marian had higher densities of Hydracarina than Lochloosa Lake in each period when differences were found among lakes and higher densities than Lake Monroe in April, June, and October (all Qs > Q 0.05, 3 = 2.394). A significant difference of Amphipoda densities among lakes was found in October 2003 (H C = 6.553; df = 8, 8, 8; P < 0.05), when densities at Lake Monroe were greater than those at Lochloosa Lake (Q = 2.429; df = 3; 0.02< P < 0.05) There were no significant differences found among lakes in the densities of Ephemeroptera larvae, Trichoptera 33

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larvae, Ceratopogonidae larvae, or Diptera pupae during any sample period (all H C s < H 0.05, 8, 8, 8 = 5.805). Differences in macroinvertebrate densities (i.e., Chironomidae larvae, Chaoboridae larvae, and Hydracarina) among lakes were accompanied by dietary differences in black crappie for these same prey taxa. In December 2002 and February 2003, when Chironomidae larvae densities were higher at Lochloosa Lake in comparison to Lake Monroe, the mean number of Chironomidae larvae consumed by black crappie from Lochloosa Lake was also higher than at Lake Monroe (Figure 11). High Chaoboridae larvae densities at Lake Marian were accompanied by both higher %Wt and higher mean number of Chaoboridae larvae values in black crappie diets, when compared to Lakes Lochloosa and Monroe (Table 7 and Figure 11). At Lake Marian, higher Hydracarina densities were associated with occurrence of this prey item in the diets of black crappie. Although Hydracarina was never found in large quantities and only occurred in 5 black crappie stomachs out of 317 examined from Lake Marian, this prey item never occurred in any of the stomachs examined from Lakes Lochloosa or Monroe. Hence, higher densities of macroinvertebrate taxa caused increased occurrence and/or consumption of those prey taxa in black crappie diets. Two major trends in prey selection were detected with Manlys index (Figure 10). First, black crappie of all sizes at Lakes Lochloosa and Marian were highly selective of Diptera pupae during most periods. Second, black crappie of all sizes at Lake Monroe were highly selective of Mysidacea during most periods. While black crappie at Lakes Lochloosa and Marian did not have Mysidacea as a prey option, black crappie at Lake Monroe had Diptera pupae as a prey option but selected Mysidacea. 34

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Manlys index produced various results for the remainder of the prey taxa (Figure 10). Selection for Chaoboridae larvae at Lakes Lochloosa and Marian was generally higher than for Lake Monroe. Black crappie at Lake Marian were more selective of Chironomidae larvae than at Lakes Lochloosa and Monroe. Ceratopogonidae larvae, Ephemeroptera larvae, Trichoptera larvae, Amphipoda, and Isopoda were generally avoided prey taxa, but results were inconsistent and these prey taxa were occasionally considered either not preferred or highly selected among all size classes of black crappie. Hydracarina was always considered an avoided prey taxa. The simplified Morisita index produced various results of C H values for the different taxa (Table 9). Relative increases and decreases of taxa density and mean number in diets are shown in Figure 11. Overall, Chironomidae larvae and Diptera pupae produced the highest C H values throughout most size classes at each lake. An exception occurred for Diptera pupae for size class 4 black crappie from Lake Monroe (C H = 0.09). The reason for such a low value (no similarity), was due to the August 2003 sampling period when 2 individual fish consumed over one thousand Diptera pupae each. This raised the mean number of Diptera pupae in the stomachs far above what was sampled in the environment for that period and was much greater than the mean numbers found in diets for the other periods. Chaoboridae larvae (C H = 0.69 0.92) and Ephemeroptera larvae (C H = 0.55 0.80) values were higher for Lake Marian black crappie throughout all size classes than at Lochloosa Lake and Lake Monroe for the same size classes. The similarities of Mysidacea (C H = 0.72 0.93), Trichoptera (C H = 0.63 0.75), Amphipoda (C H = 0.47 0.86), and Isopoda (C H = 0.67 0.93) were relatively high in Lake Monroe samples throughout most size classes, while these same taxa either were not present or had lower C H values at the other lakes. Overall, higher C H values were detected for taxa which were more 35

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utilized within a system. Thus, I was able to detect a relationship between seasonal abundance of benthic prey and black crappie diets within a lake, particularly for taxa that were highly utilized. Some tradeoffs of utilized prey resources were found for benthic macroinvertebrates as densities of those prey taxa changed. For example, black crappie at Lake Monroe increased their consumption of Chironomidae larvae in June 2003 when the highest Chironomidae densities occurred relative to the other sampling periods were recorded (Figure 11). At this same time, Mysidacea densities were declining along with the consumption of Mysidacea by black crappie (Figure 11). 36

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37 Table 1. Mean water quality parameters for Lakes Lochloosa (Source: Florida LAKEWATCH 1997), Marian (Source: FWC unpublished da ta), and Monroe (Source: Florida LAKEWATCH 2003). Water quality parame ters include years sampled (Yrs), number of sampling dates (n), total phosphorus (TP g/L), total n itrogen (TN g/L), chlorophyll (CHL g/L), secchi depth, and trophic state. Lake Yrs n TP (g/L) TN (g/L) CHL (g/L) Secchi (m) Trophic state Lochloosa 1993-96 40 48 1816 63 0.48 hypereutrophic Marian 2000-02 5 111 1759 42 0.66 hypereutrophic Monroe 2000-02 21 89 1628 19 0.61 eutrophic *Trophic state based on Forsburg and Ryding (1980).

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38 Table 2. List of types and common names of prey used to numerically and gravimetrically describe black crappie diet contents. Prey type Common name Prey type Common name Nematoda Roundworms Neuroptera Spongillaflies Oligochaeta Aquatic earthworms Trichoptera Caddisflies Hirudinea Leeches Coleoptera Beetles Cladocera Water fleas Hymenoptera Ants and Wasps Copepoda Copepods Arachnida-Araneae Spiders Copepoda-Argullus Fish lice Orthoptera Grasshoppers Ostracoda Seed shrimp Diptera Flies, Midges, etc. Mysidacea Opossum shrimp Chironomidae larvae Midge larvae Isopoda Aquatic sow bugs Chironomidae pupae Midge pupae Amphipoda Scuds, Sideswimmers Chironomidae adult Midge adult Cambaridae Crayfish Chaoboridae larvae Phantom midge larvae Palaemonidae Grass shrimp Chaoboridae pupae Phantom midge pupae Hydracarina Water mites Chaoboridae adult Phantom midge adult Unidentified Insect Insects Ceratopogonidae Biting midge larvae Plecoptera Stoneflies Stratiomyidae Soldier flylarvae Ephemeroptera Mayflies Fish Odonata Odonates Gastropoda Snails Odonata-Anisoptera Dragonflies Vegetation Odonata-Zygoptera Damselflies Detritus Hemiptera Bugs Miscellaneous material Hemiptera-Corixidae Water boatmen Digested material Megaloptera Dobsonflies

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39 Table 3. Four major prey categories used in the MANOVA procedure and the individual prey items included in each category. Major prey category Individual prey t ypes included in major prey categories Cladocera Copepoda Microcrustaceans Copepoda-Argullus Ostracoda Unidentified Insect Plecoptera Ephemeroptera Odonata Odonata-Anisoptera Odonata-Zygoptera Hemiptera Hem iptera-Corixidae Megaloptera Neuroptera Trichoptera Coleoptera Hymenoptera Orthoptera Diptera Chironom idae Chaoboridae Ceratopogonidae Stratiomyidae Arachnida-Araneae a Insects Hydracarina a Mysidacea Isopoda Amphipoda Palaem onidae Macrocrustaceans Cambaridae Fish Fish a Arachnida and Hydracarina are not true insects, but were in cluded within the insect prey category.

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Table 4. Otter trawl capture and collection data for black crappie from Lakes Lochloosa, Marian, and Monroe during each sampling period. Total time is the total number of minutes trawls were pulled at each lake. Total catch is the total number of black crappie caught in all trawls. Mean CPUE was calculated for black crappie for size class 2 (150 189 mm TL), size class 3 (190 229 mm TL), size class 4 (> 230 mm TL), and all fish. Total fish collected include all black crappie sacrificed for diet and age analysis in size classes 1 (110 149 mm TL), 2, 3, and 4. Mean CPUE (fish/min) Total collected Sampling period # of Trawls Total time (min) Total catch Size class 2 Size class 3 Size class 4 All fish Size class 1 Size class 2 Size class 3 Size class 4 All size classes Lochloosa Lake Aug-2002 a a a a a a a 10 10 10 10 40 Oct-2002 23 91 221 b 0.3 b 0.1 b 0.1 b 2.7 b 43 15 15 12 85 Dec-2002 48 323 a a a a a 32 11 10 23 76 Feb-2003 24 120 316 0.3 0.2 0.1 2.6 30 31 25 11 97 April-2003 26 160 260 0.3 0.2 0.1 1.8 30 30 22 10 92 June-2003 22 130 1,065 0.9 0.2 0.4 8.7 29 34 27 30 120 Aug-2003 23 148 978 1.0 0.1 0.1 6.9 31 30 19 15 95 Oct-2003 20 108 729 1.0 0.3 0.3 6.7 28 30 29 30 117 All Periods 186 c 1,080 c 3,569 c 0.6 0.2 0.2 4.8 233 191 157 141 722 40 a Data not recorded. b Values do not include all trawls in sampling period. c Totals based on data with missing values.

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Table 4. Continued. Mean CPUE (fish/min) Total collected Sampling period # of Trawls Total time (min) Total catch Size class 2 Size class 3 Size class 4 All fish Size class 1 Size class 2 Size class 3 Size class 4 All size classes Lake Marian Aug-2002 2 10 400 25.1 7.5 3.4 40.0 10 10 10 10 40 Oct-2002 6 12 365 6.0 b 3.1 b 8.3 b 30.4 9 10 10 10 39 Dec-2002 3 6 172 10.0 4.7 3.5 28.7 10 10 10 10 40 Feb-2003 4 8 97 5.4 2.3 2.0 12.1 10 10 10 10 40 Apr-2003 5 15 242 4.3 b 5.8 b 3.1 b 16.1 10 10 10 10 40 Jun-2003 7 23 336 3.8 b 4.3 b 3.7 b 13.9 10 10 10 8 38 Aug-2003 6 22 177 0.9 2.4 1.9 8.0 10 10 10 10 40 Oct-2003 4 12 237 3.3 7.5 5.8 19.8 10 10 10 10 40 All Periods 37 108 2,026 5.6 4.3 4.0 19.0 79 80 80 78 317 41

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42 Table 4. Continued. Mean CPUE (fish/min) Total collected Sampling period # of Trawls Total time (min) Total catch Size class 2 Size class 3 Size class 4 All fish Size class 1 Size class 2 Size class 3 Size class 4 All size classes Lake Monroe Aug-2002 26 130 855 0.1 0.2 1.1 6.6 10 10 10 10 40 Oct-2002 22 110 232 0 0.1 0.7 2.1 10 0 8 10 28 Dec-2002 9 43 404 0.2 0.4 2.4 9.0 10 10 10 10 40 Feb-2003 11 55 305 0.2 0.1 1.1 5.5 10 10 4 10 34 Apr-2003 18 130 630 0.9 b 0 b 1.2 b 4.9 10 10 8 10 38 Jun-2003 15 75 594 3.5 0.1 0.6 7.9 10 10 10 10 40 Aug-2003 5 25 261 1.0 0.4 1.2 10.4 10 10 10 10 40 Oct-2003 4 20 149 0.7 0.8 1.0 7.5 10 10 10 10 40 All Periods 110 588 3,430 0.7 0.2 1.0 5.9 80 70 70 80 300 Total 333 c 1,736 c 9,025 c 392 341 307 299 1,339

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Table 5. Linear, Gompertz, and von Bertalanffy growth functions of black crappie in Lakes Lochloosa, Marian, and Monroe based on the collected total length at age data. L t is the expected length at age t (years). Lake Growth function Linear Lochloosa )(90.4427.100tLt Marian )(34.2742.128tLt Monroe )(70.3685.123tLt Gompertz Lochloosa ))7057.0(6411.0(0.312teeLt Marian ))5182.0(4745.0(1.311teeLt Monroe ))5689.0(4917.0(4.344teeLt von Bertalanffy Lochloosa ))3761.0(3724.0(13.342teLt Marian ))8268.0(3077.0(15.328teLt Monroe ))8039.0(2999.0(15.370teLt 43

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Table 6. Number of black crappie stomachs examined for diet contents, number of empty stomachs observed, and number of stomachs with 100 % digested material in each of the three study lakes. Total stomachs examined are listed for size classes 1 (110 149 mm TL), 2 (150 mm TL), 3 (190 229 mm TL), and 4 ( > 230 mm TL). The numbers in parentheses for empty stomachs and stomachs with 100 % digested material indicate the percentages that those stomachs made up for all size classes of stomachs examined. Total stomachs examined Sampling period Size class 1 Size class 2 Size class 3 Size class 4 All size classes Empty stomachs Stomachs with 100 % digested material Lochloosa Lake Aug-2002 10 10 10 10 40 1 (2.5) 6 (15.0) Oct-2002 43 15 15 12 85 2 (2.4) 8 (9.4) Dec-2002 32 11 10 23 76 1 (1.3) 0 Feb-2003 9 10 10 11 40 0 0 Apr-2003 10 10 10 10 40 2 (5.0) 0 Jun-2003 9 11 10 15 45 1 (2.2) 7 (15.6) Aug-2003 10 10 10 15 45 1 (2.2) 5 (11.1) Oct-2003 10 10 10 30 60 5 (8.3) 9 (15.0) All Periods 133 87 85 126 431 13 (3.0) 35 (8.1) Lake Marian Aug-2002 10 10 10 10 40 1 (2.5) 1 (2.5) Oct-2002 9 10 10 10 39 5 (12.8) 1 (2.6) Dec-2002 10 10 10 10 40 1 (2.5) 0 Feb-2003 10 10 10 10 40 2 (5.0) 1 (2.5) Apr-2003 10 10 10 10 40 1 (2.5) 0 Jun-2003 10 10 10 8 38 1 (2.6) 0 Aug-2003 10 10 10 10 40 1 (2.5) 3 (7.5) Oct-2003 10 10 10 10 40 2 (5.0) 2 (5.0) All Periods 79 80 80 78 317 14 (4.4) 8 (2.5) 44

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Table 6. Continued. Total stomachs examined Sampling period Size class 1 Size class 2 Size class 3 Size class 4 All size classes Empty stomachs Stomachs with 100 % digested material Lake Monroe Aug-2002 10 10 10 10 40 5 (12.5) 1 (2.5) Oct-2002 10 0 8 10 28 4 (14.3) 0 Dec-2002 10 10 10 10 40 0 1 (2.5) Feb-2003 10 10 4 10 34 0 0 Apr-2003 10 10 8 10 38 0 0 Jun-2003 10 10 10 10 40 0 0 Aug-2003 10 10 10 10 40 7 (17.5) 0 Oct-2003 9 10 10 10 39 5 (12.8) 4 (10.3) All Periods 79 70 70 80 299 21 (7.0) 6 (2.0) Total 291 237 235 284 1047 48 (4.6) 49 (4.7) 45

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46 Table 7. Mean percent weight values (%Wt ) of dominant prey types in the Insect and Macrocrustacean (Macro) prey categories f ound in black crappie diets in size classes 1 (110 149 mm TL), 2 (150 mm TL), 3 (190 229 mm TL), and 4 ( > 230 mm TL) at Lakes Lochloosa, Marian, and Monroe. Prey types listed include Chironomidae larvae (Chi), Chaoboridae larvae (Cha), and Diptera pupae (Dip) in the Insect prey category and Mysidacea (M ys) in the Macro prey category. %Wt values are based on pooled data from all sampling periods. Size class Chi %Wt Cha %Wt Dip %Wt Insect %Wt Mys %Wt Macro %Wt Lochloosa Lake 1 29.63 4.34 31.84 71.05 0 5.22 2 21.55 7.46 25.35 66.79 0 4.23 3 14.32 1.19 30.36 60.21 0 7.55 4 6.32 0.43 21.75 37.71 0 2.60 Lake Marian 1 24.61 11.73 17.79 60.54 0 0.22 2 15.21 17.56 12.73 58.11 0 6.26 3 10.20 19.54 20.03 59.47 0 7.63 4 2.70 15.16 17.38 37.70 0 3.00 Lake Monroe 1 14.16 5.95 1.37 25.63 39.12 48.20 2 17.71 3.40 2.60 33.92 31.92 42.11 3 18.46 3.39 1.67 30.42 34.46 46.71 4 3.66 0.59 11.40 20.65 14.83 21.72

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Table 8. Mean densities (number/m 2 ) of taxa collected with petite Ponars in each period from Lakes Lochloosa, Marian, and Monroe. Periods include December of 2002 and February, April, June, August, and October of 2003. Taxa include Chironomidae larvae (Chi), Chaoboridae larvae (Cha), Ceratopogonidae larvae (Cer), Diptera pupae (Dip), Mysidacea (Mys), Trichoptera larvae (Tri), Ephemeroptera larvae (Eph), Amphipoda (Amp), Isopoda (Iso), and Hydracarina (Hyd). Mean taxa density Period Chi Cha Cer Dip Mys Tri Eph Amp Iso Hyd Lochloosa Lake December 26,065 328 3,272 5 0 0 603 2,282 0 0 February 11,313 441 3,488 38 0 22 1,528 1,109 86 22 April 3,848 102 926 22 0 5 151 495 108 0 June 5,102 86 947 0 0 0 258 409 0 0 August 7,809 899 215 11 0 43 86 0 0 0 October 5,145 1,948 463 0 0 43 43 0 0 43 47

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48 Table 8. Continued. Mean taxa density Period Chi Cha Cer Dip Mys Tri Eph Amp Iso Hyd Lake Marian December 8,939 2,508 355 0 0 0 129 2,018 0 167 February 10,220 2,185 145 27 0 0 65 97 0 108 April 10,893 1,948 43 75 0 22 22 86 0 355 June 6,044 2,508 75 43 0 118 11 285 0 350 August 17,405 1,243 97 48 0 11 0 22 0 296 October 3,374 2,842 11 0 0 0 5 22 0 248 Lake Monroe December 1,706 38 161 0 16 32 43 81 38 5 February 2,164 43 86 27 5 22 172 199 0 22 April 2,626 16 129 70 38 5 0 113 86 0 June 27,270 22 108 70 16 75 0 291 15 0 August 11,727 0 32 0 5 32 86 576 457 5 October 2,007 22 54 0 0 27 27 264 388 22

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Table 9. Simplified Morisita index values of similarity for various taxa comparing density found with petite Ponars to the total number found in black crappie diets through all sampling periods. Comparisons were made for black crappie in size classes 1 (110 149 mm TL), 2 (150 mm TL), 3 (190 229 mm TL), and 4 ( > 230 mm TL) at Lakes Lochloosa, Marian, and Monroe. Taxa used in comparisons include Chironomidae larvae (Chi), Chaoboridae larvae (Cha), Ceratopogonidae larvae (Cer), Diptera pupae (Dip), Ephemeroptera larvae (Eph), Trichoptera larvae (Tri), Mysidacea (Mys), Amphipoda (Amp), Isopoda (Iso), and Hydracarina (Aca). Values range from 0 (no similarity) to 1.0 (complete similarity). Dashes indicate cases when no individuals were found in the diets. Blanks indicate cases when no individuals were found in the diets or Ponars. Taxa Size class Chi Cha Cer Dip Eph Tri Mys Amp Iso Aca Lochloosa Lake 1 0.92 0.43 0.23 0.95 0.09 0 0.32 2 0.85 0.82 0.23 0.88 0.33 0.29 0.61 3 0.90 0.45 0.27 0.93 0.33 0.50 4 0.59 0.53 0.41 0.95 0.45 Lake Marian 1 0.69 0.69 0.10 0.92 0.55 0.99 0.04 2 0.91 0.92 0.28 0.85 0.80 0.28 0.07 0.39 3 0.92 0.74 0.23 0.66 0.60 0.17 0.08 0.39 4 0.81 0.85 0.22 0.66 0.60 0.05 0.39 Lake Monroe 1 0.92 0.59 0.31 0.74 0.19 0.65 0.93 0.70 0.93 2 0.94 0.39 0.31 0.91 0 0.69 0.77 0.86 0.69 3 0.93 0.60 0.58 0.81 0.19 0.75 0.92 0.47 0.70 4 0.89 0.30 0.38 0.09 0.42 0.63 0.72 0.67 0.67 49

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50 Figure 1. General locations of Lochloosa Lake, Lake Marian, and Lake Monroe in the state of Florida.

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51 Total Length Group (cm)Percent of FishLake MonroeLochloosa LakeLake Marian N = 124T = 6(c) N = 260T = 260102030(a) N = 296T = 220102030(b) N = 232T = 230102030(c) N = 210T = 20010203011131517192123252729313335(d) N = 189T = 4(a) N = 235T = 6(b) N = 219T = 411131517192123252729313335(d) N = 256T = 10(a) N = 296T = 13(b) N = 110T = 5(c) N = 77T = 411131517192123252729313335(d) Figure 2. Relative length frequencies of black crappie > 110 mm TL captured with otter trawls at Lakes Lochloosa, Marian, and Monroe for sampling periods (a) April, (b) June, (c) August, and (d) October of 2003. N is the total number of crappie represented in each graph, and T is the number of trawls used to collect the fish.

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Residuals (a)-100-50050100 (b)-100-50050100 (c)-100-50050100100150200250300350Predicted TL (mm) Figure 3. Residuals of the expected total length at age values from the observed total length at age values when using the respective von Bertalanffy growth models for Lakes (a) Lochloosa, (b) Marian, and (c) Monroe. 52

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0100200300400012345678Age Expected TL (mm) Lochloosa Marian Monroe Figure 4. Mean total length (TL) at age (yrs) of black crappie in Lakes Lochloosa, Marian, and Monroe using their respective von Bertalanffy growth model. 53

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Mean % Total Weight20022003 (a)0255075100 (b)0255075100 (c)0255075100 (d)0255075100AugustOctoberDecemberFebruaryAprilJuneAugustOctoberPeriod Lochloosa Lake Lake Marian Lake Monroe Figure 5. Mean percent of total diet weight of microcrustaceans (y axis) for black crappie at Lakes Lochloosa, Marian, and Monroe during sampling periods (x axis) for size classes (a) 1 (110-149 mm TL), (b) 2 (150-189 mm TL), (c) 3 (190-229 mm TL), and (d) 4 ( > 230 mm TL). 54

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Mean % Total Weight20022003 Size Class 10.0020.0040.0060.0080.00100.00AugustOctoberDecemberFebruaryAprilJuneAugustOctober Size Class 20.0020.0040.0060.0080.00100.00AugustOctoberDecemberFebruaryAprilJuneAugustOctober Size Class 30.0020.0040.0060.0080.00100.00AugustOctoberDecemberFebruaryAprilJuneAugustOctober Size Class 40.0020.0040.0060.0080.00100.00AugustOctoberDecemberFebruaryAprilJuneAugustOctoberPeriod Lochloosa Marian Monroe (a)0255075100 (b)0255075100 (c)0255075100 (d)0255075100AugustOctoberDecemberFebruaryAprilJuneAugustOctoberPeriod Lochloosa Lake Lake Marian Lake Monroe Figure 6. Mean percent of total diet weight of insects (y axis) for black crappie at Lakes Lochloosa, Marian, and Monroe during sampling periods (x axis) for size classes (a) 1 (110-149 mm TL), (b) 2 (150-189 mm TL), (c) 3 (190-229 mm TL), and (d) 4 ( > 230 mm TL). 55

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Mean % Total Weight20022003 Size Class 10.0020.0040.0060.0080.00100.00AugustOctoberDecemberFebruaryAprilJuneAugustOctober Size Class 20.0020.0040.0060.0080.00100.00AugustOctoberDecemberFebruaryAprilJuneAugustOctober Size Class 30.0020.0040.0060.0080.00100.00AugustOctoberDecemberFebruaryAprilJuneAugustOctober Size Class 40.0020.0040.0060.0080.00100.00AugustOctoberDecemberFebruaryAprilJuneAugustOctoberPeriod Lochloosa Marian Monroe (a)0255075100 (b)0255075100 (c)0255075100 (d)0255075100AugustOctoberDecemberFebruaryAprilJuneAugustOctoberPeriod Lochloosa Lake Lake Marian Lake Monroe Figure 7. Mean percent of total diet weight of macrocrustaceans (y axis) for black crappie at Lakes Lochloosa, Marian, and Monroe during sampling periods (x axis) for size classes (a) 1 (110-149 mm TL), (b) 2 (150-189 mm TL), (c) 3 (190-229 mm TL), and (d) 4 ( > 230 mm TL). 56

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Mean % Total Weight20022003 Size Class 10.0020.0040.0060.0080.00100.00AugustOctoberDecemberFebruaryAprilJuneAugustOctober Size Class 20.0020.0040.0060.0080.00100.00AugustOctoberDecemberFebruaryAprilJuneAugustOctober Size Class 30.0020.0040.0060.0080.00100.00AugustOctoberDecemberFebruaryAprilJuneAugustOctober Size Class 40.0020.0040.0060.0080.00100.00AugustOctoberDecemberFebruaryAprilJuneAugustOctoberPeriod Lochloosa Marian Monroe (a)0255075100 (b)0255075100 (c)0255075100 (d)0255075100AugustOctoberDecemberFebruaryAprilJuneAugustOctoberPeriod Lochloosa Lake Lake Marian Lake Monroe Figure 8. Mean percent of total diet weight of fish (y axis) for black crappie at Lakes Lochloosa, Marian, and Monroe during sampling periods (x axis) for size classes (a) 1 (110-149 mm TL), (b) 2 (150-189 mm TL), (c) 3 (190-229 mm TL), and (d) 4 ( > 230 mm TL). 57

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58 ight Figure 9. Mean percent total weight of (a) microcrustaceans, (b) insects, (c) macrocrustaceans, and (d) fish in the diets of black crappie of size classes 1 (110-149 mm TL), 2 (150-189 mm TL), 3 (190-229 mm TL), and 4 ( > 230 mm TL) from Lakes Lochloosa, Marian, and Monroe. % Total We (c)020406080 (d)0204060801234Size Class Lochloosa Lake Lake Marian Lake Monroe (a)020406080 (b)020406080

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TaxaLake MonroeLochloosa LakeManly's valuesLake Marian (a)0.00.20.40.60.81.0CiCaCeDiEpAm = 0.167 (b)0.00.20.40.60.81.0CiCaCeDiEpTrAmIsAc = 0.111 (a)CiCaCeDiEpAmAc = 0.143 (b)CiCaCeDiEpAmAc = 0.143 (a)CiCaCeDiMyEpTrAmIsAc = 0.10 (b)CiCaCeDiMyEpTrAmAc = 0.111 Size Class 1 Size Class 2 Size Class 3 Size Class 4 59 Figure 10. Mean Manly's values indicating selection of prey taxa by black crappie in size classes 1 (110-149 mm TL), 2 (150-189 mm TL), 3 (190-229 mm TL), and 4 ( > 230 mm TL) from Lakes Lochloosa, Marian, and Monroe during (a) December of 2002 and (b) February, (c) April, (d) June, (e) August, and (f) October of 2003. Taxa included in selectivity indices are Chironomidae larvae (Ci), Chaoboridae larvae (Ca), Ceratopogonidae larvae (Ce), Diptera pupae (Di), Mysidacea (My), Ephemeroptera larvae (Ep), Trichoptera larvae (Tr), Amphipoda (Am), Isopoda (Is), and Hydracarina (Ac). Taxa not found in stomachs or petite Ponars for a particular sampling period and/or lake were not included in that index. Trendline with value above it indicates level of selectivity. Values greater than, equal to, or less than trendline indicates selection, no preference, or avoidance of prey taxa, respectively.

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Lochloosa LakeLake MarianLake MonroeTaxaManly's values (d)0.00.20.40.60.81.0CiCaCeDiEpTrAm = 0.143 (e)0.00.20.40.60.81.0CiCaCeDiEpTrAm = 0.143 (d)CiCaCeDiEpTrAmAc = 0.125 (e)CiCaCeDiEpTrAmAc = 0.125 (f)CiCaCeDiEpTrAmAc = 0.125 (d)CiCaCeDiMyTrAmIs = 0.125 (e)Ci CaCeDiMyEpTrAmIsAc = 0.10 (f)0.00.20.40.60.81.0CiCaCeDiEpTrAc = 0.143 (f)CiCaCeDiMyEp Tr Am IsAc = 0.10 Size Class 1 Size Class 2 Size Class 3 Size Class 4 (c)0.00.20.40.60.81.0CiCaCeDiEpTrAm = 0.125 (c)CiCaCeDiEpTrAmAc = 0.125 (c)CiCaCeDiMyEpTrAmIs = 0.111 60 Figure 10. Continued.

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Chironomidae larvaeChaoboridae larvaeMean density (# m-2)Mean number in stomachsPeriod (a)0100002000030000010203040 (b)0100002000030000010203040 (c)0100002000030000DecFebAprilJuneAugOct010203040 (a)0100020003000020406080 (b)0100020003000020406080 (c)0100020003000DecFebAprilJuneAugOct020406080 1 Mean Density Size Class 1 Size Class 2 Size Class 3 Size Class 4 61 Figure 11. Mean Chironomidae larvae, Chaoboridae larvae, Diptera pupae, and Mysidacea densities collected with petite Ponars and mean numbers found in black crappie stomachs of size classes 1 (110-149 mm TL), 2 (150-189 mm TL), 3 (190-229 mm TL), and 4 ( > 230 mm TL) from Lakes (a) Lochloosa, (b) Marian, and (c) Monroe during sampling periods December (Dec) of 2002 and February (Feb), April, June, August (Aug) and October (Oct) of 2003. Mysidacea was not found with petite Ponars or in black crappie diets at Lakes Lochloosa and Marian.

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62 Mean number in stomachsMysidaceaMean density (# m-2)Diptera pupaePeriod (a)0204060800100200300400 (b)0204060800100200300400 (c)020406080DecFebAprilJuneAugOct0100200300400 010203040DecFebAprilJuneAugOct0125250(c) 1 Mean Density Size Class 1 Size Class 2 Size Class 3 Size Class 4 Figure 11. Continued.

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DISCUSSION The diet, prey availability, and population structure (i.e., abundance and size structure) differences among lakes likely contributed to the variation in population growth rates. Lochloosa Lake had the lowest abundance of black crappie based on the otter trawl mean CPUE data and the least proportion of large fish based on the length frequency data. Lake Marian had the highest abundance of all sizes of black crappie and the greatest proportion of black crappie > 190 mm TL. Lake Monroe had an intermediate abundance of black crappie, which obtained the largest size with Lochloosa Lake second and Lake Marian having the smallest length at age. Benthic prey availability and prey selection caused differences in the diet composition and ontogenetic diet shifts of black crappie among the three study lakes. Black crappie at all three systems possessed similar ontogenetic diet shifts of microcrustaceans and fish. In general, the %Wt values of microcrustaceans in stomachs decreased as black crappie increased in size and the %Wt values of fish in stomachs increased as black crappie increased in size. Diet shifts of this nature have previously been found in black crappie food habit studies (Reid 1949; Keast 1968). However, differences occurred in the intermediate prey categories (i.e., insects and macrocrustaceans) due to the additional prey resource and prey selection of Mysidacea (i.e., Americamysis almyra) by black crappie at Lake Monroe. This substantially influenced diet composition of black crappie at Lake Monroe where fish of all sizes consumed high quantities of macrocrustaceans up to size class 3, then shifted to fish as prey at size class 4. Conversely, at Lakes Lochloosa and Marian, black crappie did not have Mysidacea as a prey option and fish were highly selective of Diptera pupae. Thus, black crappie at Lakes Lochloosa and Marian consumed high quantities of insects up to size class 3, then shifted to fish as prey at size class 4. The availability and selection of a high energy Mysidacea prey by black crappie at Lake Monroe likely influenced the larger size at age attained at this system compared to Lakes 63

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Lochloosa and Marian. Previous studies have recognized Mysidacea as an important prey item of black crappie at other Florida lakes (Chable 1947; Huish 1957; Ager 1975; Schramm et al. 1985). Ager (1975) found Mysidacea to comprise 53% of the dietary items in black crappie stomachs examined from Lake Okeechobee, Florida. Examples of other fish species that utilize mysid shrimp as a prey item, when it is available in fresh and brackish water, include striped bass Morone saxatilis (Cooper et al. 1998), pikeperch Stizostedion lucioperca (Hansson et al. 1997), alewives Alosa pseudoharengus (Madenjian et al. 2003; Pothoven and Vanderploeg 2004), yellow perch (Pothoven et al. 2000), and smelt Osmerus eperlanus (Vinni et al. 2004). Other studies have attributed Mysidacea as an important dietary item that can influence growth rates. Madenjian et al. (2003) credited the larger size of the non-piscivorous alewife at Lake Michigan to the availability and utilization of the larger, more energetic prey (i.e., Mysidacea and Amphipoda) in comparison to smaller alewives at Lake Ontario where these items were not available. Vinni et al. (2004) suggested that slow growth of age-1 and age-2 smelt at a Finnish lake was most likely due to an inconsistent supply of larger invertebrates (i.e., Mysidacea and Chaoboridae) during the intermediate stage of a diet shift before piscivory. The availability of Mysidacea as an additional prey resource is also profitable when other prey resources are low. Huish (1957) found a lower number of Chironomidae larvae and pupae in black crappie stomachs at Lake George, Florida during July 1950 than in July 1949, which was replaced by the presence and volume of Mysidacea in the diets. Huish (1957) suggested that this was due to decreased abundance of Chironomidae larvae. This is similar to the tradeoff of utilized prey I found between Chironomidae larvae and Mysidacea in the diets of black crappie and their corresponding densities at Lake Monroe during April and June of 2003. 64

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The optimal foraging theory suggests that a consumer should maximize the net energy gain by selectively preying on the most beneficial items (MacArther and Pianka 1966; Emlen 1966). It takes into consideration prey densities, pursuit and capture costs, and energy return. A wide variety of fish diet studies have found selective predation of higher quality prey items, which maximized net energy returns (Mittelbach 1981; Galarowicz and Wahl 2005; Graeb et al. 2006). This in turn, can increase the growth of fish (Mittelbach 1983; Galarowicz and Wahl 2005). In caloric studies conducted by Cummins and Wuycheck (1971), the crustacean class Malacostraca, which includes Mysidacea, resulted in 1,029 calories per gram wet weight, whereas the insect order Diptera (e.g., Chironomidae, Chaoboridae, etc.) had only 613 calories per gram wet weight. Furthermore, Gardner et al. (1985) found Mysis relicta to have a higher mean lipid value than Chironomidae at Lake Michigan. These results suggest that Mysidacea is a more energetically beneficial prey item when compared to insects, which makes the selection of Mysidacea by black crappie at Lake Monroe over Diptera pupae profitable. Selective predation of more energy-rich prey items by crappie has been previously noted. Ball and Kilambi (1972) found that black crappie and white crappie fed on immature Chaoborus seven times more than the smaller cyclopoid copepod, although the copepods were more abundant in the water column. Pine and Allen (2001) and Dockendorf and Allen (2005) found that age-0 black crappie selected larger zooplankton taxa. Dockendorf and Allen (2005) associated size differences of age-0 black crappie among three Florida lakes with a higher consumption of large zooplankton. In an aquarium study, OBrien et al. (1989) observed that when large and small prey were both present, the large prey were usually pursued. By pursuing the larger prey rather than the smaller prey, they found that the net energy gained by white 65

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crappie was increased. This would improve the growth efficiency, which should improve their survival. Various factors can influence selective predation by fish including prey characteristics, such as size (Werner and Hall 1974; Mayer and Wahl 1997; Robichaud-Leblanc et al. 1997), behavior (Buskey 1994), availability (Sanyanga 1998; Galarowicz et al. 2006), and visibility (Li et al. 1985; Buskey 1994); and predator characteristics, such as size (Mayer and Wahl 1997; Robichaud-Leblanc et al. 1997) and morphology (Graeb et al. 2005). Previous examples of selective predation by crappies were related to prey size (Ball and Kilambi 1972; OBrien et al. 1989; Pine and Allen 2001; Dockendorf and Allen 2005). Measurements of individual Mysidacea and Diptera pupae found in black crappie diets and petite Ponar grabs at Lake Monroe were not made, and therefore it is unknown if prey size is a factor in the selectivity differences found at this system relative to Lakes Lochloosa and Marian. Size variation of these prey items could occur for several reasons (i.e., season, species, life stage), so it would be necessary to make individual measurements of available prey and consumed prey throughout sampling periods to determine if prey size (i.e., Mysidacea and Diptera pupae) is a factor in selection. While some specimens have been preserved in ethanol, this preservation treatment can cause significant biomass loss and size reduction (Howmiller 1972; Stanford 1973), and would not reflect the actual size and weight at the time of availability or consumption. Other differences (e.g., behavior, visibility, etc.) between Mysidacea and Diptera pupae may have also caused selectivity differences among systems. Many studies have concluded that higher densities and availability of quality benthic prey items were instrumental in growth of various fish species. Fox (1989) found a positive relationship between the growth of juvenile walleye with the density and size of available 66

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benthic prey (i.e., Chironomidae larvae) at experimental ponds. Similarly, Hayward and Margraf (1987) concluded that differences in availability of larger benthic prey at two basins of Lake Erie led to differences in the diets and growth of yellow perch in those basins. A low quality prey supply at the western basin of Lake Erie allowed smaller yellow perch to feed effectively, but the diets of larger yellow perch were inadequate, which caused slower growth. Contrarily, a high variety of larger benthic prey allowed all sizes of yellow perch to feed adequately at the central basin of Lake Erie, which allowed for higher growth rates (Hayward and Margraf 1987). In more recent years, Tyson and Knight (2001) attributed increased yellow perch growth at the western basin of Lake Erie to the increased availability and consumption of benthic prey. Lott et al. (1996) also attributed yellow perch populations with faster growth to the higher densities and availability of macroinvertebrates as prey. Comparisons among lakes indicated that black crappie growth at Lochloosa Lake was not limited by benthic prey resources within that system. Black crappie at Lochloosa Lake attained a larger maximum size (L ) in comparison to Lake Marian and reached their maximum size at a faster rate (k) than black crappie at Lakes Marian and Monroe. Mysidacea was not available to black crappie at either Lakes Lochloosa or Marian. Instead, black crappie at these systems utilized Diptera pupae, Chironomidae larvae, and Chaoboridae larvae at higher levels. Benthic macroinvertebrate densities did not differ significantly between lakes except for higher densities of Chaoboridae larvae at Lake Marian during two sampling periods. Thus, I was unable to explain the growth rate differences between Lakes Lochloosa and Marian through differences in benthic prey availability alone. Density dependent growth is commonly found in fish populations (Walters and Post 1993; Post et al. 1999; Boxrucker 2002; Buktenica et al. 2007). In general, increased densities of fish 67

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can lead to low food availability, increased competition, and reduced growth. Swingle and Swingle (1967) observed density dependent growth of crappies at ponds and large reservoirs in Alabama. Schramm et al. (1985) and Miller et al. (1990) observed density dependent growth of black crappie at Lake Okeechobee, Florida. The high abundance of black crappie based on catch rates at Lake Marian, might suggest that slower growth is a result of higher density. The fast growth of black crappie at Lochloosa Lake could result from low abundance of black crappie at this system. However, based on results I obtained from index of fullness comparisons between lakes, black crappie at Lakes Lochloosa and Marian were not feeding differently between lakes in terms of total consumption. Nor were their diet shifts different, which suggests that energetic intake was comparable between systems. However, high densities of black crappie at Lake Marian could increase competition and cause greater energy to be applied in the search and capture of prey items. This is particularly true when prey densities (i.e., benthic macroinvertebrates) are not different between systems because prey per capita would be lower. This would result in less net energy gained and reduced growth rates in the high density system (i.e., Lake Marian) in comparison to the low density system (i.e., Lochloosa Lake). Thus, density dependent growth is a potential factor in the growth variation of black crappie at Lakes Lochloosa and Marian. Many studies have found increased growth of various fish species exhibiting ontogenetic diet shifts after the onset of piscivory (Ellison 1984; Keast and Eadie 1985; Buijse and Houthuijzen 1992; Olson 1996; Madenjian et al. 1998; Vinni et al. 2004; Galarowicz and Wahl 2005). However, in this study, black crappie did not consume fish differently among lakes as they increased in size based on %Wt estimates. Therefore, initiation of fish as prey was not responsible for the growth differences of black crappie among systems. 68

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Results of the simplified Morisitas index were variable for different taxa, but indicated that benthic prey availability can influence consumption rates of prey items by black crappie. In use here, a high C H value for a benthic prey item indicates that consumption of that prey item by black crappie is proportionally similar to the density found in the environment throughout time. It does not necessarily mean that the prey item is being selected for. For example, Chironomidae had relatively high C H values for all size classes and lakes, but were not found to be a highly selective item because of their large densities relative to the other taxa included in the comparisons. In addition to the simplified Morisitas index, comparisons of benthic densities and diets (i.e., %Wt and mean number) among lakes also suggest that benthic prey availability can influence consumption rates of prey items by black crappie. Potential sources of error in the selectivity and similarity indices include inadequate habitat sampling, patchiness of prey, collection times of black crappie, and differential digestion rates of prey (Strauss 1979). The taxa included in these indices were chosen because they could be effectively sampled with a petite Ponar and would be readily available for black crappie consumption. Three taxa which could have exhibited biases were Chaoboridae larvae, Diptera pupae, and Mysidacea. Chaoboridae larvae and Mysidacea are known to have diel cycles of vertical migration in the water column, remaining close to the bottom during the day and moving up to feed at night (Pennak 1953; Cole 1994). Because I sampled with petite Ponars during the day, these taxa should have been readily available for collection. Also, the species of Mysidacea that was present in Lake Monroe, Americamysis almyra, appears not to have vertical migrations and remains close to the bottom during both day and night (Johnson and Allen 2005). The bulk of Diptera pupae found in this study (i.e., Chironomidae) are free swimming, but tend to remain at the bottom until time to emerge (Merritt et al. 1996; Coffman and Ferrington 1996). 69

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Prey patchiness is another source of error through density estimates and prey consumption. For example, two individual black crappie consumed over 1,000 Diptera pupae each in August 2003 at Lake Monroe, whereas the other black crappie in the same size class had relatively small numbers. Consequently, the similarity values for that size class of black crappie were low. Estimates of prey densities can have high variability due to prey patchiness, particularly when there is a low sample size. Collection times of fish for stomach analysis can impact diet results along with any index that uses diet as a variable when diel feeding patterns occur. For instance, if crappie feed at dusk and most fish are collected during morning and afternoon, stomach contents would not be representative of the true diet. This is particularly true when differential digestion rates of prey items occur. In this case, prey items with a higher rate of digestion would be underrepresented and vice versa (Strauss 1979). Past investigations have found black crappie to feed at various times of the day, including both day and night (Pearse 1918; Seaburg and Moyle 1964; Keast 1968; Ellison 1984). Differences in feeding times of crappies have been attributed to habits of their prey (Keast 1968; OBrien et al. 1984). All black crappie collections for this project were made during the day, primarily in the mid-morning and early-afternoon hours at Lakes Marian and Monroe. However, catch rates of black crappie at Lochloosa Lake were low, making it necessary to sample from early-morning to late-afternoon, to obtain a representative sample. Diel investigations of black crappie diets were not conducted for this project, therefore differences or similarities in diel feeding patterns of black crappie among systems are unknown. The increased consumption of fish in the diets of black crappie during the summer and fall months in this study is similar to previous studies (Dendy 1946; Reid 1949; Ball and Kilambi 1972). This is probably due to a higher availability of age-0 prey fish (i.e., shad, bluegill, etc.) 70

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after spawning periods. This trend was more distinguished in the smaller size classes, which had low %Wt values before YOY prey fish would have been available. The %Wt values of fish in the smaller-size black crappie diets also leveled off or decreased by October 2003, which could be caused by prey fish outgrowing the smaller black crappie and becoming unavailable for consumption. The occurrence of potential prey fish outgrowing their smaller predators is common (Keast 1977; Keast and Eadie 1985; Storck 1986; Frankiewicz et al. 1996). As a result, this may cause smaller black crappie to return to a less energetic diet of smaller prey items. This could explain the increase in microcrustaceans present in the diets during the winter period. The larger size classes had higher %Wt values of fish in their diets throughout the year, which was most likely a result of having the ability to consume the larger prey fish throughout the year. However, I did not obtain prey abundance estimates of fish, and therefore did not quantify how fish prey abundance and size was related to black crappie diets. When considering all sampling periods, empty stomachs made up a relatively low percentage of the total stomachs examined for each lake (all < 7 %) when compared to previous diet studies of black crappie in Florida (Chable 1947; Reid 1949; Huish 1957; Ager 1975). Previous studies all found empty stomachs to be > 14 % of the total stomachs examined. There were individual periods, which had percentages of empty stomachs that were similar to what previous studies found, particularly the August and October periods in Lake Monroe for 2002 and 2003. These results suggest that black crappie are both opportunistic and selective in their benthic macroinvertebrate feeding habits. Black crappie appeared to utilize various resources at a greater extent when their densities were up, but consistently selected for certain taxa within a lake throughout the study. Differences in diet shifts of black crappie among lakes existed 71

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because of an additional resource and selection for that resource in Lake Monroe. This, in turn, likely allowed Lake Monroe black crappie to obtain a larger size at age than black crappie at Lakes Lochloosa and Marian. Contrarily, diet shifts and total prey consumption by black crappie at Lakes Lochloosa and Marian were not different, although there were differences in growth between systems. This was probably a result of density dependence, where Lake Marian had a large population with slow growth and Lochloosa Lake had a small population with fast growth. 72

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MANAGEMENT IMPLICATIONS Stocking of black crappie at Florida water bodies is not a current management tool, but there is potential for its use in the future. A factor which can influence the stocking success of other fish is an adequate forage base, including zooplankton (Fielder 1992; Hoxmeier et al. 2004), macroinvertebrates, and prey fish (Axon and Whitehurst 1985; Stahl and Stein 1994; Donovan et al. 1997; Pierce et al. 2001). Each forage group could play an important role in the success of stocking programs, depending on the species, size, and diets of fish being stocked (Hoxmeier and Wahl 2002). The results of this study show that prey availability can influence the diet and growth of black crappie, and therefore future stocking programs of black crappie should consider the prey base before initiating a program. For example, Lake Monroe may have greater potential for stocking success of black crappie due to the additional prey taxa and fast growth of black crappie at this system. 73

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Buktenica, M. W., S. F. Girdner, G. L. Larson, and C. D. McIntire. 2007. Variability of kokanee and rainbow trout food habits, distribution, and population dynamics, in an ultraoligotrophic lake with no manipulative management. Hydrobiologia 574:235-264. Buskey, E. J. 1994. Factors affecting feeding selectivity of visual predators on the copepod Acartia tonsa: locomotion, visibility and escape responses. Hydrobiologia 292/293:447-453. Cerrato, R. M. 1990. Interpretable statistical tests for growth comparisons using parameters in the von Bertalanffy equation. Canadian Journal of Fisheries and Aquatic Sciences 47:1416-1426. Chable, A. C. 1947. A study of the food habits and ecological relationships of the sunfishes of northern Florida. Masters thesis. University of Florida, Gainesville, Florida. Chesson, J. 1978. Measuring preference in selective predation. Ecology 59:211-215. Coffman, W. P., and L. D. Ferrington, Jr. 1996 Chironomidae. Pages 635-754 in R. W. Merritt and K. W. Cummins, editors. An Introduction to the Aquatic Insects of North America. Kendall/Hunt Publishing Company, Dubuque, Iowa. Cole, G. A. 1994. Textbook of Limnology. C. V. Mosby Company, St. Louis, Missouri. Cooper, J. E., R. A. Rulifson, J. J. Isely, and S. E. Winslow. 1998. Food habits an growth of juvenile striped bass, Morone saxatilis, in Albemarie Sound, North Carolina. Estuaries 21:307-317. Crow, M. E. 1979. Multivariate statistical analysis of stomach contents. Pages 87-96 in C. A. Simenstad and S. J. Lipovsky, editors. Fish Food Habits Studies: Proceedings of the 1 st Pacific Northwest Technical Workshop. Washington Sea Grant publication, University of Washington, Seattle, Washington. Cummins, K. W., and J. C. Wuycheck. 1971. Caloric equivalents for investigations in ecological energetics. Mitteilungen Internationale Vereinigung fur Theoretische und Angewandte Limnologie 18:1-158. Dendy, J. S. 1946. Food of several species of fish, Norris Reservoir, Tennessee. Journal of the Tennessee Academy of Science 21:105-127. Dockendorf, K. J., and M. S. Allen. 2005. Age-0 black crappie abundance and size in relation to zooplankton density, stock abundance, and water clarity in three Florida lakes. Transactions of the American Fisheries Society 134:172-183. Donovan, N. S., R. A. Stein, and M. M. White. 1997. Enhancing Percid stocking success by understanding age-0 piscivore-prey interactions in reservoirs. Ecological Applications 7:1311-1329. 75

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Horn, H. S. 1966. Measurement of overlap in comparative ecological studies. The American Naturalist 100:419-424. Howmiller, R. P. 1971. A comparison of the effectiveness of Ekman and Ponar grabs. Transactions of the American Fisheries Society 100:560-564. Howmiller, R. P. 1972. Effects of preservatives on weights of some common macrobenthic invertebrates. Transactions of the American Fisheries Society101:743-746. Hoxmeier, R. J. H., and D. H. Wahl. 2002. Evaluation of supplemental stocking of largemouth bass across reservoirs: effects of predation, prey availability, and natural recruitment. Pages 639-647 in D. P. Phillip and M. S. Ridgway, editors. Black Bass: Ecology, Conservation, and Management. American Fisheries Society, Symposium 31, Bethesda, Maryland. Hoxmeier, R. J. H., D. H. Wahl, M. L. Hooe, and C. L. Pierce. 2004. Growth and survival of larval walleyes in response to prey availability. Transactions of the Amercian Fisheries Society 133:45-54. Hubert, W. A. 1996. Passive capture techniques. Pages 157-181 in B. R. Murphy and D. W. Willis, editors. Fisheries techniques. American Fisheries Society, Bethesda, Maryland. Hudson, P. L. 1970. Quantitative sampling with three benthic dredges. Transactions of the American Fisheries Society 99:603-607. Huish, M. T. 1953. Life history of the black crappie of Lake George, Florida. Transactions of the American Fisheries Society 83:176-193. Huish, M. T. 1957. Food habits of three centrarchidae in Lake George, Florida. Proceedings of the Annual Conference of the Southeastern Association of Game and Fish Commissioners 11:293-302. Hujik, R. W., E. J. Nagid, and J. B. Rowe. 2002. Annual report, black crappie stocking in Lochloosa Lake, 1 July 2001 to 30 June 2002. Florida Fish and Wildlife Conservation Commission, Tallahassee. Hyslop, E. J. 1980. Stomach contents analysis a review of methods and their application. Journal of Fish Biology 17:411-429. Int Panis, L., B. Goddeeris, and R. F. Verheyen. 1995. On the reliability of Ponar grab samples for the quantitative study of benthic invertebrates in ponds. Hydrobiologia 312:147-152. Johnson, W. S. and D. M. Allen. 2005. Zooplankton of Atlantic and Gulf Coasts: a guide to their identification and ecology. The Johns Hopkins University Press, Baltimore, Maryland. 78

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Timmons, T. J., W. L. Shelton, and W. D. Davies. 1980. Differential growth of largemouth bass in West Point Reservoir, Alabama-Georgia. Transactions of the American Fisheries Society 109:176-186. Tucker, W. H. 1972. Food habits, growth, and length-weight relationships of young-of-the-year black crappie and largemouth bass in ponds. Proceedings of the Annual Conference of the Southeastern Association of Game and Fish Commissioners 26:565-577. Tyson, J. T., and R. L. Knight. 2001. Response of yellow perch to changes in the benthic invertebrate community of western Lake Erie. Transactions of the American Fisheries Society 130:766-782. U.S. Department of the Interior, Fish and Wildlife Service and U.S. Department of Commerce, U.S. Census Bureau. 2001. National Survey of Fishing, Hunting, and Wildlife-Associated Recreation. Florida. Washington, D.C. Vinni, M., J. Lappalainen, T. Malinen, and H. Peltonen. 2004. Seasonal bottlenecks in diet shifts and growth of smelt in a large eutrophic lake. Journal of Fish Biology 64:567-579. Walters, C. J., and J. R. Post. 1993. Density-dependent growth and competitive asymmetries in size-structured fish populations: a theoretical model and recommendations for field experiments. Transactions of the American Fisheries Society 122:34-45. Werner, E. E., and D. J. Hall. 1974. Optimal foraging and the size selection of prey by the bluegill sunfish (Lepomis macrochirus). Ecology 55:1042-1052. Wicker, A. M., and W. E. Johnson. 1987. Relationships among fat content, condition factor, and first-year survival of Florida largemouth bass. Transactions of the American Fisheries Society 116:264-271. Zar, J. H. 1999. Biostatistical Analysis. Prentice Hall, Upper Saddle River, New Jersey. 83

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BIOGRAPHICAL SKETCH Travis Tuten is a second generation Floridian born in Orlando, FL on October 30, 1975. He graduated from Colonial High School in 1993 and received an Associate of Arts degree from Valencia Community College in April 1996. He started coursework at University of Florida in 1996 and graduated with a Bachelor of Science degree in wildlife ecology and conservation in December 1998. Work took him to South Florida in April 1999, where he stayed 3 years as a biological technician working in the Florida Everglades. He returned to Gainesville in January 2002 and began working on non-indigenous fish projects with the United States Geological Survey (USGS). He started coursework towards his Master of Science degree in August 2002 and was hired by the Florida Fish and Wildlife Conservation Commission (FWC) in November 2002. His masters research on black crappie Pomoxis nigromaculatus diets and benthic food availability was an opportunity to further his education while employed with FWC. After graduation, he plans to continue conducting fisheries research in the state of Florida. 84


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Title: Diet Composition and Growth Rates of Black Crappie Pomoxis nigromaculatus Relative to Benthic Food Availability at Three Florida Lakes
Physical Description: Mixed Material
Copyright Date: 2008

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DIET COMPOSITION AND GROWTH RATES OF BLACK CRAPPIE Pomoxis
nigromaculatus RELATIVE TO BENTHIC FOOD AVAILABILITY AT THREE
FLORIDA LAKES



















By

M. TRAVIS TUTEN


A THESIS PRESENTED TO THE GRADUATE SCHOOL
OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT
OF THE REQUIREMENTS FOR THE DEGREE OF
MASTER OF SCIENCE

UNIVERSITY OF FLORIDA

2007






































O 2007 M. Travis Tuten


































To my family, who are the meaning of life.









ACKNOWLEDGMENTS

I would like to thank Micheal S. Allen, Chuck E. Cichra, Marty M. Hale, and Gary L.

Warren for serving as members of my supervisory committee. The various help and knowledge

that each of them individually provided was instrumental and will be influential in my future.

I am especially appreciative of the long list of people who provided help in the field,

laboratory, and office including Holly Alred, Anne Cichra, Gina DelPizzo, Kevin Dockendorf,

Mike Duncan, Tracy Ferring, Darrie Hohlt, Cory Keller, Cara Miller, Eric Nagid, Summer

Pardo, Tracy Peters, Eric Porak, Marina Post, Tracey Smith, Andy Strickland, Will Strong,

Loanna Torrance, and David Ziesk. Without them, I would still have my eyes at a scope and be

wishing for the last sample. I would also like to send a special thanks to Howard Jelks and Daryl

Parkyn for their help and advice on data analysis.

Funding for this proj ect was provided by the Florida Fish and Wildlife Conservation

Commission. I am thankful to Jim Estes and Dick Krause for providing extra means to

accelerate this proj ect and also to Eric Nagid for going to bat for me to get more help.

The most important piece of this puzzle is my family. I am grateful to my Mom and Dad,

who provided the foundation of my life. It is comforting to know that I have supportive parents

who have always been there. Della is my "greatest catch". I am thankful for the way she puts up

with me and giving me an extra push every now and then. I look forward to our future together

raising Eli and any other little Tuten we may be blessed with.












TABLE OF CONTENTS


page

ACKNOWLEDGMENT S .........__... ......._. ...............4....


LIST OF TABLES ........._.__........_. ...............6....


LI ST OF FIGURE S .............. ...............7.....


AB S TRAC T ......_ ................. ............_........8


INTRODUCTION .............. ...............10....


M ETHOD S .............. ...............14....


Study Lakes ................ ...............14...
Black Crappie Collection............... ...............1
Proc e ss of F ish and Stom ach s ................ ...............15...........

Age Estimation ................. .... .. ..............1
Macroinvertebrate Collection and Processing ................. ...............17................
Data Analysis............... ... .. ... ..........1
Population Abundance and Size Structure .............. ...............18....
Age and Growth Comparisons .............. ...............19....
Diet Comparisons ................. ... ...............20
Macroinvertebrate Density Comparisons ................ ...............23........... ....
Ponar-Diet Comparisons .............. ...............24....


RE SULT S .............. ...............27....


DI SCUS SSION ................. ...............63.......... ......


MANAGEMENT IMPLICATIONS .............. ...............73....


LIST OF REFERENCES ................. ...............74........... ....


BIOGRAPHICAL SKETCH .............. ...............84....










LIST OF TABLES


Table page

1 Mean water quality parameters for Lakes Lochloosa, Marian, and Monroe. ....................37

2 List of types and common names of prey used to numerically and gravimetrically
describe black crappie diet contents. ............. ...............38.....

3 Four maj or prey categories used in the MANOVA procedure and the individual prey
items included in each category. .............. ...............39....

4 Otter trawl capture and collection data for black crappie at Lakes Lochloosa, Marian,
and Monroe during each sampling period. ............. ...............40.....

5 Linear, Gompertz, and von Bertalanffy growth functions of black crappie at Lakes
Lochloosa, Marian, and Monroe based on the collected total length at age data. .............43

6 Number of black crappie stomachs examined for diet contents, number of empty
stomachs observed, and number of stomachs with 100 % digested material in each of
the three study lakes............... ...............44.

7 Mean percent weight values of dominant prey types in the Insect and
Macrocrustacean prey categories found in black crappie diets at Lakes Lochloosa,
Marian, and Monroe............... ...............46.

8 Mean densities (number/m2) Of taxa collected with petite Ponars in each period at
Lakes Lochloosa, Marian, and Monroe. ............. ...............47.....

9 Simplified Morisita index values of similarity for various taxa comparing density
found with petite Ponars to the total number found in black crappie diets through all
sampling periods. ............. ...............49.....










LIST OF FIGURES


Figure page

1 General locations of Lochloosa Lake, Lake Marian, and Lake Monroe in the state of
Florida. .............. ...............50....

2 Relative length frequencies of black crappie > 1 10 mm TL captured with otter trawls
at Lakes Lochloosa, Marian, and Monroe. ............. ...............51.....

3 Residuals of the expected total length at age values from the observed total length at
age values when using von Bertalanffy growth models. ............. .....................5

4 Mean total length at age of black crappie at Lakes Lochloosa, Marian, and Monroe
using their respective von Bertalanffy growth model ................. ................. ........ 53

5 Mean percent of total diet weight of microcrustaceans for black crappie at Lakes
Lochloosa, Marian, and Monroe during sampling periods for all size classes. ................54

6 Mean percent of total diet weight of insects for black crappie at Lakes Lochloosa,
Marian, and Monroe during sampling periods for all size classes. ........._.._... ........._......55

7 Mean percent of total diet weight of macrocrustaceans for black crappie at Lakes
Lochloosa, Marian, and Monroe during sampling periods for all size classes. ................56

8 Mean percent of total diet weight of fish for black crappie at Lakes Lochloosa,
Marian, and Monroe during sampling periods for all size classes. ........._.._... ........._......57

9 Mean percent total weight of maj or prey types in the diets of black crappie for all
size classes at Lakes Lochloosa, Marian, and Monroe. .................. ................5

10 Mean Manly's a values indicating selection of prey taxa by black crappie in all size
classes at Lakes Lochloosa, Marian, and Monroe during all sampling periods. ...............59

11 Mean Chironomidae larvae, Chaoboridae larvae, Diptera pupae, and Mysidacea
densities collected with petite Ponars and mean numbers found in black crappie
stomachs for all size classes at Lakes Lochloosa, Marian, and Monroe during all
sampling periods. ............. ...............61.....









Abstract of Thesis Presented to the Graduate School
of the University of Florida in Partial Fulfillment of the
Requirements for the Degree of Master of Science

DIET COMPOSITION AND GROWTH RATES OF BLACK CRAPPIE Pontoxis
nigrontaculatus RELATIVE TO BENTHIC FOOD AVAILABILITY AT THREE FLORIDA
LAKES

By

M. Travis Tuten

May 2007

Chair: Chuck E. Cichra
Cochair: Micheal S. Allen
Major: Fisheries and Aquatic Sciences

Factors influencing black crappie growth are an important research need for management

of black crappie fisheries. I evaluated the diets and growth of black crappie in relation to benthic

food availability and population structures (e.g., abundance) among three Florida systems: Lakes

Lochloosa, Marian, and Monroe. The simplified Morisita index was used to measure similarity

of diet contents (i.e., mean numbers) relative to benthic macroinvertebrate densities throughout

sampling periods. Manly's a index of selectivity was used to measure selective predation by

black crappie for benthic prey taxa. Black crappie at Lake Monroe obtained the largest size at

age, whereas Lake Marian had the smallest size at age. Lake Marian had the highest abundances

of black crappie based on otter trawl mean catch per unit effort data and Lochloosa Lake had the

lowest abundance. Manly's a index of selectivity resulted in two major trends. Black crappie at

Lakes Lochloosa and Marian were consistently selective of Diptera pupae, whereas black crappie

at Lake Monroe were consistently selective of Mysidacea Anzericanyis alnzyra. Differences in

prey availability and prey selection were influential in producing differences in the diet

composition and ontogenetic diet shifts of black crappie among the three study lakes. Results

were variable for different taxa, but indicated that benthic prey availability can influence









consumption rates of prey items by black crappie, particularly for more utilized taxa. The diet,

prey availability, and black crappie population structure differences among lakes likely

contributed to the variation in population growth rates.









INTRODUCTION

Black crappie Pomoxis nigromaculatus support important recreational Eisheries in Florida

including 22% of the state' s freshwater anglers and more than 5.8 million days of annual Eishing

effort (U. S. Department of Interior 2001). Factors that influence growth and abundance of black

crappie are thus important to the management of black crappie fisheries. Understanding how

black crappie growth rates are related to diet composition and benthic food availability is an

important research need for management of black crappie fisheries.

The diets of both black crappie and white crappie P. annularis are well documented. In

Florida alone, food items found in black crappie diets have included crustacean zooplankton,

such as cladocera and copepoda; diptera larvae, pupae and adults, particularly Chironomidae and

Chaoboridae; Palaemonetes and Mysidopsis shrimp; and various fishes, especially shads

Dorosoma spp. (Chable 1947; Reid 1949; Huish 1957; Ager 1975). Keast (1968) and Hanson

and Quadri (1979) found that diets of black crappie did not vary greatly throughout their

distribution. Conversely, Mathur and Robbins (1971) suggested that differences in feeding

habits among populations of white crappie were due to differences in food availability at those

water bodies.

Ontogenetic diet shifts from zooplankton to aquatic insects to fish occur in many fishes

including Eurasian perch Perca fluviatilis (Hj elm et al. 2000), yellow perch Perca flavescens

(Keast 1977), walleye Sander vitreus (Galarowicz et al. 2006), largemouth bass M~icropterus

salmoides (Keast and Eadie 1985; Olson 1996; Garcia-Berthou 2002), and northern pike Esox

lucius (Frost 1954). Diet shifts occur as a result of morphological changes (i.e., larger gape

width), which allow fish to utilize larger food items (McCormick 1998; Hjelm et al. 2000). It is

optimal for individuals to select prey items that maximize the net energy gain, which typically

are the larger items available (Mittelbach 1981). Higher quality foods can produce faster growth









(Buij se and Houthuijzen 1992; Frankiewicz et al. 1996), which allows the transition to the next

larger prey item (Frankiewicz et al. 1996; Olson 1996), alters resource competition (Keast and

Eadie 1985), and allows piscivorous fish to maintain or obtain a size advantage over prey fish

(Timmons et al. 1980; Keast and Eadie 1985; Olson 1996). Olson (1996) found that largemouth

bass with faster growth rates in the invertebrate-feeding stage became piscivorous significantly

faster than fish with slower growth rates at the same stage. An increase in growth also influences

recruitment by limiting mortality (Post et al. 1998; Olson 1996) and reducing risk of predation

(Frankiewicz et al. 1996; Post et al. 1998). Applegate et al. (1967) attributed the growth rates of

juvenile largemouth bass at one Arkansas reservoir to be twice as fast as those at another

Arkansas reservoir because of greater availability and consumption of midge larvae between the

diet shift from zooplankton to fish. At one Florida lake, Wicker and Johnson (1987) found that

periods of high mortality of age-0 largemouth bass occurred directly after periods when low fish

prey: predator biomass ratios occurred.

Juvenile black crappie exhibit shifts from primarily zooplankton to a combination of

zooplankton and macroinvertebrates at about 65 to 100 mm TL (Reid 1949; Keast 1968; Tucker

1972; Pine and Allen 2001; Dockendorf and Allen 2005). Fish become a common prey item

when crappies Pomoxis spp. attain a TL of 140 to 200 mm (Keast 1968; Ellison 1984; O'Brien et

al. 1984; Schramm et. al. 1985; Muoneke et al. 1992; Mittelbach and Persson 1998). Crappies

will continue to feed on zooplankton when they are greater than 150 mm TL (Muoneke et al.

1992) and have been found to feed on fish when as small as 60 mm TL (Reid 1949; Huish 1957).

However, it is important for crappies to shift their diet to optimize growth and survival. For

example, Muoneke et al. (1992) credited the reduced growth of white crappie at an Oklahoma

reservoir to their inability to become piscivorous at 150 mm TL. Dockendorf and Allen (2005)









found larger age-0 black crappie at one Florida lake, which had a higher frequency of fish in

their diets, in comparison to two other Florida populations. Ellison (1984) found lower growth

and survival rates of black crappie feeding as insectivores and planktivores than for white

crappie that had switched to a fish diet at the same Nebraska lake, particularly after the crappie

reached 200 mm TL.

Seasonal and monthly trends of crappie diets have been analyzed in numerous studies

(Pearse 1918; Dendy 1946; Reid 1949; Ball and Kilambi 1972; Mathur 1972; Liao et al. 2002).

Fish become a more important, if not the most important, part of the crappie diet in the summer

and/or fall months. Ball and Kilambi (1972) found crappie diets to be 92% fish in the summer

months at an Arkansas reservoir. In the spring, fall, and winter seasons, fish were consumed to a

lesser degree, and benthic insects, annelids, and crustaceans increased in importance. Likewise,

Dendy (1946) found a high proportion of aquatic insects and zooplankton in adult black crappie

diets in the spring and early summer, but fish dominated the diets in the late summer and fall at a

Tennessee reservoir. Reid (1949) also found a Florida black crappie population to feed largely

on fish in the summer and fall. The foods consumed during the summer are considered the most

important on a yearly basis, because this is when much of the annual growth occurs and energy

requirements are the highest (Ball and Kilambi 1972; Ellison 1984). At Lake George, Florida,

Huish (1953) found that black crappie made most of their annual growth from April through

November.

Lochloosa Lake, Florida, had a successful black crappie fishery prior to 1992, when

fishing effort and harvest dropped significantly (Hujik et al. 2002). For five years, the fishery

showed no signs of improvement and consequently, the Florida Fish and Wildlife Conservation

Commission (FWC) stocked more than 500,000 advanced fingerling (100 mm 150 mm TL)









black crappie from 1997 to 2001. Hujik et al. (2002) found that angler effort and harvest were

30% and 85% lower, respectively, for the post-stocking period (1997-2002) when compared to

the pre-stocking period (1988-1996). Catch curve analysis estimated 93% total annual mortality

of black crappie > age-1 in 1999 and 71% in 2001 (Hujik et al. 2002). Although 71% total

annual mortality is comparable to the average of other crappie populations in the U.S. compiled

by Allen and Miranda (1995) and Allen et al. (1998), the 93% estimate is on the upper range of

those reported. Because exploitation was apparently low since stocking began, natural mortality

was suspected to be the primary component of total annual mortality. This led to the question of

whether food availability at Lochloosa Lake was limiting the growth and survival of black

crappie larger than 200 mm total length (TL), which is also the approximate age and length that

crappie are recruited into sport fisheries (Schramm et al. 1985; Larson et al. 1991; Miranda and

Dorr 2000). I compared diets and benthic food availability of black crappie at Lochloosa Lake

with that of two other Florida lakes, that supported successful black crappie fisheries.

I evaluated the diets of black cra pie > 1 10 mm TL at three Florida lakes in com arison to

the benthic macroinvertebrate availability within these lakes. My objectives were to (1) compare

differences in diets among size groups of black crappie within each lake, (2) compare differences

in diets across size groups among the three lakes, (3) relate diets to benthic food availability, and

(4) evaluate trends between diet composition and fish growth rates among the three lakes.









METHOD S

Study Lakes

Lakes Lochloosa, Marian, and Monroe were the study lakes for this research (Figure 1).

Lakes Lochloosa and Marian are hypereutrophic and Lake Monroe is eutrophic, according to

average chlorophyll a concentrations sampled between 1993 and 2002, as classified by Forsburg

and Ryding (1980; Table 1). These lakes were selected because of the differences in their black

crappie population characteristics. Lochloosa Lake is a 2,310-ha lake in eastern Alachua County

and the fishery characteristics were described above. Lake Marian is a 2,323-ha lake located in

southern Osceola County. It was listed as one of FWC's top-ten black crappie lakes of 2003 and

is known for producing high recreational catches of black crappie, although it is not known for

catches of large black crappie (Hale and Alred 2003). Lake Monroe is a 3,808-ha lake located in

Seminole and Volusia counties. It was also listed as one of FWC's 2003 top-ten black crappie

lakes (Hale and Alred 2003) and is known for producing large black crappie. There was a 304-

mm minimum length limit on the black crappie fishery at Lake Monroe from 1998 to 2005.

Black Crappie Collection

Otter trawls have frequently been used as a method for sampling black crappie at Florida

water bodies (Huish 1953; Ager 1975; Schramm et al. 1985; Allen et al. 1999; Pine 2000).

Huish (1957) used shrimp trawls to collect bluegill Leponsis nzacrochirus, reader sunfish

Leponsis naicrolophus, and black crappie at Lake George, Florida as early as 1950 because

commercial seines did not catch Hish < 152 mm TL effectively. Similarly, Allen et al. (1999)

found otter trawls to be preferred over trap nets for sampling black crappie due to a larger size

range of fish caught, reduced sampling effort required, precision of catch per effort, and reduced

sampling expenses.









Otter trawls (4.6 m mouth, 4.9 m long, 38.1 mm stretch mesh body, and 31.8 mm stretch

mesh bag) were used to collect black crappie from each lake during the study. Sample periods

included August, October, and December of 2002 and February, April, June, August, and

October of 2003. A minimum of three trawls were pulled at each lake during each period.

During each period, the first three or four trawls in Lakes Monroe and Marian were pulled at

separate fixed sites. Trawls pulled at Lochloosa Lake were scattered throughout the lake,

because Lochloosa Lake was sampled much more intensively than the other systems (below).

Time length of the trawls was adjusted based on catch. Black crappie were measured to the

nearest mm TL. I attempted to collect 10 fish in each of four size classes from Lakes Marian and

Monroe and 30 fish in each of four size classes from Lochloosa Lake during each sampling

period. The size classes include (1) 110 149, (2) 150 189, (3) 190 229, and (4) > 230 mm

TL. The fish collected for stomach analysis were immediately stored on ice to reduce the

likelihood of regurgitation (Doxtater 1963), and then taken to the laboratory. Fish that could not

be immediately processed at the laboratory were frozen for later analysis.

Processing of Fish and Stomachs

At the laboratory, each fish was measured to the nearest mm TL, weighed to the nearest

gram, and the sagittal otoliths were removed. The stomach and hindgut of each fish were

removed from the esophagus to the anal opening. The stomach was placed into a labeled jar with

10% buffered formalin acetate for preservation. Formalin was eventually replaced by 95%

ethanol, prior to stomach content analysis.

A dissecting microscope was used when sorting through the contents of the stomachs.

Individual food items were categorized (Table 2) and counted for each taxonomic group. When

contents were partially digested, countable parts such as eyes and head capsules were counted to

obtain consumption estimates of those items. For example, two diptera pupae eyes made up one









individual. All remaining unidentifiable contents were placed together and categorized as

unidentified digested material. Each category was wet weighed to the nearest 10-4 g

Stomachs and hindguts, that were completely full of small digested parts (e.g., Diptera

eyes), were subsampled to reduce sampling time. All larger items (e.g., fish, Palaemonetes, etc.)

were separated from the bulk of the contents, identified, counted, and weighed. The remaining

diet contents were stirred and visually divided into quarter sections, using one section as the

subsample. The contents of the subsample were categorized, counted, and weighed. The

remaining portion of the sample was placed together and wet weighed to the nearest 10-4 g

Results were used to extrapolate the remainder of the sample.

Age Estimation

Numerous studies have validated the use of otoliths for accurate age assessments for

crappies (Schramm and Doerzbacher 1982; Hammers and Miranda 1991; Ross et al. 2005).

Whole views of otoliths were read for aging. If three or more rings were found, one otolith from

each fish was sectioned transversely from the ventral to dorsal gradient using a South Bay

Technology, Inc. low-speed diamond-wheel saw. Two sections, 0.5 mm wide, were cut from

each sectioned otolith. The sections were mounted on a labeled glass slide using Thermo

Shandon Synthetic Mountant with the inner-nucleus side facing up. Two independent readers

aged each fish using a dissecting microscope. The age-class of the fish was equal to the number

of rings if the collection date was in the latter half of the year. However, the age-class of a fish,

collected in the first half of the year, was equal to the number of rings if a new ring had recently

formed at the margin, or the number of rings plus one if a new ring had not yet formed at the

margin. Any disagreement in age-class between readers was reexamined, and if conflict

remained, a third reader was used. If no agreement could be reached with a third reader, that fish

was not used in the analyses.









Based on an observation of peak hatch dates of black crappie at the north Florida Lake

Wauberg, between mid-March and mid-April (Pine and Allen 2001), the hatch date of all fish in

this study was set at March 1st. A March 1st hatch date could act as a midpoint for the possible

earlier spawning periods of black crappie in the more southern lakes of Marian and Monroe and

the later spawning period of the north Florida Lochloosa Lake, which is latitudinally equivalent

to Lake Wauberg. An age of each fish was then set based on the proportion of the year that

occurred between March 1st and the collection date.

Macroinvertebrate Collection and Processing

Benthic macroinvertebrates were sampled at eight fixed sites in each lake using a petite

Ponar during each sampling period from December 2002 to October 2003. The sites were

selected based on substrate types and locations that corresponded with the trawl sites. The

contents of each sample were sieved through a 300-um mesh bucket and preserved in a labeled

jar with 95% denatured ethanol.

The petite Ponar (15.24 cm long and 15.24 cm wide) is a smaller version of the Ponar grab

designed by Powers and Robertson (1967). Ponars have been compared with other forms of

benthic samplers (Flannagan 1970; Hudson 1970; Howmiller 1971; Elliott and Drake 1981) and

across a variety of substrate types (Nalepa et al. 1988; Int Panis et al. 1995). The reliability of

the various samplers for adequate assessment of benthic community structure and abundance

depends on the sediment type (Flannagan 1970; Hudson 1970; Howmiller 1971; Elliott and

Drake 1981; Int Paris et al. 1995). In studies where three or more grabs were compared, the

Ponar has been found to be the most adequate benthic sampler among a range of substrate types

(Flannagan 1970; Hudson 1970; Elliot and Drake 1981).

A dissecting microscope was used when sorting through the samples. If the contents

included a large quantity of sand, a sugar solution flotation procedure described by Anderson










(1959) was used to reduce processing time. If the content of a Ponar was large, a fixed fraction

of the sample was processed. Contents were poured into a pan and stirred to form a

homogeneous sample and weighed. A proportion of the sample based on weight, was removed

from the pan and used as a subsample. Proportions used as subsamples included 0.50, 0.25 and

0.125, depending on the total sample volume. Macroinvertebrates contained in the subsample

were removed, identified taxonomically, and counted. Subsample data were used to estimate

total sample contents.

Data Analysis

Population Abundance and Size Structure

Mean catch per unit of effort (CPUE) values were used as an index to compare crappie

population relative abundance among the three lakes. Black crappie were classified into four

size groups (Size classes 2, 3, 4, and all fish) and mean CPUE values were calculated for each

lake and sampling period. A one-way ANOVA was used to compare mean log transformed

CPUE values among lakes for each group. Values of CPUE were log (X + 1) transformed to

improve the homogeneity of variances. The least squares means (LSMEANS) procedure was

used to determine differences between lakes when ANOVAs were significant (SAS Institute

1997). I assumed that mean CPUE values were proportional to the population densities (Hubert

1996).

Size structure of black cra pie > 1 10 mm TL, ca tured with otter trawls at each of the

three lakes, was expressed with a length frequency histogram for the last four sampling periods.

A chi-square test was used to determine if the proportion of black crappie among the four size

classes was homogeneous among lakes.










Age and Growth Comparisons

Ages of black crappie, collected from the three lakes, were used to make inferences about

the age structure of black crappie at each lake. Fish ages and total lengths were used to fit linear,

von Bertalanffy (VBGM) and Gompertz growth models for each lake. Residuals of the observed

versus predicted total lengths were plotted against the predicted values to evaluate the fit of the

three models for each lake. A variance ratio test was used to assess differences in the models

and choose the best-fit model for the data in the form of

M~SE
1 df 1
M~SE


where M~SE1 and M~SE2 are the mean squared errors obtained by using separate growth models

for the same lake, with degrees of freedom dfi and df2, TOSpectively. The larger M~SE was used

as the numerator and F was compared to an F-statistic at P = 0.05. A significant result meant the

model used to receive M~SE2 had a better fit to the data. After comparisons among all three

models were made, the one that best fit the data was used to estimate mean TL at age for each

lake.

The likelihood ratio test described by Kimura (1980) and Haddon (2001) was used to

compare growth curves among the three lakes using the VBGM

L, = L, ji-k[t-to1

where Lt is the mean length at age t, L, is the asymptotic maximum length, k is the growth rate

coefficient determining how quickly La, is obtained, and to is the hypothetical age when length is

equal to zero. The likelihood ratio test compares two or more non-linear equations by first

treating them as separate populations and then combining all observations as if they were from

the same population to make a new growth curve with new values for parameters k, to and Lb7.










Cerrato (1990) suggested using the likelihood ratio test over three other tests when comparing

VBGMs because of more accurate and reliable results. This test uses a chi-square statistic to see

if the combined curve residual sum of squares is significantly different from the sum of the

residual sum of squares for each model separately as

2 HS,RS



where k is the degrees of freedom (equal to the number of parameters fixed), N is the total

number of observations used, RRSm is the total residual sum of squares derived from fitting the

curves together, and RRSo is the total residual sum of squares derived from fitting all curves

separately. This analysis tested the hypothesis that the quality of fit was not significantly

different for a combined model versus separate models. To test the hypotheses that parameters

(i.e., L, and k) of the growth curves were different, I fitted the VBGM for each lake using only

the value of the parameter in question, obtained from the combined equation. A chi-square

statistic was calculated again for each hypothesis (L, values are different, etc.) where RRS, is

the total residual sum of squares derived from fitting the curves with one of the parameter

constraints and RRSo is the same total residual sum of squares derived from fitting all curves

separately with no constraints. Likelihood ratio tests were then used to make pair-wise

comparisons among the three lakes using the same procedures as above.

Diet Comparisons

Mean percent weights of prey categories were used to compare diet compositions of black

crappie. Percent weights were calculated as

Wt, x 100
%Wt,
SWt,










where Wt, is the weight of category i found in a stomach and Wt, is the total weight of all

categories found in that stomach. Empty stomachs and stomachs which contained nothing but

unidentified digested material were not included in the analysis for %Wt~ Unidentifiable digested

material was not included for the summation of Wt,, because it would distort the description of

the identifiable prey categories. Weights of partially digested items were not projected into

whole weights for two reasons. First, this would require substantial extrapolation. Second,

individual species or life stages within a particular prey category (e.g., Chironomidae larvae)

might be far different in size. Thus, predicted weights would not be accurate without further

identification or classification. Percent composition by weight of dietary items provides an idea

of the relative importance of various food types to the nutrition of fish (Bowen 1996). However,

Liao et al. (2001) found percent weight indices to overemphasize the importance of larger prey

taxa.

Diet compositions of black crappie were compared using multivariate analysis of variance

(MANOVA). Crow (1979) suggested the use of a MANOVA for diet comparisons when it was

desirable to test for differences in more than one prey species because it simultaneously

evaluates multiple prey categories, whereas a series of univariate ANOVAs on separate prey

variables may not reveal among-group differences. Individual %Wts of each category were

arcsine-transformed to normalize the data (Kleinbaum et al. 1998; Zar 1999). The arcsine-

transformed %Wts of prey categories were pooled into four maj or categories (Table 3) based on

taxonomy, size, and previous published Eindings about shifts in crappie diets. Mean arcsine-

transformed %Wts of the major categories were then calculated for each group. A three-way

MANOVA was used to evaluate if mean arcsine-transformed percent composition by weight of

the four major prey categories in the stomach contents varied with lake, period, and size class. A









significant interaction of the treatments lead to univariate F tests by analysis of variance

(ANOVA), to expose which prey categories were responsible for the interaction. Significant

interactions of the ANOVAs were explained graphically and by comparisons of the treatment

means using the LSMEANS procedure adjusted for the Tukey-Kramer multiple comparison test

(SAS Institute 1997).

To evaluate diet shifts with fish size among the three lakes, the %Wt data for all periods

were pooled for each size class at each lake. Comparisons of ontogenetic diet shifts were made

by two-way ANOVAs, using the mean arcsine-transformed values for %Wt of the maj or diet

categories as the dependent variable, with lake, size class, and the interaction of these variables

as factors. The LSMEANS procedure adjusted for Tukey-Kramer was used to separate the

means if the ANOVA was significant (SAS Institute 1997).

I used an index of stomach fullness to evaluate total prey weight standardized for fish size

among lakes with the equation

Tota~lStomachCon~ten~~tWetieght
zTotaFishStan~dddd~~~ddddard~ etWeightl, j V~

where i is an individual observation in a set of Ntotal fish. The total stomach content wet weight

included all material found in a stomach. An index of fullness is a useful measurement of diet

because it is relative to fish size (Hyslop 1980). Standard wet weights based on individual total

lengths were used in the IF equation because of differences of the length-weight relationships

among the three lakes. Standard weights were taken from a standard weight equation by using

the logarithmic transformations of the pooled length-weight data, in the form

log,,o(Wt) = a' +b -log,,o(TL)










where Wt is weight, TL is total length, a'is the y-axis intercept, and b is the slope of the

equation. Because the sample sizes of length-weight data were not equal among the three lakes,

the sample size for each lake in the pooled data was limited to the number of observations in the

smallest sample by randomly selecting data from the lakes with larger samples. This procedure

provided a length-weight relationship that was weighted equally for all lakes. The standard

weight equation was

logo (Wt) = -5.458 + 3.246 logo (TL).

Average total stomach content weights were then compared with one-way and two-way

ANOVAs using mean log-transformed IF values as the dependent variable and lake, size class,

and the interaction as factors. The individual IF observations were log (X+ 1) transformed to

homogenize the variances. The LSMEANS procedure adjusted for the Tukey-Kramer multiple

comparison test (SAS Institute 1997) was used to compare mean IF values between lakes, size

classes, and lakes for each size class.

Macroinvertebrate Density Comparisons

Estimated densities of the macroinvertebrate taxa used in selectivity and similarity indices

were compared among lakes by one of two methods. Chironomidae larvae densities were log (X

+ 1) transformed and ANOVAs were used for each sample period using lakes as the treatments

and the log-transformed Chironomidae larvae densities as the variables. If a significant

difference was found, the LSMEANS procedure adjusted for Tukey's multiple comparison test

(SAS Institute 1997) was used to compare values between lakes to determine the differencess.

Comparisons among lake mean densities of the other macroinvertebrate taxa were made with a

Kruskal-Wallis test because of the non-normal structure of the data, even after transformations

were conducted. If significant differences were found, nonparametric multiple comparisons for









data with tied ranks (i.e., Dunn test) were made to locate where differences occurred (Zar 1999).

Mysidacea and Isopoda (i.e., Suborder Anthuridea) were not included in this analysis because

they were only found at Lake Monroe.

Ponar-Diet Comparisons

Between-lake comparisons of mean %Wt, mean number, and/or occurrence of prey taxa in

black crappie diets were used to express how density differences of macroinvertebrate taxa

between lakes could influence black crappie diets. Mean number of prey items was calculated as

N =No,


where No, is the total number of prey taxa i found in stomachs from a group of n total fish.

Occurrence was considered as presence of a prey item in black crappie diets.

Selective feeding of black crappie on benthic macroinvertebrates at each lake was

measured using Manly's a index of preference for each size class in six sampling periods. The

sampling periods included December of 2002 and February, April, June, August, and October of

2003. Manly et al. (1972) originally developed the index, which was later refined by Chesson

(1978). Manly's a estimates were calculated for individual black crappie as



rl





where a, is Manly's a (preference index) for prey type i, r, and r, is the proportion of prey type i

and j in the diet (number of individuals), n, and n, is the proportion of prey type i and j in the

environment (petite Ponar density), and j is an individual prey type out of m possible prey types.

Mean Manly's a estimates were calculated for each size class in each sampling period by














where a, is one observation out of a total of K observations made for that group. Inferences of


prey selection were made using a, = ~Ias an indication level where values greater than, equal

to, and less than a, indicate preference, no selection, and avoidance of that prey item,

respectively. Taxa used in Manly's a indices include Chironomidae larvae, Chaoboridae larvae,

Ceratopogonidae larvae, Diptera pupae, Ephemeroptera larvae, Trichoptera larvae, Amphipoda,

Isopoda, Hydracarina, and Mysidacea. These taxa were chosen because they were represented in

both the benthic grabs and black crappie diets. These taxa could also be effectively sampled

with the benthic grabs and would be available for black crappie consumption. Individual taxa

were not included in Manly's a estimates for periods or lakes when they were not observed in the

benthic grabs or diets. Consumption of a particular resource is considered selective when the

relative proportion of that resource in the diet is greater than the relative proportion available in

the environment (Chesson 1978).

The simplified Morisita index of similarity was used to measure similarity of diet contents

(i.e., mean numbers) relative to benthic densities for individual taxa throughout sampling periods

for each lake. Taxa and sampling periods included in similarity indices were the same used in

the selectivity indices. Horn (1966) suggested this version to ignore cases where negative

numbers would appear in Morisita' s original function. The simplified Morisita index is in the

form of


CH 1X, /N + Ik N N









where CH is the simplified Morisita index of similarity, X, and X~k are the numbers of individuals

from sampling period i in sample j and sample k, N, is the total number of individuals in sample

j, Nk is the total number of individuals in sample k, j represents diets, and k represents petite

Ponars. Values of the index range from 0 (no similarity) to 1 (complete similarity).









RESULTS

Catch rates of black crappie with otter trawls varied widely among lakes (Table 4). One-

way ANOVAs resulted in significant differences of mean log-transformed CPUE values among

lakes for each group (all P < 0.0029). Lake Marian had the highest CPUE value for all groups of

black crappie (LSMEANS procedure; all P < 0.0001) and required the least amount of effort

(total trawls = 37; total minutes = 108) to collect the desired number of individuals for diet

analyses. Individual tow times of each trawl at Lake Marian were reduced because of the

extremely high catch rates. Mean CPUE values did not differ significantly for size classes 2

(P = 0.3453) and 3 (P = 0.6457) black crappie between Lakes Lochloosa and Monroe, but

Lochloosa Lake had the lowest mean CPUE for size class 4 (P < 0.0001) and all black crappie

(P = 0.0119). Thus, Lochloosa Lake required the greatest amount of effort (total trawls = 186;

total minutes = 1080) to collect enough specimens for diet analysis.

Length frequency distributions also differed among the three sampling lakes (Figure 2).

Chi square tests between lakes and size classes were significant for each period tested

(all P < 0.0001), indicating that black crappie at Lakes Lochloosa and Monroe had higher

proportions in size class 1 compared to Lake Marian. Lake Marian consistently had a higher

proportion of black crappie in size class 3 compared to Lakes Lochloosa and Monroe (Figure 2).

Lochloosa Lake generally had the lowest proportion of black crappie in the largest size class,

whereas Lakes Marian and Monroe were comparable (Figure 2).

A total of 1,351 black crappie were used for age and growth comparisons. Lakes

Lochloosa, Marian, and Monroe had sample sizes of 734, 317, and 300, respectively. Lochloosa

Lake had the greatest percent of black crappie collected < age 1 (75.1 %) and the lowest percent

of black crappie > age 2, with only one observation as high as age 6. Lake Marian had both the









oldest individual black crappie observed (age 1 1) and the highest percentage of black crappie

collected > age 2 (56.4 %). The oldest black crappie collected at Lake Monroe were age 8.

Linear, Gompertz and VBGM growth models (Table 5) were developed using the age at

length data for the three lakes. Variance ratio tests resulted in significantly lower M~SE values

obtained from the Gompertz growth model and VBGM when compared to the linear growth

model for all three lakes (all P < 0.0005). There was no significant difference found in the

variance between the Gompertz growth model and VBGM for any of the study lakes

(all P > 0.39). The residual plots of the VBGMs expected versus observed TL at age values

(Figure 3) were uniformly distributed, which supports the use of this function. The VBGMs

were chosen to estimate mean TL at age of black crappie for each lake and were used to plot the

expected growth curves (Figure 4).

The likelihood ratio test used to compare the VBGMs among the three lakes was

significant (X2 = 212.3; df = 3; P < 0.0001), indicating that at least one curve was significantly

different from at least one of the other two curves. Tests of the individual parameters LCZ and k

of the three growth models were also significant at P < 0.05, indicating that the parameter being

tested was significantly different in at least one of the growth models. Pairwise comparisons

between the three growth curves showed that each model was significantly different from the

other at P < 0.0001. Lake Monroe had a significantly higher LCZ than Lochloosa Lake

(X2 = 5.21; df = 1; P = 0.0357), which had a significantly higher LCZ than Lake Marian

(X = 4.41; df = 1; P = 0.0225). The estimate of k was higher at Lochloosa Lake than for Lakes

Marian (X2 = 7.73; df = 1; P = 0.0054) and Monroe (X2 = 6.48; df = 1; P = 0.0109), but k did not

differ significantly between the latter two lakes (X2 = 0. 18; df = 1; P = 0.6695). Thus, growth









rates varied among populations with Lake Monroe having the largest mean TL-at-age, Lochloosa

intermediate, and Lake Marian the lowest size-at-age.

A total of 1,047 black crappie stomachs were examined for diet contents (Table 6). Lakes

Lochloosa, Marian, and Monroe had sample sizes of 431i, 3 17, and 299, respectively. There

were 48 (4.6 %) empty stomachs and 49 (4.7 %) stomachs that contained nothing but

unidentifiable digested material, which were not included in the mean %Wt analysis.

Diets varied widely among lakes, size groups, and periods. The arcsine-transformed mean

%Wt of maj or prey categories in black crappie diets was significantly different due to the lake,

size class, and period interaction (MANOVA, Wilk's Lambda: Fl64, 3399 = 2.45, P < 0.0001).

Univariate ANOVAs of the four maj or prey categories revealed significant three-way

interactions for microcrustaceans (F41, 855 = 4.06, P < 0.0001), insects (F41, 855 = 2.29,

P < 0.0001), macrocrustaceans (F41, 855 = 1.55, P = 0.0157), and fish (F41, 855 = 2.99, P < 0.0001).

Thus, all of the maj or prey categories were responsible for the significant three-way interaction

found in the MANOVA (Figures 5-8), which caused inconsistent differences for the importance

of the major prey categories throughout the sampling periods, lakes, and size classes. For

example, the mean arcsine-transformed % Wt value of microcrustaceans of size class 1 black

crappie diets collected from Lochloosa Lake during October 2003 was higher than Lake Marian

(Tukey-Kramer test; P = 0.0094), whereas Lake Monroe was not significantly different from

Lochloosa Lake (P = 0.0631) or Lake Marian (P = 1.000). During this same sampling period,

there was no significant difference of the mean arsine-transformed % Wt values of

microcrustaceans between any of the lakes for size class 4 fish (all P = 1.000). When

considering size class 1 in February 2003, the mean arcsine-transformed %Wt value of

Lochloosa Lake was significantly smaller than both Lake Marian (P < 0.0001) and Lake Monroe










(P < 0.0001), whereas there was no difference between Lake Marian and Lake Monroe

(P = 0.9999). Thus, the diet composition expressed as mean %Wt for all the major prey

categories (i.e., microcrustaceans, insects, macrocrustaceans, and fish) exhibited inconsistent

differences among periods, size classes, and lakes.

Two seasonal trends of maj or diet categories were evident in black crappie diets at all three

study lakes (Figures 5-8). Microcrustaceans were a more important component of the diets

during the winter (December and February) and were least important during the summer (June

and August), with spring (April) and fall (October) varying depending on the lake and size class

(Figure 5). No seasonal trends among lakes were evident in the mean % Wt values obtained for

insects and macrocrustaceans in black crappie diets because of high variation of those values

among the periods, size groups, and lakes (Figures 6 and 7). Fish prey generally increased in

black crappie diets from the spring to the fall, whereas it was less important during the winter

(Figure 8). This was more noticeable in the smaller size classes of Esh, which had lower mean

%Wt values of Eish throughout the seasons than the larger size classes.

Ontogenetic diet shifts of black crappie were evident at each lake (Figure 9). In general,

mean %Wt values of microcrustaceans decreased and fish increased as crappie increased in size

in each lake. There was no lake-size class interaction for mean arcsine-transformed % Wt values

for microcrustaceans (ANOVA: F6, 938 = 1.05, P = 0.3891) or fish (F6, 938 = 0.20, P = 0.9762),

which is supported by the parallelism present among lake values through all size classes

(Figure 9). However, trends in the values for insects and macrocrustaceans were different among

lakes as black crappie increased in size. A significant lake-size class interaction was found for

the insect (F6, 938 = 2.19, P = 0.0419) and macrocrustacean (F6, 938 = 5.67, P < 0.0001) categories,

which was due to the lack of parallelism across lakes and size classes, particularly for









macrocrustaceans (Figure 9). Insect values obtained in size class 4 black crappie from

Lochloosa Lake were significantly lower than in size classes 1, 2, and 3 (Tukey-Kramer test,

all P < 0.003) and insect values in size class 4 black crappie from Lake Marian were significantly

lower than those in size classes 1 and 3 (all P < 0.05). However, there were no significant

differences between any size classes in the insect values from Lake Monroe (all P > 0.05). Lake

Monroe macrocrustacean values were significantly lower for size class 4 than size classes 1, 2,

and 3 (all P < 0.0005), whereas there were no differences in macrocrustacean values found

between any of the size classes for Lochloosa Lake or Lake Marian (all P > 0.05). When

comparing insect and macrocrustacean values between lakes for individual size groups,

Lochloosa Lake and Lake Marian had no significant differences (all P > 0.05). When compared

to Lake Monroe, these two lakes had significantly higher values of insects (all P < 0.01) for all

size classes except size class 4 and significantly lower values of macrocrustaceans

(all P < 0.0001) for every size class. Hence, differences in ontogenetic diet shifts of black

crappie between lakes were due to the intermediate sized prey categories (insects and

macrocrustaceans) rather than microcrustaceans or fish.

There were four prey types that made up the maj ority of the %Wt values of the insect and

macrocrustacean prey categories (Table 7). These included Chironomidae larvae, Chaoboridae

larvae, Diptera pupae, and Mysidacea. Chironomidae larvae was a highly consumed prey type

by black crappie in size classes 1, 2, and 3 among all systems. However, there were differences

in the %Wt values of Chaoboridae larvae, Diptera pupae, and Mysidacea among lakes. While

black crappie at Lochloosa Lake preyed highly upon Diptera pupae and black crappie at Lake

Marian preyed highly upon Diptera pupae and Chaoboridae larvae, these two prey types were not

highly utilized by black crappie at Lake Monroe. This resulted in higher %Wt values of the










insect category at Lakes Lochloosa and Marian relative to Lake Monroe. Black crappie at Lake

Monroe instead utilized the additional resource of Mysidacea (i.e., Americamyis almyra) as a

prey item, which caused the macrocrustacean category %Wt values to be much larger than what

was found in the other two systems. Diet shifts of the insect and macrocrustacean prey

categories occurred when the %Wt values were consistently higher throughout size classes within

a system. Therefore, differences in the utilization of Chaoboridae larvae, Diptera pupae, and

Mysidacea by black crappie among systems led to the differences in ontogenetic diets shifts

among systems.

There was not a significant lake-size class interaction found for the mean log (X+ 1)-

transformed total stomach content IF values (ANOVA; F6, 935 = 1.36, P = 0.2293). Tukey-

Kramer multi le com arison tests resulted in no si nificant differences tall P >0.05) found

between lakes for any size class, implying that total consumption expressed as a function of fish

weight was similar across all lakes for each size class. The main effects showed significant

differences of the IF values for both lakes (F2, 935 = 5.87, P = 0.0029) and size classes

(F3, 935 = 7.63, P < 0.0001). Tukey-Kramer multiple comparison tests resulted in greater IF

values at Lakes Lochloosa and Marian compared with Lake Monroe (both P < 0.008), whereas

the prior two lake' s IF values were not significantly different from each other (P = 0.9797). Size

class 1 black crappie IF values were greater when compared to size classes 3 (P = 0.0001) and 4

(P = 0.0006), and greater than size class 2 IF values by a marginal significance (P = 0.0579).

There were no differences found in the IF values among size classes 2, 3, and 4 (all P > 0.30).

Thus, black crappie at Lakes Lochloosa and Marian consumed a greater amount (i.e., weight) of

total prey when expressed as a function of fish weight then black crappie at Lake Monroe. Also,









size class 1 black crappie had larger diets in proportion to fish weight compared to larger size

classes of black crappie.

Differences in densities of benthic macroinvertebrates among lakes were significant for

four taxa including Chironomidae larvae, Chaoboridae larvae, Amphipoda, and Hydracarina.

Mean densities of all taxa are listed in Table 8. Chironomidae larvae densities were significantly

different among lakes in December 2002 (ANOVA; F2, 21= 6.30, P = 0.0072) and marginally

significant in February 2003 (F2, 21= 3.31, P = 0.0563). Differences occurred due to higher

densities of Chironomidae larvae at Lochloosa Lake than at Lake Monroe for December

(Tukey test; q = 4.9855; df = 21, 3; P = 0.0055) and February (q = 3.6146; df = 21, 3;

P = 0.0465). Differences among lakes for Chaoboridae larvae and Hydracarina densities were

found in all periods (Kruskal-Wallis test; all Hcs > Ho.os, s, s, s = 5.805), except the February 2003

Hydracarina values (He = 4.062; df = 8, 8, 8; P > 0.05). Lake Marian had higher densities of

Chaoboridae larvae when compared to Lake Monroe for each sample period (Dunn test;

all Qs > Q0.05, 3 = 2.394). Chaoboridae densities at Lochloosa Lake were greater than those at

Lake Monroe during April (Q = 2.856; df = 3; 0.01< P < 0.02) and June (Q = 3.246; df = 3;

0.001< P < 0.005) and lower than those at Lake Marian during August (Q = 2.766; df = 3;

0.01< P < 0.02) and October (Q = 2.799; df = 3; 0.01 < P < 0.02). Lake Marian had higher

densities of Hydracarina than Lochloosa Lake in each period when differences were found

among lakes and higher densities than Lake Monroe in April, June, and October

(all Qs > Q0.05, 3 = 2.394). A significant difference of Amphipoda densities among lakes was

found in October 2003 (Hc = 6.553; df = 8, 8, 8; P < 0.05), when densities at Lake Monroe were

greater than those at Lochloosa Lake (Q = 2.429; df = 3; 0.02< P < 0.05) There were no

significant differences found among lakes in the densities of Ephemeroptera larvae, Trichoptera









larvae, Ceratopogonidae larvae, or Diptera pupae during any sample period

(all Hcs < Ho.os, s, s, s = 5.805).

Differences in macroinvertebrate densities (i.e., Chironomidae larvae, Chaoboridae larvae,

and Hydracarina) among lakes were accompanied by dietary differences in black crappie for

these same prey taxa. In December 2002 and February 2003, when Chironomidae larvae

densities were higher at Lochloosa Lake in comparison to Lake Monroe, the mean number of

Chironomidae larvae consumed by black crappie from Lochloosa Lake was also higher than at

Lake Monroe (Figure 11). High Chaoboridae larvae densities at Lake Marian were accompanied

by both higher %Wt and higher mean number of Chaoboridae larvae values in black crappie

diets, when compared to Lakes Lochloosa and Monroe (Table 7 and Figure 11). At Lake

Marian, higher Hydracarina densities were associated with occurrence of this prey item in the

diets of black crappie. Although Hydracarina was never found in large quantities and only

occurred in 5 black crappie stomachs out of 317 examined from Lake Marian, this prey item

never occurred in any of the stomachs examined from Lakes Lochloosa or Monroe. Hence,

higher densities of macroinvertebrate taxa caused increased occurrence and/or consumption of

those prey taxa in black crappie diets.

Two major trends in prey selection were detected with Manly's a index (Figure 10). First,

black crappie of all sizes at Lakes Lochloosa and Marian were highly selective of Diptera pupae

during most periods. Second, black crappie of all sizes at Lake Monroe were highly selective of

Mysidacea during most periods. While black crappie at Lakes Lochloosa and Marian did not

have Mysidacea as a prey option, black crappie at Lake Monroe had Diptera pupae as a prey

option but selected Mysidacea.










Manly's a index produced various results for the remainder of the prey taxa (Figure 10).

Selection for Chaoboridae larvae at Lakes Lochloosa and Marian was generally higher than for

Lake Monroe. Black crappie at Lake Marian were more selective of Chironomidae larvae than at

Lakes Lochloosa and Monroe. Ceratopogonidae larvae, Ephemeroptera larvae, Trichoptera

larvae, Amphipoda, and Isopoda were generally avoided prey taxa, but results were inconsistent

and these prey taxa were occasionally considered either not preferred or highly selected among

all size classes of black crappie. Hydracarina was always considered an avoided prey taxa.

The simplified Morisita index produced various results of CH ValUeS for the different taxa

(Table 9). Relative increases and decreases of taxa density and mean number in diets are shown

in Figure 11. Overall, Chironomidae larvae and Diptera pupae produced the highest CH ValUeS

throughout most size classes at each lake. An exception occurred for Diptera pupae for size class

4 black crappie from Lake Monroe (CH = 0.09). The reason for such a low value (no similarity),

was due to the August 2003 sampling period when 2 individual fish consumed over one thousand

Diptera pupae each. This raised the mean number of Diptera pupae in the stomachs far above

what was sampled in the environment for that period and was much greater than the mean

numbers found in diets for the other periods. Chaoboridae larvae (CH = 0.69 0.92) and

Ephemeroptera larvae (CH = 0.55 0.80) values were higher for Lake Marian black crappie

throughout all size classes than at Lochloosa Lake and Lake Monroe for the same size classes.

The similarities of Mysidacea (CH = 0.72 0.93), Trichoptera (CH = 0.63 0.75), Amphipoda

(CH = 0.47 0.86), and Isopoda (CH = 0.67 0.93) were relatively high in Lake Monroe samples

throughout most size classes, while these same taxa either were not present or had lower CH

values at the other lakes. Overall, higher CH ValUeS were detected for taxa which were more









utilized within a system. Thus, I was able to detect a relationship between seasonal abundance of

benthic prey and black crappie diets within a lake, particularly for taxa that were highly utilized.

Some tradeoffs of utilized prey resources were found for benthic macroinvertebrates as

densities of those prey taxa changed. For example, black crappie at Lake Monroe increased their

consumption of Chironomidae larvae in June 2003 when the highest Chironomidae densities

occurred relative to the other sampling periods were recorded (Figure 11). At this same time,

Mysidacea densities were declining along with the consumption of Mysidacea by black crappie

(Figure 11).









Table 1. Mean water quality parameters for Lakes Lochloosa (Source: Florida LAKEWATCH
1997), Marian (Source: FWC unpublished data), and Monroe (Source: Florida
LAKEWATCH 2003). Water quality parameters include years sampled (Yrs),
number of sampling dates (n), total phosphorus (TP Cpg/L), total nitrogen (TN Cpg/L),
chlorophyll (CHL Cpg/L), secchi depth, and trophic state.
TP TN CHL Secchi
Lake Yrs n (Cpg/L) (Cpg/L) (Cpg/L) (m) Trophic state
Lochloosa 1993-96 40 48 1816 63 0.48 hypereutrophic
Marian 2000-02 5 111 1759 42 0.66 hypereutrophic
Monroe 2000-02 21 89 1628 19 0.61 eutrophic
*Trophic state based on Forsburg and Ryding (1980).












Prey type
Neuroptera
Trichoptera
Coleoptera
Hymenoptera
Arachnida-Araneae
Orthoptera
Diptera
Chironomidae larvae
Chironomidae pupae
Chironomidae adult
Chaoboridae larvae
Chaoboridae pupae
Chaoboridae adult
Ceratopogonidae
Stratiomyidae
Fish
Gastropoda
Vegetation
Detritus
Miscellaneous material
Digested material


Common name
Spongillaffies
Caddi sflies
Beetles
Ants and Wasps
Spiders
Grasshoppers
Flies, Midges, etc.
Midge larvae
Midge pupae
Midge adult
Phantom midge larvae
Phantom midge pupae
Phantom midge adult
Biting midge larvae
Soldier fly larvae


Snails


Table 2. List of types and common names of prey used to numerically and gravimetrically describe black crappie diet contents.


Prey type
Nematoda
Oligochaeta
Hirudinea
Cladocera
Copepoda
Copepoda-Argullus
Ostracoda
Mysidacea
Isopoda
Amphipoda
SCambaridae
Palaemonidae
Hydracarina
Unidentified Insect
Plecoptera
Ephemeroptera
Odonata
Odonata-Ani soptera
Odonata-Zygoptera
Hemiptera
Hemiptera-Corixidae
Megaloptera


Common name
Roundworms
Aquatic earthworms
Leeches
Water fleas
Copepods
Fish lice
Seed shrimp
Opossum shrimp
Aquatic sow bugs
Scuds, Sideswimmers
Crayfish
Grass shrimp
Water mites
Insects
Stoneflies
Mayflies
Odonates
Dragonflies
Damselflies
Bugs
Water boatmen
Dob sonflies









Table 3. Four maj or prey categories used in the MANOVA procedure and the individual prey
items included in each category.

Maj or prey category Individual prey types included in maj or prey categories
Microcrustaceans Cladocera Copepoda

Copepoda-Argullus Ostracoda
Insects Unidentified Insect Plecoptera

Ephemeroptera Odonata
Odonata-Anisoptera Odonata-Zygoptera

Hemiptera Hemiptera-Corixidae

Megaloptera Neuroptera
Trichoptera Coleoptera

Hymenoptera Orthoptera

Diptera Chironomidae
Chaoboridae Ceratopogonidae

Stratiomyidae Arachnida-Araneaea

Hydracarinaa
Macrocrustaceans My si dacea Isopoda

Amphipoda Palaemonidae
Cambaridae

Fish Fish
a Arachnida and Hydracarina are not true insects, but were included within the insect prey
category .









Table 4. Otter trawl capture and collection data for black crappie from Lakes Lochloosa, Marian, and Monroe during each sampling
period. Total time is the total number of minutes trawls were pulled at each lake. Total catch is the total number of black
crappie caught in all trawls. Mean CPUE was calculated for black crappie for size class 2 (150 189 mm TL), size class 3
(190 229 mm TL), size class 4 (> 230 mm TL), and all fish. Total fish collected include all black crappie sacrificed for
diet and age analysis in size classes 1 (110 149 mm TL), 2, 3, and 4.
Total Mean CPUE (fish/min) Total collected
Sampling # of time Total Size Size Size Size Size Size Size All size
period Trawls (min) catch class 2 class 3 class 4 All fish class 1 class 2 class 3 class 4 classes

Lochloosa Lake

Aug-2002 a a a a a a a 10 10 10 10 40

Oct-2002 23 9 2b 0.3b 0.1b 0.1 b 2.7b 43 15 15 12 85

Dec-2002 48 323 a a a a a 32 11 10 23 76

Feb-2003 24 120 316 0.3 0.2 0.1 2.6 30 31 25 11 97

April-2003 26 160 260 0.3 0.2 0.1 1.8 30 30 22 10 92

June-2003 22 130 1,065 0.9 0.2 0.4 8.7 29 34 27 30 120

Aug-2003 23 148 978 1.0 0.1 0.1 6.9 31 30 19 15 95
Oct-2003 20 108 729 1.0 0.3 0.3 6.7 28 30 29 30 117

All Periods 1860 1,080" 3,5690 0.6 0.2 0.2 4.8 233 191 157 141 722


a Data not recorded.
b Values do not include all


trawls in sampling period.


" Totals based on data with missing values.










Table 4. Continued.
Total Mean CPUE (fish/min) Total collected
Sampling # of time Total Size Size Size Size Size Size Size All size
period Trawls (min) catch class 2 class 3 class 4 All fish class 1 class 2 class 3 class 4 classes


Lake Marian

3.4

b8.3b

3.5

2.0

Ib 3.1b

;b 3.7b

1.9

5.8


Aug-2002

Oct-2002

Dec-2002

Feb-2003

Apr-2003

Jun-2003

Aug-2003

Oct-2003

All Periods


400

365

172

97

242

336

177

237


25.1

6.0b

10.0

5.4

4.3b

3.8b

0.9

3.3


7.5

3.1

4.7

2.3

5.8

4.3

2.4

7.5


40.0

30.4

28.7

12.1

16.1

13.9

8.0

19.8


37 108 2,026


5.6 4.3 4.0 19.0


79 80 80 78 317










Table 4. Continued.
Total Mean CPUE (fish/min) Total collected
Sampling # of time Total Size Size Size Size Size Size Size All size
period Trawls (min) catch class 2 class 3 class 4 All fish class 1 class 2 class 3 class 4 classes


Lake Monroe

0.2 1.1

0.1 0.7

0.4 2.4

0.1 1.1

Ob 1.2b

0.1 0.6

0.4 1.2

0.8 1.0

0.2 1.0


Aug-2002

Oct-2002

Dec-2002

Feb-2003

Apr-2003

Jun-2003

Aug-2003

Oct-2003

All Periods


130

110

43

55

130

75

25

20

588


855

232

404

305

630

594

261

149

3,430


0.1

0

0.2

0.2

0.9b

3.5

1.0

0.7

0.7


6.6

2.1

9.0

5.5

4.9

7.9

10.4

7.5

5.9


40

28

40

34

38

40

40

40

300


Total 333" 1,7360 9,0250


341 307 299 1,339










Table 5. Linear, Gompertz, and von Bertalanffy growth functions of black crappie in Lakes
Lochloosa, Marian, and Monroe based on the collected total length at age data. L, is
the expected length at age t (years).


Lake


Growth function


Linear


L, = 100.27 + 44.90(t)

L, = 128.42 + 27.34(t)

L, = 123.85 + 36.70(t)


Gompertz


Lochloosa


Marian

Monroe


_(-0.6411(t-0.7057))`

-e(-0.4745(t-0.5182))\

-e(-0.4917(t-0.5689))


L, = 312.0 xe

L, = 311.1 xe

L, = 344.4 x e


Lochloosa


Marian

Monroe


von Bertalanffy


L, = 342.3 1- e(-0.724(t+0.3761))

L, = 328.5 1- e(-0.3077(t+0.8268)))

L, = 370.5 1-e(-0.2999(t+(1 \**n~~


Lochloosa

Marian

Monroe









Table 6. Number of black crappie stomachs examined for diet contents, number of empty
stomachs observed, and number of stomachs with 100 % digested material in each of
the three study lakes. Total stomachs examined are listed for size classes 1 (110 -
149 mm TL), 2 (150 -189 mm TL), 3 (190 229 mm TL), and 4 (1 230 mm TL).
The numbers in parentheses for empty stomachs and stomachs with 100 % digested
material indicate the percentages that those stomachs made up for all size classes of
stomachs examined.
Stomachs
Total stomachs examined.
with 100 %
Sampling Size Size Size Size All size Empty digested
period class 1 class 2 class 3 class 4 classes stomachs material


Lochloosa Lake

10 10 10 10 40 1 (2.5)
43 15 15 12 85 2 (2.4)
32 11 10 23 76 1 (1.3)


Aug-2002
Oct-2002
Dec-2002
Feb-2003

Apr-2003
Jun-2003

Aug-2003
Oct-2003
All Periods


6 (15.0)
8 (9.4)
0
0
0

7 (15.6)
5 (11.1)
9 (15.0)
35 (8.1)


9 10 10 11


40 0


10 10 10 10 40 2 (5.0)
9 11 10 15 45 1 (2.2)
10 10 10 15 45 1 (2.2)
10 10 10 30 60 5 (8.3)


87 85 126


13 (3.0)


Lake Marian

10 10 10 10 40 1 (2.5)
9 10 10 10 39 5 (12.8)
10 10 10 10 40 1 (2.5)
10 10 10 10 40 2 (5.0)
10 10 10 10 40 1 (2.5)


Aug-2002
Oct-2002
Dec-2002
Feb-2003

Apr-2003
Jun-2003

Aug-2003
Oct-2003
All Periods


1 (2.5)
1 (2.6)
0

1 (2.5)
0
0

3 (7.5)
2 (5.0)
8 (2.5)


10 10 10


8 38 1 (2.6)


10 10 10 10 40 1 (2.5)
10 10 10 10 40 2 (5.0)


79 80 80 78 317


14 (4.4)









Table 6. Continued.
Stomachs
Total stomachs examined.
with 100 %
Sampling Size Size Size Size All size Empty digested
period class 1 class 2 class 3 class 4 classes stomachs material

Lake Monroe

Aug-2002 10 10 10 10 40 5 (12.5) 1 (2.5)
Oct-2002 10 0 8 10 28 4 (14.3) 0

Dec-2002 10 10 10 10 40 0 1 (2.5)
Feb-2003 10 10 4 10 34 0 0

Apr-2003 10 10 8 10 38 0 0
Jun-2003 10 10 10 10 40 0 0

Aug-2003 10 10 10 10 40 7 (17.5) 0
Oct-2003 9 10 10 10 39 5 (12.8) 4 (10.3)
All Periods 79 70 70 80 299 21 (7.0) 6 (2.0)


Total 291 237 235 284 1047 48 (4.6) 49 (4.7)










Table 7. Mean percent weight values (%Wt) of dominant prey types in the Insect and
Macrocrustacean (Macro) prey categories found in black crappie diets in size classes
1 (110 149 mm TL), 2 (150 -189 mm TL), 3 (190 229 mm TL), and 4 (> 230 mm
TL) at Lakes Lochloosa, Marian, and Monroe. Prey types listed include
Chironomidae larvae (Chi), Chaoboridae larvae (Cha), and Diptera pupae (Dip) in the
Insect prey category and Mysidacea (Mys) in the Macro prey category. %Wt values
are based on pooled data from all sampling periods.

Size Chi Cha Dip Insect Mys Macro
class %Wt %Wt %Wt %Wt %Wt %Wt

Lochloosa Lake

1 29.63 4.34 31.84 71.05 0 5.22

2 21.55 7.46 25.35 66.79 0 4.23

3 14.32 1.19 30.36 60.21 0 7.55

4 6.32 0.43 21.75 37.71 0 2.60

Lake Marian

1 24.61 11.73 17.79 60.54 0 0.22

2 15.21 17.56 12.73 58.11 0 6.26

3 10.20 19.54 20.03 59.47 0 7.63

4 2.70 15.16 17.38 37.70 0 3.00

Lake Monroe

1 14.16 5.95 1.37 25.63 39.12 48.20

2 17.71 3.40 2.60 33.92 31.92 42.11

3 18.46 3.39 1.67 30.42 34.46 46.71

4 3.66 0.59 11.40 20.65 14.83 21.72









Table 8. Mean densities (number/m2) Of taxa collected with petite Ponars in each period from Lakes Lochloosa, Marian, and Monroe.
Periods include December of 2002 and February, April, June, August, and October of 2003. Taxa include Chironomidae
larvae (Chi), Chaoboridae larvae (Cha), Ceratopogonidae larvae (Cer), Diptera pupae (Dip), Mysidacea (Mys), Trichoptera
larvae (Tri), Ephemeroptera larvae (Eph), Amphipoda (Amp), Isopoda (Iso), and Hydracarina (Hyd).
Mean taxa density
Period Chi Cha Cer Dip Mys Tri Eph Amp Iso Hyd

Lochloosa Lake

December 26,065 328 3,272 5 0 0 603 2,282 0 0
February 11,313 441 3,488 38 0 22 1,528 1,109 86 22

April 3,848 102 926 22 0 5 151 495 108 0
June 5,102 86 947 0 0 0 258 409 0 0

August 7,809 899 215 11 0 43 86 0 0 0
October 5,145 1,948 463 0 0 43 43 0 0 43









Table 8. Continued.

Mean taxa density
Period Chi Cha Cer Dip Mys Tri Eph Amp Iso Hyd

Lake Marian

December 8,939 2,508 355 0 0 0 129 2,018 0 167

February 10,220 2, 185 145 27 0 0 65 97 0 108

April 10,893 1,948 43 75 0 22 22 86 0 355
June 6,044 2,508 75 43 0 118 11 285 0 350

August 17,405 1,243 97 48 0 11 0 22 0 296
October 3,374 2,842 11 0 0 0 5 22 0 248
p Lake Monroe
OO
December 1,706 38 161 0 16 32 43 81 38 5

February 2, 164 43 86 27 5 22 172 199 0 22

April 2,626 16 129 70 38 5 0 113 86 0
June 27,270 22 108 70 16 75 0 291 15 0

August 11,727 0 32 0 5 32 86 576 457 5
October 2,007 22 54 0 0 27 27 264 388 22










Table 9. Simplified Morisita index values of similarity for various taxa comparing density found
with petite Ponars to the total number found in black crappie diets through all
sampling periods. Comparisons were made for black crappie in size classes 1 (110 -
149 mm TL), 2 (150 -189 mm TL), 3 (190 229 mm TL), and 4 (> 230 mm TL) at
Lakes Lochloosa, Marian, and Monroe. Taxa used in comparisons include
Chironomidae larvae (Chi), Chaoboridae larvae (Cha), Ceratopogonidae larvae (Cer),
Diptera pupae (Dip), Ephemeroptera larvae (Eph), Trichoptera larvae (Tri),
Mysidacea (Mys), Amphipoda (Amp), Isopoda (Iso), and Hydracarina (Aca). Values
range from 0 (no similarity) to 1.0 (complete similarity). Dashes indicate cases when
no individuals were found in the diets. Blanks indicate cases when no individuals
were found in the diets or Ponars.

Taxa
Size
class Chi Cha Cer Dip Eph Tri Mys Amp Iso Aca

Lochloosa Lake

1 0.92 0.43 0.23 0.95 0.09 0 0.32

2 0.85 0.82 0.23 0.88 0.33 0.29 0.61

3 0.90 0.45 0.27 0.93 0.33 -0.50

4 0.59 0.53 0.41 0.95 -0.45

Lake Marian

1 0.69 0.69 0.10 0.92 0.55 0.99 0.04

2 0.91 0.92 0.28 0.85 0.80 0.28 0.07 0.39

3 0.92 0.74 0.23 0.66 0.60 0.17 0.08 0.39

4 0.81 0.85 0.22 0.66 0.60 -0.05 0.39

Lake Monroe

1 0.92 0.59 0.31 0.74 0.19 0.65 0.93 0.70 0.93

2 0.94 0.39 0.31 0.91 0 0.69 0.77 0.86 0.69

3 0.93 0.60 0.58 0.81 0.19 0.75 0.92 0.47 0.70

4 0.89 0.30 0.38 0.09 0.42 0.63 0.72 0.67 0.67






















Y ~-~S~t ~ Lochloosa Lake

9-I Lakee Monroe


Lake Marian










Figure 1. General locations of Lochloosa Lake, Lake Marian, and Lake Monroe in the state of
Florida.









Lochloosa Lake
(a)


S. 11.. ..


Lake Marian


Lake Monroe


N=~ 260(a)


N= 189
T= 4


N = 256
T= 10


N = 235 (b)
T 6

..Ill g.


N = 296
T =13


....


N = 232
T =23


N= 124
T=6


N= 110
T=5


.(d)




11 13 15 17 19 21


23 25 27 29 31 33 35


23 25 27 29 313


Total Length Group (cm)


Figure 2. Relative length frequencies of black crappie 1 10 mm TL captured with otter trawls at Lakes Lochloosa, Marian, and
Monroe for sampling periods (a) April, (b) June, (c) August, and (d) October of 2003. N is the total number of crappie
represented in each graph, and T is the number of trawls used to collect the fish.


N = 296 (b)111111 I
T 22


30 -()



11 13 15 17 19 21


210 I(d) N =219




i3 35 11 13 15 17 19 21 23 25 27 29 31 33 35











100


50 -: *





-50 "


-100

100 (b)



50






50 -



-50- *


-100

100 15 20 5030 5

PrdctdTL(m

Fiur 3 esdulso te xpcedtoallngh t g vlus rm heobeve tta entha
age~ ~ ~~.L vauswe uigterspcievnBetlnf rot oesfo ae a
Loclosa () Mrinan ( )Moroe












400-



300-



S200-


w- Lochloosa
100 -p -x-Marian
-= Monroe




0 1 2 3 4 5 6 7 8
Age


Figure 4. Mean total length (TL) at age (yrs) of black crappie in Lakes Lochloosa, Marian, and
Monroe using their respective von Bertalanffy growth model.







































______ _C __


2002


2003


100 1 (a)


P
Z *


100 1(b)


2C



100-(c

75-

50-


100 (d

75-

50 -'


August October December February April


June August October


Period


- Lochloosa Lake


-0o- Lake Marian


+--Lake Monroe


Figure 5. Mean percent of total diet weight of microcrustaceans (y axis) for black crappie at
Lakes Lochloosa, Marian, and Monroe during sampling periods (x axis) for size
classes (a) 1 (110-149 mm TL), (b) 2 (150-189 mm TL), (c) 3 (190-229 mm TL), and
(d) 4 (2 230 mm TL).











2002


1075


2003


r
P
r
/ *


LOO
75 j"' *\
5 yr C *

50 '[75
1


OL


--O


August October December February


June August October


Period


- + Lochloosa Lake


-0 Lake Marian


~-- Lake Monroe


Figure 6. Mean percent of total diet weight of insects (y axis) for black crappie at Lakes
Lochloosa, Marian, and Monroe during sampling periods (x axis) for size classes (a)
1 (110-149 mm TL), (b) 2 (150-189 mm TL), (c) 3 (190-229 mm TL), and (d) 4 (2
230 mm TL).













2002 2003

100 (a)

75-

50-

25 -.- *



100 -(b)

75-

50-

25-



100 -(c)

75-

ai 50-

25- *0



100 -(d)

75-

50-

25-


August October December February April June August October

Period

+ Lochloosa Lake -0- Lake Marian ~-A-Lake Monroe



Figure 7. Mean percent of total diet weight of macrocrustaceans (y axis) for black crappie at
Lakes Lochloosa, Marian, and Monroe during sampling periods (x axis) for size
classes (a) 1 (110-149 mm TL), (b) 2 (150-189 mm TL), (c) 3 (190-229 mm TL), and
(d) 4 ( 230 mm TL).






































































Figure 8. Mean percent of total diet weight of fish (y axis) for black crappie at Lakes Lochloosa,
Marian, and Monroe during sampling periods (x axis) for size classes (a) 1 (110-149
mm TL), (b) 2 (150-189 mm TL), (c) 3 (190-229 mm TL), and (d) 4 (1 230 mm TL).


I ~f- I ~--I 1 I I I I


(b)


D

*O C
~ ,O _*
O
/t '



(C) 1*
~,
r *
*
/O
r r
O C
~ 2-- O pC;h
*, /*
*
*----~CI~-~


(d)
~o *-,
6~ -o

bc;~
[y **
*
*C~ -*~ ~_** 'd


2002


2003


100 1(a)


-

-


75

50






100

75


D\
~--


August October December February


April June August October


Period


- Lochloosa Lake


-0o- Lake Marian


~-- Lake Monroe












80 -(a)

60-

40-

20-




so -(b)



40 -'1

20-



o 0






60-

40-

20 --**



60



1 2 3 4
Size Class

+ Lochloosa Lake -0- Lake Marian Lake Monroe



Figure 9. Mean percent total weight of (a) microcrustaceans, (b) insects, (c) macrocrustaceans,
and (d) fish in the diets of black crappie of size classes 1 (1 10-149 mm TL), 2 (150-
189 mm TL), 3 (190-229 mm TL), and 4 (1 230 mm TL) from Lakes Lochloosa,
Marian, and Monroe.











Lochloosa Lake


Lake Marian


Lake Monroe


1.0 -(a) l(a) -(a)
0.8
0.6
0.4
a 0.2 = 0.167 u 111 = 0.143 u 1 = 0.10

>Ci Ca Ce Di Ep Am Ci Ca Ce Di Ep Am Ac Ci Ca Ce Di My Ep Tr Am Is Ac

~ 1.0 -(b) l(b) l(b)
cs0.8
2 0.6-


02 u= 0.11

Ci Ca Ce Di Ep Tr Am Is Ac Ci Ca Ce Di Ep Am Ac Ci Ca Ce Di My Ep Tr Am Ac
Taxa

HSize Class 1 0 Size Class 2 II Size Class 3 I~l Size Class 4





Figure 10. Mean Manly's a values indicating selection of prey taxa by black crappie in size classes 1 (1 10-149 mm TL), 2 (150-189
mm TL), 3 (190-229 mm TL), and 4 (> 230 mm TL) from Lakes Lochloosa, Marian, and Monroe during (a) December of
2002 and (b) February, (c) April, (d) June, (e) August, and (f) October of 2003. Taxa included in selectivity indices are
Chironomidae larvae (Ci), Chaoboridae larvae (Ca), Ceratopogonidae larvae (Ce), Diptera pupae (Di), Mysidacea (My),
Ephemeroptera larvae (Ep), Trichoptera larvae (Tr), Amphipoda (Am), Isopoda (Is), and Hydracarina (Ac). Taxa not
found in stomachs or petite Ponars for a particular sampling period and/or lake were not included in that index. Trendline
with a value above it indicates level of selectivity. Values greater than, equal to, or less than trendline indicates selection,
no preference, or avoidance of prey taxa, respectively.


































~m~Hiiir~


a=0.125


, -


,


Ci Ca Ce Di Ep Tr Am

1.0 (p, -


Ci C e i E T c


(e)


u= 0.125 .


IIIII h\V-ll -I e. -_111


Lochloosa Lake


Lake Marian


Lake Monroe


1.0 -()
0.8
0.6
0.4
0.2
0.0 I I .
Ci Ca Ce Di


u= 0.125
~~-


u= 0.125


Ep Tr Am


.. III1


Ci Ca Ce Di Ep Tr Am Ac


Ci Ca Ce Di My Ep Tr Am Is


(d)



m = 0.125


Tr Am


Ci Ca Ce Di Ep Tr Am Ac


Ci Ca Ce Di My Tr Am Is


n~n


u= 0.10


Ci Ca Ce Di Ep Tr Am Ac







Ci Ca Ce Di Ep Tr Am Ac


Ci Ca Ce Di My Ep Tr Am Is Ac

f)





Ci Ca Ce Di My Ep Tr Am Is Ac


HSize Class 1


0 Size Class 2


II Size Class 3


I~l Size Class 4


Figure 10. Continued.


1.0 -( )
0.8




Ci Ca


(d)


Ce Di Ep


n~n,


2 0.8-


(e)










Chironomidae larvae


Chaoboridae larvae


30000 --(al 40 3000 --(a) s 8
-30 -60
20000 -0
10000 -0








'E30000 (b) 40 3000 (b) 80 o
20000 0 2000 -6


Period
100 MenDniy --*-- ieCas1 -SzeCas2Sz ls 3 ----Sz ls

Figur 11 enCiooia ave hooiaelraDpeappe n yiae eniiscletdwt eiePnr n
mea nubr on nbakcapesoah of siz clse 1 (1014 mm TL) 2 1019m L) 1029m
TLad4( 3 mT)fo ae a ohos,()Main n c oredrn apigprosDcme
(Dec of20 n eray(e) piJnAgs Ag n coe Ot f20.M sdcawsntfudwt
peit Ponars0 ore in black crpi it tLks ohos n ain














Diptera pupae


n,


250 .s
B
d
125
5'
O I~
o
B
3


Mysidacea

40 (c) 4
30 -
20 x.



Dec Feb April June Aug Oct


Dec Feb April June Aug Oct



I IMean Density - Size Class 1


Period

- Size Class 2 Size Class 3 -x- Size Class 4


Figure 11. Continued.









DISCUSSION

The diet, prey availability, and population structure (i.e., abundance and size structure)

differences among lakes likely contributed to the variation in population growth rates.

Lochloosa Lake had the lowest abundance of black crappie based on the otter trawl mean CPUE

data and the least proportion of large fish based on the length frequency data. Lake Marian had

the highest abundance of all sizes of black crappie and the greatest proportion of black crappie

S190 mm TL. Lake Monroe had an intermediate abundance of black crappie, which obtained

the largest size with Lochloosa Lake second and Lake Marian having the smallest length at age.

Benthic prey availability and prey selection caused differences in the diet composition and

ontogenetic diet shifts of black crappie among the three study lakes. Black crappie at all three

systems possessed similar ontogenetic diet shifts of microcrustaceans and fish. In general, the

%Wt values of microcrustaceans in stomachs decreased as black crappie increased in size and the

%Wt values of Eish in stomachs increased as black crappie increased in size. Diet shifts of this

nature have previously been found in black crappie food habit studies (Reid 1949; Keast 1968).

However, differences occurred in the intermediate prey categories (i.e., insects and

macrocrustaceans) due to the additional prey resource and prey selection of Mysidacea (i.e.,

Americamyis almyra) by black crappie at Lake Monroe. This substantially influenced diet

composition of black crappie at Lake Monroe where fish of all sizes consumed high quantities of

macrocrustaceans up to size class 3, then shifted to fish as prey at size class 4. Conversely, at

Lakes Lochloosa and Marian, black crappie did not have Mysidacea as a prey option and fish

were highly selective of Diptera pupae. Thus, black crappie at Lakes Lochloosa and Marian

consumed high quantities of insects up to size class 3, then shifted to fish as prey at size class 4.

The availability and selection of a high energy Mysidacea prey by black crappie at Lake

Monroe likely influenced the larger size at age attained at this system compared to Lakes









Lochloosa and Marian. Previous studies have recognized Mysidacea as an important prey item

of black crappie at other Florida lakes (Chable 1947; Huish 1957; Ager 1975; Schramm et al.

1985). Ager (1975) found Mysidacea to comprise 53% of the dietary items in black crappie

stomachs examined from Lake Okeechobee, Florida. Examples of other fish species that utilize

mysid shrimp as a prey item, when it is available in fresh and brackish water, include striped

bass M~orone saxatilis (Cooper et al. 1998), pikeperch Stizostedion lucioperca (Hansson et al.

1997), alewives Alosa pseudoharengus (Madenjian et al. 2003; Pothoven and Vanderploeg

2004), yellow perch (Pothoven et al. 2000), and smelt Osmerus eperlan2us (Vinni et al. 2004).

Other studies have attributed Mysidacea as an important dietary item that can influence growth

rates. Madenjian et al. (2003) credited the larger size of the non-piscivorous alewife at Lake

Michigan to the availability and utilization of the larger, more energetic prey (i.e., Mysidacea

and Amphipoda) in comparison to smaller alewives at Lake Ontario where these items were not

available. Vinni et al. (2004) suggested that slow growth of age-1 and age-2 smelt at a Finnish

lake was most likely due to an inconsistent supply of larger invertebrates (i.e., Mysidacea and

Chaoboridae) during the intermediate stage of a diet shift before piscivory.

The availability of Mysidacea as an additional prey resource is also profitable when other

prey resources are low. Huish (1957) found a lower number of Chironomidae larvae and pupae

in black crappie stomachs at Lake George, Florida during July 1950 than in July 1949, which

was replaced by the presence and volume of Mysidacea in the diets. Huish (1957) suggested that

this was due to decreased abundance of Chironomidae larvae. This is similar to the tradeoff of

utilized prey I found between Chironomidae larvae and Mysidacea in the diets of black crappie

and their corresponding densities at Lake Monroe during April and June of 2003.









The optimal foraging theory suggests that a consumer should maximize the net energy gain

by selectively preying on the most beneficial items (MacArther and Pianka 1966; Emlen 1966).

It takes into consideration prey densities, pursuit and capture costs, and energy return. A wide

variety of fish diet studies have found selective predation of higher quality prey items, which

maximized net energy returns (Mittelbach 1981; Galarowicz and Wahl 2005; Graeb et al. 2006).

This in tumn, can increase the growth of fish (Mittelbach 1983; Galarowicz and Wahl 2005).

In caloric studies conducted by Cummins and Wuycheck (1971), the crustacean class

Malacostraca, which includes Mysidacea, resulted in 1,029 calories per gram wet weight,

whereas the insect order Diptera (e.g., Chironomidae, Chaoboridae, etc.) had only 613 calories

per gram wet weight. Furthermore, Gardner et al. (1985) found M~ysis relicta to have a higher

mean lipid value than Chironomidae at Lake Michigan. These results suggest that Mysidacea is

a more energetically beneficial prey item when compared to insects, which makes the selection

of Mysidacea by black crappie at Lake Monroe over Diptera pupae profitable.

Selective predation of more energy-rich prey items by crappie has been previously noted.

Ball and Kilambi (1972) found that black crappie and white crappie fed on immature Chaoborus

seven times more than the smaller cyclopoid copepod, although the copepods were more

abundant in the water column. Pine and Allen (2001) and Dockendorf and Allen (2005) found

that age-0 black crappie selected larger zooplankton taxa. Dockendorf and Allen (2005)

associated size differences of age-0 black crappie among three Florida lakes with a higher

consumption of large zooplankton. In an aquarium study, O'Brien et al. (1989) observed that

when large and small prey were both present, the large prey were usually pursued. By pursuing

the larger prey rather than the smaller prey, they found that the net energy gained by white










crappie was increased. This would improve the growth efficiency, which should improve their

survival .

Various factors can influence selective predation by fish including prey characteristics,

such as size (Werner and Hall 1974; Mayer and Wahl 1997; Robichaud-Leblanc et al. 1997),

behavior (Buskey 1994), availability (Sanyanga 1998; Galarowicz et al. 2006), and visibility (Li

et al. 1985; Buskey 1994); and predator characteristics, such as size (Mayer and Wahl 1997;

Robichaud-Leblanc et al. 1997) and morphology (Graeb et al. 2005). Previous examples of

selective predation by crappies were related to prey size (Ball and Kilambi 1972; O'Brien et al.

1989; Pine and Allen 2001; Dockendorf and Allen 2005). Measurements of individual

Mysidacea and Diptera pupae found in black crappie diets and petite Ponar grabs at Lake

Monroe were not made, and therefore it is unknown if prey size is a factor in the selectivity

differences found at this system relative to Lakes Lochloosa and Marian. Size variation of these

prey items could occur for several reasons (i.e., season, species, life stage), so it would be

necessary to make individual measurements of available prey and consumed prey throughout

sampling periods to determine if prey size (i.e., Mysidacea and Diptera pupae) is a factor in

selection. While some specimens have been preserved in ethanol, this preservation treatment can

cause significant biomass loss and size reduction (Howmiller 1972; Stanford 1973), and would

not reflect the actual size and weight at the time of availability or consumption. Other

differences (e.g., behavior, visibility, etc.) between Mysidacea and Diptera pupae may have also

caused selectivity differences among systems.

Many studies have concluded that higher densities and availability of quality benthic prey

items were instrumental in growth of various fish species. Fox (1989) found a positive

relationship between the growth of juvenile walleye with the density and size of available









benthic prey (i.e., Chironomidae larvae) at experimental ponds. Similarly, Hayward and Margraf

(1987) concluded that differences in availability of larger benthic prey at two basins of Lake Erie

led to differences in the diets and growth of yellow perch in those basins. A low quality prey

supply at the western basin of Lake Erie allowed smaller yellow perch to feed effectively, but the

diets of larger yellow perch were inadequate, which caused slower growth. Contrarily, a high

variety of larger benthic prey allowed all sizes of yellow perch to feed adequately at the central

basin of Lake Erie, which allowed for higher growth rates (Hayward and Margraf 1987). In

more recent years, Tyson and Knight (2001) attributed increased yellow perch growth at the

western basin of Lake Erie to the increased availability and consumption of benthic prey. Lott et

al. (1996) also attributed yellow perch populations with faster growth to the higher densities and

availability of macroinvertebrates as prey.

Comparisons among lakes indicated that black crappie growth at Lochloosa Lake was not

limited by benthic prey resources within that system. Black crappie at Lochloosa Lake attained a

larger maximum size (La3) in comparison to Lake Marian and reached their maximum size at a

faster rate (k) than black crappie at Lakes Marian and Monroe. Mysidacea was not available to

black crappie at either Lakes Lochloosa or Marian. Instead, black crappie at these systems

utilized Diptera pupae, Chironomidae larvae, and Chaoboridae larvae at higher levels. Benthic

macroinvertebrate densities did not differ significantly between lakes except for higher densities

of Chaoboridae larvae at Lake Marian during two sampling periods. Thus, I was unable to

explain the growth rate differences between Lakes Lochloosa and Marian through differences in

benthic prey availability alone.

Density dependent growth is commonly found in fish populations (Walters and Post 1993;

Post et al. 1999; Boxrucker 2002; Buktenica et al. 2007). In general, increased densities of fish









can lead to low food availability, increased competition, and reduced growth. Swingle and

Swingle (1967) observed density dependent growth of crappies at ponds and large reservoirs in

Alabama. Schramm et al. (1985) and Miller et al. (1990) observed density dependent growth of

black crappie at Lake Okeechobee, Florida. The high abundance of black crappie based on catch

rates at Lake Marian, might suggest that slower growth is a result of higher density. The fast

growth of black crappie at Lochloosa Lake could result from low abundance of black crappie at

this system. However, based on results I obtained from index of fullness comparisons between

lakes, black crappie at Lakes Lochloosa and Marian were not feeding differently between lakes

in terms of total consumption. Nor were their diet shifts different, which suggests that energetic

intake was comparable between systems. However, high densities of black crappie at Lake

Marian could increase competition and cause greater energy to be applied in the search and

capture of prey items. This is particularly true when prey densities (i.e., benthic

macroinvertebrates) are not different between systems because prey per capital would be lower.

This would result in less net energy gained and reduced growth rates in the high density system

(i.e., Lake Marian) in comparison to the low density system (i.e., Lochloosa Lake). Thus,

density dependent growth is a potential factor in the growth variation of black crappie at Lakes

Lochloosa and Marian.

Many studies have found increased growth of various fish species exhibiting ontogenetic

diet shifts after the onset of piscivory (Ellison 1984; Keast and Eadie 1985; Buij se and

Houthuijzen 1992; Olson 1996; Madenjian et al. 1998; Vinni et al. 2004; Galarowicz and Wahl

2005). However, in this study, black crappie did not consume fish differently among lakes as

they increased in size based on % Wt estimates. Therefore, initiation of fish as prey was not

responsible for the growth differences of black crappie among systems.









Results of the simplified Morisita' s index were variable for different taxa, but indicated

that benthic prey availability can influence consumption rates of prey items by black crappie. In

use here, a high CH Value for a benthic prey item indicates that consumption of that prey item by

black crappie is proportionally similar to the density found in the environment throughout time.

It does not necessarily mean that the prey item is being selected for. For example, Chironomidae

had relatively high CH ValUeS for all size classes and lakes, but were not found to be a highly

selective item because of their large densities relative to the other taxa included in the

comparisons. In addition to the simplified Morisita' s index, comparisons of benthic densities

and diets (i.e., %Wt and mean number) among lakes also suggest that benthic prey availability

can influence consumption rates of prey items by black crappie.

Potential sources of error in the selectivity and similarity indices include inadequate habitat

sampling, patchiness of prey, collection times of black crappie, and differential digestion rates of

prey (Strauss 1979). The taxa included in these indices were chosen because they could be

effectively sampled with a petite Ponar and would be readily available for black crappie

consumption. Three taxa which could have exhibited biases were Chaoboridae larvae, Diptera

pupae, and Mysidacea. Chaoboridae larvae and Mysidacea are known to have diel cycles of

vertical migration in the water column, remaining close to the bottom during the day and moving

up to feed at night (Pennak 1953; Cole 1994). Because I sampled with petite Ponars during the

day, these taxa should have been readily available for collection. Also, the species of Mysidacea

that was present in Lake Monroe, Americamyis almyra, appears not to have vertical migrations

and remains close to the bottom during both day and night (Johnson and Allen 2005). The bulk

of Diptera pupae found in this study (i.e., Chironomidae) are free swimming, but tend to remain

at the bottom until time to emerge (Merritt et al. 1996; Coffman and Ferrington 1996).









Prey patchiness is another source of error through density estimates and prey consumption.

For example, two individual black crappie consumed over 1,000 Diptera pupae each in August

2003 at Lake Monroe, whereas the other black crappie in the same size class had relatively small

numbers. Consequently, the similarity values for that size class of black crappie were low.

Estimates of prey densities can have high variability due to prey patchiness, particularly when

there is a low sample size.

Collection times of fish for stomach analysis can impact diet results along with any index

that uses diet as a variable when diel feeding patterns occur. For instance, if crappie feed at dusk

and most fish are collected during morning and afternoon, stomach contents would not be

representative of the true diet. This is particularly true when differential digestion rates of prey

items occur. In this case, prey items with a higher rate of digestion would be underrepresented

and vice versa (Strauss 1979). Past investigations have found black crappie to feed at various

times of the day, including both day and night (Pearse 1918; Seaburg and Moyle 1964; Keast

1968; Ellison 1984). Differences in feeding times of crappies have been attributed to habits of

their prey (Keast 1968; O'Brien et al. 1984). All black crappie collections for this project were

made during the day, primarily in the mid-morning and early-afternoon hours at Lakes Marian

and Monroe. However, catch rates of black crappie at Lochloosa Lake were low, making it

necessary to sample from early-morning to late-afternoon, to obtain a representative sample.

Diel investigations of black crappie diets were not conducted for this project, therefore

differences or similarities in diel feeding patterns of black crappie among systems are unknown.

The increased consumption of fish in the diets of black crappie during the summer and fall

months in this study is similar to previous studies (Dendy 1946; Reid 1949; Ball and Kilambi

1972). This is probably due to a higher availability of age-0 prey fish (i.e., shad, bluegill, etc.)









after spawning periods. This trend was more distinguished in the smaller size classes, which had

low %Wt values before YOY prey fish would have been available. The %Wt values of Eish in

the smaller-size black crappie diets also leveled off or decreased by October 2003, which could

be caused by prey fish outgrowing the smaller black crappie and becoming unavailable for

consumption. The occurrence of potential prey fish outgrowing their smaller predators is

common (Keast 1977; Keast and Eadie 1985; Storck 1986; Frankiewicz et al. 1996). As a result,

this may cause smaller black crappie to return to a less energetic diet of smaller prey items. This

could explain the increase in microcrustaceans present in the diets during the winter period. The

larger size classes had higher %Wt values of Eish in their diets throughout the year, which was

most likely a result of having the ability to consume the larger prey fish throughout the year.

However, I did not obtain prey abundance estimates of Esh, and therefore did not quantify how

Hish prey abundance and size was related to black crappie diets.

When considering all sampling periods, empty stomachs made up a relatively low

percentage of the total stomachs examined for each lake (all < 7 %) when compared to previous

diet studies of black crappie in Florida (Chable 1947; Reid 1949; Huish 1957; Ager 1975).

Previous studies all found empty stomachs to be > 14 % of the total stomachs examined. There

were individual periods, which had percentages of empty stomachs that were similar to what

previous studies found, particularly the August and October periods in Lake Monroe for 2002

and 2003.

These results suggest that black crappie are both opportunistic and selective in their

benthic macroinvertebrate feeding habits. Black crappie appeared to utilize various resources at

a greater extent when their densities were up, but consistently selected for certain taxa within a

lake throughout the study. Differences in diet shifts of black crappie among lakes existed









because of an additional resource and selection for that resource in Lake Monroe. This, in turn,

likely allowed Lake Monroe black crappie to obtain a larger size at age than black crappie at

Lakes Lochloosa and Marian. Contrarily, diet shifts and total prey consumption by black crappie

at Lakes Lochloosa and Marian were not different, although there were differences in growth

between systems. This was probably a result of density dependence, where Lake Marian had a

large population with slow growth and Lochloosa Lake had a small population with fast growth.









MANAGEMENT IMPLICATIONS

Stocking of black crappie at Florida water bodies is not a current management tool, but

there is potential for its use in the future. A factor which can influence the stocking success of

other fish is an adequate forage base, including zooplankton (Fielder 1992; Hoxmeier et al.

2004), macroinvertebrates, and prey fish (Axon and Whitehurst 1985; Stahl and Stein 1994;

Donovan et al. 1997; Pierce et al. 2001). Each forage group could play an important role in the

success of stocking programs, depending on the species, size, and diets of fish being stocked

(Hoxmeier and Wahl 2002). The results of this study show that prey availability can influence

the diet and growth of black crappie, and therefore future stocking programs of black crappie

should consider the prey base before initiating a program. For example, Lake Monroe may have

greater potential for stocking success of black crappie due to the additional prey taxa and fast

growth of black crappie at this system.










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BIOGRAPHICAL SKETCH

Travis Tuten is a second generation Floridian born in Orlando, FL on October 30, 1975.

He graduated from Colonial High School in 1993 and received an Associate of Arts degree from

Valencia Community College in April 1996. He started coursework at University of Florida in

1996 and graduated with a Bachelor of Science degree in wildlife ecology and conservation in

December 1998. Work took him to South Florida in April 1999, where he stayed 3 years as a

biological technician working in the Florida Everglades. He returned to Gainesville in January

2002 and began working on non-indigenous fish proj ects with the United States Geological

Survey (USGS). He started coursework towards his Master of Science degree in August 2002

and was hired by the Florida Fish and Wildlife Conservation Commission (FWC) in November

2002. His masters research on black crappie Pomoxis nigromaculatus diets and benthic food

availability was an opportunity to further his education while employed with FWC. After

graduation, he plans to continue conducting fisheries research in the state of Florida.