North American Journal of Fisheries Management 18:854–863, 1998 q Copyright by the American Fisheries Society 1998
Use of Equilibrium Yield Models to Evaluate Length Limits for Crappies in Weiss Lake, Alabama MICHAEL J. MACEINA,* OZCAN OZEN,1
AND
MICHEAL S. ALLEN2
Department of Fisheries and Allied Aquacultures, Alabama Agricultural Experiment Station Auburn University, Alabama 36849, USA
STEPHEN M. SMITH Alabama Department of Conservation and Natural Resources Post Office Box 158, Eastaboga, Alabama 36260, USA Abstract.—We used a Beverton–Holt equilibrium yield model to predict the effects of four different length limits (203, 229, 254, and 279 mm) on harvest of black crappies Pomoxis nigromaculatus and white crappies P. annularis in Weiss Lake, Alabama. The current 254-mm length limit took effect in 1990, and we wanted to assess length limits with more recent data. We documented angler harvest and catch rates before and after the initiation of the size limit. Size structure, growth, and total mortality were estimated for fish collected with trap nets and by electrofishing. Growth was above average compared with other reservoirs in the state with fish reaching 254 mm in about 2.4 years. Estimates of total annual mortality ranged from 51% to 64% and annual exploitation was 33%, but because of uncertainty, a wide range of fishing and natural mortality rates were incorporated into the simulations. Three years after the length limit took effect, angler harvest and catch of crappies increased two–four fold and the size structure of the population was skewed towards smaller fish. However, recruitment indices showed production of strong yearclasses in the 1990s, compared with weak year-classes in the 1980s, which confounded interpretation of creel and size structure data and the effects of the length limit. Modeling indicated higher harvest in weight would be achieved with a 254-mm size limit only if conditional natural mortality was less than 35%. Yield benefits were comparable or decreased at higher length limits when conditional natural mortality rates were higher than 35%. We predicted substantially reduced numbers harvested at progressively higher natural mortality rates and increased length limits. The 254-mm minimum length limit for crappies in Weiss Lake appeared to provide potential benefits to the fishery. Yield (in weight) would increase because conditional natural mortality was probably less than 35%; however, the actual numbers of fish that anglers could keep would be reduced.
During the past decade, state regulatory agencies throughout the southeastern and midwestern USA have increasingly adopted minimum length limits for crappies Pomoxis spp. Previously, agencies set liberal bag and length limits because overexploitation was considered unlikely. However, with the advent of electronic fish finders, the popularization of crappies in fishing magazines, and the proliferation of new techniques to catch these fish year round when in the past only a spring spawning fishery existed, the potential for higher exploitation has led many agencies to set more restrictive bag and length limits. The success of minimum length limits on crappies has varied among water bodies (Colvin 1991; * Corresponding author:
[email protected] 1 Present address: Department of Zoology, North Carolina State University, Raleigh, North Carolina 27695, USA. 2 Present address: Department of Fisheries and Aquatic Sciences, University of Florida, 7922 Northwest 71st Street, Gainesville, Florida 36253–3071, USA.
Larson et al. 1991; Webb and Ott 1991; Mitzner 1995) and is dependent, in part, on growth and natural mortality. Allen and Miranda (1995) reported that conditional natural annual mortality averaged 49% for white crappies P. annularis from a review of previous studies, but that it was highly variable and ranged from 8% to 92%. High natural mortality alone, or in combination with poor growth rates, would negate any benefits of a relatively high minimum length limit on a crappie fishery (Allen and Miranda 1995). Hence, accurate information on mortality and growth rates appears necessary to evaluate the impact of length limits on crappie populations. In Weiss Lake, Alabama, a 254-mm total length limit, imposed in March 1990, was the first time a length limit was placed on harvesting crappies in Alabama. The basis for this length limit was to prevent overexploitation and protect adult fish during years when recruitment was poor. Weiss Lake supports a popular year-round crappie fishery. In this rural region in Alabama, about $11.3 million
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(21% of the local economic input) is derived from sportfishing on Weiss Lake (Bridges 1989). Recently, local concerns arose about the status of the crappie fishery and the feasibility of the existing length limit with support for lowering, retaining, or even raising it. In this paper, we evaluated the effect of this minimum length limit on angler catch and harvest rates and on the size structure of the crappie population in Weiss Lake. However, because crappie recruitment has been highly erratic in Weiss Lake and was related to water level fluctuations (Maceina and Stimpert 1998), we examined the associations among recruitment, population, and creel characteristics. To assess the impacts of different length limits on angler harvest while holding the effects of variable recruitment, we also conducted population simulations by using Beverton–Holt equilibrium yield models to estimate harvest for four different minimum length limits (203, 229, 254, and 279 mm). These length limits represent essentially no length limit (203 mm), the statewide minimum except in Weiss Lake (229 mm), the current minimum in Weiss Lake (254 mm), and a trophy-length regulation (279 mm). Methods Weiss Lake is an 11,247-ha impoundment of the Coosa River in northeast Alabama. The reservoir is shallow (mean depth at full pool, 3.1 m) and has an annual regulated water level fluctuation of 1.8 m that results in a 40% change in storage. Weiss Lake is eutrophic; the long-term growing season (April–October) chlorophyll a averaged 27 mg/L. Average annual retention time was 15 d but typically ranged from less than 8 d during winter low pool (January–March) to more than 25 d during summer full pool. From 1990 to 1996, crappies were collected with Indiana style trap nets (Smith et al. 1994) from 19 fixed stations during both October and November. Fish were removed after 24 h and fish and nets were removed after 48 h. Hence, total trap-net effort was 76 net-nights each year. Catch rate of age0 crappies from trap nets (N per net-night) was used as an index of recruitment. In Weiss Lake, crappie reproductive success was positively related to winter water levels prior to spawning (Maceina and Stimpert 1998). We predicted age-0 crappie catch from average water levels from 1 February to 31 March during 1982–1989. Water level data were obtained from Alabama Power Company. During March and April of 1992, 1993, and
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1996, crappies were collected with DC electrofishing from randomly selected areas. In spring 1993, some fish were collected with trap nets. Length-frequency histograms were constructed and compared with data collected by Reed and Davies (1991) for crappies collected with electrofishing and trap nets in 1988. Preferred and memorable relative stock densities (P-RSDs and M-RSDs) were computed by following the methods of Anderson and Neumann (1996); preferred and memorable lengths were greater than 25 and 30 cm total length, respectively. Fish were measured in total length (TL, mm) and weighed (g), and the sagittal otoliths were removed to estimate age according to procedures described by Maceina and Betsill (1987). In our analyses, we did not distinguish crappie species. Both black crappies and white crappies are sympatric in Weiss Lake, but natural hybridization occurred between these two species, and about 20% of the crappies are first-generation or higher hybrids (Smith et al. 1994; Travnichek et al. 1996). Crappie meristics do not provide a reliable means to separate crappie species in Alabama (Smith et al. 1995). Finally, a crappie fishery should be considered a homogenous population because anglers are likely to have difficulty identifying crappie species and a common length limit would have to apply to both species. Access point creel surveys were conducted at selected popular boat ramps around Weiss Lake from 1 March to 31 May for 1989–1993 and 1996. During this 3-month period, 8–12 weekend days were systematically chosen, and sites were randomly chosen and then surveyed for 8 h including 1 h after sunset. Anglers targeting crappies were identified, amount of fishing effort was summed, and the numbers of fish caught and harvested were recorded on each survey day. Mean-of-ratio estimates and associated variances (Malvestuto 1996) were computed, and one-way analysis of variance (ANOVA) and the Student–Newman–Keuls’ test were used to detect statistical differences (P , 0.05) among years. For data collected in 1988, a nonuniform roving creel survey was conducted from 1 March to 31 May 1988 (Reed 1990), and crappie effort and harvest were estimated. The reservoir was divided into five sections and three time periods and sampled once a day during 4 weekend days and 4 weekdays per month. The raw data for daily harvest and effort were not available, hence the mean-of-ratio estimate could not be computed and was not included in statistical analysis. Growth and weight-to-length relations were
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TABLE 1.—The population dynamic parameters and variables used to model and estimate yield for the crappie population from Weiss Lake, Alabama. Variable or parameter Recruitment Growth
Natural mortality
Exploitation
Definition Constant recruitment of 100 fish/year (N0) into the population at time t0 Coefficients for the von Bertalanffy equation: L` 5 330.97, k 5 0.716, t0 5 0.3054 Regression equation of weight (WT, g) to total length (TL, mm): WT 5 0.000001067TL3.494 Conditional rates of annual natural mortality were 25, 35, and 45% and started at age t0 Conditional rates of annual fishing mortality ranged from 10% to 60% at 5% intervals and started at age tr
computed for the most recent electrofishing data collected in 1996. We chose to use spring electrofishing data to compute growth because few older crappies were collected with trap nets, and trapnet data collected in the fall appeared to be skewed toward younger and slower-growing fish (Bales 1993). The length-at-age relation was described with the von Bertalanffy (1957) equation. Total annual mortality was estimated and compared by using five methods or data sets. Catchcurve regressions (Ricker 1975) were used to estimate instantaneous annual mortality (Z ) for 2– 6-year-old fish captured in fall 1995 with trap nets, 3–7-year-old fish captured in the spring with electrofishing, and for the dominant 1990 year-class captured from 1992 to 1995 with trap nets. Survival (S) was computed from e2Z and total annual mortality (A) equaled 1 2 S. Survival was also computed with Jackson’s method (Everhart and Youngs 1982): S 5 (N 3 1 N 4 1 N 5 )/(N 2 1 N 3 1 N 4 ), where Ni was the trap-net catch for age-i fish from the 1990 year-class. Finally, mortality was estimated from the spring 1996 sample with the formula from Gulland (1976): Z 5 k(L` 2 l c )/(l c 2 l r ); k 5 growth coefficient derived from the von Bertalanffy (1957) equation (Table 1); L` 5 maximum theoretical length from the von Bertalanffy (1957) equation (Table 1); l c 5 mean TL of capture from the sample (288 mm); and l r 5 minimum TL of recruitment to the current legal fishery (254 mm). Exploitation was computed for a 2-month period from 1 March 1997 to 30 April 1997 in conjunction with a crappie fishing derby. In mid-February 1997, 1,400 crappies greater than 254 mm were collected throughout the reservoir via DC electro-
fishing and tagged with a Floy T-bar tag with individual coded numbers inserted at the base of the dorsal fin. One hundred of these crappies were double-tagged to estimate tag loss. The entrance fee to participate in the crappie fishing derby was $5, prizes ranged in value from $10 to about $15,000, and all returned tags received a prize. In 1988, 68% of the fishing effort for crappies in Weiss Lake for the entire year was expended during March and April (Reed 1990) and was used to estimate annual exploitation from the 2-month period. Our modeling approach was similar to that of Allen and Miranda (1995) except they used hypothetical data and we used data collected from Weiss Lake. Determination of growth and a weight-to-length relation were relatively easy to derive for modeling. However, the separation of natural mortality from fishing mortality is time consuming and expensive and could be biased because of angler nonreporting or tag loss (Larson et al. 1991; Zale and Bain 1994; Maceina et al. 1998). In addition, highly variable recruitment was observed in Weiss Lake, which could lead to error when total annual mortality is derived from catchcurves (Allen 1997). We estimated total annual mortality and exploitation from organized fishing tournament data. Our approach attempted to determine the impact of size limits and to predict harvest at certain size limits when uncertainty in the accuracy of fishing and natural mortality rates existed. We estimated yield (Y ) by adapting Jones’ (1957) modification of the Beverton–Holt equilibrium yield model (Ricker 1975). Yield-per-recruit values were identical for our adaptation of Jones’ (1957) Beverton–Holt model and Jones’ (1957) modification. The formulas differ because we substituted N t for N 0 , which allowed us to evaluate the number of fish entering the fishery for a particular length limit after the initial population (N 0 ) was reduced by instantaneous natural mortality (M). The parameters and variables used to model the population, including ranges, are in Table 1 and were used in the equation Y5 F Nt M tr t0
5 5 5 5 5
F · N t · e Zr · W` [b(X, P, Q)]; K
instantaneous fishing mortality; N 0 · e2M(t r 2 t 0); instantaneous natural mortality; age of recruitment to the fishery; hypothetical age at which the fish length
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FIGURE 1.—Angler catch (filled circles) and harvest (open circles) rates of crappies from 1 March to 31 May in Weiss Lake, Alabama, 1989–1996. Annual ratio-ofmean estimates followed by the same letter within either catch or harvest (separate analyses) were not significantly different (P . 0.05). Raw data were not available from 1988 and not included in the statistical analysis.
Z5 r5 W` 5 b X P Q
5 5 5 5
would be 0 mm from the von Bertalanffy equation; M 1 F, or the instantaneous rate of total mortality; tr 2 t 0 ; asymptotic weight derived from L` and the weight : length relation; incomplete beta function; e2kr ; Z/k; and slope of the weight–length relation 1 1.
We computed b, which adjusted the yield for the weight–length relation, by using the GAMMA and PROBBETA functions of the SAS Institute (1988). The incomplete beta function was obtained from these functions by multiplying the beta probability by the complete beta functions, which are derived from the GAMMA function. This permitted more accurate estimates of yield than the incomplete beta function tables in Wilimovsky and Wicklund (1963). The number of fish harvested by anglers (Ncatch ) after reaching the minimum size was computed from (N t·F )/Z.
FIGURE 2.—Length-frequency and size structure indices of crappies collected with trap nets and by electrofishing during spring 1988, 1992–1993, and 1996 from Weiss Lake, Alabama; P 5 preferred length, M 5 memorable length, and RSD 5 relative stock density.
Results Creel Survey, Population Assessment, and Recruitment Catch rates of crappies increased after the initiation of the 254-mm length limit (Figure 1). Catch rates were about 2–4 times higher in 1992, 1993, and 1996 than from 1989 to 1991 (P , 0.05). By 1993, crappie harvest rates approximately doubled compared with those during 1988–1991, although no significant differences in harvest rate were detected among the years of 1989, 1993, and 1996. Nevertheless, the length limit was associated with higher crappie catch and appeared to increase harvest. The size structure of the crappie population was skewed towards smaller fish after 1990 because these fish were protected from harvest (Figure 2). The percentage of preferred-size fish and memo-
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rable-size fish declined in 1992–1993 and 1996 compared with 1988; only preferred-size or larger fish could be legally harvested after 1990. Age-0 catch rates of crappies from 1990 to 1996 were positively related to winter (February– March) water levels before spawning began (Figure 3). From the relation between water level and age-0 catch, predicted catch rates from 1982 to 1989, when no data were collected, were generally less than one fish per net-night from 1983 to 1988 (Figure 3). After 1989, catch rates of age-0 fish were generally higher than those predicted in the 1980s. Derivation of Parameters Used in Modeling Simulations In 1996 we collected 621 crappies that ranged in age and size from 1 to 7 years and from 125 to 358 mm. Growth in Weiss Lake was higher than the statewide average (Maceina et al. 1996). Fish reached 203, 229, 254, and 279 mm in 1.64, 1.95, 2.36, and 2.92 years, respectively, based on the von Bertalanffy (1957) relation (Table 1). The relation between weight (W ) and total length (TL) was W 5 0.000001067(TL 3.494 ). We estimated exploitation was 22.5% after adjustment for tag loss in 1997. Of the 1,400 crappies that were tagged, 258 fish were returned for prizes during the 2-month crappie derby. Four of the 22 double-tagged fish caught by anglers had lost one of their tags, thus tag retention was 81.8 6 17.2% (695% confidence interval). If 68% of the fishing effort for crappies was expended during March and April (Reed 1990), then this would confer an annual exploitation rate of 33%. However, exploitation rate was likely biased because the fishing derby encouraged increased fishing effort and the amount of angler effort expended during March– April 1997 was based on creel data collected in 1988. Estimates of annual mortality by using the five different methods or data sets ranged from 51% to 64%. Mortality was 59% with Jackson’s method for catch of the dominant 1990 year-class captured in fall trap nets from 1992 to 1995. Similarly, the mortality estimate was 59% for fish collected in spring 1996 with the length-frequency method of Gulland (1976). Three different catch curves were computed for data collected in 1995 and 1996 and mortality estimates ranged from 51% to 64% (Figure 4). Thus, these methods provided fairly consistent estimates of total annual mortality of crappies in Weiss Lake. Based on our estimates of exploitation and total
FIGURE 3.—(Top) The relation between average stage (water level in m above mean sea level, msl) in February and March and catch rates of age-0 crappies in Weiss Lake, Alabama. Numbers within the panel represent 1990–1996 year-classes. (Middle) Average stage in February and March in Weiss Lake from 1982 to 1996. (Bottom) Predicted catch (open circles) of age-0 crappies from the relation between age-0 catch and stage from 1982 to 1996 compared with observed catches (filled circles) from 1990 to 1996.
annual mortality, we modeled the effects of conditional fishing mortality rates (m 5 1 2 e2F ) ranging from 10% to 60% (5% intervals) and conditional natural mortality rates (n 5 1 2 e2M ) of 25, 35, and 45% (Table 1). This range of m encompassed the observed rate (m 5 1 2 e20.479 5 0.38) assuming total annual mortality (A) was 55% and F was 0.479, F 5 uZ/(1 2 S) 5 (0.33·0.799)/(1 2 0.45), where u is exploitation. If F was 0.479, then M 5 Z 2 F 5 0.799 2 0.479 5 0.32. This conferred a conditional natural mortality rate of 28%, which approximated the lower rate used in the model. We chose a maximum conditional natural mortality of 45% because, based on estimates of total mortality and even low levels of exploitation
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greater with 203- and 229-mm length limits than with 254- and 279-mm length limits. Although yields in weight were predicted to be greater with the 254- and 279-mm length limits than with smaller length limits at conditional natural mortality less than 35%, the number of fish harvested by anglers showed much more sensitivity to different length limits (Figure 6). For example, at a conditional natural mortality rate of 25%, about 23% and 11% more crappies would be harvested with the 203- and 229-mm limit, respectively, than a 254-mm length limit. At higher rates of conditional natural mortality, about 39% and 54% more crappies would be harvested with a 203-mm limit than with a 254-mm length limit with conditional natural mortality rates of 35% and 45%, respectively. With a 229-mm length limit, 20% and 27% more crappies would be harvested than if a 254-mm length limit was imposed at the intermediate and higher levels of conditional natural mortality. Finally, no increase in yield in weight was evident with the 279-mm length limit, but the number of fish harvested would be much less than with any other length limit. Discussion
FIGURE 4.—Catch curves for crappies collected in fall 1995 with trap nets (top panel) and in spring 1996 with electrofishing (middle panel) and for the dominant 1990 year-class at ages 2–5 years (bottom panel) in Weiss Lake, Alabama, 1990–1996; Z 5 instantaneous annual mortality, A 5 total annual mortality.
(i.e., less than 20%), conditional natural mortality probably did not exceed this level. We assumed a type II fishery (Ricker 1975) for which natural and fishing mortality rates were additive. Estimates of Yield and Number Harvested from Modeling At a conditional natural mortality rate of 25% and exploitation greater than about 25%, yield in weight was nearly identical for the 254- and 279mm length limits and was higher with these than with 229- or 203-mm length limits (Figure 5). At a conditional natural mortality rate of 35% and exploitation rates greater than 30%, yield estimates were higher with 229- and 254-mm length limits than with 203- or 279-mm length limits. At a conditional natural mortality rate of 45%, yields were
The results of the creel survey suggested that the 254-mm length limit provided a substantial increase in the catch and harvest of crappies from Weiss Lake. A higher proportion of fish shorter than 254 mm were present after the length limit was imposed. Angler catch and harvest increased in 1992 and 1993 as the strong 1990 year-class was recruited into the fishery. In contrast, sizes of crappies were skewed towards larger fish and angler catch rates of crappies were lower in Weiss Lake from 1988 to 1991 in response to poor recruitment that probably occurred in the 1980s. We could not determine if relative abundance of crappies greater than 203 mm increased after the length limit was imposed because no data were available before 1990. Population simulations indicated that the 254mm length limit on crappies would not adversely affect yield in weight if conditional natural mortality was 35% and could increase yield if conditional natural mortality was lower. Conditional natural mortality rates were probably less than 35% in Weiss Lake. However, yield would be only 5% greater with the 254-mm length limit than with the statewide 229-mm length limit when exploitation was high. In addition, anglers would harvest fewer fish with length limits greater than 203 mm, though the fish harvested would be larger. A length
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FIGURE 5.—Yield per recruit plotted against exploitation for three different levels of conditional natural mortality (n) in Weiss Lake, Alabama. Numeric values of 203, 229, 254, and 279 represent minimum length (mm) limits.
limit of 279 mm could reduce yield at a conditional natural mortality higher than 25%. Our results suggested that 254-mm length limits could reduce yield more than was suggested by Allen and Miranda (1995). Allen and Miranda (1995) found that yields could increase with a 254mm length limit if conditional natural mortality was less than 30–40% and fish could reach 254mm TL within 2.9 years. In Weiss Lake, crappie growth was faster because fish reached 254 mm in 2.4 years, but yield would not increase unless conditional natural mortality was less than 35%. However, yield was greater with 229- and 254-mm length limits than with a 203-mm length limit. Colvin (1991) used a Thompson and Bell (Ricker 1975) yield-per-recruit model and predicted that protecting age-2 fish from harvest until they reached age 3 (25 cm) would increase yield by 10% but reduce harvest number by 16% if growth was adequate in Missouri reservoirs. However,
Colvin (1991) used a conditional natural mortality rate of only 13% for age-2 and older fish, which was much lower than the average conditional natural mortality rates used by Allen and Miranda (1995) and by us (this study). Mitzner (1995) simulated harvest of crappies from an Iowa reservoir and predicted that 229- and 254-mm length limits would drastically reduce yield. However, crappies grew much slower in the reservoir studied by Mitzner (1995) and took more than 5 years to reach 254 mm. Reed and Davies (1991) determined exploitation and total mortality in Weiss Lake and concluded that natural mortality was high, which implied a length limit would not benefit the fishery. From the data presented by Reed and Davies (1991), we computed a conditional natural mortality rate of 38%, and our modeling indicated that a 229- and 254-mm length limit could slightly increase yield if exploitation was high at a conditional natural
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FIGURE 6.—Predicted number of crappies harvested by anglers plotted against exploitation for three different levels of conditional natural mortality (n) in Weiss Lake, Alabama. Numeric values of 203, 229, 254, and 279 mm represent minimum length (mm) limits.
mortality rate of 35% or less. Finally, our growth rates were higher than those reported by Reed and Davies (1991), which might have been due to differences in ages estimated from otoliths and scales. Length limits potentially can provide for greater yields when growth rates are faster. Our modeling approach permits fishery biologists to evaluate the effects of alternative length limits on angler harvest and yield within a range of natural mortality. Our estimates of conditional fishing and natural mortalities were subject to error, but the ranges we used probably included actual rates in Weiss Lake. In addition, the success or failure of a crappie length limit may be misjudged when using population or creel survey data that are influenced by highly variable recruitment. A modeling approach can assume constant recruitment and predict long-term effects of a regulation on harvest. Colvin (1991) reported that
poor year-class formation prevented an accurate assessment of a crappie length limit, and although Webb and Ott (1991) found a 254-mm minimum length limit improved crappie fisheries, their evaluation after the limit was imposed in three reservoirs was short in duration (3–4 years). In Weiss Lake, interpretation of creel data indicated strong improvement in the fishery after implementation of the minimum length limit. However, lower catch rates before the minimum length limit was imposed were probably due to weak recruitment. Harvest simulations showed modest improvement in yield with a minimum length limit but not as great as inferred from the creel data. Wilde (1997) recommended that longer posttreatment evaluation is necessary to evaluate effects of length limits. Simulation modeling prior to the decision-making process can provide one tool to predict effects of minimum length limits, and subsequent collection of
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field data can verify or refute the results of modeling. In conclusion, we found that the 254-mm length limit could increase crappie yield in Weiss Lake. Creel survey data showed catch and harvest was higher after initiation of the length limit but was influenced by greater reproductive success. If slower growth or higher natural mortality of crappies occurs, then this minimum length limit could reduce yield. However, we predicted the number of fish harvested by anglers with the 254-mm length limit was reduced. In many instances, fishery biologists assume higher yield in total weight is a desired goal of anglers, but preference for higher numbers of fish may also be desired. Knowledge of angler preference would assist in the decision-making process when minimum length limits are being considered. Finally, although many state agencies have adopted minimum length limits for crappies, our analyses agree with Allen and Miranda (1995) that results depend on rates of growth and natural mortality. Our simulation approach provides managers with an additional tool to assess the potential success of minimum length limits. Acknowledgments Funding for this project was provided by the Alabama Department of Conservation and Natural Resources, Game and Fish Division, through Federal Aid in Sport Fish Restoration Projects F-38 and F-40. The manuscript was improved with assistance from J. Boxrucker, J. Slipke, S. Szedlmayer, and an anonymous reviewer. This paper is journal number 8-985924 of the Alabama Agricultural Experiment Station. References Allen, M. S. 1997. Effects of variable recruitment on catch-curve analysis for crappie populations. North American Journal of Fisheries Management 17: 202–205. Allen, M. S., and L. E. Miranda. 1995. An evaluation of the value of harvest restrictions in managing crappie fisheries. North American Journal of Fisheries Management 15:766–772. Anderson, R. O., and R. M. Neumann. 1996. Length, weight, and associated structural indices. Pages 447–482 in B. R. Murphy and D. W. Willis, editors. Fisheries techniques, 2nd edition. American Fisheries Society, Bethesda, Maryland. Bales, C. W. 1993. Assessing reservoir crappie populations with trap nets and electrofishing gear. Master’s thesis. Auburn University, Auburn, Alabama. Bridges, W. L. 1989. Economic assessment of the Lake
Weiss fishery business community. Master’s thesis. Auburn University, Auburn, Alabama. Colvin, M. A. 1991. Evaluation of minimum-size limits and reduced daily bag limits on the crappie populations and fisheries in five large Missouri reservoirs. North American Journal of Fisheries Management 11:585–597. Everhart, W. H., and W. D. Youngs. 1982. Principles of fishery science, 2nd edition. Cornell University Press, Ithaca, New York. Gulland, J. A. 1976. Manual of methods for fish stock assessment. Part 1, fish population analysis. Food and Agriculture Organization of the United Nations, Rome. Jones, R. 1975. A much simplified version of the fish yield equation. International Commission for the Northwest Atlantic Fisheries, International Council for the Exploration of the Sea, and Food and Agriculture Organization of the United Nations, Document P. 21, Lisbon. (Not seen; cited in Ricker 1975.) Larson, S. C., B. Saul, and S. Schleiger. 1991. Exploitation and survival of black crappies in three Georgia reservoirs. North American Journal of Fisheries Management 11:604–613. Maceina, M. J., and R. K. Betsill. 1987. Verification and use of whole otoliths to age white crappie. Pages 267–278 in R. C. Summerfelt and G. E. Hall, editors. Age and growth of fish. Iowa State University Press, Ames. Maceina, M. J., P. W. Bettoli, S. D. Finely, and V. J. DiCenzo. 1998. Analysis of the sauger fishery with simulated effects of a minimum size limit in the Tennessee River of Alabama. North American Journal of Fisheries Management 18:66–75. Maceina, M. J., and five coauthors. 1996. Compatibility between water clarity and quality black bass and crappie fisheries in Alabama. Pages 296–305 in L. E. Miranda, and D. R. DeVries, editors. Multidimensional approaches to reservoir fisheries management. American Fisheries Society, Symposium 16, Bethesda, Maryland. Maceina, M. J., and M. R. Stimpert. 1998. Relations between reservoir hydrology and crappie recruitment in Alabama. North American Journal of Fisheries Management 18:66–75. Malvestuto, S. P. 1996. Sampling the recreational creel. Pages 591–624 in B. R. Murphy and D. W. Willis, editors. Fisheries techniques, 2nd edition. American Fisheries Society, Bethesda, Maryland. Mitzner, L. R. 1995. Effects of environmental factors and harvest regulations upon the crappie (Pomoxis) sportfishery at Rathbun Lake. Iowa Department of Natural Resources, Technical Bulletin 5, Des Moines. Reed, J. R. 1990. Determination of appropriate management strategies for crappie populations in Weiss Reservoir, Alabama. Master’s thesis. Auburn University, Auburn, Alabama. Reed, J. R., and W. D. Davies. 1991. Population dynamics of black crappies and white crappies in Weiss Reservoir, Alabama: implications for the im-
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plementation of harvest restrictions. North American Journal of Fisheries Management 11:598–603. Ricker, W. E. 1975. Computation and interpretation of biological statistics in fish populations. Fisheries Research Board of Canada Bulletin 191. SAS Institute. 1988. SAS language guide for personal computers, release 6.03. SAS Institute, Cary, North Carolina. Smith, S. M., M. J. Maceina, and R. A. Dunham. 1994. Natural hybridization between black crappie and white crappie in Weiss Lake, Alabama. Transactions of the American Fisheries Society 123:71–79. Smith, S. M., M. J. Maceina, V. H. Travnichek, and R. A. Dunham. 1995. Failure of quantitative phenotypic characteristics to distinguish black crappie, white crappie, and their first-generation hybrid. North American Journal of Fisheries Management 15:121–125. Travnichek, V. H., M. J. Maceina, S. M. Smith, and R. A. Dunham. 1996. Natural hybridization between black and white crappies (Pomoxis) in 10 Alabama
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reservoirs. American Midland Naturalist 135:310– 316. von Bertalanffy, L. 1957. Quantitative laws of metabolism and growth. Quarterly Review of Biology 32: 217–231. Webb, M. A., and R. A. Ott. 1991. Effects of length and bag limits on population structure and harvest of white crappies in three Texas reservoirs. North American Journal of Fisheries Management 11: 614–622. Wilde, G. R. 1997. Largemouth bass fishery responses to length limits. Fisheries 22(6):14–23. Wilimovsky, N. J., and E. C. Wicklund. 1963. Tables of the incomplete beta function for the calculation of fish population yield. University of British Columbia, Vancouver. Zale, A. V., and M. B. Bain. 1994. Estimating tag-reporting rates with postcards as tag surrogates. North American Journal of Fisheries Management 14: 208–211. Received October 14, 1997 Accepted April 29, 1998
