Population Characteristics of Black Crappies in South Dakota Waters: A Case for Ecosystem-Specific Management

Abstract

We sampled 22 populations of black crappie Pomoxis nigromaculatus from three ecosystem types (large impoundments, >40 ha; small impoundments, ≤40 ha; natural lakes) to determine the factors that influence population characteristics (recruitment, growth, size structure, and condition) in South Dakota. Recruitment variability was best correlated with the log10 of the shoreline development index (r = 0.63, df = 16) and the log10 of the watershed : lake area ratio (r = 0.89, df = 12). Mean back-calculated length at age was highly variable among ecosystems and was inversely correlated with the log10 of the catch per unit effort (CPUE; r = –0.35 to –0.69). Mean back-calculated length for all ages was positively correlated with mean relative weight (r = 0.48–0.78, df = 18-21). Proportional stock density and relative stock density of preferred-length fish were inversely correlated with log10 CPUE (Spearman correlation, rs = –0.31 to –0.83, df = 21) and were positively correlated with growth of black crappies (rs = 0.55–0.73, df = 18–21 ). Bivariate centroids differed significantly (P ≤ 0.05) among ecosystems for canonical analysis; canonical factor scores were derived from growth, recruitment, CPUE, and condition. These data suggest that black crappie population characteristics differ among ecosystems. Natural lakes typically had black crappie populations with low density, unstable recruitment, fast growth rates, and high condition factors. Conversely, small impoundments had black crappie populations with high density, more stable recruitment, slow growth, and low condition factors. Black crappie population characteristics in large impoundments were typically intermediate between those of natural lakes and small impoundments. The differences observed in recruitment variability, growth, size structure, and condition of black crappie populations among ecosystems facilitate a better understanding of the factors that influence these variables and illustrate the importance of ecosystem-specific management.