Evaluation of Recently Implemented Harvest Regulations in a Data-Limited Catfish Fishery with Bayesian Estimation

Abstract

In 2015, the Illinois Department of Natural Resources changed size and harvest limits for catfishes (Blue Catfish Ictalurus furcatus, Flathead Catfish Pylodictis olivaris, and Channel Catfish I. punctatus) in the lower Ohio River to match those of neighboring states. The new regulations imposed a daily limit of one 88.9-cm (35-in) or larger Blue or Flathead Catfish per fisher, one 71.1-cm (28-in) or larger Channel Catfish per fisher, and a 33.0-cm (13-in) minimum length limit for all species, with no harvest restrictions between these limit lengths (permissive slot). When these management regulations were implemented, potential efficacy was unknown. The goal of this study was to evaluate the potential effects of these regulations using the limited data for baseline demographic parameters. Bayesian modeling was used to estimate growth and mortality because of the ability to estimate derived functions of parameters and associated uncertainty (as credible intervals). Yield-per-recruit (YPR) modeling was used to estimate and evaluate the fishing mortality rates (F) that would induce growth overfishing (FMAX) and the yield at FMAX (YPRMAX) for three management scenarios: no harvest restrictions (former regulation), a 33.0-cm minimum length limit, and the enacted permissive slot limits. Model results suggested that catfish stocks are unlikely to benefit from current regulations given the near-complete overlap of YPRMAX credible intervals for all estimable scenarios and the small significant differences (1–3%) based on FMAX between the most permissive and most restrictive scenarios. Despite the existence of significant differences in FMAX, they are likely biologically irrelevant based on the life histories of these species. Although modeling results suggested that the implemented harvest regulations will not likely affect catfish population demographics or fishery yield in the lower Ohio River, a post hoc evaluation examining the accuracy of these predictions is needed and would improve the accuracy and precision of parameter estimates.