Smoothing over “rough” mismanagement: Establishing protective harvest limits for native nongame fishes

Abstract There is growing interest in establishing more protective regulations for native fishes that historically have been classified as “rough fish,” a term ascribed to species of low-to-zero commercial value. Yet high-quality population data are lacking for most species and populations, precluding the determination of sustainable harvest limits using standard methods. Here, we present an inductive and ecosystem-based approach for comparing and aligning harvest limits of diverse fish species. Our approach centers on the production/biomass (P/B) ratio as the main instrument for gauging sustainable harvest. Production/biomass is the biomass turnover rate in populations and, therefore quantifies the return rate of any removed biomass in populations. We extracted and summarized data from existing studies, representing a total of 517 empirical estimates of secondary production, biomass, and P/B ratios. We subsequently developed a highly predictive statistical model (R2 = 0.90), demonstrating that P/B is largely a function of maximum age across species. We then developed a separate database on age, growth, and longevity data for most native fishes of interest across the United States. For each species and population, we leveraged the above statistical model to predict and compare mean P/B across species. The results show that most native fishes express P/B values that are similar to or lower than those for traditional game fish species. Accordingly, harvest limits across species groups can be harmonized with those of other managed species. For example, native nongame species like Bigmouth Buffalo Ictiobus cyprinellus and Freshwater Drum Aplodinotus grunniens are long-lived with slow replacement rates that are statistically clustered with those observed in Lake Sturgeon Acipenser fulvescens and trophy Muskellunge Esox masquinongy populations, two popular game fish species. Harvest limits for these nongame species would therefore need to be similarly low for these species to ensure comparable sustainability. To understand broad patterns of harvest limit alignment, we modeled relationships between daily bag limits of managed species and P/B for five test states. The models uniformly showed nonlinear trends with high residuals (suggesting excessive bag limits) being common for panfish species and low residuals (suggesting overly conservative bag limits) being common for trout species. Managers can adapt the results and approach from this study to complement the social limit-setting process, especially in absence of more robust biological data.