Quantifying Temporal Trends in Fisheries Abundance Using Bayesian Dynamic Linear Models: A Case Study of Riverine Smallmouth Bass Populations

Abstract

Detecting temporal changes in fish abundance is an essential component of fisheries management. Because of the need to understand short‐term and nonlinear changes in fish abundance, traditional linear models may not provide adequate information for management decisions. This study highlights the utility of Bayesian dynamic linear models (DLMs) as a tool for quantifying temporal dynamics in fish abundance. To achieve this goal, we quantified temporal trends of Smallmouth Bass Micropterus dolomieu catch per effort (CPE) from rivers in the mid‐Atlantic states, and we calculated annual probabilities of decline from the posterior distributions of annual rates of change in CPE. We were interested in annual declines because of recent concerns about fish health in portions of the study area. In general, periods of decline were greatest within the Susquehanna River basin, Pennsylvania. The declines in CPE began in the late 1990s—prior to observations of fish health problems—and began to stabilize toward the end of the time series (2011). In contrast, many of the other rivers investigated did not have the same magnitude or duration of decline in CPE. Bayesian DLMs provide information about annual changes in abundance that can inform management and are easily communicated with managers and stakeholders.

Redefining risk in data‐poor fisheries

“…Decisions on mitigation strategies rely on integration of vulnerability analyses with the needs of the communities that rely on the managed fishery. Corroborating vulnerability assessment provided by the PSA with local knowledge, trend analyses and extrapolation techniques can give a more complete picture of how to best prioritize research and management efforts (Finkbeiner et al., 2017; Frawley et al., 2019; Mason et al., 2019; Oestreich et al., 2019; Schall et al., 2018). Previous studies employing the existing PSA could benefit from re‐analysis to discover whether management priorities require shifts.…”

Reproductive health and endocrine disruption in smallmouth bass (Micropterus dolomieu) from the Lake Erie drainage, Pennsylvania, USA

“…Health issues, including mortality events of young-of-year (Smith et al, 2015;Walsh et al, 2018), as well as skin lesions (Blazer et al, 2020), a high prevalence of intersex (testicular oocytes; TO), and other signs of exposure to endocrine disrupting contaminants in adults (Blazer et al, 2014a) have been observed there. These have not only raised concerns of resource managers and the public but have also been associated with population declines (Schall et al, 2018a;Smith et al, 2015). To date, no single cause for the health anomalies has been identified; rather, poor water quality, complex mixtures of contaminants, and various pathogens and parasites have been identified as potential risk factors (Boonthai et al, 2018;Schall et al, 2018b;Walsh et al, 2018).…”