Working Towards a Framework for Stock Evaluations in Data‐Limited Fisheries

Abstract

Data‐limited approaches to managing fisheries are widespread in regions where insufficient data prevent traditional stock assessments from determining stock status with sufficient certainty to be useful for management. Where severe data limitations persist, a catch‐only approach is commonly employed, such as in the U.S. Caribbean region. This approach, however, has not received the level of scrutiny required to determine the potential long‐term risks (e.g., probability of overfishing) to fish stocks. In this study, we present a framework for comparison and implementation of data‐limited methods, including the static Status Quo approach, which uses average catch landings. Candidate species for stock evaluation were identified through a data triage and included Yellowtail Snapper Ocyurus chrysurus (Puerto Rico), Queen Triggerfish Balistes vetula (St. Thomas and St. John), and Stoplight Parrotfish Sparisoma viride (St. Croix). Feasible data‐limited methods, based on data availability and quality, included empirical indicator approaches using relative abundance (i.e., catch per unit effort) or mean length. Results from the management strategy evaluation support the use of adaptive data‐limited methods, which incorporate feedback in contrast to the static Status Quo approach. The proposed framework can help guide the development of catch advice for dynamic fisheries management in data‐limited regions.

Life history demographic parameter synthesis for exploited Florida and Caribbean coral reef fishes

“…mean) values (Ault et al, 2019;Carruthers et al, 2014;Methot & Wetzel, 2013;Sagarese et al, 2018). This information allows for the uncertainty in length at age and weight at age to be incorporated into stock assessments along with the respective expected (i.e.…”

“…This information allows for the uncertainty in length at age and weight at age to be incorporated into stock assessments along with the respective expected (i.e. mean) values (Ault et al, 2019;Carruthers et al, 2014;Methot & Wetzel, 2013;Sagarese et al, 2018). In contrast, parameter values (i.e.…”

“…Smooth Trunkfish (0) Bohnsack and Harper (1988) (2) (Sadovy et al, 1992); Rock hind (Burton et al, 2012); Dog snapper ; Pigfish (Taylor, 1916) TA B L E 6 (Continued) value for L m , the length at 50% maturity, whereas the length-at-maturity function and its uncertainty would be of much higher utility for stock assessments. This is especially critical for data-limited stock assessment packages such as DLMtool, which include data-limited approaches that require estimates of 50% and 95% maturity as well as estimates of their uncertainty (Carruthers et al, 2014;Sagarese et al, 2018). Future growth and maturity studies could also greatly benefit by employing parameter estimate procedures that minimize size-selection bias (Gwinn, Allen, & Rogers, 2010).…”

The interim management procedure approach for assessed stocks: Responsive management advice and lower assessment frequency

“…Assessment intervals have generally not been considered in a strategic context for managing fisheries, even though they can be crucial for successful fisheries management (Hutniczak, Lipton, Wiedenmann, & Wilberg, 2019; Wiedenmann, Wilberg, Sylvia, & Miller, 2017). Fixed TACs over long intervals amount to static management, which has been found to have poorer performance than adaptive management procedures (Harford & Carruthers, 2017; Sagarese et al, 2018; Shertzer & Prager, 2007). Static management also has implications for other exploited stocks in multispecies fisheries.…”

The Data‐Limited Methods Toolkit (DLMtool): An R package for informing management of data‐limited populations

“…The first practical applications of the package were in U.S. Federal fisheries (e.g., Sagarese, Rios, Cass‐Calay, & Cummings, ). It has since been applied to four fisheries by the California Department of Fish and Wildlife (CDFW) (Hordyk, Newman, Carruthers, & Suatoni, ).…”