Exploring the Use of a Size‐Based Egg‐per‐Recruit Model for the Red Abalone Fishery in California

Abstract

AbstractEggs‐per‐recruit (EPR) models are widely used for management of invertebrate fisheries to provide guidance to managers about the magnitude of egg production for a given level of instantaneous annual fishing mortality (F). We constructed a deterministic size‐based EPR model that utilizes size‐specific natural mortality rates and egg production for red abalone Haliotis rufescens in California. We analyzed the sensitivity of the model to alterations in biological parameters, modeled the effect of incidental mortality of sublegal individuals on EPR, and modeled the effects of various management actions, including incorporation of a slot size limit, incorporation of a harvest refugium, and alternative legal minimum size limits. Model results were more sensitive to alterations in growth parameters and lower mortality estimates than to changes in upper mortality estimates or fecundity parameters. When F increased from 0.0 to 0.1 per year, EPR exhibited a large decline from 100% to 70%. Only the incorporation of a harvest refugium and an increase in the minimum size limit produced increases in the percent of maximum EPR. Implementing a slot limit of 152.4–203.2 mm maximum shell length (MSL) decreased the EPR value, indicating the importance of egg production by red abalone that are smaller than the current minimum size limit of 177.8 mm MSL. Because of the sensitivity of model predictions to changes in certain biological parameters, we recommend caution when applying EPR models to management, particularly for regions without spatially explicit parameter values. Despite this sensitivity, EPR models provide a heuristic framework for exploring the potential impacts of proposed fishery management strategies (e.g., harvest refugia), establishing biological reference points, examining how spatial and temporal variability in biological parameters affects egg production, and providing a guide for prioritizing research to improve data quality used for red abalone management.