The SPoRC Stock Assessment Package: A Generalized Next-Generation Platform to Assess Spatial, Age and Sex-Structured Populations Fish and Fisheries

Fisheries managers increasingly rely on stock assessment models to provide sustainable management advice, which must balance complex and competing objectives. Although assessment models necessitate simplifying assumptions, there is increasing recognition to improve the integration of realistic biological and fishery dynamics. While ongoing and future development of increasingly complex stock assessments requires increased capacity (i.e., time, training, and personnel), there are concerns that the growing demand for assessment advice cannot be adequately fulfilled under current resources. To address these needs, we present the Stochastic Population over Regional Components (SPoRC) model, a modern integrated analysis platform that is generalized, modular and developed in a user‐friendly programming language (R with Template Model Builder, RTMB). Development of SPoRC emphasized consideration of age, sex, and spatial dynamics at the outset, while ensuring the ability to integrate diverse data sources (e.g., catch, abundance indices, age/length compositions and tagging). Moreover, state‐space specification of time‐varying processes through random effects and robust simulation capabilities were primary design features. Here, we highlight SPoRC's utility in cohesively implementing single‐and multi‐region applications, its ability to estimate time‐varying processes as random effects, and the potential to conduct closed‐loop simulations for evaluating the robustness of management procedures. By developing a generalized assessment platform in a user‐friendly R package, we suggest that SPoRC reduces barriers to implementation of next‐generation stock assessment models and facilitates team‐based model development, which will ultimately help improve the capacity to implement stock assessments globally.