The effects of implementing a ?dynamic B0? harvest control rule in Australia?s Southern and Eastern Scalefish and Shark Fishery

The harvest control rules for many fish and invertebrate stocks, managed using stock assessments based on fitting population dynamics models to monitoring data, rely on biological reference points. These reference points are often related to unfished conditions ('B0') and are calculated assuming that biological parameters and their associated functional forms (e.g., unfished recruitment ('R0'), natural mortality, growth) are stationary. However, there is increasing evidence that the assumption of stationarity is untenable in the face of environmental change. In principle, non-stationarity can be addressed by defining stock status (i.e., spawning biomass relative to unfished spawning biomass) using 'dynamic B0' (the spawning biomass that would be expected in the absence of fishing). We show how catch limits (Recommended Biological Catches) for stocks in Australia's Southern and Eastern Scalefish and Shark Fishery would have differed had management been based on dynamic B0. We also explore the performance of static and dynamic B0-based harvest control rules using simulations where various biological parameters (R0, B0, L infinity, kappa, natural mortality, and stock-recruitment steepness) exhibit trends over time. The results confirm previous work that the implications of adopting a dynamic B0 approach would differ among species, with quite major changes in stock status and catch limits for some species and negligible changes for others. In terms of management performance in projections, there are species-specific trade-offs, with a dynamic B0 approach tending to lead to higher catches, lower biomass on occasion and less inter-annual variation in catches than a static B0 approach. The implications of harvest control rules based on static and dynamic B0 also differ depending on which biological parameter is changing over time.

Automated summary

The study suggests that harvest control rules based on stationary assumptions may not be accurate in the face of environmental change. Adopting a dynamic B0 approach could lead to significant changes in stock status and catch limits for different species, with species-specific trade-offs in management performance.