Accounting for spatial dependence improves relative abundance estimates in a benthic marine species structured as a metapopulation

Sea urchin (Loxechinus albus) is one of the most important benthic resource in Chile. Due to their large-scale spatial metapopulation structure, sea urchin subpopulations are interconnected by larval dispersion, so the recovery of local abundance depends on the distance and hydrodynamic characteristics of their spatial domain. Currently, this resource is evaluated with classical stock assessment models, using standardized catch per unit effort (an index of relative abundance) as a key piece of information to determine catch quotas and achieve sustainability. However, these estimates assume hyperstability for the total population, ignoring spatial dependence among fishing sites, which is a fundamental concept for populations structured as metapopulation. We develop a Bayesian catch standardization model with explicit spatial dependence to better address the structure of this population. The proposed model performs statistically better compared to a model without spatial dependence, based on leave-one-out cross-validation, and predictive distributions also show that parameter estimation is consistent with the data. We argue that incorporating spatial structure improves the estimated relative abundance index in a population structured as a metapopulation. Our improved index of abundance will lead to better assessments and management advice, thus improving the sustainability of the stock.

Automated summary

Sea urchin is an important benthic resource in Chile, with subpopulations interconnected through larval dispersion. Existing assessment methods overlook spatial dependence among populations, while a newly proposed Bayesian model with explicit spatial dependence shows statistical improvement and consistency with data, leading to better stock sustainability.