Playing the detective: Using multispecies approaches to estimate natural mortality rates

Abstract

Stock assessment models often assume natural mortality rates (M) are constant and attribute the variability in a stock’s overall mortality rate to variability in fishing mortality and recruitment. However, this assumption may not be valid if M varies due to both direct and indirect trophic interactions as well as environmental variability. This is particularly the case when there are substantial changes in the overlapping abundances of a key predator or prey species, or extreme environmental changes impacting an ecosystem. Hence multispecies models (MSMs) are used to explicitly capture variations in natural mortality rates and improve the ability to discriminate between mortality due to fishing versus natural mortality, plus quantify the influences of fishing on the broader ecosystem, consistent with an ecosystem approach to fishing (EAF). There are a growing number of approaches to modelling natural mortality rates in MSMs, with models developed for tactical applications requiring a higher level of rigour and consideration of uncertainty than broad strategic ecosystem models. We overview approaches to modelling natural mortality in Models of Intermediate Complexity for Ecosystem assessments (MICE) and use four case studies to highlight lessons learnt, applications and provide some guidelines going forward. We identify ten broad application categories for MSMs (incorporating explicit representation of components of M), to advance EAF. These include: (1) quantify variability in natural mortality by age and over time as inputs to single species stock assessment models, because of the recognition that predation mortality (M2) is a large and variable portion of total M; (2) inform ecosystem reference points; (3) use as operating models in Management Strategy Evaluation frameworks; (4) simulation test broader management levers; (5) optimise multispecies harvest strategies; (6) inform on management of bycatch and ‘choke’ species; (7) represent and forward project trajectories and model recovery scenarios for threatened and protected species; (8) correctly attribute sources of mortality to support management efforts; (9) pest management and (10) broader applications (e.g. habitat alterations). Using well-constructed MSMs to correctly specify M reduces bias in model parameters, reference points and projections and is increasingly important as ecosystems respond to a more variable and changing climate.