Testing models of increasing complexity to develop ecosystem‐informed fisheries advice

• DOI: 10.1111/faf.12820
• Publication Date: 2024-02-29T03:04:48Z
• Authors: Matthew D. Robertson; Noel G. Cadigan; Paul M. Regular; Mariano Koen‐Alonso; Frédéric Cyr; Fan Zhang; Tyler D. Eddy
• Keywords: Stock (firearms); Ecosystem-Based Management; Stock assessment; Population model; Fish stock; Ecosystem Management

Abstract Despite continued calls for the application of ecosystem‐based fisheries management, tactical management continues to be heavily reliant on single‐species stock assessments. These assessments rarely quantitatively integrate effects ecosystem processes fish productivity. This lack integration is ultimately driven by complexity interactions between populations, ecosystems and fisheries, which produces uncertainty when defining include how them. Models developed using a structured hypothesis testing framework would allow formalizing uncertainties while underscoring importance incorporating different population explain non‐stationary Here, we develop conceptual extending comparing dynamics models increasing complexity. We illustrate utility investigating that most likely affected differential recovery two flatfish populations (American plaice yellowtail flounder) Newfoundland Grand Banks over past three decades. found flounder were primarily recruitment variability, was negatively warmer climatological conditions, as indicated an integrated regional climate index. Meanwhile, American combination temporal variability in natural mortality, where mortality increased during colder than average conditions. By exploring hypotheses about dynamics, this modelling will improve understanding drivers shifts productivity serving transparent robust approach support management.