Causal modelling of climate-fish-fisheries: confronting models with data

Area of Science:

• Marine Ecology
• Fisheries Science
• Ecological Modelling

Background:

• Marine fish stock dynamics are influenced by complex interactions between environmental and anthropogenic factors.
• Interpreting past stock changes and predicting future trends necessitates understanding these drivers.
• Norwegian spring-spawning herring (NSSH) serves as a critical case study for fisheries management.

Purpose of the Study:

• To quantify the effects of climate and fisheries on NSSH stock biomass and catches.
• To apply a structured causal modelling framework for robust ecological inference.
• To investigate the interplay of recruitment, biomass, and total allowable catch (TAC) advice.

Main Methods:

• Utilized an iterative structured causal modelling framework.
• Combined causal knowledge analysis with structural equation models.
• Gradually incorporated multiple causal pathways, feedback loops, and confounders, emphasizing data structure integration.

Main Results:

• Final models explained over 90% of observed variation in NSSH biomass and catch.
• Found no causal effect of ocean climate variables (Relative Heat Content, Arctic Water Content) on NSSH biomass.
• Catch levels were primarily governed by TAC advice and international fishing agreements, not Spawning Stock Biomass.

Conclusions:

• Reliable causal inference in ecology demands iterative model refinement and explicit accounting for data structure.
• Fisheries management, particularly TAC advice and international cooperation, plays a dominant role in NSSH stock dynamics.
• This structured approach enhances ecological studies supporting sustainable fisheries management.