Modeling Dynamics in Fisheries Management

Dynamic modelling forms the backbone of modern fisheries management by uniting population biology, economic incentives and policy constraints within quantitative frameworks. Early bioeconomic models captured the interplay between harvest effort and stock growth, revealing optimal exploitation rates, the tragedy of open-access regimes and the value of limited-entry licences. Advances in multi-species and spatially explicit approaches have since incorporated migration, habitat heterogeneity and recruitment variability, allowing managers to anticipate stock shifts under changing environmental conditions. Agent-based simulations further enrich this landscape by representing individual vessel behaviour, adaptive decision-making and fleet interactions, thereby uncovering emergent patterns of effort concentration, spill-over and effort displacement around closures. Structural behavioural models that embed quota markets and price equilibria have shed new light on the efficiency and distributive impacts of catch-share regimes, including unintended distortions arising from ecosystem-based measures. Together, these integrated tools support rigorous scenario testing, risk assessment and policy optimisation—addressing challenges such as transboundary stocks, irreversible capital investment and climate-driven regime shifts. By enabling the design of dynamic regulatory instruments—from seasonal effort controls and marine protected areas to adaptive closures and community-based cooperatives—modelling underpins global efforts to reconcile sustainable yields with ecological resilience and socio-economic well-being.

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Modeling Dynamics in Fisheries Management publication trend

The graph below shows the total number of articles in modeling dynamics in fisheries management across all publications each year (not limited to Nature Index journals).

Technical terms

Bioeconomic model: A quantitative framework that combines biological stock dynamics with economic decision-making to evaluate management outcomes.

Agent-based model: A simulation in which individual decision-making units (e.g. vessels or fishers) interact within a virtual ecological environment, producing emergent system behaviour.

Common-pool resource: A resource system characterised by non-exclusive access and subtractable use, prone to over-exploitation without collective governance.

Irreversible investment: Capital inputs (such as specialised vessels or gear) that cannot be recovered or redeployed once committed to the fishery.

Catch-share fishery: A rights-based management regime allocating individual or community quotas of total allowable catch, often coupled with tradable shares to coordinate harvest effort.

References

1. Over-capitalization in fisheries with irreversible investment and factor substitution. Ecological Economics (2025).
2. A computational approach to managing coupled human–environmental systems: the POSEIDON model of ocean fisheries. Sustainability Science (2018).
3. An agent‐based model to optimize transboundary management for the walleye pollock (Gadus chalcogrammus) fishery in the Gulf of Alaska. Natural Resource Modeling (2021).
4. Structural behavioral models for rights-based fisheries. Resource and Energy Economics (2022).