MPAs represent one of the most widely implemented spatial management tools in marine conservation, yet predicting their ecosystem-wide effects requires modelling to understand the complex interactions between MPA design choices and ecological processes. The fundamental question in MPA evaluation centers on spillover effects—whether biomass production increases within protected areas and subsequently spills over to adjacent fishing grounds—with dispersal rates serving as the critical parameter determining these outcomes in spatial models like Ecospace. Today's session will use the modified Anchovy Bay model to explore how alternative MPA configurations interact with species dispersal patterns, habitat preferences, and fishing effort redistribution to shape conservation and fisheries outcomes, while addressing the challenge of parameter uncertainty that makes real-world MPA design so complex yet essential for evidence-based marine spatial planning.
Spillover effects and dispersal dynamics. The relationship between species dispersal rates (km/year) and biomass spillover from protected to fished areas, including how dispersal parameter uncertainty affects MPA effectiveness predictions.
Spatial design trade-offs (SLOSS). Comparing Single Large Or Several Small MPAs in terms of biodiversity protection, ecosystem resilience, and fisheries sustainability, considering species-specific habitat requirements and dispersal patterns.
Protection level strategies. Evaluating no-take versus multi-use MPAs and fleet-specific enforcement scenarios to understand how different restriction levels affect ecosystem-wide outcomes and stakeholder compliance.
Trophic cascades and food web effects. How MPAs influence predator recovery and subsequent cascading effects throughout the food web, including impacts on bycatch species like sneaker shark and goldfish in the trawl fishery.
Effort displacement and fishing fleet responses. Understanding how fishing effort redistributes spatially when MPAs are implemented, and the implications for catch rates, economic outcomes, and conservation effectiveness in surrounding areas.
Model uncertainty and parameter sensitivity. Assessing the reliability of MPA predictions by testing sensitivity to key parameters (especially dispersal rates), identifying data gaps, and determining when additional field studies or model refinements are needed for policy applications.
This session will provide an introduction to and experience with how to:
Build and run a spatial-temporal Ecospace scenario and extract region-specific biomass and catch indicators.
Analyze how alternative MPA configurations (size, number, placement, access rules) interact with species dispersal to shape inside-vs-outside outcomes (“spill-over”).
Diagnose model behaviour by linking parameter choices (especially dispersal, habitat preference and effort redistribution) to ecological mechanisms and observed results.
Compare scenarios quantitatively and articulate trade-offs among conservation, fisheries yield and bycatch reduction in a form useful to managers.
Critically assess model uncertainty and identify additional data or analyses (e.g., field tagging, sensitivity tests, spatial optimization) needed before applying results to real-world policy.
Please prepare for the session by reading the following.
MPA effectiveness chapter.
MPA chapter.