This analysis finds that integer linear programming identifies key conservation areas in marine ecosystems, suggesting improved strategies for marine biodiversity protection.
Intense human activities negatively impact marine ecosystems, creating an urgent need for effective strategies to safeguard marine biodiversity and ecosystem services. Systematic conservation planning has become a key approach to identify priority areas and designing management measures. The Marxan software, based on simulated annealing (SA) algorithms, is widely used in this context. However, recent advances in integer linear programming (ILP), as implemented in the prioritizr R package, offer a promising alternative with enhanced computational efficiency and improved solution quality. In this study, we compare prioritisation solutions generated using SA (Marxan) and ILP (prioritizr) for the Weddell Sea Marine Protected Area Phase 1 (WSMPA P1), one of four Marine Protected Areas (MPAs) currently proposed and under negotiation by the Commission for the Conservation of Antarctic Marine Living Resources (CCAMLR). The planning area includes 57,077 hexagonal planning units covering almost 3 million km² and 54 conservation features, alongside a cost metric reflecting potential Antarctic toothfish fisheries interests. Three conservation target scenarios - minimum, mixed, and medium - were evaluated to assess the performance of both approaches. Our results show that both methods identify largely overlapping priority areas. However, ILP solutions consistently exhibit less spatial fragmentation, smaller total area, lower costs, resulting in more compact and cost-efficient reserve designs. Computational times were comparable for the minimum and mixed target scenarios; for the medium scenario, prioritizr required moderately more processing time. These findings highlight the benefits of ILP for systematic conservation planning, particularly in real-world contexts requiring rapid, iterative adjustments during stakeholder consultations and political negotiations. Our study suggests ILP-based methods as a valuable alternative to SA for the WSMPA P1 planning process, thereby strengthening the scientific foundation for effective marine conservation strategies.
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