Understanding biological and socioeconomic tradeoffs of marine reserve planning via a flexible integer linear programming approach. (January 2020)

• Record Type: Journal Article
• Authors: Oyafuso, Zack S.; Leung, PingSun; Franklin, Erik C.
• Is Part Of: Biological conservation. Volume 241(2020)
• Publication Date: 2020-01
• Subjects: Multiple-Criteria Decision Making (MCDM) -- Integer Linear Programming (ILP) -- Reserve selection models -- Marine protected areas -- Fisheries; Conservation of natural resources -- Periodicals; Nature conservation -- Periodicals; Ecology -- Periodicals; Environment -- Periodicals; Environmental Pollution -- Periodicals; Electronic journals; 333.9516
• DOI: 10.1016/j.biocon.2019.108319
• Languages: English
• ISSNs: 0006-3207

Abstract

Highlights: A reserve selection model was designed to identify bioeconomic tradeoffs. Compromise solutions can offer protection without steep socioeconomic impacts. Economic data was important for accounting for the opportunity cost of reserves. The equity of reserve benefits and costs across space was analyzed. Protecting only indicator species lowered overall conservation value of reserves. Abstract: Analyzing tradeoffs among ecological, economic, and management goals with respect to marine reserve network design is an important facet of systematic conservation planning. We designed an integer linear programming model to quantify tradeoffs among five marine reserve network aspects: ecological conservation value, economic opportunity cost, geographic domain size, total reserve area, and reserve spatial compactness. Using ecological and economic data from the Hawaiian deepwater bottomfish fishery as a case study, an integer linear programming model was designed to choose areas that 1) maximize conservation value and 2) minimize opportunity cost, defined as foregone fisheries revenue. Compromise solutions that equally weighted conservation value and opportunity cost resulted in solutions with dramatically lower foregone fisheries revenue and a relatively small loss in conservation value compared to solutions with the maximum conservation value. When opportunity cost was assumed uniform across the spatial domain, solutions had considerably higher foregone revenue for a given level of conservation value, highlighting the drawback of not including a spatially explicit metric of opportunity cost in reserve selection models. Inclusion of only indicator species, rather than the entire species complex, in the optimization led to considerable representation gaps in conservation value for non-included species. We found that optimizations performed at the archipelago scale provided geographically disproportionate reserve allocations and thus disproportionate conservation benefits and socioeconomic impacts across geopolitically distinct island regions. We showed how reserve selection models can be used to support systematic conservation planning exercises characterized by many diverse and conflicting objectives and parties.