A multi-criteria method for making tradeoffs and hard decisions spatially explicit in marine conservation planning

Agapito, Melinda T. (2016) A multi-criteria method for making tradeoffs and hard decisions spatially explicit in marine conservation planning. Doctoral (PhD) thesis, Memorial University of Newfoundland.

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Abstract

Identifying new marine protected areas (MPAs) typically requires considering competing priorities from a large range of stakeholders. While balancing socioeconomic losses with biodiversity gains is challenging, it is central to the planning process and will influence the effectiveness of the MPAs to be created. This paper presents a new decision-support method named Spatial Tier Framework-Ordered Weighted Averaging (STF-OWA) that allows stakeholders to share their values and explore alternative planning scenarios, by varying levels of losses and gains, in a collaborative setting. Unlike methods that aim at finding one optimal solution (e.g. Marxan), the STF-OWA provides stakeholders with alternative planning options based on weights reflecting their priorities among and between biodiversity interests (e.g. corals vs. birds) and socioeconomic interests (e.g. fishing employment vs. fishing dollars). The approach was tested in the Newfoundland and Labrador shelf bioregion, Atlantic Canada (~1.2x106 km²), using scientific survey data on groundfish, seabirds, and habitat-forming invertebrates, commercial fishing logbooks, data on marine transportation, and oil and gas activities. Results show that the STF-OWA can identify easy-to-implement conservation sites (i.e. high biodiversity with low socioeconomic activities), although they represent only <5% of the analyzed area. Subsequently, the STF-OWA demonstrated that identifying >5% of the study area as an MPA often involves hard decision areas (i.e. sites with both high socioeconomic impacts and high biodiversity gains). On making tradeoffs and hard decisions spatially explicit, the STF-OWA: (1) offers various options such as cheap, cost-effective, and expensive scenarios, making the toughest conservation decisions spatially explicit -- namely, tough decisions for and against biodiversity protection and tough decisions for and against socioeconomic protection; (2) allows visualizing multiple competing interests in a solution set that provides empirical evidence that a win-win option is rare; and (3) permits delineating regions of interest (ROIs) and percent area targets within a conservation scenario that makes balancing loss and gain more spatially explicit at a finer scale. With these features available in the STF-OWA decision-support method, it is possible to identify not only the areas that minimize potential conflicts, but also areas of high importance for biological protection, and to do so without masking the tough political decisions needed in advancing conservation goals.

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