Using Forecasting Methods to Incorporate Social, Economic, and Political Considerations Into Marine Protected Area Planning
As the global environmental crisis grows in scale and complexity, conservation professionals and policymakers are increasingly called upon to make decisions despite high levels of uncertainty, limited resources, and insufficient data. Global efforts to protect biodiversity in areas beyond national jurisdiction require substantial international cooperation and negotiation, both of which are characterized by unpredictability and high levels of uncertainty. Here we build on recent studies to adapt forecasting techniques from the fields of hazard prediction, risk assessment, and intelligence analysis to forecast the likelihood of marine protected area (MPA) designation in the Southern Ocean. We used two questionnaires, feedback, and a discussion round in a Delphi-style format expert elicitation to obtain forecasts, and collected data on specific biophysical, socioeconomic, geopolitical, and scientific factors to assess how they shape and influence these forecasts. We found that areas further north along the Western Antarctic Peninsula were considered to be less likely to be designated than areas further south, and that geopolitical factors, such as global politics or events, and socioeconomic factors, such as the presence of fisheries, were the key determinants of whether an area was predicted to be more or less likely to be designated as an MPA. Forecasting techniques can be used to inform protected area design, negotiation, and implementation in highly politicized situations where data is lacking by aiding with spatial prioritization, targeting scarce resources, and predicting the success of various spatial arrangements, interventions, or courses of action.
Sykora-Bodie, ST; Álvarez-Romero, JG; Arata, JA; Dunn, A; Hinke, JT; Humphries, G; Jones, C; Skogrand, P; Teschke, K; Trathan, PN; Welsford, D; Ban, NC; Murray, G; Gill, DA
Volume / Issue
Electronic International Standard Serial Number (EISSN)
Digital Object Identifier (DOI)