Minimum data requirements for designing a set of marine protected areas, using commonly available abiotic and biotic datasets |
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Authors: | Natalie C Ban |
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Institution: | (1) Fisheries Centre/Project Seahorse, University of British Columbia, 2202 Main Mall, Vancouver, BC, Canada, V6T 1Z4;(2) Australian Research Council Centre of Excellence for Coral Reef Studies, James Cook University, Townsville, QLD, 4811, Australia |
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Abstract: | Marine protected areas (MPAs) can be an effective tool for marine biodiversity conservation, yet decision-makers usually have
limited and biased datasets with which to make decisions about where to locate MPAs. Using commonly available abiotic and
biotic datasets, I asked how many datasets are necessary to achieve robust patterns of conservation importance. I applied
a decision support tool for marine protected area design in two regions of British Columbia, Canada, and sequentially excluded
the datasets with the most limited geographic distribution. I found that the reserve selection method was robust to some missing
datasets. The removal of up to 15 of the most geographically limited datasets did not significantly change the geographic
patterns of the importance of areas for conservation. Indeed, including abiotic datasets plus at least 12 biotic datasets
resulted in a spatial pattern similar to including all available biotic datasets. It was best to combine abiotic and biotic
datasets in order to ensure habitats and species were represented. Patterns of clustering differed according to whether I
used one set alone or both combined. Biotic datasets served as better surrogates for abiotic datasets than vice versa, and
both represented more biodiversity features than randomly selected reserves. These results should provide encouragement to
decision-makers engaged in MPA planning with limited spatial data. |
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Keywords: | Biodiversity surrogates Data limitations Marine conservation Marine reserves Marxan Selection algorithm Systematic conservation planning |
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