Spatial nestedness of conservation priorities

Full description

This dataset contains information on the degree to which fine-resolution priorities (determined with small planning units) were spatially nested within all coarse-resolution priorities (determined with large planning units). All coarse-resolution priorities were evaluated against two test scenarios, of the highest resolutions possible. Coarse-scenario and test ("best") scenario codes reflect those used in publication to which these datasets relate. SF is an abbreviation for selection frequency; high-priority areas were defined at two levels. Percentage values represent the percentage small high-priority planning units from each of the test scenarios that overlapped with high-priority large planning units from the ten coarse scenarios that were tested.

Notes

There are several datasets associated with the study described in the related publication. The study quantifies the individual and interacting effects of three factors - planning-unit size, thematic resolution of habitat maps, and spatial variability of socioeconomic costs - on spatial priorities for conservation, by creating 20 unique prioritisation scenarios involving different levels of each factor. Prioritisations were run using the reserve selection tool Marxan. Because output data from these scenarios are analogous to ecological data, ecological statistics were applied to determine spatial similarities between reserve designs. The other datasets for this study can be found at the Related Data links below.

This dataset is available as a comma-separated values (.csv) file.

Coral-reef habitats in Fiji and Micronesia (consisting of the Mariana Islands, Marshall Islands, Palau, Guam, and the Federated States of Micronesia) were used as case studies. Although analyses are grounded in real data, they are demonstration exercises and not intended to inform real-world conservation action in the study regions.