Spatial nestedness of conservation priorities

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.

    Data Record Details
    Data record related to this publication Spatial nestedness of conservation priorities
    Data Publication title Spatial nestedness of conservation priorities
  • 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.

  • Other Descriptors
    • Descriptor

      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.

    • Descriptor type Note
    • Descriptor

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

    • Descriptor type Note
    • Descriptor

      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.

    • Descriptor type Note
  • Data type dataset
  • Keywords
    • systematic conservation planning
    • spatial nestedness
    • Marxan
    • ARC Centre of Excellence for Coral Reef Studies
  • Funding source
  • Research grant(s)/Scheme name(s)
  • Research themes
    Tropical Ecosystems, Conservation and Climate Change
    FoR Codes (*)
    • 050202 - Conservation and Biodiversity
    • 050205 - Environmental Management
    SEO Codes
    • 960507 - Ecosystem Assessment and Management of Marine Environments
    • 960701 - Coastal and Marine Management Policy
    Specify spatial or temporal setting of the data
    Temporal (time) coverage
  • Start Date 2015/11/11
  • End Date 2015/11/12
  • Time Period 21st Century
    Spatial (location) coverage
  • Locations
    • Fiji
    • Micronesia
    Data Locations

    Type Location Notes
    Attachment nestedness_results.csv Csv table containing information on spatial nestedness results. Coarse-scenario and test ("best") scenario codes reflect the same referred to in the publication that is based on these published datasets. 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.
    The Data Manager is: Jessica Miao Jin Cheok
    College or Centre
    Access conditions Open: free access under license
  • Alternative access conditions
  • Data record size 2 KB
  • Related publications
      Name Cheok, Jessica, Pressey, Robert L., Weeks, Rebecca, Andrefouet, Serge and Moloney, James (2016) Sympathy for the devil: detailing the effects of planning-unit size, thematic resolution of reef classes, and socioeconomic costs on spatial priorities for marine conservation. PLoS ONE, 11(11): e0164869
    • URL http://dx.doi.org/10.1371/journal.pone.0164869
    • Notes Open Access
  • Related websites
      Name
    • URL
    • Notes
  • Related metadata (including standards, codebooks, vocabularies, thesauri, ontologies)
  • Related data
  • Related services
      Name
    • URL
    • Notes
    Select or add a licence for the data
    The data will be licensed under CC BY: Attribution 3.0 AU
  • Other Licence
  • Statement of rights in data
  • Data owners
      Jessica Cheok
    Citation Cheok, Jessica Miao Jin (2016): Spatial nestedness of conservation priorities . James Cook University. https://doi.org/10.4225/28/579AB6F042DD7