Data for the calculation of an indicator of the comprehensiveness of conservation of useful wild plants

Colin K. Khoury, Daniel Amariles, Jonatan Stivens Soto, Maria Victoria Diaz, Steven Sotelo, Chrystian C. Sosa, Julian Ramírez-Villegas, Harold A. Achicanoy, Nora P. Castañeda-Álvarez, Blanca León, John H. Wiersema

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4 Scopus citations

Abstract

The indicator methodology includes five main steps, each requiring and producing data, which are fully described and available here. These data include: species taxonomy, uses, and general geographic information (dataset 1); species occurrence data (dataset 2); global administrative areas data (dataset 3); eco-geographic predictors used in species distribution modeling (dataset 4); a world map raster file (dataset 5); species spatial distribution modeling outputs (dataset 6); ecoregion spatial data used in conservation analyses (dataset 7); protected area spatial data used in conservation analyses (dataset 8); and countries, sub-regions, and regions classifications data (dataset 9). These data are available at http://dx.doi.org/10.17632/2jxj4k32m2.1. In combination with the openly accessible methodology code (https://github.com/CIAT-DAPA/UsefulPlants-Indicator), these data facilitate indicator assessments and serve as a baseline against which future calculations of the indicator can be measured. The data can also contribute to other species distribution modeling, ecological research, and conservation analysis purposes.
Original languageAmerican English
Pages (from-to)90-97
Number of pages8
JournalData in Brief
Volume22
DOIs
StatePublished - 1 Feb 2019

Keywords

  • Bioclimatic variables
  • Biodiversity indicators
  • Eco-geographic predictors
  • Economic plants
  • Occurrence data

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    Khoury, C. K., Amariles, D., Soto, J. S., Diaz, M. V., Sotelo, S., Sosa, C. C., Ramírez-Villegas, J., Achicanoy, H. A., Castañeda-Álvarez, N. P., León, B., & Wiersema, J. H. (2019). Data for the calculation of an indicator of the comprehensiveness of conservation of useful wild plants. Data in Brief, 22, 90-97. https://doi.org/10.1016/j.dib.2018.11.125