Published September 23, 2022 | Version 3.0
Dataset Open

Mapping the planet's critical areas for biodiversity and people

  • 1. Department of Natural Resources and Environment, Cornell University, 226 Mann Drive, Ithaca NY 14853 USA
  • 2. Natural Capital Project, Stanford University, 327 Campus Drive, Stanford CA USA
  • 3. SPRING, 5455 Shafter Ave, Oakland CA USA
  • 4. Nature Conservancy of Canada, 245 Eglinton Ave East, Suite 410, Toronto, Ontario, M4P 3J1, Canada
  • 5. Cornell Lab of Ornithology, Cornell University, 159 Sapsucker Woods Rd, Ithaca, NY 14850
  • 6. Conservation International, 2100 Crystal Drive #600, Arlington, VA 22202, USA
  • 7. Department of Geography, King's College London, Bush House, North East Wing, 40 Aldwych, London, WC2B 4BG, UK
  • 8. UN Environment Programme World Conservation Monitoring Centre, 219 Huntingdon Road, Cambridge, CB3 0DL, United Kingdom
  • 9. Global Protect Oceans, Lands and Waters Program, The Nature Conservancy, Fort Collins, CO, 80524, USA
  • 10. Department of Applied Economics, University of Minnesota, St. Paul, MN 55108, USA
  • 11. Department of Biology, Carleton University, Ottawa, Canada

Description

Data associated with "Mapping the planet's critical areas for biodiversity and people"

Abstract: Meeting global commitments to conservation, climate, and sustainable development requires consideration of synergies and tradeoffs among targets. We evaluate the spatial congruence of ecosystems providing globally high levels of nature’s contributions to people, biodiversity, and areas with high development potential across several sectors. We find that conserving approximately half of global land area through protection or sustainable management could provide 90% of the current levels of ten of nature’s contributions to people and meet minimum representation targets for 26,709 terrestrial vertebrate species. This finding supports recent commitments by national governments under the Global Biodiversity Framework to conserve at least 30% of global lands and waters, and proposals to conserve “half Earth”. More than one-third of areas required for conserving nature’s contributions to people and species are also highly suitable for agriculture, renewable energy, oil and gas, mining, or urban expansion. This indicates potential conflicts among conservation, climate and development goals.

This dataset contains code and outputs of spatial optimizations run using prioritizr (https://prioritizr.net/index.html). R code used to run the spatial optimizations is contained in a zipfile named "code.zip".

Output data includes raster files (TIF format). Raster values are 0-1, where 1 means the grid cell was selected to achieve a particular target, 0 means the grid cell was not selected, and values between 0 and 1 indicate a grid cell was partially selected.

Three variations of the spatial optimization were run. Each TIF or ZIP file contains the outputs from one of these variations:

  1. NCP (Nature's contributions to people) only
    1. File name: NCP_only_2km.zip (ZIP file)
  2. NCP and biodiversity, prioritization run at 10km then masked to natural and semi-natural habitat at 2km
    1. File names: es00bio1_nathab_mask.tif, es05bio1_nathab_mask.tif, etc. (TIF files)
  3. NCP and biodiversity, with protected areas and OECM (WDPA) locked in
    1. File name: NCP_biod_WDPA_nathab.zip (ZIP file)

Within each variation, 19 different spatial optimizations were run, with NCP targets ranging from 5%-95% in 5% increments.

  • Raster filenames within ZIP files indicate the NCP (ecosystem service) target (for example, es05 indicates a target of 5%)
  • Whether biodiversity was included or not (for example, bio1 indicates biodiversity was included, bio0 indicates it was not)

Two additional TIF files were included, which are the result of summing the rasters from the above scenarios. Raster values range from 0-19, where 19 indicates grid cells selected in all scenarios, 0 indicates grid cells selected in 0 scenarios. Higher values (e.g. 19) indicate cells with the highest levels of NCP globally in the least amount of area. These rasters were used to create Figure 2 in the paper.

  1. NCP_only_2km_sum - NCP only scenario, all rasters summed.
  2. NCP_biod_nathab_sum - NCP and biodiversity scenario, masked to natural habitat, all rasters summed.

Additional files include:

  1. dpi.tif - Development Potential Index raster
  2. dpi_key.csv - legend describing the DPI raster values
  3. HDP_DriverCats.tif - High Development Potential areas disaggregated by sector (raster)
  4. HDP_DriverCats_key.csv - legend describing the HDP raster values
  5. es90bio1_hdp_drivers_multiply.tif - raster resulting from the combination of the prioritized areas for NCP and biodiversity combined with High Development Potential areas for each economic sector (key is the same as for HDP raster)
  6. nathab_2km_WGS84.tif - raster with natural and semi-natural habitat mask (based on ESA 2015 land cover) (2 km)

 

Notes

Version uploaded August 8 2023

Files

code.zip

Files (1.2 GB)

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