20201021 16340300 1.0 FALSE nm_threatened_species_richness 002 -20036974.138100 20026963.164000 -19589728.605300 21266586.329800 1 Projected GCS_WGS_1984 Linear Unit: Meter (1.000000) WGS_1984_Web_Mercator_Auxiliary_Sphere <ProjectedCoordinateSystem xsi:type='typens:ProjectedCoordinateSystem' xmlns:xsi='http://www.w3.org/2001/XMLSchema-instance' xmlns:xs='http://www.w3.org/2001/XMLSchema' xmlns:typens='http://www.esri.com/schemas/ArcGIS/2.6.0'><WKT>PROJCS["WGS_1984_Web_Mercator_Auxiliary_Sphere",GEOGCS["GCS_WGS_1984",DATUM["D_WGS_1984",SPHEROID["WGS_1984",6378137.0,298.257223563]],PRIMEM["Greenwich",0.0],UNIT["Degree",0.0174532925199433]],PROJECTION["Mercator_Auxiliary_Sphere"],PARAMETER["False_Easting",0.0],PARAMETER["False_Northing",0.0],PARAMETER["Central_Meridian",0.0],PARAMETER["Standard_Parallel_1",0.0],PARAMETER["Auxiliary_Sphere_Type",0.0],UNIT["Meter",1.0],AUTHORITY["EPSG",3857]]</WKT><XOrigin>-20037700</XOrigin><YOrigin>-30241100</YOrigin><XYScale>148923141.92838538</XYScale><ZOrigin>-100000</ZOrigin><ZScale>10000</ZScale><MOrigin>-100000</MOrigin><MScale>10000</MScale><XYTolerance>0.001</XYTolerance><ZTolerance>0.00020000000000000001</ZTolerance><MTolerance>0.00020000000000000001</MTolerance><HighPrecision>true</HighPrecision><WKID>102100</WKID><LatestWKID>3857</LatestWKID></ProjectedCoordinateSystem> 20201029 16122700 20201029 16122700 150000000 5000 Esri ArcGIS 12.6.2.24783 Threatened species richness refined by area of habitat 2020-09-30T00:00:00 external 1f4f0b59e370fa7df2d008bf3b77c27eee9b31e3 Data Manager UNEP-WCMC Data Manager spatialanalysis@unep-wcmc.org True Data Manager 1 -179.995201 179.905271 85.917716 -84.691702 This map shows the number of threatened amphibians, birds, mammals, reptiles, and plant species whose distributions overlap. <DIV STYLE="text-align:Left;"><DIV><DIV>This layer represents the number of species of threatened amphibians, birds, mammals, reptiles and plant taxa whose distribution overlaps in each 10 km cell.Conservation status data was used to select a subset of threatened species, based on data from the IUCN Red List and the ThreatSearch online database (BGCI 2019). Given that extinction risk data is not available for all species considered in the analyses, users should be aware of the taxonomic bias of the layer.To develop it, species ranges were rasterised at 1 km resolution from polygon maps from the IUCN Red List (IUCN Red List of Threatened Species (2019) Version 2019.2. http://www.iucnredlist.org), the Global Assessment of Reptile Distributions (GARD) (Roll et al. 2017), Version 1.5, https://datadryad.org/stash/dataset/doi:10.5061/dryad.83s7k) and the Botanical Information and Ecology Network (BIEN) database (Enquist et al. in prep. and Maitner et al. 2017, version 4.1. http://bien.nceas.ucsb.edu/bien/biendata/). Additional vascular plant species ranges were created from point data from the IUCN Red List (IUCN Red List of Threatened Species (2019) Version 2019.2. http://www.iucnredlist.org), Botanic Gardens Conservation International (BGCI) (https://www.bgci.org/), the Global Biodiversity Information Facility (GBIF) (https://www.gbif.org/) and iNaturalist (https://www.inaturalist.org). Species range maps were refined, when possible, by removing unsuitable areas using information on species’ habitat preferences and species' known altitudinal limits. Habitats distributions were obtained from the global map of terrestrial habitat types (Jung et al. 2020), while altitudinal data was obtained from the Global Multi-resolution Terrain Elevation Data (GMTED2010) (USGS). For species without habitat preference information, such as those with modelled ranges, anthropogenic land use classes from the map of terrestrial habitat types were used to remove potentially unsuitable areas within their ranges. This refinement process produced Areas of Habitat (AOH) (Brooks et al. 2019) maps for each species.Ten representative sets of species were then chosen to limit the geographic bias in the plant data. For each set, the species richness was calculated based on AOH presence in each cell of a 10km raster and scaled between 0 and 1. The average scores from these maps was used to create the final map of relative richness for threatened species.ReferencesBGCI. (2019) ThreatSearch online database. BGCI Threat search www.bgci.org/threat_search.phpBrooks, T. M. et al. (2019). Measuring Terrestrial Area of Habitat (AOH) and Its Utility for the IUCN Red List. Trends in Ecology & Evolution 34:977–986. https://doi.org/10.1016/j.tree.2019.06.009 Enquist, B.J. et al. (in prep.). Botanical big data shows that plant diversity in the New World is driven by climatic-linked differences in evolutionary rates and biotic exclusion.IUCN (2019). The IUCN Red List of Threatened Species. Version 2019.2. Jung, M., et al. (2020). A global map of terrestrial habitat types. Nature Scientific Data 7, 256. https://www.nature.com/articles/s41597-020-00599-8Maitner, B.S. et al. (2017). The BIEN R package: A tool to access the Botanical Information and Ecology Network (BIEN) database. Methods in Ecology and Evolution; 9:373–379. https://besjournals.onlinelibrary.wiley.com/doi/10.1111/2041-210X.12861 Roll, U. et al. (2017), The global distribution of tetrapods reveals a need for targeted reptile conservation, Nature Ecology & Evolution, 1: 1677–1682, https://doi.org/10.1038/s41559-017-0332-2</DIV></DIV></DIV> UNEP-WCMC (2020) Threatened species richness. Derived from Areas of Habitat maps created from data from the IUCN Red List, BirdLife International, the Global Assessment of Reptile Distributions (GARD), the Botanical Information and Ecology Network (BIEN) database and additional vascular plant species ranges were created from point data from the IUCN Red List, Botanic Gardens Conservation International (BGCI), the Global Biodiversity Information Facility (GBIF) and iNaturalist. Cambridge, UK. IUCN Red List UNEP-WCMC NatureMap Threatened Species Richness <DIV STYLE="text-align:Left;"><DIV>CC BY NC 4.0</DIV></DIV> 10000 "A semi-automated process was developed in Google Earth Engine to rasterise all species ranges from the various sources to 1 km resolution. To reduce overeestimation of due to commission errors (false indication of presence) during the raster conversion we refined the ranges, when possible, by removing unsuitable areas using information on species' habitat preferences and species' known altitudinal limits obtained from the IUCN Red List and collated from the scientific literature. For species without habitat preference information, such as those with modelled ranges, anthropogenic land use classes from the map of terrestrial habitat types were used to remove potentially unsuitable areas within their ranges. This refinement process produced Area of Habitat (AOH) maps for each species (Brooks et al. 2019). To limit geographic bias, due to the plant data being incomplete, AOH maps were split into 10 representative sets. For each set, the species richness was calculated based on AOH aggregated to 10km resolution, and scaled between 0 and 1. The average score from these maps was then used to create the final map of species richness. " external 1f4f0b59e370fa7df2d008bf3b77c27eee9b31e3 Data Manager UNEP-WCMC Data Manager spatialanalysis@unep-wcmc.org True Data Manager File Geodatabase Raster Dataset 2 dataset EPSG 8.8(9.3.1.2) Pixel 4484 3588 11166.091779 9111.577818 32 1 Upper Left FALSE LZ77 1 pixel codes FGDBR TRUE row and column 11166.091779 9111.577818 20201029 external 1f4f0b59e370fa7df2d008bf3b77c27eee9b31e3 Data Manager UNEP-WCMC Data Manager spatialanalysis@unep-wcmc.org True Data Manager A semi-automated process was developed in Google Earth Engine to rasterise all species ranges from the various sources to 1 km resolution. To reduce overeestimation of due to commission errors (false indication of presence) during the raster conversion we refined the ranges, when possible, by removing unsuitable areas using information on species' habitat preferences and species' known altitudinal limits obtained from the IUCN Red List and collated from the scientific literature. For species without habitat preference information, such as those with modelled ranges, anthropogenic land use classes from the map of terrestrial habitat types were used to remove potentially unsuitable areas within their ranges. This refinement process produced Area of Habitat (AOH) maps for each species (Brooks et al. 2019). To limit geographic bias, due to the plant data being incomplete, AOH maps were split into 10 representative sets. For each set, the species richness was calculated based on AOH aggregated to 10km resolution, and scaled between 0 and 1. The average score from these maps was then used to create the final map of species richness.