Raster files of the diversity and climate change analyses of regionally priority CWR in the SADC region
This set of raster files resulted from the diversity analysis of regionally priority CWR across the SADC region and the study of the impact of climate change on their distribution and richness. Three folders are made available: CWR_distribution, CC_threat, summary_files. [CWR_distribution]: Species...
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| Formato: | Conjunto de datos |
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2021
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| Acceso en línea: | https://hdl.handle.net/10568/117475 |
| _version_ | 1855542146992439296 |
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| author | Gaisberger, Hannes |
| author_browse | Gaisberger, Hannes |
| author_facet | Gaisberger, Hannes |
| author_sort | Gaisberger, Hannes |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| description | This set of raster files resulted from the diversity analysis of regionally priority CWR across the SADC region and the study of the impact of climate change on their distribution and richness. Three folders are made available: CWR_distribution, CC_threat, summary_files. [CWR_distribution]: Species distribution models (SDMs) were created for 75 taxa based on 22 environmental variables that included three geophysical (altitude, aspect, slope) and 19 bioclimatic layers. Altitude and the 19 bioclimatic variables, representing contemporary baseline climatology (1950–2000), were obtained from the WorldClim 1.4 (Hijmans et al., 2005) at 2.5 arc minutes (about 4.5 km at the equator) spatial resolution (http://www.worldclim.org/current), and the derived variables “aspect” and “slope” were calculate in ArcGIS 10.4.1. Species distribution models were obtained using MaxEnt 3.4.0 (Phillips et al., 2006) and were considered accurate and stable if they fulfilled the criteria suggested by Ramiréz-Villegas et al. (2010). Potential distributions for 35 taxa (those with less than 10 presence records or whose MaxEnt models did not comply with the validation criteria) were estimated by creating circular buffers of 50 km (CA50) around each occurrence point (Hijmans et al. 2001). File name: First three letters from ‘Genus’, plus first three letters from ‘Species’, plus first three letters from ‘Subspecies’ or ‘Variety’ if applicable, plus either ‘ca50’ (circular buffers of 50 km) or ‘sdm’ (Species Distribution Model), plus ‘_01’. Values: 0 = no species presence is predicted 1 = species presence is predicted. [CC_threat]: Climate projections for 2050 (average 2041−2060) obtained from Worldclim 1.4, (http://www.worldclim.org, Hijmans et al., 2005), consisting of downscaled data from General Circulation Models (GCMs) at a spatial resolution of 2.5 arc minutes (about 4.5 km at the equator). Median ensembles of 19 GCMs for RCP 4.5 and RCP 8.5 derived from the fifth assessment of the Intergovernmental Panel on Climate Change (IPCC−AR5) (IPCC 2014). The model results were projected under contemporary baseline conditions (WorldClim v1.4) to future climate scenarios (2050) creating binary layers of suitable versus unsuitable area (Scheldeman and van Zonneveld, 2010). Maps of change in CWR richness were obtained where: (i) species is not predicted by both current and future climate models, (ii) new potential areas: both future models (RCP 4.5 and RCP 8.5) predict presence in areas where the current model predicts absence; (ii) low impact areas: both future models (RCP 4.5 and RCP 8.5) predict presence in areas where the current model predicts presence; (iii) high impact areas: one future model (RCP 4.5 or RCP 8.5) predicts absence in area where the current model predicts presence; and (iv) very high impact areas: both future models (RCP 4.5 and RCP 8.5) predict absence in areas where the current model predicts presence. File name: First three letters from ‘Genus’, plus first three letters from ‘Species’, plus first three letters from ‘Subspecies’ or ‘Variety’ if applicable, plus ‘cc_recl’. Values: 0 = no species presence is predicted by both current and future climate models 1 = new potential areas: both future models (RCP 4.5 and RCP 8.5) predict presence in areas where the current model predicts absence 2 = low impact areas: both future models predict presence in areas where the current model predicts presence 3 = high impact areas: one future model (RCP 4.5 or RCP 8.5) predicts absence in area where the current model predicts presence 4 = very high impact areas: both future models (RCP 4.5 and RCP 8.5) predict absence in areas where the current model predicts presence. [Summary_files]: CWR richness maps were obtained for the 75 taxa for which SDM were developed and for all 110 taxa (SDM + CA50), under current/baseline climatic conditions and for both future climate scenarios (RCP 4.5 and RCP 8.5). File name: Either ‘cwr75’ (summary file for 75 CWR species) or ‘cwr110’ (summary file for 110 CWR species), plus either ‘ca50’ (circular buffers of 50 km) a/o ‘sdm’, plus either ‘current’ (baseline), ‘rcp45’ (RCP4.5 scenario) or ‘rcp85’ (RCP 8.5 scenario). Values: 0 = no species presence is predicted X = number of species presences predicted (species richness) |
| format | Conjunto de datos |
| id | CGSpace117475 |
| institution | CGIAR Consortium |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| record_format | dspace |
| spelling | CGSpace1174752024-04-25T06:01:55Z Raster files of the diversity and climate change analyses of regionally priority CWR in the SADC region Gaisberger, Hannes agrobiodiversity climate change plant genetic resources This set of raster files resulted from the diversity analysis of regionally priority CWR across the SADC region and the study of the impact of climate change on their distribution and richness. Three folders are made available: CWR_distribution, CC_threat, summary_files. [CWR_distribution]: Species distribution models (SDMs) were created for 75 taxa based on 22 environmental variables that included three geophysical (altitude, aspect, slope) and 19 bioclimatic layers. Altitude and the 19 bioclimatic variables, representing contemporary baseline climatology (1950–2000), were obtained from the WorldClim 1.4 (Hijmans et al., 2005) at 2.5 arc minutes (about 4.5 km at the equator) spatial resolution (http://www.worldclim.org/current), and the derived variables “aspect” and “slope” were calculate in ArcGIS 10.4.1. Species distribution models were obtained using MaxEnt 3.4.0 (Phillips et al., 2006) and were considered accurate and stable if they fulfilled the criteria suggested by Ramiréz-Villegas et al. (2010). Potential distributions for 35 taxa (those with less than 10 presence records or whose MaxEnt models did not comply with the validation criteria) were estimated by creating circular buffers of 50 km (CA50) around each occurrence point (Hijmans et al. 2001). File name: First three letters from ‘Genus’, plus first three letters from ‘Species’, plus first three letters from ‘Subspecies’ or ‘Variety’ if applicable, plus either ‘ca50’ (circular buffers of 50 km) or ‘sdm’ (Species Distribution Model), plus ‘_01’. Values: 0 = no species presence is predicted 1 = species presence is predicted. [CC_threat]: Climate projections for 2050 (average 2041−2060) obtained from Worldclim 1.4, (http://www.worldclim.org, Hijmans et al., 2005), consisting of downscaled data from General Circulation Models (GCMs) at a spatial resolution of 2.5 arc minutes (about 4.5 km at the equator). Median ensembles of 19 GCMs for RCP 4.5 and RCP 8.5 derived from the fifth assessment of the Intergovernmental Panel on Climate Change (IPCC−AR5) (IPCC 2014). The model results were projected under contemporary baseline conditions (WorldClim v1.4) to future climate scenarios (2050) creating binary layers of suitable versus unsuitable area (Scheldeman and van Zonneveld, 2010). Maps of change in CWR richness were obtained where: (i) species is not predicted by both current and future climate models, (ii) new potential areas: both future models (RCP 4.5 and RCP 8.5) predict presence in areas where the current model predicts absence; (ii) low impact areas: both future models (RCP 4.5 and RCP 8.5) predict presence in areas where the current model predicts presence; (iii) high impact areas: one future model (RCP 4.5 or RCP 8.5) predicts absence in area where the current model predicts presence; and (iv) very high impact areas: both future models (RCP 4.5 and RCP 8.5) predict absence in areas where the current model predicts presence. File name: First three letters from ‘Genus’, plus first three letters from ‘Species’, plus first three letters from ‘Subspecies’ or ‘Variety’ if applicable, plus ‘cc_recl’. Values: 0 = no species presence is predicted by both current and future climate models 1 = new potential areas: both future models (RCP 4.5 and RCP 8.5) predict presence in areas where the current model predicts absence 2 = low impact areas: both future models predict presence in areas where the current model predicts presence 3 = high impact areas: one future model (RCP 4.5 or RCP 8.5) predicts absence in area where the current model predicts presence 4 = very high impact areas: both future models (RCP 4.5 and RCP 8.5) predict absence in areas where the current model predicts presence. [Summary_files]: CWR richness maps were obtained for the 75 taxa for which SDM were developed and for all 110 taxa (SDM + CA50), under current/baseline climatic conditions and for both future climate scenarios (RCP 4.5 and RCP 8.5). File name: Either ‘cwr75’ (summary file for 75 CWR species) or ‘cwr110’ (summary file for 110 CWR species), plus either ‘ca50’ (circular buffers of 50 km) a/o ‘sdm’, plus either ‘current’ (baseline), ‘rcp45’ (RCP4.5 scenario) or ‘rcp85’ (RCP 8.5 scenario). Values: 0 = no species presence is predicted X = number of species presences predicted (species richness) 2021 2022-01-12T14:31:30Z 2022-01-12T14:31:30Z Dataset https://hdl.handle.net/10568/117475 Open Access Gaisberger, H. (2021) Raster files of the diversity and climate change analyses of regionally priority CWR in the SADC region. https://doi.org/10.7910/DVN/7ONUBJ, Harvard Dataverse, V1 |
| spellingShingle | agrobiodiversity climate change plant genetic resources Gaisberger, Hannes Raster files of the diversity and climate change analyses of regionally priority CWR in the SADC region |
| title | Raster files of the diversity and climate change analyses of regionally priority CWR in the SADC region |
| title_full | Raster files of the diversity and climate change analyses of regionally priority CWR in the SADC region |
| title_fullStr | Raster files of the diversity and climate change analyses of regionally priority CWR in the SADC region |
| title_full_unstemmed | Raster files of the diversity and climate change analyses of regionally priority CWR in the SADC region |
| title_short | Raster files of the diversity and climate change analyses of regionally priority CWR in the SADC region |
| title_sort | raster files of the diversity and climate change analyses of regionally priority cwr in the sadc region |
| topic | agrobiodiversity climate change plant genetic resources |
| url | https://hdl.handle.net/10568/117475 |
| work_keys_str_mv | AT gaisbergerhannes rasterfilesofthediversityandclimatechangeanalysesofregionallyprioritycwrinthesadcregion |