CHELSA Bioclimatic & Environmental Predictors for SDMs — OneSTOP Baseline (1981–2010)

CHELSA Bioclimatic and Environmental Predictors for Species Distribution Models (OneSTOP Project – Task 5.1): Historical Baseline (1981–2010)

Access to data in Zenodo: https://zenodo.org/records/17644815

This dataset provides bioclimatic and environmental predictor variables used in Species Distribution Models (SDMs) developed within the OneSTOP Project (Task 5.1). The original climatic data are based on the CHELSA v2.1 BIOCLIM+ dataset, which provides high-resolution (~1 km) bioclimatic variables derived from downscaled and bias-corrected climate data.

For future projections, CHELSA v2.1 climate layers were obtained for all five available CMIP6 Global Circulation Models (GCMs): GFDL-ESM4, UKESM1-0-LL, MPI-ESM1-2-HR, IPSL-CM6A-LR, and MRI-ESM2-0) and corresponding to the relevant SSP scenario. To produce a consistent climatic baseline that matches land-cover projections in the Chen et al. (2022) dataset, all available GCMs were averaged to generate a single ensemble mean for each time period and scenario. This ensemble approach reduces individual model biases and aims to provide a robust representation of mid- and late-century climatic conditions for SDMs. Raster data has been internally scaled and reprojected (bilinear method) in the terra R package.

All raster layers are provided as GeoTIFF (float) files in the coordinate reference system EPSG:6933, WGS 1984/NSIDC EASE-Grid 2.0 Global (Cylindrical Equal Area projection). The datasets correspond to one of the following temporal windows and SSP scenarios:

  • Historical Baseline: 1981–2010 (used for model training)
  • Future Mid-Century (2041–2070): SSP1–2.6, SSP3–7.0, SSP5–8.5 (used for model projection)
  • Future Late-Century (2071–2100): SSP1–2.6, SSP3–7.0, SSP5–8.5 (used for model projection)

These predictor/projection datasets are intended for use in SDM workflows to assess climatic suitability and potential species distributions under changing environmental conditions. They were prepared to support the OneSTOP project’s modeling of Invasive Alien Species (IAS) and integration with land-cover projections (Chen et al., 2022).

Climatic variables were obtained from CHELSA v2.1 (https://www.chelsa-climate.org/datasets), including the full set of bioclimatic variables describing temperature and precipitation regimes. In addition to the standard BIOCLIM variables, the predictor set includes BIOCLIM+ metrics such as growing-season length, growing-season precipitation, growing-season mean temperature, growing-degree days above 0 °C, 5 °C, and 10 °C, and net primary productivity, providing an expanded representation of climate conditions relevant to species’ ecological requirements.


References

Chen, G., Li, X., & Liu, X. (2022). Global land projection based on plant functional types with a 1-km resolution under socio-climatic scenarios. Scientific Data, 9, 125. https://doi.org/10.1038/s41597-022-01208-6

Notes

List of variables in the dataset

Variable Name Description
BIO1 Annual Mean Temperature Mean annual air temperature
BIO2 Mean Diurnal Range Mean of monthly Tmax - Tmin
BIO3 Isothermality BIO2 / BIO7 x 100
BIO4 Temperature Seasonality Standard deviation of temperature x 100
BIO5 Max Temperature of Warmest Month Highest monthly mean temperature
BIO6 Min Temperature of Coldest Month Lowest monthly mean temperature
BIO7 Annual Temperature Range BIO5 - BIO6
BIO8 Mean Temperature of Wettest Quarter Average temperature during the wettest quarter
BIO9 Mean Temperature of Driest Quarter Average temperature during the driest quarter
BIO10 Mean Temperature of Warmest Quarter Average temperature during the warmest quarter
BIO11 Mean Temperature of Coldest Quarter Average temperature during the coldest quarter
BIO12 Annual Precipitation Total annual precipitation
BIO13 Precipitation of Wettest Month Highest monthly precipitation
BIO14 Precipitation of Driest Month Lowest monthly precipitation
BIO15 Precipitation Seasonality Coefficient of variation of monthly precipitation
BIO16 Precipitation of Wettest Quarter Total precipitation in the wettest quarter
BIO17 Precipitation of Driest Quarter Total precipitation in the driest quarter
BIO18 Precipitation of Warmest Quarter Total precipitation in the warmest quarter
BIO19 Precipitation of Coldest Quarter Total precipitation in the coldest quarter
GDD0 Growing Degree Days >0 °C Annual sum of degree-days above 0 °C
GDD5 Growing Degree Days >5 °C Annual sum of degree-days above 5 °C
GDD10 Growing Degree Days >10 °C Annual sum of degree-days above 10 °C
GSL Growing Season Length Number of days with mean temperature above the growing-season threshold
GSP Growing Season Precipitation Total precipitation during the growing season
GST Growing Season Temperature Mean temperature during the growing season
NPP Net Primary Productivity Modelled net primary productivity (vegetation biomass production)

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