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  3. Impact model: SDM-GAM

Impact model: SDM-GAM

Sector
Terrestrial biodiversity
Region
global

The SDM-gam models are species distribution models of 20567 terrestrial vertebrate species (2739 amphibians, 8115 birds, 5711 reptiles, and 4002 mammals) using Generalized Additive Models as model algorithm. SDM-gam are statistical models, which were calibrated using a 30-year average (1981-2010) of the GSWP3-W5E5 observed climate input data set and IUCN and BirdLife range maps of each vertebrate species. The models are then projected to simulated historical, current and future 30-year average climate data from ISIMIP3b, and where filtered using species specific habitat preferences resulting in probabilities of occurrence.

Information for the model SDM-GAM is provided for the simulation rounds shown in the tabs below. Click on the appropriate tab to get the information for the simulation round you are interested in.

Confirm data for simulation round ISIMIP3b
Person responsible for model simulations in this simulation round
Mirely Guzman Torres: mirely.guzman@wyssacademy.org, 0000-0003-2274-5217, Wyss Academy for Nature (Switzerland)
Dirk Karger: dirk.karger@wsl.ch, 0000-0001-7770-6229, Swiss Federal Research Institute WSL (Switzerland)
Output Data
Experiments: (*) ssp126_ssp126soc-noadapt+image_default, ssp370_nat_default, ssp370_ssp370soc-noadapt+image_default, ssp126_ssp126soc-adapt+image_default, ssp370_ssp370soc-adapt+image_default, ssp585_nat_default, ssp585_ssp585soc-adapt+magpie_default, ssp370_ssp370soc-adapt+magpie_default, ssp126_ssp126soc-noadapt+magpie_default, ssp585_ssp585soc-noadapt+magpie_default, ssp585_ssp585soc-noadapt+image_default, ssp585_ssp585soc-adapt+image_default, ssp126_nat_default, ssp126_ssp126soc-adapt+magpie_default, ssp370_ssp370soc-noadapt+magpie_default
Climate Drivers: GFDL-ESM4, IPSL-CM6A-LR, MPI-ESM1-2-HR, MRI-ESM2-0, UKESM1-0-LL
Date: 2026-07-02
Basic information
Model Version: 1.1
Model Homepage: https://gitlabext.wsl.ch/karger/isimip3_sdm/-/tree/V.1.1?ref_type=heads
Model License: CC 0
Resolution
Horizontal resolution: 0.5°x0.5°
Vertically resolved: No
Input data
Simulated atmospheric climate data sets used: MRI-ESM2-0, IPSL-CM6A-LR, MPI-ESM1-2-HR, UKESM1-0-LL, GFDL-ESM4
Climate variables: hurs, tasmax, tas, tasmin, rsds, ps, pr
Spin-up
Was a spin-up performed?: No
Model specifications
Model algorithm: Generalised Additive Model (GAM)
Explanatory variables: Annual Mean Temperature Temperature Seasonality Annual Precipitation Precipitation Seasonality Mean Relative Humidity Relative Humidity Range Relative Humidity SD Frost Day Site Water Balance
Response variable: absence/presence of species
Distribution of response variable: Binomial
Software function: gam()
Confirm data for simulation round ISIMIP3a
Person responsible for model simulations in this simulation round
Mirely Guzman Torres: mirely.guzman@wyssacademy.org, 0000-0003-2274-5217, Wyss Academy for Nature (Switzerland)
Dirk Karger: dirk.karger@wsl.ch, 0000-0001-7770-6229, Swiss Federal Research Institute WSL (Switzerland)
Output Data
Experiments: (*) obsclim_histsoc_default, obsclim_nat_default
Climate Drivers: GSWP3-W5E5
Date: 2026-07-02
Basic information
Model Version: 1.1
Model Homepage: https://gitlabext.wsl.ch/karger/isimip3_sdm/-/tree/V.1.1?ref_type=heads
Model License: CC 0
Resolution
Horizontal resolution: 0.5°x0.5°
Vertically resolved: No
Input data
Observed atmospheric climate data sets used: GSWP3-W5E5 (ISIMIP3a)
Land use data sets used: Historical, gridded land use
Climate variables: hurs, tasmax, tas, tasmin, rsds, ps, pr
Spin-up
Was a spin-up performed?: No
Model specifications
Model algorithm: Generalised Additive Model (GAM)
Explanatory variables: Annual Mean Temperature Temperature Seasonality Annual Precipitation Precipitation Seasonality Mean Relative Humidity Relative Humidity Range Relative Humidity SD Frost Day Site Water Balance
Response variable: absence/presence of species
Distribution of response variable: Binomial
Software function: gam()




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