DOI: 10.5061/dryad.stqjq2cdk
title: SDMapCH (v1.3): a Comprehensive database of modelled species habitat suitability maps for Switzerland

description: Conserving natural ecosystems requires consistent and standardized
 biodiversity data to advance scientific research and improve ecological
 understanding. While species occurrence records are commonly used in
 biodiversity assessments, they provide only a snapshot of distributions at
 sampled sites and fail to capture potential habitat suitability or future
 shifts, both of which species distribution models can effectively
 generalize and predict. Despite several national initiatives to develop
 databases of modelled species habitat suitability maps, even well-studied
 countries often lack comprehensive, standardized datasets that cover a
 wide range of taxonomic groups modelled using a consistent framework.
 Using Switzerland as a case study, we demonstrate how these gaps can be
 addressed and introduce SDMapCH (v1.3), a nationwide raster database of
 modelled species habitat suitability maps at a 25-meter resolution.
 SDMapCH provides individual maps for about 7,500 species, as well as
 aggregated maps for 11 major taxonomic groups, 26 ecological guilds, and 5
 conservation status categories, under both present conditions and future
 climate change scenarios projected through the end of the century. SDMapCH
 was developed using the N-SDM modelling pipeline, an end-to-end platform
 built on a spatially nested hierarchical framework and optimized for
 high-performance computing environments. N-SDM enables multi-level and
 multi-resolution integration of species and covariate data, addressing
 niche truncation issues and supporting parallel high-resolution modelling
 of numerous species within tight timeframes. SDMapCH maps were evaluated
 using a state-of-the-art cross-validation procedure, and all layers were
 systematically validated through a data integrity check. By providing
 standardized, high-resolution habitat suitability maps for diverse species
 across various taxonomic and functional groups, SDMapCH stands as a key
 resource for advancing scientific research and enhancing biodiversity
 assessments in Switzerland and beyond.
description: # SDMapCH (v1.3) — a Comprehensive database of modelled species habitat
 suitability maps for Switzerland Dataset DOI:
 [10.5061/dryad.stqjq2cdk](10.5061/dryad.stqjq2cdk) This dataset was
 generated to support biodiversity and conservation planning research by
 providing high-resolution habitat suitability maps for a wide range of
 species. The data was produced using species distribution models (SDMs)
 applied to Switzerland, leveraging a spatially nested hierarchical
 modelling framework. The models integrate species occurrence records with
 environmental predictors to estimate habitat suitability under current
 conditions and future climate change scenarios. The dataset includes
 raster files representing habitat suitability maps for about 7,500 species
 across various taxonomic and functional groups. **For the use and
 validation of habitat suitability maps, please note:** a. The habitat
 suitability maps were primarily developed for research purposes. b. These
 maps were not validated for each individual species; therefore,
 interpretation at the species level should be complemented with additional
 taxonomic or faunistic expertise. c. The results of these models were not
 systematically validated by InfoSpecies. d. Individual maps should not be
 used directly for practical applications or management decisions without
 consultation with experts in the relevant taxonomic groups. The authors
 disclaim responsibility for the accuracy of individual maps. e. Maps for
 83 sensitive species (1.1% of the 7,508 modelled) whose distribution data
 posed conservation or legal concerns were excluded from the archives.
 These concerns relate to the risk of collection, destruction, or
 disturbance of rare and endangered species, such as certain orchids and
 reptiles, their potential exploitation through the international illegal
 wildlife trade, and the requirements of Swiss biodiversity conservation
 law. However, individual habitat suitability maps for all these sensitive
 species are available upon formal request to InfoSpecies (Swiss Species
 Information Centre) by contacting
 [info.species@unine.ch](mailto:info.species@unine.ch), in accordance with
 their standard access procedure. The detailed species list is available in
 the file 1_SDMapCHv1_3_spinfo.csv. **File: SDMapCHv1_3_current.tar.zst**
 Description: Individual maps for the 7,425 species (out of 7,508 modelled,
 excluding 83 sensitive species) for the current period. The file is
 a `.zst` compressed file, which can be decompressed and extracted using
 the following command: `zstd -dc archive.tar.zst | tar -xvf -`. All
 extracted files are in GeoTIFF (.tiff) format, which can be opened with a
 wide range of free and open-source software. For each species, values were
 rescaled to a 0–100 range for data storage purposes and improved
 readability. **File: SDMapCHv1_3_2020_2049.tar.zst** Description:
 Individual maps for the 7,425 species (out of 7,508 modelled, excluding 83
 sensitive species) for for the future period 2020_2049 under two future
 climate scenarios (RCP 4.5 and RCP 8.5). The file is a `.zst` compressed
 file, which can be decompressed and extracted using the following
 command: `zstd -dc archive.tar.zst | tar -xvf -`. All extracted files are
 in GeoTIFF (.tiff) format, which can be opened with a wide range of free
 and open-source software. For each species, values were rescaled to a
 0–100 range for data storage purposes and improved readability. **File:
 SDMapCHv1_3_2045_2074.tar.zst** Description: Individual maps for the 7,425
 species (out of 7,508 modelled, excluding 83 sensitive species) for for
 the future period 2045_2074 under two future climate scenarios (RCP 4.5
 and RCP 8.5). The file is a `.zst` compressed file, which can be
 decompressed and extracted using the following command: `zstd -dc
 archive.tar.zst | tar -xvf -`. All extracted files are in GeoTIFF (.tiff)
 format, which can be opened with a wide range of free and open-source
 software. For each species, values were rescaled to a 0–100 range for data
 storage purposes and improved readability. **File:
 SDMapCHv1_3_2070_2099.tar.zst** Description: Individual maps for the 7,425
 species (out of 7,508 modelled, excluding 83 sensitive species) for for
 the future period 2070_2099 under two future climate scenarios (RCP 4.5
 and RCP 8.5). The file is a `.zst` compressed file, which can be
 decompressed and extracted using the following command: `zstd -dc
 archive.tar.zst | tar -xvf -`. All extracted files are in GeoTIFF (.tiff)
 format, which can be opened with a wide range of free and open-source
 software. For each species, values were rescaled to a 0–100 range for data
 storage purposes and improved readability. **File:
 SDMapCHv1_3_aggregates.tar.zst** Description: Mean (mn) and coefficient of
 variation (cv) maps by ecological GUILD (refer to \_spinfo.csv, column
 "GUILD.X"), Swiss Red List STATUS category (refer to
 \_spinfo.csv, column "status"), major taxonomic GROUP (refer to
 \_spinfo.csv, column "group"), and ALL species combined. Maps
 are provided for the current period as well as for three future periods
 (2020_2049, 2045_2074, 2070_2099) under two future climate scenarios (RCP
 4.5 and RCP 8.5). The file is a `.zst` compressed file, which can be
 decompressed and extracted using the following command: `zstd -dc
 archive.tar.zst | tar -xvf -`. All extracted files are in GeoTIFF (.tiff)
 format, which can be opened with a wide range of free and open-source
 software. **File: metadata.zip** 1. **Detailed species list** * File:
 1_SDMapCHv1_3_spinfo.csv * Description: Taxonomic information (genus,
 family, order, class, phylum, group), conservation status according to the
 Swiss Red List (“status”), and species origin (“origin”). The Red List
 status follows specific codes: Regionally extinct (RE), Critically
 endangered (CR), Endangered (EN), Vulnerable (VU), Near threatened (NT),
 Least concern (LC), Not evaluated (NE), Not applicable regionally (NA),
 Data deficient (DD), and No assigned status (NULL). The species origin
 classification follows specific codes: Species within their natural
 distribution range: IEN (endemic), IEP (shared endemic), INN (indigenous),
 INR (indigenous, regionally introduced), INM (indigenous, sporadic
 reproduction). Species outside their natural distribution range: NEO
 (exotic), NLI (exotic, potentially invasive), NLS (exotic, invasive), NLV
 (exotic, prohibited under ODE). The dataset also provides guild
 classifications (ranging from 1 to 26; see details below) for each
 species, as well as spatial prediction categorization (“scheme,” aquatic
 or terrestrial), automatically determined based on the location of
 occurrence points. Finally, the “sensible” column flags species considered
 sensitive under Swiss regulations, for which the dissemination of
 distribution data may pose conservation or legal concerns (individual maps
 for these 83 species were not made available). See Guild explanations in
 \_Table of Contents.pdf within the metadata.zip folder. 2. **ODMAP
 Protocol** * File: 2_SDMapCHv1_3_odmap.pdf * Description: Standardized
 ODMAP protocol for reporting the modelling framework. 3. **Detailed
 candidate covariate list** * File: 3_SDMapCHv1_3_candidate_covariates.csv
 * Description: Candidate covariates for the models, providing detailed
 information on each covariate's environmental category, dataset,
 variable, level, attribute, and measurement radius (focal). Additionally,
 it includes the DOI for cross-referencing with the SWECO25 dataset. 4.
 **Expert Table** * File: 4_SDMapCHv1_3_expert_table.csv * Description:
 N-SDM expert table completed by experts to evaluate candidate covariates
 for modelling species groups. In this table, each covariate is marked as
 either a candidate (1) or a non-candidate (0) for modelling, based on
 expert assessment of its relevance. 5. **Covariate selection and
 importance results** * File: 5_SDMapCHv1_3_selected_covariates.csv *
 Description: Covariates automatically selected by N-SDM for modelling each
 individual species, along with their relative importance (avg_importance;
 max=1), averaged over five modelling algorithms (GLM, GAM, MAX, RF, and
 GBM; see nsdm::nsdm.varimp for further details). It also specifies the
 measurement radius in meters for each covariate. 6. **Model evaluation
 results** * File: 6a_SDMapCHv1_3_evaluationbyspecies.csv * Description:
 Evaluation metrics for each individual species and each modelling
 algorithm. Metrics provided are Sommer’s D AUC (AUC_S), Continuous Boyce
 Index (CBI), maximized True Skill Statistic (maxTSS), and their average
 "Score" value. Additionally, the dataset provides the
 "threshold" at which the TSS value is maximized. For further
 details, refer to nsdm:: nsdm.all_metrics_function. * File:
 6b_SDMapCHv1_3_evaluationbygroup.csv * Description: Evaluation metrics
 averaged by main taxonomic group for each modelling algorithm. Metrics
 provided are Sommer’s D AUC (AUC_S), Continuous Boyce Index (CBI),
 maximized True Skill Statistic (maxTSS), and their average
 "Score" value. For further details, refer to nsdm::
 nsdm.all_metrics_function. 7. **N-SDM settings** * File:
 7_SDMapCHv1_3_nsdm_settings.csv * Description: Configuration settings used
 to run N-SDM. 8. **Note on taxonomic matching** * File:
 8_SDMapCHv1_3_species_matching.pdf * Description: Note on the matching
 between GBIF and InfoSpecies taxonomies.