Features
Features of the SABINA Geoportal for Spain
The SABINA Geoportal for Spain offers interactive tools to explore the current and future distributions of 100 tree species and 150 shrub species across peninsular Spain. The main features include:
- Exploring and Downloading Potential Species Distributions: In the Models tab, users can view and download potential distribution maps for tree and shrub species, both for the present and for four future climate scenarios. These maps are derived from species distribution models (see the following sections for more details on the models and climate scenarios). The maps are available at a 1 km resolution, allowing detailed analysis of areas of interest. All distribution models can be downloaded in GeoTIF format, facilitating their integration into Geographic Information Systems (GIS). This is particularly useful for conservation, ecological restoration, or forest planning projects, as it allows for deeper data analysis and manipulation.
- Identification of the Most Suitable Species: By clicking on any point on the map, the geoportal generates a list of the 10 most suitable tree species and the 10 most suitable shrub species for that area, according to our models. This tool is ideal for selecting species in restoration or reforestation plans. Additionally, each species in the list includes a link to a detailed species sheet with key information about its ecology, distribution, physiological traits, uses, and other characteristics. In addition, each species in the list has a link to a detailed profile that includes key information about its ecology, distribution, physiological traits, uses, and other characteristics. By clicking on each species, an explanatory sheet appears with relevant information about its ecology, such as lithological preferences, distribution, and habitat characteristics. This information is crucial to complement the model results with the manager’s practical knowledge, especially considering that the model’s resolution (1 km) may limit the accuracy of some predictions.
- Species Presence Atlas: In the Atlas tab, users can view and download presence data for all vascular plant species in Spain. These data are available at a resolution of 10 km UTM cells and can serve as a valuable reference for biodiversity studies and conservation planning. The atlas contains presence data for vascular plants in Spain, sourced from the AFLIBER database. Together with the Spanish Botanical Society, we are continuously updating this database through a chorology working group. When using the atlas, please cite it as follows: Ramos-Gutiérrez, I., Lima, H., Pajarón, S., Romero-Zarco, C., Sáez, L., Pataro, L., Molina-Venegas, R., Rodríguez, M.Á. & Moreno-Saiz, J.C. (2021) Atlas of the vascular flora of the Iberian Peninsula biodiversity hotspot (AFLIBER). Global Ecology and Biogeography, 30, 1951-1957.
- Species sheets: In the Species Sheets tab, users can access a complete list of species for which distribution models have been generated. Each species has a detailed sheet that includes key information, such as its main functional traits, the habitat characteristics where it lives, its current distribution, primary uses, and other relevant additional observations.This information is crucial to complement and improve the interpretation of the model results.
Together, these features provide users with a powerful tool for planning and decision-making in conservation, ecological restoration, and forest management. This tool is also ideal for evaluating climate change impacts.
Additionally, the SABINA geoportal will soon include new features:
- Biodiversity thematic maps: Maps designed to guide conservation and restoration actions, including: a) Priority areas and corridors to promote forest connectivity, calculated using habitat availability indices (See Goicolea et al., in prep); b) Biodiversity models based on stacked species distribution models; and c) Distribution of major vegetation types in mainland Spain (See Goicolea et al., in prep).
- Data: The database facilitates the download of selected data to support advanced ecological research, species distribution modeling, and conservation planning. The database is structured into four main collections: a) Species presence records, b) Environmental and climatic variables, c) Species distribution models, and d) Thematic maps to guide conservation. Each dataset is accompanied by detailed metadata. All data is open access through the Zenodo repository. For more details, see: Goicolea, T., García-Viñas, J. I., Gastón, A., Calleja, J. A., Aroca-Fernández, M., Moreno, J. C., Fernández, M. Á., Broennimann, O., Guisan, A., Adde, A., & Mateo, R. G. (In prep.) GeoSABINA: A unified ecological database for Spain.
Species Distribution Models
The SABINA Geoportal offers species distribution models for woody species (trees and shrubs) in peninsular Spain, both for the current climate scenario and for four future climate scenarios. The resulting potential distribution maps are available at a 1 km resolution. There is a toggle switch that allows users to switch between tree models and shrub models. By sliding this switch, the list of species and the potential distributions specific to trees or shrubs are unlocked. In the following sections, you can find more detailed information about the methodology used to generate the tree and shrub models. The suitability values in the maps range from 0 to 1000, where low values, close to 500-600, may indicate a low probability of the species’ presence (Mateo et al., 2024).
When using the models, please cite it using:
- Mateo, R.G., J. Morales-Barbero, A. Zarzo-Arias, H. Lima, V. Gómez Rubio & T. Goicolea. sabinaNSDM: an R package for spatially nested hierarchical species distribution modelling. (2024) Methods in Ecology and Evolution.
- Goicolea, T., A. Adde, O. Broennimann, J.I. García-Viñas, A. Gastón, M. José Aroca-Fernández, A. Guisan. & R.G. Mateo (2024) Spatially-nested hierarchical species distribution models to overcome niche truncation in national-scale studies. Ecography.
1. Tree Models
The distribution models for tree species have been developed using a spatially nested hierarchical approach (NSDM). These models combine large-scale global patterns with finer regional characteristics. The models were developed using the sabinaNSDM R package, designed by our research team. Tutorials on how to use the package areavailable in the following links: to work with individual species or with multiple especies. The models correspond to the ‘covariate’ option of the sabinaNSDM package.
The models were trained with species data from various sources, such as the third Forest Spanish Inventory, GBIF, BIEN, and EUForest, using 25 environmental variables, including bioclimatic, edaphic, hydrological, and solar exposure characteristics (see table). More details on the species data and climatic variables used in these models can be found in the publication Goicolea et al. (2024) Ecography.
Consensus models were generated by combining three statistical algorithms: generalized linear models (GLM), gradient boosted machines (GBM), and random forests (RF). The specific methodology followed for the development of these models is available in supplementary material number 2 of Mateo et al. (2024) in Methods in Ecology and Evolution.
Table 1. Environmental variables
Variable | Tipo | Fuente |
Bio1: Annual Mean Temperature | Bioclimatic | CHELSA |
Bio2: Mean Diurnal Range | Bioclimatic | CHELSA |
Bio3: Isothermality | Bioclimatic | CHELSA |
Bio4: Temperature Seasonality | Bioclimatic | CHELSA |
Bio5: Max Temperature of Warmest Month | Bioclimatic | CHELSA |
Bio6: Min Temperature of Coldest Month | Bioclimatic | CHELSA |
Bio7: Temperature Annual Range | Bioclimatic | CHELSA |
Bio10: Mean Temperature of Warmest Quarter | Bioclimatic | CHELSA |
Bio11: Mean Temperature of Coldest Quarter | Bioclimatic | CHELSA |
Bio12: Annual Precipitation | Bioclimatic | CHELSA |
Bio13: Precipitation of Wettest Month | Bioclimatic | CHELSA |
Bio14: Precipitation of Driest Month | Bioclimatic | CHELSA |
Bio15: Precipitation Seasonality | Bioclimatic | CHELSA |
Bio16: Precipitation of Wettest Quarter | Bioclimatic | CHELSA |
Bio17: Precipitation of Driest Quarter | Bioclimatic | CHELSA |
soil pH at 0-5cm depth | Edaphic | Soilgrids |
soil nitrogen content at 0-5cm depth | Edaphic | Soilgrids |
soil sand content at 0-5cm depth | Edaphic | Soilgrids |
soil organic carbon stock at 0-5cm depth | Edaphic | Soilgrids |
Distance to rivers | Hidrologic | DEM |
Accumulated flow | Hidrologic | DEM |
Topographic index | Hidrologic | DEM |
Annual solar radiation | Topoclimatic | DEM |
2. Shrub Models
The distribution models for shrub species were calibrated at a European scale and projected exclusively in Spain, following the approach described in Mateo et al. (2014). The species occurrence data used to train the models came from the Forest Forest Map of Spain, GBIF, and BIEN. The same environmental variables used in the tree models were applied here.
Consensus models were also generated using a combination of three statistical algorithms: generalized linear models (GLM), gradient boosted machines (GBM), and random forests (RF).
Future Climate Scenarios
The species distribution models have been projected into four future climate scenarios, based on two socioeconomic pathways (optimistic and pessimistic) and two global circulation models (A and B) (see table). The two socioeconomic pathways are:
- Optimistic: Corresponds to the SSP126 pathway (SSP1-RCP2.6), representing a sustainability scenario, with limited climate change due to strict greenhouse gas mitigation policies.
- Pessimistic: Corresponds to the SSP585 pathway (SSP5-RCP8.5), assuming development driven by fossil fuels, with little to no effective climate policy, following a “business as usual” trend.
The two global circulation models used are:
- A: IPSL-CM6A-LR model (Institut Pierre Simon Laplace, France)
- B: MRI-ESM2-0 model (Meteorological Research Institute, Japan)
Table 2. Climate Scenarios
Scenario name | Shared Socioeconomic Pathway (SSP) | Global Circulation Model |
Optimistic A | SSP 126 | IPSL-CM6A-LR |
Optimistic B | SSP 126 | MRI-ESM2-0 |
Pesimistic A | SSP 585 | IPSL-CM6A-LR |
Pesimistic B | SSP 585 | MRI-ESM2-0 |
How to cite the different resources from the geoportal?
We are preparing a publication that will include all the resources of the geoportal:
- Goicolea, T., García-Viñas, J. I., Gastón, A., Calleja, J. A., Aroca-Fernández, M., Moreno, J. C., Fernández, M. Á., Broennimann, O., Guisan, A., Adde, A. & Mateo, R. G. (In prep.) geoSABINA: A unified ecological database for Spain.
Until then, please use the following citations.
When using the models, please cite them as follows:
- Mateo, R.G., J. Morales-Barbero, A. Zarzo-Arias, H. Lima, V. Gómez Rubio & T. Goicolea. sabinaNSDM: an R package for spatially nested hierarchical species distribution modelling. (2024) Methods in Ecology and Evolution.
- Goicolea, T., A. Adde, O. Broennimann, J.I. García-Viñas, A. Gastón, M. José Aroca-Fernández, A. Guisan. & R.G. Mateo (2024) Spatially-nested hierarchical species distribution models to overcome niche truncation in national-scale studies. Ecography.
When using the vascular plants atlas, please cite it as follows:
- Ramos-Gutiérrez, I., Lima, H., Pajarón, S., Romero-Zarco, C., Sáez, L., Pataro, L., Molina-Venegas, R., Rodríguez, M.Á. & Moreno-Saiz, J.C. (2021) Atlas of the vascular flora of the Iberian Peninsula biodiversity hotspot (AFLIBER). Global Ecology and Biogeography, 30, 1951-1957.
When using the butterfly atlas, please cite it as follows:
- Mañas-Jordá, S., Acosta, C.R., Ariño, A., Baquero, E., Bartomeus, I., Bonada, N., Galicia, D., García-Barros, E., García-Meseguer, A.J., García-Roselló, E., Lobo, J. M., Mungira, M.L., López-Rodríguez, M.J., Martínez-Menéndez, J., Millán, A., Monserrat, V.J., Prieto, C., Romo, H., Sánchez-Campaña, C., Tierno de Figueroa, J.M., Yela, J. L., Sánchez-Fernández, D. (2024). IberArthro: A database compiling taxonomic and distributional data on Ibero-Balearic arthropods. Version 2.0. Department of Ecology and Hydrology. University of Murcia. Occurrence dataset. https://doi.org/10.15470/pqq9oc