Species Presence

Description

This indicator shows the species that are most likely to be present in a given area. Probabilities of presence are estimated using species occurrence records from the Global Biodiversity Information Facility (GBIF) combined with environmental covariates that describe habitat characteristics.

The dataset integrates global species observations from field surveys, camera traps, and citizen science, cleaned to ensure data quality. Environmental layers provide additional information on preferred habitats, such as elevation and water availability, to improve accuracy.

What it measures

• Species with a high probability of occurrence in the area.
• Scientific names and taxonomic information of species.
• Probability-based presence derived from species distribution models.

How to interpret

• Presence does not guarantee detection in every survey but indicates high likelihood of occurrence.
• Higher numbers of predicted species reflect richer biodiversity and ecological importance.

Unit / Scale

Species (spp.).

Temporal coverage: 2024.

Spatial resolution: 0 m (point-based).

Update frequency: Annual.

Author / Source

Lemu, based on GBIF and global environmental data layers.
🔗 https://www.gbif.org

📄 GBIF.org. (2023). GBIF occurrence data. Global Biodiversity Information Facility.

📄 Jung, M., Dahal, P. R., Butchart, S. H., Donald, P. F., De Lamo, X., Lesiv, M., Kapos, V., Rondinini, C., & Visconti, P. (2020). A global map of terrestrial habitat types. Scientific Data, 7(1), 1–8.

📄 Trabucco, A., & Zomer, R. J. (2019). Global high-resolution soil-water balance (Version 3) [Dataset]. Figshare.

📄 Japan Aerospace Exploration Agency (JAXA). (2024). ALOS Global Digital Surface Model “ALOS World 3D – 30m (AW3D30)” (Version 4.1). JAXA Earth Observation Research Center (EORC).

Applications in Atlas

• Provide a baseline list of species likely to occur in the area.
• Support biodiversity assessments for conservation or project planning.
• Complement observed records (GBIF sightings) with modelled distributions.
• Inform habitat suitability and ecosystem service analyses.