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| Main Authors: | , |
|---|---|
| Format: | Recurso digital |
| Language: | English |
| Published: |
Zenodo
2025
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| Online Access: | https://doi.org/10.5281/zenodo.15774279 |
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Table of Contents:
- <p>The attached files contain predicted probabilities of species occurrence in both the Cairngorms and across the entirety of Scotland, generated using species distribution models. These models were developed using occurrence data from the Global Biodiversity Information Facility (GBIF) and bioclimatic variables from the WorldClim V1 dataset (University of California). Much of the modelling workflow was supported by the flexsdm R package (Velazco et al., 2022, <a href="https://doi.org/10.1111/2041-210X.13874" target="_new" rel="noopener">https://doi.org/10.1111/2041-210X.13874</a>). Prior to model fitting, occurrence data were filtered for environmental redundancy to reduce sampling bias, and background (pseudo-absence) points were randomly sampled within a 5 km buffered calibration area around presence records. The dataset was partitioned using four-fold spatial cross-validation, and models were fitted using Generalised Linear Models, Gaussian Processes, and Support Vector Machines (SVM). Ensemble predictions were then refined using an occurrence-informed posterior constraint to minimise overprediction. The number in each filename corresponds to the GBIF species ID.</p> <p>Two sets of model outputs are provided: One for the Cairngorms region (see 'past_outputs_cairngorms.zip') and another for the entirety of Scotland (see 'scotland_sdm_results.zip'). The national-level estimates cover a broader area but are provided at a coarser spatial resolution. Additionally, the national-level outputs are accompanied by reports generated in accordance with the ODMAP (Overview, Data, Model, Assessment and Prediction) protocol (Zurell et al., 2020, <a href="https://doi.org/10.1111/ecog.04960" target="_new" rel="noopener">https://doi.org/10.1111/ecog.04960</a>), offering structured documentation of the modelling process.</p> <p>Funding for BioDT came from the European Union’s Horizon Europe Research and Innovation Programme under grant agreement No 101057437 (BioDT project, <a href="https://doi.org/10.3030/101057437">https://doi.org/10.3030/101057437</a>). Views and opinions expressed are those of the author(s) only and do not necessarily reflect those of the European Union or the European Commission. Neither the European Union nor the European Commission can be held responsible for them.</p>