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Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling
Sillero, N.; Arenas-Castro, S.; Enriquez-Urzelai, U.; Vale, C.G.; Sousa-Guedes, D.; Martínez-Freiría, F.; Real, R.; Barbosa, A.M. (2021). Want to model a species niche? A step-by-step guideline on correlative ecological niche modelling. Ecol. Model. 456: 109671. https://dx.doi.org/10.1016/j.ecolmodel.2021.109671
In: Ecological Modelling. Elsevier: Amsterdam; Lausanne; New York; Oxford; Shannon; Tokyo. ISSN 0304-3800; e-ISSN 1872-7026
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| Trefwoord |
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| Author keywords |
Species distribution models; Best practices; Model assumptions and limitations; Model preparation and parametrization; Model validation; Model performance |
| Auteurs | | Top |
- Sillero, N.
- Arenas-Castro, S.
- Enriquez-Urzelai, U.
- Vale, C.G.
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- Sousa-Guedes, D.
- Martínez-Freiría, F.
- Real, R.
- Barbosa, A.M.
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| Abstract |
The use of correlative ecological niche models has highly increased in the last decade. Despite all literature and textbooks in this field, few practical guidelines exist on the correct application of these techniques. We present here a step-by-step guideline explaining best practices for calculating correlative ecological niche models considering their conceptual and statistical assumptions and limitations. We divided the modelling process into four stages: 1) data collection and preparation; 2) model calculation; 3) model evaluation and validation; 4) and model application. Based on ecological niche theory, we review the concepts of ecological niche and how they can be modelled; classes of correlative models; modelling software; selection of study area; data sources for species records and environmental variables; types of species records and their influence on correlative models; errors in species records; minimum number of species records and environmental variables; effects of prevalence, sampling design, biases, and collinearity between variables; model calculation; model projection to different scenarios in time and space; ensemble modelling; model validation; classification, discrimination and calibration metrics; calculation of null models; analysis of model results; and model thresholding. This guideline is expected to help potential users to obtain better results when using correlative ecological niche models. |
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