An evaluation of methods for modelling species distributions
Abstract
Aim Various statistical techniques have been used to model species probabilities of occurrence in response to environmental conditions. This paper provides a comprehensive assessment of methods and investigates whether errors in model predictions are associated to specific kinds of geographical and environmental distributions of species. Location Portugal, Western Europe. Methods Probabilities of occurrence for 44 species of amphibians and reptiles in Portugal were modelled using seven modelling techniques: Gower metric, Ecological Niche Factor Analysis, classification trees, neural networks, generalized linear models, generalized additive models and spatial interpolators. Generalized linear and additive models were constructed with and without a term accounting for spatial autocorrelation. Model performance was measured using two methods: sensitivity and Kappa index. Species were grouped according to their spatial (area of occupancy and extent of occurrence) and environmental (marginality and tolerance) distributions. Two‐way comparison tests were performed to detect significant interactions between models and species groups. Results Interaction between model and species groups was significant for both sensitivity and Kappa index. This indicates that model performance varied for species with different geographical and environmental distributions. Artificial neural networks performed generally better, immediately followed by generalized additive models including a covariate t…
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Artificial neural networks generally perform well for addressing questions related to species distribution modeling.
“They generally perform well for addressing questions related to species distribution modeling (Segurado & Araujo 2004).”
From Comparison between environmental characteristics of larval bluefin tuna Thunnus thynnus habitat in the Gulf of Mexico and western Mediterranean Sea (2013) · cites this paper as Segurado & Araujo 2004
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References 67 · Cited by 875
- Authors
- Segurado, P., & Araújo, M. B.
- Affiliations
- University of Évora (PT)
- Centre National de la Recherche Scientifique (FR)
- Corresponding author
- Araújo, Miguel B.
- Venue
- Journal of Biogeography
- Publisher
- Wiley
- Published
- 2004-09-13
- Volume
- 31
- Issue
- 10
- Pages
- 1555-1568
- ISSN
- 0305-0270 (ISSN-L)
- 1365-2699
- OpenAlex
- W1838542636
- Cited by
- 875
- References
- 67
- Citations by year
- 2026: 19 · 2025: 28 · 2024: 26 · 2023: 44 · 2022: 32 · 2021: 35 · 2020: 31 · 2019: 35 · 2018: 35 · 2017: 36 · 2016: 45 · 2015: 28 · 2014: 43 · 2013: 39 · 2012: 54
- FWCI
- 27.12
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Biogeography (publishedVersion)
- Topics
- Physical Sciences › Environmental Science › Ecological Modeling › Species Distribution and Climate Change
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ecology and Vegetation Dynamics Studies
- Physical Sciences › Environmental Science › Global and Planetary Change › Amphibian and Reptile Biology
- Keywords
- species distribution modeling, amphibians, reptiles, model performance comparison, spatial autocorrelation, generalized additive models, artificial neural networks, classification trees, generalized linear models, ecological niche factor analysis, area of occupancy, extent of occurrence, species tolerance, model sensitivity, kappa index, Portugal
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