Generalized linear and generalized additive models in studies of species distributions: setting the scene
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HSCNN out-performed CNN with a high prediction score and explainable results.
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Mendonça, P., Carneiro, L. S., Leandro‐Silva, V., Aleixo, A., Araripe, J., & Rêgo, P. S. (2025) · Ecology and Evolution · doi:10.1002/ece3.70331
- Authors
- Guisan, A., Edwards, T. C., & Hastie, T.
- Affiliations
- info fauna (CH)
- Utah State University (US)
- Stanford University (US)
- Corresponding author
- Guisan, Antoine
- Venue
- Ecological Modelling
- Publisher
- Elsevier BV
- Published
- 2002-11
- Volume
- 157
- Issue
- 2-3
- Pages
- 89-100
- ISSN
- 0304-3800 (ISSN-L)
- OpenAlex
- W2060298585
- Cited by
- 2,356
- References
- 87
- Citations by year
- 2026: 101 · 2025: 154 · 2024: 145 · 2023: 139 · 2022: 179 · 2021: 151 · 2020: 164 · 2019: 138 · 2018: 131 · 2017: 112 · 2016: 113 · 2015: 89 · 2014: 98 · 2013: 86 · 2012: 73
- FWCI
- 23.55
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Ecological Modelling (publishedVersion)
- IRIS (submittedVersion)
- SERVAL (Université de Lausanne) (submittedVersion)
- Funders
- Akademie der Naturwissenschaften
- Topics
- Physical Sciences › Environmental Science › Ecological Modeling › Species Distribution and Climate Change
- Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Applications
- Physical Sciences › Environmental Science › Nature and Landscape Conservation › Ecology and Vegetation Dynamics Studies
- Keywords
- generalized linear models, generalized additive models, species distribution modeling, ecological regression, predictor selection, model diagnostics, ridge regression, stepwise selection, interaction detection, regression trees, environmental management
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