Keywords
Principle of maximum entropyEnvironmental niche modellingRange (aeronautics)Species distributionEcologyStatisticsComputer scienceBiologyMathematicsEcological niche
Affiliated Institutions
Related Publications
Model‐based uncertainty in species range prediction
Abstract Aim Many attempts to predict the potential range of species rely on environmental niche (or ‘bioclimate envelope’) modelling, yet the effects of using different niche‐b...
Uses and Requirements of Ecological Niche Models and Related Distributional Models
Modeling approaches that relate known occurrences of species to landscape features to \ndiscover ecological properties and predict geographic occurrences have seen extensive...
ORIGINAL ARTICLE: Predicting species distributions from small numbers of occurrence records: a test case using cryptic geckos in Madagascar
Abstract Aim Techniques that predict species potential distributions by combining observed occurrence records with environmental variables show much potential for application ac...
Predicting species distributions from museum and herbarium records using multiresponse models fitted with multivariate adaptive regression splines
ABSTRACT Current circumstances — that the majority of species distribution records exist as presence‐only data (e.g. from museums and herbaria), and that there is an established...
Presence‐absence versus presence‐only modelling methods for predicting bird habitat suitability
Habitat suitability models can be generated using methods requiring information on species presence or species presence and absence. Knowledge of the predictive performance of s...
Publication Info
- Year
- 2005
- Type
- article
- Volume
- 190
- Issue
- 3-4
- Pages
- 231-259
- Citations
- 16826
- Access
- Closed
External Links
Social Impact
Altmetric
PlumX Metrics
Social media, news, blog, policy document mentions
Citation Metrics
16826
OpenAlex
Cite This
Steven J. Phillips,
Robert P. Anderson,
Robert E. Schapire
(2005).
Maximum entropy modeling of species geographic distributions.
Ecological Modelling
, 190
(3-4)
, 231-259.
https://doi.org/10.1016/j.ecolmodel.2005.03.026
Identifiers
- DOI
- 10.1016/j.ecolmodel.2005.03.026