The DOI matches its Crossref record; 34 of the 34 references it cites were found in a registry or an index.
BIOMOD – a platform for ensemble forecasting of species distributions
Abstract
BIOMOD is a computer platform for ensemble forecasting of species distributions, enabling the treatment of a range of methodological uncertainties in models and the examination of species‐environment relationships. BIOMOD includes the ability to model species distributions with several techniques, test models with a wide range of approaches, project species distributions into different environmental conditions (e.g. climate or land use change scenarios) and dispersal functions. It allows assessing species temporal turnover, plot species response curves, and test the strength of species interactions with predictor variables. BIOMOD is implemented in R and is a freeware, open source, package.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
R: A Language and Environment for Statistical Computing
R Core Team (2025) · doi:10.32614/r.manuals · Cited by 352,181
Breiman, L. (2001) · Machine Learning · doi:10.1023/a:1010933404324 · Cited by 133,538
Classification and Regression Trees.
Gordon, A. D., Breiman, L., Friedman, J. H., Olshen, R. A., & Stone, C. J. (1984) · Biometrics · doi:10.2307/2530946 · Cited by 23,522
The meaning and use of the area under a receiver operating characteristic (ROC) curve.
Hanley, J. A., & McNeil, B. J. (1982) · Radiology · doi:10.1148/radiology.143.1.7063747 · Cited by 21,856
(2005) · Statistics for Biology and Health · doi:10.1007/0-387-27255-0_9 · Cited by 20,133
McCullagh, P., & Nelder, J. A. (1989) · doi:10.1007/978-1-4899-3242-6 · Cited by 16,836
Novel methods improve prediction of species’ distributions from occurrence data
Elith*, J., H. Graham*, C., P. Anderson, R., Dudík, M., Ferrier, S., Guisan, A., J. Hijmans, R., Huettmann, F., R. Leathwick, J., Lehmann, A., et al. (2006) · Ecography · doi:10.1111/j.2006.0906-7590.04596.x · Cited by 9,088
Brown, R. A., Hastie, T. J., & Tibshirani, R. J. (1991) · Biometrics · doi:10.2307/2532174 · Cited by 8,176
Multivariate Adaptive Regression Splines
Friedman, J. H. (1991) · The Annals of Statistics · doi:10.1214/aos/1176347963 · Cited by 8,000
Koyak, R. A., Hastie, T. J., & Tibshirani, R. J. (1991) · Journal of the American Statistical Association · doi:10.2307/2290538 · Cited by 7,596
Cited by
Selecting pseudo‐absences for species distribution models: how, where and how many?
Barbet‐Massin, M., Jiguet, F., Albert, C. H., & Thuiller, W. (2012) · Methods in Ecology and Evolution · doi:10.1111/j.2041-210x.2011.00172.x · Cited by 2,716
Self-citationBrown, J. L. (2014) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.12200 · Cited by 1,254
Valavi, R., Guillera‐Arroita, G., Lahoz‐Monfort, J. J., & Elith, J. (2022) · Ecological Monographs · doi:10.1002/ecm.1486 · Cited by 830
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) · Ecological Modelling · doi:10.1016/j.ecolmodel.2021.109671 · Cited by 456
Qiao, H., Soberón, J., & Peterson, A. T. (2015) · Methods in Ecology and Evolution · doi:10.1111/2041-210x.12397 · Cited by 448
Metadata
- Authors
- Thuiller, W., Lafourcade, B., Engler, R., & Araújo, M. B.
- Venue
- Ecography
- Publisher
- Wiley
- Published
- 2009-06
- Volume
- 32
- Issue
- 3
- Pages
- 369-373
- ISSN
- 0906-7590 (ISSN-L)
- 1600-0587
- OpenAlex
- W2002758482
- Cited by
- 2,749
- References
- 34
- FWCI
- 32.56
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: BIOMOD – a platform for ensemble forecasting of species distributions. https://app.cochat.ai/papers/10.1111/j.1600-0587.2008.05742.x
- The paper
- Thuiller, W., Lafourcade, B., Engler, R., & Araújo, M. B. (2009). BIOMOD – a platform for ensemble forecasting of species distributions. Ecography. https://doi.org/10.1111/j.1600-0587.2008.05742.x
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
