The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Habitat availability for amphibians and extinction threat: a global analysis
Open accessAbstract
Aim: Habitat loss and degradation are the factors threatening the largest number of amphibian species. However, quantitative measures of habitat availability only exist for a small subset of them. We evaluated the relationships between habitat availability, extinction risk and drivers of threat for the world's amphibians. We developed deductive habitat suitability models to estimate the extent of suitable habitat and the proportion of suitable habitat (PSH) inside the geographic range of each species, covering species and areas for which little or no high‐resolution distribution data are available. Location: Global. Methods: We used information on habitat preferences to develop habitat suitability models at 300‐m resolution, by integrating range maps with land cover and elevation. Model performance was assessed by comparing model output with point localities where species were recorded. We then used habitat availability as a surrogate of area of occupancy. Using the IUCN criteria, we identified species having narrow area of occupancy, for which extinction risk is likely underestimated. Results: We developed models for 5363 amphibians. Validation success of models was high (94%), being better for forest specialists and generalists than for open habitat specialists. Generalists had proportionally more habitat than forest or open habitat specialists. The PSH was lower for species having small geographical ranges, currently listed as threatened, and for which habitat loss is recognized as a threat. Differences in habitat availability among biogeographical realms were strong. We identified 61 forest species for which the extinction risk may be higher that currently assessed in the Red List, due to limited extent of suitable habitat. Main conclusions: Habitat models can accurately predict amphibian distribution at fine scale and allow describing biogeographical patterns of habitat availability. The strong relationship between amount of suitable habitat and extinction threat may help the conservation assessment in species for which limited information is currently available.
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
High-Resolution Global Maps of 21st-Century Forest Cover Change
Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., Thau, D., Stehman, S. V., Goetz, S. J., Loveland, T. R., et al. (2013) · Science · doi:10.1126/science.1244693 · Cited by 11,704
Terrestrial ecoregions of the world: a new map of life on Earth
Olson, D. M., Dinerstein, E., Wikramanayake, E. D., Burgess, N. D., Powell, G. V. N., Underwood, E. C., D'amico, J. A., Itoua, I., Strand, H. E., Morrison, J. C., et al. (2001) · BioScience · doi:10.1641/0006-3568(2001)051[0933:teotwa]2.0.co;2 · Cited by 8,488
F. Dormann, C., M. McPherson, J., B. Araújo, M., Bivand, R., Bolliger, J., Carl, G., G. Davies, R., Hirzel, A., Jetz, W., Daniel Kissling, W., et al. (2007) · Ecography · doi:10.1111/j.2007.0906-7590.05171.x · Cited by 3,433
The Impact of Conservation on the Status of the World’s Vertebrates
Hoffmann, M., Hilton-Taylor, C., Angulo, A., Böhm, M., Brooks, T. M., Butchart, S. H. M., Carpenter, K. E., Chanson, J., Collen, B., Cox, N. A., et al. (2010) · Science · doi:10.1126/science.1194442 · Cited by 1,515
Self-citationThe importance of correcting for sampling bias in MaxEnt species distribution models
Kramer‐Schadt, S., Niedballa, J., Pilgrim, J. D., Schröder, B., Lindenborn, J., Reinfelder, V., Stillfried, M., Heckmann, I., Scharf, A. K., Augeri, D. M., et al. (2013) · Diversity and Distributions · doi:10.1111/ddi.12096 · Cited by 1,321
Cited by
Quantitative evidence for the effects of multiple drivers on continental-scale amphibian declines
Grant, E. H. C., Miller, D. A. W., Schmidt, B. R., Adams, M. J., Amburgey, S. M., Chambert, T., Cruickshank, S. S., Fisher, R. N., Green, D. M., Hossack, B. R., et al. (2016) · Scientific Reports · doi:10.1038/srep25625 · Cited by 283
Resurrecting biodiversity: Advanced assisted reproductive technologies and biobanking
Bolton, R. L., Mooney, A., Pettit, M. T., Bolton, A. E., Morgan, L., Drake, G. J., Appeltant, R., Walker, S. L., Gillis, J. D., & Hvilsom, C. (2022) · Reproduction and Fertility · doi:10.1530/raf-22-0005 · Cited by 108
Assumption‐versus data‐based approaches to summarizing species’ ranges
Peterson, A. T., Navarro‐Sigüenza, A. G., & Gordillo, A. (2018) · Conservation Biology · doi:10.1111/cobi.12801 · Cited by 72
Environmental Factors Affecting Amphibian Communities in River Basins of the Southern Apennines
Nessi, A., Cioccarelli, S., Tremolada, P., Gariano, P., Grandinetti, M., Balestrieri, A., & Manenti, R. (2023) · Diversity · doi:10.3390/d15050625 · Cited by 7
Ramos, A. G., Mena, H., Schneider, D., & Zambrano, L. (2025) · PLOS ONE · doi:10.1371/journal.pone.0314257 · Cited by 2
Metadata
- Authors
- Ficetola, G. F., Rondinini, C., Bonardi, A., Baisero, D., & Padoa‐Schioppa, E.
- Venue
- Diversity and Distributions
- Publisher
- Wiley
- Published
- 2014-12-22
- Volume
- 21
- Issue
- 3
- Pages
- 302-311
- ISSN
- 0967-9952 (ISSN-L)
- 1366-9516
- 1472-4642
- OpenAlex
- W1968131663
- Cited by
- 163
- References
- 5
- FWCI
- 5.43
- Type
- journal article
- Language
- en
- Open access
- green
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
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.