The DOI matches its Crossref record.
Mapping Species Distributions: Spatial Inference and Prediction
Abstract
Maps of species' distributions or habitat suitability are required for many aspects of environmental research, resource management and conservation planning. These include biodiversity assessment, reserve design, habitat management and restoration, species and habitat conservation plans and predicting the effects of environmental change on species and ecosystems. The proliferation of methods and uncertainty regarding their effectiveness can be daunting to researchers, resource managers and conservation planners alike. Franklin summarises the methods used in species distribution modeling (also called niche modeling) and presents a framework for spatial prediction of species distributions based on the attributes (space, time, scale) of the data and questions being asked. The framework links theoretical ecological models of species distributions to spatial data on species and environment, and statistical models used for spatial prediction. Providing practical guidelines to students, researchers and practitioners in a broad range of environmental sciences including ecology, geography, conservation biology, and natural resources management.
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Each is checked against this paper’s own text: does it say what the citing paper says it does?
In the citing paper
“In other words, the model shows moderate performance, which is able to discriminate between random points and the environment associated with site locations (Franklin 2010; Galletti et al. 2013).”
From A maxent predictive model for hunter-gatherer sites in the southern pampas, argentina (2021) · cites this paper as Franklin 2010
In the citing paper
“In other words, the model shows moderate performance, which is able to discriminate between random points and the environment associated with site locations (Franklin 2010; Galletti et al. 2013).”
From A maxent predictive model for hunter-gatherer sites in the southern pampas, argentina (2021) · cites this paper as Franklin 2010
Citations
Cited by
Valavi, R., Guillera‐Arroita, G., Lahoz‐Monfort, J. J., & Elith, J. (2022) · Ecological Monographs · doi:10.1002/ecm.1486 · Cited by 830
Species Distribution Modeling and Ecological Niche Modeling: Getting the Concepts Right
Peterson, A. T., & Soberón, J. (2012) · Natureza & Conservação · doi:10.4322/natcon.2012.019 · Cited by 702
A checklist for maximizing reproducibility of ecological niche models
Feng, X., Park, D. S., Walker, C., Peterson, A. T., Merow, C., & Papeş, M. (2019) · Nature Ecology & Evolution · doi:10.1038/s41559-019-0972-5 · Cited by 323
Potential ecological impacts of climate intervention by reflecting sunlight to cool Earth
Zarnetske, P. L., Gurevitch, J., Franklin, J., Groffman, P. M., Harrison, C. S., Hellmann, J. J., Hoffman, F. M., Kothari, S., Robock, A., Tilmes, S., et al. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1921854118 · Cited by 119
Self-citationHow Do Data Analysts Respond to AI Assistance? A Wizard-of-Oz Study
Gu, K., Grunde-McLaughlin, M., McNutt, A., Heer, J., & Althoff, T. (2024) · Proceedings of the CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3641891 · Cited by 40
Landscape Analysis of Adult Florida Panther Habitat
Frakes, R. A., Belden, R. C., Wood, B. E., & James, F. E. (2015) · PLOS ONE · doi:10.1371/journal.pone.0133044 · Cited by 30
A maxent predictive model for hunter-gatherer sites in the southern pampas, argentina
Rafuse, D. J. (2021) · Open Quaternary · doi:10.5334/oq.97 · Cited by 17
Hillers, A., Buchanan, G. M., Garteh, J. C., Tommy, S. M., Fofana, M. L., & Lindsell, J. A. (2017) · Oryx · doi:10.1017/s003060531600020x · Cited by 10
Wang, J., Soroush, M., Maziar, S., & Khazraee, E. (2026) · Journal of Archaeological Method and Theory · doi:10.1007/s10816-025-09733-5 · Cited by 3
Evaluation of Deep Species Distribution Models Using Environment and Co-occurrences
Deneu, B., Servajean, M., Botella, C., & Joly, A. (2019) · Lecture Notes in Computer Science · doi:10.1007/978-3-030-28577-7_18 · Cited by 8
Metadata
- Authors
- Franklin, J.
- Publisher
- Cambridge University Press
- Published
- 2010-01-07
- Cited by
- 1,534
- References
- 0
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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.
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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.
