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Cited by 394

The DOI matches its Crossref record; 245 of the 245 references it cites were found in a registry or an index.

Joint Species Distribution Modelling: With Applications in R

Ovaskainen, Otso, Abrego, Nerea·2020·Cambridge University Press eBooks

Abstract

Joint species distribution modelling (JSDM) is a fast-developing field and promises to revolutionise how data on ecological communities are analysed and interpreted. Written for both readers with a limited statistical background, and those with statistical expertise, this book provides a comprehensive account of JSDM. It enables readers to integrate data on species abundances, environmental covariates, species traits, phylogenetic relationships, and the spatio-temporal context in which the data have been acquired. Step-by-step coverage of the full technical detail of statistical methods is provided, as well as advice on interpreting results of statistical analyses in the broader context of modern community ecology theory. With the advantage of numerous example R-scripts, this is an ideal guide to help graduate students and researchers learn how to conduct and interpret statistical analyses in practice with the R-package Hmsc, providing a fast starting point for applying joint species distribution modelling to their own data.

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Metadata

Authors
Ovaskainen, O., & Abrego, N.
Venue
Cambridge University Press eBooks
Published
2020-05-18
OpenAlex
W3154551701
Cited by
394
References
245
FWCI
7.56
Type
book
Language
en
Open access
closed

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CoChat. (2026). Citation check: Joint Species Distribution Modelling: With Applications in R. https://app.cochat.ai/papers/10.1017/9781108591720
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Ovaskainen, O., & Abrego, N. (2020). Joint Species Distribution Modelling: With Applications in R. Cambridge University Press eBooks. https://doi.org/10.1017/9781108591720

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.