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dynamicSDM: An R package for species geographical distribution and abundance modelling at high spatiotemporal resolution

Dobson, Rachel; Challinor, Andy J.; Cheke, Robert A.; Jennings, Stewart; Willis, Stephen G.; Dallimer, Martin

dynamicSDM: An R package for species geographical distribution and abundance modelling at high spatiotemporal resolution Thumbnail


Authors

Rachel Dobson

Andy J. Challinor

Robert A. Cheke

Stewart Jennings

Martin Dallimer



Abstract

1. Species distribution models (SDM) are widely applied to understand changing species geographical distribution and abundance patterns. However, existing SDM tools are inherently static and inadequate for modelling species distributions that are driven by dynamic environmental conditions. 2. dynamicSDM provides novel tools that explicitly consider the temporal dimension at key SDM stages, including functions for: (a) Cleaning and filtering species occurrence records by spatial and temporal qualities; (b) Generating pseudo-absence records through space and time; (c) Extracting spatiotemporally buffered explanatory variables; (d) Fitting SDMs whilst accounting for temporal biases and autocorrelation and (e) Projecting intra- and inter- annual geographical distributions and abundances at high spatiotemporal resolution. 3. Package functions have been designed to be: flexible for targeting specific study species; compatible with other SDM tools; and, by utilising Google Earth Engine and Google Drive, to have low computing power and storage needs. We illustrate dynamicSDM functions with an example of a nomadic bird in southern Africa, the red-billed quelea Quelea quelea. 4. As dynamicSDM functions are flexible and easily applied, we suggest that these tools could be readily applied to other taxa and systems globally.

Citation

Dobson, R., Challinor, A. J., Cheke, R. A., Jennings, S., Willis, S. G., & Dallimer, M. (2023). dynamicSDM: An R package for species geographical distribution and abundance modelling at high spatiotemporal resolution. Methods in Ecology and Evolution, 14(5), 1190-1199. https://doi.org/10.1111/2041-210x.14101

Journal Article Type Article
Acceptance Date Mar 10, 2023
Online Publication Date Mar 26, 2023
Publication Date 2023-05
Deposit Date Mar 28, 2023
Publicly Available Date May 31, 2023
Journal Methods in Ecology and Evolution
Electronic ISSN 2041-210X
Publisher Wiley
Peer Reviewed Peer Reviewed
Volume 14
Issue 5
Pages 1190-1199
DOI https://doi.org/10.1111/2041-210x.14101

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Publisher Licence URL
http://creativecommons.org/licenses/by/4.0/

Copyright Statement
© 2023 The Authors. Methods in Ecology and Evolution published by John Wiley & Sons Ltd on behalf of British Ecological Society.

This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.







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