Dobson, R, Challinor, AJ orcid.org/0000-0002-8551-6617, Cheke, RA et al. (3 more authors) (2023) dynamicSDM: An R package for species geographical distribution and abundance modelling at high spatiotemporal resolution. Methods in Ecology and Evolution, 14 (5). pp. 1190-1199. ISSN 2041-210X
Abstract
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.
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.
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.
As dynamicSDM functions are flexible and easily applied, we suggest that these tools could be readily applied to other taxa and systems globally.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Authors. This is an open access article under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution and reproduction in any medium, provided the original work is properly cited. |
Keywords: | dynamic ecological niche modelling, dynamic species abundance modelling, dynamic species distribution modelling, R package, spatial ecology, statistics: spatial or time-series |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Inst for Climate & Atmos Science (ICAS) (Leeds) The University of Leeds > Faculty of Environment (Leeds) > School of Earth and Environment (Leeds) > Sustainability Research Institute (SRI) (Leeds) |
Funding Information: | Funder Grant number BBSRC (Biotechnology & Biological Sciences Research Council) BB/P027784/1 |
Depositing User: | Symplectic Publications |
Date Deposited: | 29 Mar 2023 11:37 |
Last Modified: | 21 Jul 2023 13:10 |
Published Version: | https://besjournals.onlinelibrary.wiley.com/doi/10... |
Status: | Published |
Publisher: | Wiley |
Identification Number: | 10.1111/2041-210x.14101 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:197798 |