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DynamicSDM: an R package for species geographical distribution and abundance modelling at high spatiotemporal resolution

DynamicSDM: an R package for species geographical distribution and abundance modelling at high spatiotemporal resolution

Dobson, Rachel, Challinor, Andy J., Cheke, Robert ORCID logoORCID: https://orcid.org/0000-0002-7437-1934, Jennings, Stewart, Willis, Stephen G. and Dallimer, Martin (2023) DynamicSDM: an R package for species geographical distribution and abundance modelling at high spatiotemporal resolution. Methods in Ecology and Evolution, 14 (5):17674644. pp. 1190-1199. ISSN 2041-210X (Online) (doi:10.1111/2041-210X.14101)

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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.

Item Type: Article
Uncontrolled Keywords: dynamic ecological niche modelling; dynamic species abundance modelling; dynamic species distribution modelling; R package; spatial ecology; statistics; spatial or time-series
Subjects: G Geography. Anthropology. Recreation > GE Environmental Sciences
Q Science > QA Mathematics > QA76 Computer software
S Agriculture > S Agriculture (General)
Faculty / School / Research Centre / Research Group: Faculty of Engineering & Science
Faculty of Engineering & Science > Natural Resources Institute
Faculty of Engineering & Science > Natural Resources Institute > Agriculture, Health & Environment Department
Faculty of Engineering & Science > Natural Resources Institute > Centre for Sustainable Agriculture 4 One Health
Faculty of Engineering & Science > Natural Resources Institute > Centre for Sustainable Agriculture 4 One Health > Behavioural Ecology
Last Modified: 27 Nov 2024 14:29
URI: http://gala.gre.ac.uk/id/eprint/39074

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