Data-driven analysis of fine-scale badger movement in the UK

Understanding animal movements at different spatial scales presents a significant challenge as their patterns can vary widely from daily foraging behaviours to broader migration or territorial movements. This challenge is of general interest because it impacts the ability to manage wildlife populations effectively. In this study, we conduct diffusion analysis based on European badger (Meles meles) movement data obtained from three different regions in the UK (Gloucestershire, Cornwall, and Northern Ireland) and fit a generalised linear mixed-effects model to examine the relationship between variables. We also feature a novel application of extended dynamic mode decomposition (EDMD) to uncover patterns relating to badger social organisation. By applying our approach to these different populations, we were able to assess its performance across a range of badger densities. A key result was that in some areas, EDMD clusters matched observed group home ranges, whilst in others, discrepancies likely arose because of population management interventions, such as badger culling. The methods presented offer a promising approach for studying territoriality and the impacts of management strategies on animal movement behaviour.

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Publication Details

Journal
PLoS Computational Biology
Published
2025-08-28
DOI
https://doi.org/10.1371/journal.pcbi.1013372
Primary Topic
Wildlife Ecology and Conservation
Type
article
Field-Weighted Citation Impact
0.00

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article

Data-driven analysis of fine-scale badger movement in the UK

Mark A. Chambers, Naratip Santitissadeekorn, Maria O’Hagan, Ruth Cox et al.
PLoS Computational Biology
Wildlife Ecology and Conservation
article

Data-driven analysis of fine-scale badger movement in the UK

Mark A. Chambers, Naratip Santitissadeekorn, Maria O’Hagan, Ruth Cox, Stefan Klus, David J. B. Lloyd, Roșie Woodroffe, Giovanni Lo Iacono, Richard J. Delahay, Jessica Rachel Furber
article en

Abstract

Understanding animal movements at different spatial scales presents a significant challenge as their patterns can vary widely from daily foraging behaviours to broader migration or territorial movements. This challenge is of general interest because it impacts the ability to manage wildlife populations effectively. In this study, we conduct diffusion analysis based on European badger (Meles meles) movement data obtained from three different regions in the UK (Gloucestershire, Cornwall, and Northern Ireland) and fit a generalised linear mixed-effects model to examine the relationship between variables. We also feature a novel application of extended dynamic mode decomposition (EDMD) to uncover patterns relating to badger social organisation. By applying our approach to these different populations, we were able to assess its performance across a range of badger densities. A key result was that in some areas, EDMD clusters matched observed group home ranges, whilst in others, discrepancies likely arose because of population management interventions, such as badger culling. The methods presented offer a promising approach for studying territoriality and the impacts of management strategies on animal movement behaviour.

PLoS Computational BiologyVol. 21(8)
Zoological Society of London (GB), Animal and Plant Health Agency (GB), University of Surrey (GB), Department of Agriculture and Rural Development (GB), Heriot-Watt University (GB), Institute for Sustainability (GB)
European Commission, University of Surrey, HORIZON EUROPE Framework Programme, Research Executive Agency
Openalex Percentile: Top 78%
Wildlife Ecology and Conservation
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