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A camera trap method for estimating target densities of grey squirrels to inform wildlife management applications

Beatham, S.E.; Stephens, P.A.; Coats, J.; Phillips, J.; Massei, G.

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Authors

Sarah Beatham sarah.e.beatham@durham.ac.uk
PGR Student Doctor of Philosophy

J. Coats

J. Phillips

G. Massei



Abstract

Effective wildlife population management requires an understanding of the abundance of the target species. In the UK, the increase in numbers and range of the non-native invasive grey squirrel Sciurus carolinensis poses a substantial threat to the existence of the native red squirrel S. vulgaris, to tree health, and to the forestry industry. Reducing the number of grey squirrels, is crucial to mitigate their impacts. Camera traps are increasingly used to estimate animal abundance, and methods have been developed that do not require the identification of individual animals. Most of these methods have been focussed on medium to large mammal species with large range sizes and may be unsuitable for measuring local abundances of smaller mammals that have variable detection rates and hard to measure movement behaviour. The aim of this study was to develop a practical and cost-effective method, based on a camera trap index, that could be used by practitioners to estimate target densities of grey squirrels in woodlands to provide guidance on the numbers of traps or contraceptive feeders required for local grey squirrel control. Camera traps were deployed in ten independent woods of between 6 and 28 ha in size. An index, calculated from the number of grey squirrel photographs recorded per camera per day had a strong linear relationship (R2 = 0.90) with the densities of squirrels removed in trap and dispatch operations. From different time filters tested, a 5 minute filter was applied, where photographs of squirrels recorded on the same camera within 5 minutes of a previous photograph were not counted. There were no significant differences between the number of squirrel photographs per camera recorded by three different models of camera, increasing the method's practical application. This study demonstrated that a camera index could be used to inform the number of feeders or traps required for grey squirrel management through culling or contraception. Results could be obtained within six days without requiring expensive equipment or a high level of technical input. This method can easily be adapted to other rodent or small mammal species, making it widely applicable to other wildlife management interventions.

Citation

Beatham, S., Stephens, P., Coats, J., Phillips, J., & Massei, G. (2023). A camera trap method for estimating target densities of grey squirrels to inform wildlife management applications. Frontiers in Ecology and Evolution, 11, Article 1096321. https://doi.org/10.3389/fevo.2023.1096321

Journal Article Type Article
Acceptance Date May 9, 2023
Online Publication Date Jun 13, 2023
Publication Date 2023
Deposit Date May 9, 2023
Publicly Available Date May 11, 2023
Journal Frontiers in Ecology and Evolution
Print ISSN 2296-701X
Publisher Frontiers Media
Peer Reviewed Peer Reviewed
Volume 11
Article Number 1096321
DOI https://doi.org/10.3389/fevo.2023.1096321
Public URL https://durham-repository.worktribe.com/output/1174920

Files

Published Journal Article (1.5 Mb)
PDF

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

Copyright Statement
© 2023 Beatham, Stephens, Coats, Phillips and Massei. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.


Accepted Journal Article (692 Kb)
PDF

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

Copyright Statement
© 2023 Beatham, Stephens, Coats, Phillips and Massei. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.







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