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Large-scale mammal monitoring: the potential of a citizen science camera-trapping project in the United Kingdom

Hsing, Pen-Yuan; Hill, Russell; Smith, Graham; Bradley, Steven; Green, Sian; Kent, Vivien; Mason, Samantha; Rees, Jonathan; Whittingham, Mark; Cokill, Jim; scientists, MammalWeb citizen; Stephens, Philip

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Authors

Pen-Yuan Hsing

Graham Smith

Sian Green sian.e.green@durham.ac.uk
PGR Student Doctor of Philosophy

Vivien Kent

Samantha Mason samantha.s.mason@durham.ac.uk
PGR Student Doctor of Philosophy

Jonathan Rees jonathan.p.rees@durham.ac.uk
PGR Student Doctor of Philosophy

Mark Whittingham

Jim Cokill

MammalWeb citizen scientists



Abstract

1. In light of global biodiversity loss, there is an increasing need for large-scale wildlife monitoring. This is difficult for mammals, since they can be elusive and nocturnal. In the United Kingdom (UK), there is a lack of systematic, widespread mammal monitoring, and a recognised deficiency of data. Innovative new approaches are required. 2. We developed MammalWeb, a portal to enable UK-wide camera-trapping by a network of citizen scientists and partner organisations. MammalWeb citizen scientists contribute to both the collection and classification of camera trap data. Following trials in 2013-17, MammalWeb has grown organically to increase its geographic reach (e.g. ~2,000 sites in Britain). It has so far provided the equivalent of over 340 camera trap-years of wild mammal monitoring, and produced nearly 440,000 classified image sequences and videos, of which, over 180,000 are mammal detections. 3. We describe MammalWeb, its background, its development and the novel approaches we have for participation. We consider the data collected by MammalWeb participants, especially in light of their relevance to the main goals of wildlife monitoring: to provide spatial data, abundance data, and temporal behavioural data. 4. MammalWeb can complement existing approaches to mammal monitoring. Explicit accounting for spatial and temporal patterns in animal activity enables accounting of bias relative to ad hoc observational data. Estimating abundance presents challenges, as for many camera trapping studies, but we discuss the potential of the data as they stand, and opportunities to advance their value for abundance estimation. 5. Challenges remain to MammalWeb’s central missions of enhancing engagement with and connection to nature, and delivering policy-relevant data on Britain's wild mammals. We discuss these challenges and the opportunities they provide for advances in respect of engagement, science and financial security. 6. Our approach reduces administrative burden and increases spatial coverage and, as such, MammalWeb provides a useful addition to existing case studies of citizen science camera trapping program design. We believe MammalWeb is an important step towards fulfilling calls for UK-wide mammal monitoring and our description of challenges identifies an agenda for fulfilling that purpose.

Citation

Hsing, P.-Y., Hill, R., Smith, G., Bradley, S., Green, S., Kent, V., Mason, S., Rees, J., Whittingham, M., Cokill, J., scientists, M. C., & Stephens, P. (2022). Large-scale mammal monitoring: the potential of a citizen science camera-trapping project in the United Kingdom. Ecological Solutions and Evidence, 3(4), Article e12180. https://doi.org/10.1002/2688-8319.12180

Journal Article Type Article
Acceptance Date Aug 18, 2022
Online Publication Date Oct 11, 2022
Publication Date Oct 11, 2022
Deposit Date Aug 18, 2022
Publicly Available Date Oct 12, 2022
Journal Ecological solutions and evidence.
Print ISSN 2688-8319
Publisher Wiley Open Access
Peer Reviewed Peer Reviewed
Volume 3
Issue 4
Article Number e12180
DOI https://doi.org/10.1002/2688-8319.12180
Public URL https://durham-repository.worktribe.com/output/1196776

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

Copyright Statement
© 2022 The Authors. Ecological Solutions and Evidence 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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