Modeling current and potential distributions of mammal species using presence‐only data: a case study on British deer

Croft, Simon; Ward, Alastair I.; Aegerter, James N.; Smith, Graham C.

Abstract

Aim: Decisions on wildlife conservation, management, and epidemiological risk are best based on robust evidence. The continual improvement of species distributions, such that they can be relied upon in decision‐making, is important. Here we seek to refine aspects of a generic modelling approach and improve the utility of species
distribution maps.
Location: Great Britain (GB).
Methods: We applied a modeling framework based on hierarchical Bayesian species distribution models exploiting opportunistic occurrence records from citizen science datasets to predict both current and potential distributions for each of the six deer
species known to be present in GB. Using the resulting maps, we performed a simple analysis of the overlap between species to illustrate possible contact, which we interpret as the relative risk of potential disease spread given an introduction.
Results: Predicted distribution maps showed good agreement with the broader scale occurrence reported by a recent national deer survey with an average True Skill Statistics and AUC of 0.69 and 0.89, respectively. Aggregation of the maps for all species highlighted regions of central and eastern England as well as parts of Scotland
where extensive areas of range overlap could result in interspecific contact with consequences for risk assessments for diseases of deer. However, if populations are allowed to expand to their predicted potential, then areas of overlap, and therefore disease interspecific transmission risk, will become extensive and widespread across all of mainland Britain.
Main conclusions: The generic modeling approach outlined performed well across all of the deer species tested, offering a robust and reliable tool through which current and potential animal distributions can be estimated and presented. Our application,
intended to inform quantitative risk assessments, demonstrates the practical use of such outputs to generate the valuable evidence required to inform policy decisions on issues such as management strategy.

Citation

Croft, S., Ward, A. I., Aegerter, J. N., & Smith, G. C. (2019). Modeling current and potential distributions of mammal species using presence‐only data: a case study on British deer. Ecology and Evolution, https://doi.org/10.1002/ece3.5424

• Journal Article Type: Article
• Acceptance Date: Jun 14, 2019
• Online Publication Date: Jul 11, 2019
• Publication Date: Jul 11, 2019
• Deposit Date: Jul 25, 2019
• Publicly Available Date: Jul 26, 2019
• Journal: Ecology and Evolution
• Electronic ISSN: 2045-7758
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• DOI: https://doi.org/10.1002/ece3.5424
• Keywords: Citizen science; Deer; Disease; Risk assessment; Species distribution modeling; Wildlife management
• Public URL: https://hull-repository.worktribe.com/output/2239798
• Publisher URL: https://onlinelibrary.wiley.com/doi/full/10.1002/ece3.5424
• Additional Information: © 2019 Crown copyright. Ecology and Evolution published by John Wiley & Sons Ltd. This article is published with the permission of the Controller of HMSO and the Queen's Printer for Scotland.; ; 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.
• Contract Date: Jul 25, 2019