Using geographic profiling to compare the value of sightings vs trap data in a biological invasion

Faulkner, Sally C. and Verity, Robert and Roberts, David L. and Roy, Sugoto S. and Robertson, Peter A. and Stevenson, Mark D. and Le Comber, Steven C. (2017) Using geographic profiling to compare the value of sightings vs trap data in a biological invasion. Diversity and Distributions, 23 . pp. 104-112. ISSN 1366-9516. (doi:https://doi.org/10.1111/ddi.12498) (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Official URL
http://dx.doi.org/10.1111/ddi.12498

Abstract

Aim: The development of conservation plans, including those dealing with invasive species, is underpinned by the need to obtain reliable and accurate data. However, in many cases responding rapidly is equally critical. Location: The data were obtained from the Hebridean Mink Project, which was set up with the objective of removing mink from North Uist, Benbecula and South Uist. Methods: Here, we introduce an extension of the Dirichlet process mixture (DPM) model of geographic profiling that can be used to estimate source locations of invasions directly from spatial point pattern data without the need to specify dispersal parameters. We use this model to analyse a biological invasion of American mink (Neovison vison) in the Hebrides. Results: Our results suggest that sightings data – which are relatively easy and quick to acquire – can be used to capture much of the information about sources of invasive species that is obtained from the harder to acquire and more intensive trap data. Main conclusion: These results have important implications for the development of conservation plans and, in this case, in the early stages of biological invasions, when interventions are most likely to be successful.

Item Type: Article
Uncontrolled keywords: Bayesian models; citizen science; conservation management; geographic profiling; invasive species; mink
Subjects: Q Science > QH Natural history
Q Science > QH Natural history > QH324.2 Computational biology
Q Science > QH Natural history > QH541 Ecology
Q Science > QH Natural history > QH75 Conservation (Biology)
Q Science > QL Zoology
Divisions: Faculties > Social Sciences > School of Anthropology and Conservation
Faculties > Social Sciences > School of Anthropology and Conservation > Biodiversity Conservation Group
Faculties > Social Sciences > School of Anthropology and Conservation > Biodiversity Management Group
Faculties > Social Sciences > School of Anthropology and Conservation > DICE (Durrell Institute of Conservation and Ecology)
Depositing User: David Roberts
Date Deposited: 28 Oct 2016 11:39 UTC
Last Modified: 01 Mar 2017 12:53 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/58184 (The current URI for this page, for reference purposes)
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