The importance of fine‐scale predictors of wild boar habitat use in an isolated population
Open Access
- 22 June 2022
- journal article
- research article
- Published by Wiley in Ecology and Evolution
- Vol. 12 (6), e9031
- https://doi.org/10.1002/ece3.9031
Abstract
Predicting the likelihood of wildlife presence at potential wildlife-livestock interfaces is challenging. These interfaces are usually relatively small geographical areas where landscapes show large variation over small distances. Models of wildlife distribution based on coarse data over wide geographical ranges may not be representative of these interfaces. High-resolution data can help identify fine-scale predictors of wildlife habitat use at a local scale and provide more accurate predictions of species habitat use. These data may be used to inform knowledge of interface risks, such as disease transmission between wildlife and livestock, or human-wildlife conflict. This study uses fine-scale habitat use data from wild boar (Sus scrofa) based on activity signs and direct field observations in and around the Forest of Dean in Gloucestershire, England. Spatial logistic regression models fitted using a variant of penalized quasi-likelihood were used to identify habitat-based and anthropogenic predictors of wild boar signs. Our models showed that within the Forest of Dean, wild boar signs were more likely to be seen in spring, in forest-type habitats, closer to the center of the forest and near litter bins. In the area surrounding the Forest of Dean, wild boar signs were more likely to be seen in forest-type habitats and near recreational parks and less likely to be seen near livestock. This approach shows that wild boar habitat use can be predicted using fine-scale data over comparatively small areas and in human-dominated landscapes, while taking account of the spatial correlation from other nearby fine-scale data-points. The methods we use could be applied to map habitat use of other wildlife species in similar landscapes, or of movement-restricted, isolated, or fragmented wildlife populations.Funding Information
- Biotechnology and Biological Sciences Research Council (BB/E/I/00007036, BB/E/I/00007037, BB/M009513/1)
This publication has 43 references indexed in Scilit:
- African swine fever (ASF): Five years around EuropeVeterinary Microbiology, 2013
- Fine‐scale environmental variation in species distribution modelling: regression dilution, latent variables and neighbourly adviceMethods in Ecology and Evolution, 2011
- Updating coarse-scale species distribution models using small fine-scale samplesEcological Modelling, 2010
- Use of Coarse‐Resolution Models of Species’ Distributions to Guide Local Conservation InferencesConservation Biology, 2010
- Environmental Factors Affecting the Distribution of the Wild Boar, Sika Deer, Asiatic Black Bear and Japanese Macaque in Central Japan, with Implications for Human-Wildlife ConflictMammal Study, 2009
- Evidence of the role of European wild boar as a reservoir of Mycobacterium tuberculosis complexVeterinary Microbiology, 2008
- Effects of incorporating spatial autocorrelation into the analysis of species distribution dataGlobal Ecology and Biogeography, 2007
- Foot-and-Mouth DiseaseClinical Microbiology Reviews, 2004
- Spatial Autocorrelation: Trouble or New Paradigm?Ecology, 1993
- Notes on Continuous Stochastic PhenomenaBiometrika, 1950