Title
Spatial analysis of aerial survey data reveals correlates of elephant carcasses within a heavily poached ecosystem
Author(s)
Beale, Colin M.; Hauenstein, Severin; Mduma, Simon; Frederick, Howard; Jones, Trevor; Bracebridge, Claire; Maliti, Honori; Kija, Hamza; Kohi, Edward M.
Published
2018
Publisher
Biological Conservation
Abstract
Growth of the illegal wildlife trade is a key driver of biodiversity loss, with considerable research focussing on trafficking and trade, but rather less focussed on supply. Elephant poaching for ivory has driven a recent population decline in African elephants and is a typical example of illegal wildlife trade. Some of the heaviest poaching has been in Southern Tanzania's Ruaha-Rungwa ecosystem. Using data from three successive aerial surveys and modern spatial analysis techniques we identify the correlates of elephant carcasses within the ecosystem, from which important information about how poachers operate can be gleaned. Carcass density was highest close to wet-season (but not dry season) waterholes, at higher altitudes and at intermediate travel cost from villages. We found no evidence for an ecosystem-wide impact of ranger patrol locations on carcass abundance, but found strong evidence that different ranger posts showed contrasting patterns in relation to carcasses, some being significantly associated with clusters of carcasses, others showing the expected negative correlation and most showing no pattern at all. Despite a spatial change in elephant carcass locations between years, we find little evidence to suggest poachers have changed their behaviour in relation to key modelled covariates. Our maps of poaching activity can feed directly into anti-poaching control measures, but also provide general insights into how illegal harvest of high value wildlife products occurs in the field, and our spatio-temporal analysis provides a valuable analysis framework for aerial survey data from protected areas globally.
Keywords
Loxodonta africana;Illegal wildlife trade;Systematic reconnaissance flight (SRF) survey;Ruaha-Rungwa;Bayesian analysis;Continuous autoregressive models
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PUB21338