Spatially-explicit model for assessing wild dog control strategies in Western Australia

Carlo Pacioni, Malcolm S. Kennedy, Oliver Berry, Danielle Stephens, Nathan H. Schumaker

Research output: Contribution to journalArticle

6 Citations (Scopus)

Abstract

Large predators can significantly impact livestock industries. In Australia, wild dogs (Canis lupus familiaris, Canis lupus dingo, and hybrids) cause economic losses of more than AUD$40 M annually. Landscape-scale exclusion fencing coupled with lethal techniques is a widely practiced control method. In Western Australia, the State Barrier Fence encompasses approximately 260,000 km2 of predominantly agricultural land, but its effectiveness in preventing wild dogs from entering the agricultural region is difficult to evaluate. We conducted a management strategy evaluation (MSE) based on spatially-explicit population models to forecast the effects of upgrades to the Western Australian State Barrier Fence and several control scenarios varying in intensity and spatial extent on wild dog populations in southwest Western Australia. The model results indicate that populations of wild dogs on both sides of the State Barrier Fence are self-sustaining and current control practices are not sufficient to effectively reduce their abundance in the agricultural region. Only when a combination of control techniques is applied on a large scale, intensively and continuously are wild dog numbers effectively controlled. This study identifies the requirement for addressing extant populations of predators within fenced areas to meet the objective of preventing wild dog expansion. This objective is only achieved when control is applied to the whole area where wild dogs are currently present within the fence plus an additional buffer of ∼20 km. Our modelling focused on the use of baiting, trapping and shooting; however, we acknowledge that additional tools may also be applied. Finally, we recommend that a cost-benefit analysis be performed to evaluate the economic viability of an integrated control strategy.

Original languageEnglish
Pages (from-to)246-256
Number of pages11
JournalEcological Modelling
Volume368
DOIs
Publication statusPublished - 24 Jan 2018

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