Predicting targets and costs for feral-cat reduction on large islands using stochastic population models

Author:

Venning Kathryn R. W.ORCID,Saltré FrédérikORCID,Bradshaw Corey J. A.ORCID

Abstract

AbstractFeral cats are some of the most destructive invasive predators worldwide, particularly in insular environments; hence, density-reduction campaigns are often applied to alleviate the predation mortality they add to native fauna. Density-reduction and eradication efforts are costly procedures with important outcomes for native fauna recovery, so they require adequate planning to be successful. These plans need to include empirical density-reduction models that can guide yearly culling quotas, and resource roll-out for the duration of the culling period. This ensures densities are reduced over the long term and that no resources are wasted. We constructed a stochastic population model with cost estimates to test the relative effectiveness and cost-efficiency of two main culling scenarios for a 10-year eradication campaign of cats on Kangaroo Island, Australia: (1) constant proportional annual cull (one-phase), and (2) high initial culling followed by a constant proportional maintenance cull (two-phase). A one-phase cull of at least 0.35 of the annual population size would reduce the final population to 0.1 of its original size, while a two-phase cull with an initial cull of minimum 0.6 and minimum 0.5 maintenance cull would reduce the final population to 0.01 of its initial size by 2030. Cost estimates varied widely depending on the methods applied (shooting, trapping, aerial poison baits, Felixer™ poison-delivery system), but using baiting, trapping and Felixers with additional shooting to meet culling quotas was the most cost-effective combination (minimum cost: AU$19.56 million; range: AU$16.87 million–AU$20.69 million). Our model provides an adaptable and general assessment tool for cat reductions in Australia and potentially elsewhere, and provides relative culling costs for the Kangaroo Island programme specifically.

Publisher

Cold Spring Harbor Laboratory

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