Abstract

Summary Many species of wildlife are harvested for sale but there are few time‐series analyses of the factors determining the number of animals harvested. Economic theory predicts that price paid per animal is likely to be an important determinant of the harvest, but prices paid for alternative activities could reduce the harvest, and environmental factors such as rainfall could either constrain or enhance the harvest. About 1 million feral goats Capra hircus L. are commercially harvested annually in the semi‐arid rangelands of Australia, and there is much interest in how the harvest can be maximized so that the environmental impacts of the goats are minimized. We developed 27 candidate models to explain monthly variation in the numbers of feral goats commercially harvested in Western Australia during July 1988 to June 2003. We fitted linear AR(1) models to the first 89 months of data and used Akaike's Information Criterion corrected for small sample size to identify the model(s) with substantial support. We then evaluated how much variation in the latter 88 months of the time series each model explained. Almost 2·9 million feral goats were harvested in the study period. The two models with substantial support accounted for 70·5% and 70·6% of variation in the number of feral goats harvested during the first 89 months and 64·6% and 66·7% of variation in the subsequent 88 months. The models both included month of harvest and negative effects of rainfall in both the month of harvest and the previous month. One of the models also included a strong positive effect of the Australian Consumer Price Index‐adjusted average price paid per feral goat on the number of feral goats harvested, and this model had the most support when fitted to the entire time series. Synthesis and applications. This is the first study to demonstrate how both an environmental factor (rainfall) and an economic factor (average price paid per animal) can influence the size of a commercial wildlife harvest. Whilst managers can seldom modify environmental factors, our results suggest that the size of a wildlife harvest can be manipulated by altering the economics of the harvest.

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