Abstract

Eurasian lynx in Scandinavia are subject to regular harvest and lethal control to reduce depredation on domestic livestock and semi-domestic reindeer. Here we introduce the use of total reproductive value to model the effects of current harvest on population dynamics and to propose sustainable harvest strategies for lynx. Demographic stochasticity strongly influences lynx population dynamics. Analyses of the number of lynx shot in relation to the number of family groups registered in annual censuses showed proportional harvest in large parts of Norway because the quotas were higher at larger population sizes. In other areas of Norway the number of lynx shot was independent of population size. The analyses of the model showed that a pure proportional harvest strategy may lead to rapid extinction of lynx populations. In contrast, applying a threshold or proportional threshold harvest strategy in which no harvest occurs below a given threshold can result in the maintenance of viable populations. Thus, this study shows that harvest without any lower threshold for stopping harvest will result in rapid extinction of lynx populations. Accordingly, lynx harvest is not likely to be sustainable if the illegal killing of animals is not controlled because poaching can result in a de facto proportional harvest even at very small population sizes. Under the influence of the large demographic stochasticity in lynx populations this harvest would result in short expected times to extinction. This gives an empirical demonstration that a correct choice of harvest strategy is essential for maintenance of viable populations of harvested species. Our analyses illustrate that parameters determining the viability of small populations can be estimated from individual-based demographic data from a sample of individuals without using time series of fluctuations in population size, which facilitates quantitative analyses of how harvest or removal of individuals, e.g. for captive breeding or translocations, affect the expected lifetime of populations.

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