When States set target limits on killing Carnivores, both Biological and Outcome Uncertainty can lead to excess mortality up to 70% of the time.............Deaths unrelated to hunting, disease, harsh winter and summer weather, drought, highway death and Animal Control to protect livestock can be grossly underestimated which then in combination with excessive "bag limits" can send Grizzlies, Wolves, Pumas and other Carnivores into a death spiral ...............read the full article on this topic by clicking on the link below

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I thought you would find this article interesting.

Read the open-access, full-text article here:
http://dx.plos.org/10.1371/journal.pone.0078041

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Confronting Uncertainty in Wildlife Management: Performance of Grizzly Bear Management

Abstract:

Scientific management of wildlife requires confronting the complexities of natural and social systems. Uncertainty poses a central problem. Whereas the importance of considering uncertainty has been widely discussed, studies of the effects of unaddressed uncertainty on real management systems have been rare. We examined the effects of outcome uncertainty and components of biological uncertainty on hunt management performance, illustrated with grizzly bears (Ursus arctos horribilis) in British Columbia, Canada. We found that both forms of uncertainty can have serious impacts on management performance. Outcome uncertainty alone – discrepancy between expected and realized mortality levels – led to excess mortality in 19% of cases (population-years) examined. Accounting for uncertainty around estimated biological parameters (i.e., biological uncertainty) revealed that excess mortality might have occurred in up to 70% of cases. We offer a general method for identifying targets for exploited species that incorporates uncertainty and maintains the probability of exceeding mortality limits below specified thresholds. Setting targets in our focal system using this method at thresholds of 25% and 5% probability of overmortality would require average target mortality reductions of 47% and 81%, respectively. Application of our transparent and generalizable framework to this or other systems could improve management performance in the presence of uncertainty.