The role of science in wildlife management: From grizzly bears in British Columbia to hunted species across Canada and the United States

Agencies often claim, and societies often assume, a scientific basis to natural resource management. Science does have potential for informing management, for example by providing rigorous approaches for advancing understanding of managed systems and predicting management outcomes. However, the extent to which science informs real-world management is rarely tested. I offer a simple conceptualization of the management process and show how it identifies multiple focal points for testing the scientific basis of management systems. I illustrate this first with hunt management of grizzly bears (Ursus arctos horribilis) in British Columbia (BC), Canada. I find that the number of kills often exceeds agency-defined sustainable limits, associated with unaddressed uncertainty. I refine approaches from fisheries management to illustrate how uncertainty could be buffered against when setting hunting targets. I then assess the ecology of grizzly bear-human conflict in BC. I find limited support for the common hypotheses that conflict- and hunt-related kills reduce subsequent conflict rates, despite both being management responses. Instead, I find that food availability is correlated with conflict rates, suggesting that more effective management might focus on protecting natural foods. I then focus on protected areas. I use a spatial capture-recapture approach to characterize spatial patterns of grizzly bears in the Great Bear Rainforest and find that existing protected areas do no better, or worse, than random at capturing areas with high densities of grizzly bear activity centres, suggesting protected areas shortcomings. Finally, I explore the process of management itself across Canada and the USA, where hunting is guided by a model which asserts that management is ‘science-based’. However, in 667 management plans from agencies across the continent, I find key hallmarks of science (evidence, measurable objectives, transparency, independent review) largely lacking, raising doubts about a scientific basis. These chapters illustrate how shortcomings at various stages of the management process might undermine the ostensible scientific basis of an overall management system. I argue that assessing the role of science in management is important not only for enabling the evolution of management systems, but also for honest and transparent governance, by clarifying where science begins and ends in decision-making.