Using empirical data to quantify implementation uncertainty in small game harvest management
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Sustainable resource management requires that managers are able to control the harvest offtake. This is challenging in systems with multiple objectives and great uncertainties, which is often the case in small game harvest management. The difference between the strategies implemented by management and the actual harvest bag size (i.e. implementation uncertainty) may be substantial, but few studies have so far explored this. In this study I investigated how different management strategies and system parameters affected actual offtake in willow ptarmigan (Lagopus lagopus L.) harvest, using empirical data and simulating performance of strategies and risk of harvest above selected harvest rate thresholds under varying population states. I used data from nine independently managed state owned hunting areas in Central and South Norway. Two paths were explored; analysing harvest directly (as bagged birds per km2) and indirectly by combining models for hunting pressure (hunting days per km2) and hunter efficiency (bagged birds per hunting day). My results show that the best model explaining bagged birds per km2 included total allowable catch per km2 (TAC) set by managers and willow ptarmigan density, where number of bagged birds at high TAC and low density was comparable to the number at lower TAC and higher density. Hunting pressure was best explained by number of sold permits per km2 and type of quota, while the best hunter efficiency model only included density. The results strongly suggested that hunters were relatively more effective at low densities and removed a higher proportion of birds from the area when densities were low. The simulations with alternative harvest management scenarios revealed that this effect was present for all strategies, whether managers used a constant harvest strategy (TAC or effort) or had adapted their strategy to the density estimates. High risks at lower densities of harvest rates above the levels associated with sustainability, indicate the need for knowledge of population state before hunting permits are sold, and urges the use of threshold strategies to balance the competing objectives of hunting opportunities and sustainability. Quantified risks of harvest rates over a range of densities enable informed manager decisions of trade-offs between competing objectives. This study is one of the first approaches to quantifying implementation uncertainty in small game harvest, and shows how estimates from empirical analyses may be used as elements of a full management strategy evaluation (MSE) framework.