Aligning population models with data: Adaptive management for big game harvests

ABSTRACT Models of population dynamics are a central piece for harvest management, allowing managers to evaluate alternative strategies and to identify uncertainty. Here we present a density-dependent population dynamics model that can be used in conjunction with adaptive management to optimize big game management, designed to use data commonly collected by state and provincial wildlife agencies. We review a case study for white-tailed deer (Odocoileus virginianus) in North Dakota, USA, where we evaluate how harvest composition and monitoring frequency affect the maximum sustainable yield (MSY). Data were obtained from winter aerial surveys and hunter questionnaires over six years between 2009 to 2019. Harvest composition moderately skewed towards antlered individuals (37.5% antlerless deer and 62.5% antlered deer, i.e., antlerless:antlered harvest ratio = 0.6) resulted in a harvest rate of 0.2, which translates to a long-term harvest that is more than double that obtained if the harvest composition matched the population composition. However, given environmental uncertainty, we recommend that managers adopt a harvest strategy that is at least 10-15% lower than the maximum sustainable yield to buffer against environmental variability. Despite the fact that contrasting monitoring schemes resulted in similar optimal harvest rates, we illustrated how adopting an adaptive harvest strategy (i.e., where harvests change with population size) affords lower risks of overexploitation than a static strategy in which populations are assessed only occasionally. An adaptive harvest strategy features resilience allowing harvested populations to return to equilibrium even after substantial perturbation events