Regehr Eric V, Wilson Ryan R, Rode Karyn D, Runge Michael C, Stern Harry L
U.S. Fish and Wildlife Service Anchorage AK USA.
Present address: University of Washington Seattle WA USA.
J Appl Ecol. 2017 Oct;54(5):1534-1543. doi: 10.1111/1365-2664.12864. Epub 2017 Mar 8.
The conservation of many wildlife species requires understanding the demographic effects of climate change, including interactions between climate change and harvest, which can provide cultural, nutritional or economic value to humans.We present a demographic model that is based on the polar bear life cycle and includes density-dependent relationships linking vital rates to environmental carrying capacity (). Using this model, we develop a state-dependent management framework to calculate a harvest level that (i) maintains a population above its maximum net productivity level (MNPL; the population size that produces the greatest net increment in abundance) relative to a changing , and (ii) has a limited negative effect on population persistence.Our density-dependent relationships suggest that MNPL for polar bears occurs at approximately 0·69 (95% CI = 0·63-0·74) of . Population growth rate at MNPL was approximately 0·82 (95% CI = 0·79-0·84) of the maximum intrinsic growth rate, suggesting relatively strong compensation for human-caused mortality.Our findings indicate that it is possible to minimize the demographic risks of harvest under climate change, including the risk that harvest will accelerate population declines driven by loss of the polar bear's sea-ice habitat. This requires that (i) the harvest rate - which could be 0 in some situations - accounts for a population's intrinsic growth rate, (ii) the harvest rate accounts for the quality of population data (e.g. lower harvest when uncertainty is large), and (iii) the harvest level is obtained by multiplying the harvest rate by an updated estimate of population size. Environmental variability, the sex and age of removed animals and risk tolerance can also affect the harvest rate. . We present a coupled modelling and management approach for wildlife that accounts for climate change and can be used to balance trade-offs among multiple conservation goals. In our example application to polar bears experiencing sea-ice loss, the goals are to maintain population viability while providing continued opportunities for subsistence harvest. Our approach may be relevant to other species for which near-term management is focused on human factors that directly influence population dynamics within the broader context of climate-induced habitat degradation.
许多野生动物物种的保护需要了解气候变化的人口统计学影响，包括气候变化与捕猎之间的相互作用，捕猎可为人类提供文化、营养或经济价值。我们提出了一个基于北极熊生命周期的人口统计模型，该模型包含将生命率与环境承载能力联系起来的密度依赖关系。利用这个模型，我们开发了一个状态依赖管理框架，以计算出一个捕猎水平，该水平（i）相对于不断变化的情况，使种群数量维持在其最大净生产力水平（MNPL；即产生最大数量净增量的种群规模）之上，且（ii）对种群持续性的负面影响有限。我们的密度依赖关系表明，北极熊的MNPL约为环境承载能力的0·69（95%置信区间 = 0·63 - 0·74）。MNPL时的种群增长率约为最大内在增长率的0·82（95%置信区间 = 0·79 - 0·84），这表明对人为导致的死亡率有相对较强的补偿作用。我们的研究结果表明，在气候变化的情况下，有可能将捕猎的人口统计学风险降至最低，包括捕猎会加速北极熊海冰栖息地丧失所导致的种群数量下降的风险。这要求（i）捕猎率（在某些情况下可能为0）考虑到种群的内在增长率，（ii）捕猎率考虑到种群数据的质量（例如，不确定性大时降低捕猎量），以及（iii）捕猎水平通过将捕猎率乘以种群规模的最新估计值来获得。环境变异性、被捕猎动物的性别和年龄以及风险承受能力也会影响捕猎率。我们提出了一种针对野生动物的耦合建模与管理方法，该方法考虑了气候变化，可用于平衡多个保护目标之间的权衡。在我们针对北极熊海冰丧失情况的示例应用中，目标是维持种群生存能力，同时为自给性捕猎提供持续机会。我们的方法可能与其他物种相关，对于这些物种，近期管理关注的是在气候导致栖息地退化的更广泛背景下直接影响种群动态的人为因素。
