Data from: Harvesting wildlife affected by climate change: a modelling and management approach for polar bears

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 Ursus maritimus life cycle and includes density-dependent relationships linking vital rates to environmental carrying capacity (K). 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 K, 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 K. 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. Synthesis and applications. 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工作，需要明晰气候变化所带来的种群统计学效应，其中包括气候变化与狩猎活动之间的交互作用——这类交互作用可为人类带来文化、营养或经济价值。
本研究提出了一种基于北极熊（Ursus maritimus）生命周期的种群统计学模型，该模型纳入了将种群生命率与环境容纳量（environmental carrying capacity, K）相关联的密度依赖关系。
依托该模型，我们开发了一种状态依赖型管理框架，用于计算可持续狩猎水平：其一，在动态变化的环境容纳量下，维持种群规模高于其最大净生产力水平（maximum net productivity level, MNPL，即实现最大种群净增长的种群规模）；其二，对种群存续仅产生有限的负面影响。
我们的密度依赖关系分析表明，北极熊的MNPL约为环境容纳量K的0.69（95%置信区间：0.63–0.74）。处于MNPL时的种群增长率约为最大内禀增长率的0.82（95%置信区间：0.79–0.84），这表明人类引发的死亡率可得到较强的补偿效应。
研究结果显示，在气候变化背景下，可将狩猎活动带来的种群统计学风险降至最低，其中包括狩猎会加速因北极熊海冰栖息地丧失所引发的种群衰退这一风险。这一目标的实现需要满足以下条件：（i）狩猎率（部分场景下可为0）需适配种群的内禀增长率；（ii）狩猎率需考虑种群数据的质量（例如不确定性较高时应降低狩猎强度）；（iii）狩猎水平需通过狩猎率乘以种群规模的最新估算值来确定。此外，环境变异性、被移除个体的性别与年龄，以及风险耐受度也会对狩猎率产生影响。
综合与应用
本研究提出了一种野生动物种群建模与管理的耦合方法，该方法可纳入气候变化因素，用于平衡多重保护目标间的权衡取舍。以海冰栖息地正在丧失的北极熊为例，我们的管理目标为维持种群存续性，同时为生计狩猎保留持续机会。该方法也可推广应用于其他物种——这类物种的近期管理重点聚焦于在气候诱导的栖息地退化大背景下，直接影响种群动态的人为因素。

搜集汇总

背景与挑战

背景概述

该数据集基于北极熊的生命周期，构建了一个密度依赖的人口统计模型，并开发了一个状态依赖管理框架，用于在气候变化背景下计算可持续的收获水平，以维持种群在最大净生产力水平以上。数据集包含楚科奇海和南波弗特海的海冰数据，支持研究气候变化对北极熊栖息地的影响及管理策略的制定。