Human activity influences wildlife. However, the ecological and conservation significances of these influences are difficult to predict and depend on their population‐level consequences. This difficulty arises partly because of information gaps, and partly because the data on stressors are usually collected in a count‐based manner (e.g., number of dead animals) that is difficult to translate into rate‐based estimates important to infer population‐level consequences (e.g., changes in mortality or population growth rates). However, ongoing methodological developments can provide information to make this transition. Here, we synthesize tools from multiple fields of study to propose an overarching, spatially explicit framework to assess population‐level consequences of anthropogenic stressors on terrestrial wildlife. A key component of this process is using ecological information from affected animals to upscale from count‐based field data on individuals to rate‐based demographic inference. The five steps to this framework are (1) framing the problem to identify species, populations, and assessment parameters; (2) field‐based measurement of the effect of the stressor on individuals; (3) characterizing the location and size of the populations of interest; (4) demographic modeling for those populations; and (5) assessing the significance of stressor‐induced changes in demographic rates. The tools required for each of these steps are well developed, and some have been used in conjunction with each other, but the entire group has not previously been unified together as we do in this framework. We detail these steps and then illustrate their application for two species affected by different anthropogenic stressors. In our examples, we use stable hydrogen isotope data to infer a catchment area describing the geographic origins of affected individuals, as the basis to estimate population size for that area. These examples reveal unexpectedly greater potential risks from stressors for the more common and widely distributed species. This work illustrates key strengths of the framework but also important areas for subsequent theoretical and technical development to make it still more broadly applicable.

中文翻译：

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评估人为压力源对陆地野生动植物的种群影响

人类活动影响野生生物。但是，这些影响的生态和保护意义很难预测，并取决于其对人口的影响。造成这一困难的部分原因是信息鸿沟，部分原因是应激源的数据通常是以计数为基础的方式收集的（例如，死动物的数量），很难转化为基于比率的估计，这对推断人口水平的后果很重要（例如，死亡率或人口增长率的变化）。但是，正在进行的方法学开发可以提供信息以实现这一过渡。在这里，我们综合了多个研究领域的工具，提出了一个总体的，空间明确的框架，以评估人为压力源对陆地野生动植物的种群级后果。该过程的关键组成部分是利用受感染动物的生态信息，从基于个体的基于计数的实地数据到基于比率的人口统计学推断，进行扩展。该框架的五个步骤是：（1）找出问题，以识别物种，种群和评估参数；（2）基于现场的压力源对个人影响的测量；（3）描述感兴趣人群的位置和大小；（4）针对这些人群的人口统计模型；（5）评估压力源引起的人口统计学变化的重要性。这些步骤中每个步骤所需的工具都已经很好地开发，并且某些工具已经相互结合使用，但是整个团队之前并未像我们在此框架中那样被统一在一起。我们详细介绍了这些步骤，然后说明了它们在受不同人为压力源影响的两个物种中的应用。在我们的示例中，我们使用稳定的氢同位素数据推断出描述受影响个体的地理起源的集水区，以此为该区域的人口规模进行估算。这些例子揭示了应激源对于更常见和分布广泛的物种而言意料之外的更大潜在风险。这项工作既说明了该框架的主要优势，也说明了随后的理论和技术发展的重要领域，以使其更广泛地适用。作为估算该地区人口规模的基础。这些例子揭示了应激源对于更常见和分布广泛的物种而言意料之外的更大潜在风险。这项工作既说明了该框架的主要优势，也说明了随后的理论和技术发展的重要领域，以使其更广泛地适用。作为估算该地区人口规模的基础。这些例子揭示了应激因素对更常见和分布广泛的物种造成的意想不到的更大潜在风险。这项工作既说明了该框架的主要优势，也说明了随后的理论和技术发展的重要领域，以使其更广泛地适用。