Extreme climatic events (ECEs) are becoming more frequent and more intense due to climate change. Furthermore, there is reason to believe ECEs may modify "tail associations" between distinct population vital rates, or between values of an environmental variable measured in different locations. "Tail associations" between two variables are associations that occur between values in the left or right tails of the distributions of the variables. Two positively associated variables can be principally "left‐tail associated" (i.e., more correlated when they take low values than when they take high values) or "right‐tail associated" (more correlated when they take high than low values), even with the same overall correlation coefficient in both cases. We tested, in the context of non‐spatial stage‐structured matrix models, whether tail associations between stage‐specific vital rates may influence extinction risk. We also tested whether the nature of spatial tail associations of environmental variables can influence metapopulation extinction risk. For instance, if low values of an environmental variable reduce the growth rates of local populations, one may expect that left‐tail associations increase metapopulation extinction risks because then environmental "catastrophes" are spatially synchronized, presumably reducing the potential for rescue effects. For the non‐spatial, stage‐structured models we considered, left‐tail associations between vital rates did accentuate extinction risk compared to right‐tail associations, but the effect was small. In contrast, we showed that density dependence interacts with tail associations to influence metapopulation extinction risk substantially: For population models showing undercompensatory density dependence, left‐tail associations in environmental variables often strongly accentuated and right‐tail associations mitigated extinction risk, whereas the reverse was usually true for models showing overcompensatory density dependence. Tail associations and their asymmetries are taken into account in assessing risks in finance and other fields, but to our knowledge, our study is one of the first to consider how tail associations influence population extinction risk. Our modeling results provide an initial demonstration of a new mechanism influencing extinction risks and, in our view, should help motivate more comprehensive study of the mechanism and its importance for real populations in future work.

中文翻译：

---

尾部生态变量及其对物种灭绝风险的影响

由于气候变化，极端气候事件（ECE）变得越来越频繁和激烈。此外，有理由相信ECE可能会改变不同人口生命率之间或在不同位置测得的环境变量值之间的“尾部关联”。两个变量之间的“尾部关联”是发生在变量分布的左尾或右尾的值之间的关联。两个正相关的变量可以主要是“左尾相关”（即，当它们取低值时比它们取高值时相关性更高）或“右尾相关”（当它们取高值而不是低值时相关性更高），甚至两种情况下的总体相关系数都相同。我们测试过 在非空间阶段结构矩阵模型的背景下，特定阶段生命率之间的尾部关联是否会影响灭绝风险。我们还测试了环境变量的空间尾部关联的性质是否会影响种群灭绝的风险。例如，如果环境变量的低值降低了当地人口的增长率，那么人们可能会认为左尾联系会增加种群灭绝的风险，因为环境“灾难”在空间上是同步的，从而可能降低了救援的可能性。对于我们考虑的非空间，阶段结构的模型，与右尾关联相比，生命率之间的左尾关联确实加剧了灭绝的风险，但影响很小。相反，我们表明，密度依赖性与尾巴关联相互作用，从而极大地影响了种群灭绝的风险：对于显示代偿性密度依赖性不足的种群模型，环境变量中的左尾关联通常会加剧，而右尾关联会降低灭绝风险，而相反的情况对于模型显示出过度补偿的密度依赖性。在评估金融和其他领域的风险时会考虑到尾部关联及其不对称性，但是据我们所知，我们的研究是第一个考虑尾部关联如何影响种群灭绝风险的研究。我们的建模结果初步证明了一种影响灭绝风险的新机制，并且我们认为，