Climate change is expected to alter the distribution and abundance of tree species, impacting ecosystem structure and function. Yet, anticipating where this will occur is often hampered by a lack of understanding of how demographic rates, most notably recruitment, vary in response to climate and competition across a species range. Using large-scale monitoring data on two dry woodland tree species (Pinus edulis and Juniperus osteosperma), we develop an approach to infer recruitment, survival, and growth of both species across their range. In doing so, we account for ecological and statistical dependencies inherent in large-scale monitoring data. We find that drying and warming conditions generally lead to declines in recruitment and survival, but the strength of responses varied between species. These climate conditions point to geographic regions of high vulnerability for particular species, such as Pinus edulis in northern Arizona, where both survival and recruitment are low. Our approach provides a path forward for leveraging emerging large-scale monitoring and remotely sensed data to anticipate the impacts of global change on species distributions.

中文翻译：

---

使用广泛的监测数据量化干旱林地对气候和竞争的人口脆弱性

预计气候变化将改变树种的分布和丰度，影响生态系统的结构和功能。然而，由于缺乏对人口统计率（尤其是招募率）如何随着物种范围内的气候和竞争的反应而变化的了解，预测这种情况将发生在哪里通常会受到阻碍。使用两种干旱林地树种（Pinus edulis和Juniperus bonesperma）的大规模监测数据)，我们开发了一种方法来推断两个物种在其范围内的招募、生存和生长。在这样做时，我们考虑了大规模监测数据中固有的生态和统计依赖性。我们发现干燥和变暖条件通常会导致招募和存活率下降，但反应强度因物种而异。这些气候条件指向特定物种的高度脆弱性地理区域，例如亚利桑那州北部的松树，那里的存活率和补充率都很低。我们的方法为利用新兴的大规模监测和遥感数据预测全球变化对物种分布的影响提供了一条前进的道路。