Biology, Duke University, Durham, North Carolina, United States of America.
Division of Biology, Kansas State University, Manhattan, Kansas, United States of America.
PLoS One. 2021 Mar 3;16(3):e0247290. doi: 10.1371/journal.pone.0247290. eCollection 2021.
Impacts of climate change can differ substantially across species' geographic ranges, and impacts on a given population can be difficult to predict accurately. A commonly used approximation for the impacts of climate change on the population growth rate is the product of local changes in each climate variable (which may differ among populations) and the sensitivity (the derivative of the population growth rate with respect to that climate variable), summed across climate variables. However, this approximation may not be accurate for predicting changes in population growth rate across geographic ranges, because the sensitivities to climate variables or the rate of climate change may differ among populations. In addition, while this approximation assumes a linear response of population growth rate to climate, population growth rate is typically a nonlinear function of climate variables. Here, we use climate-driven integral projection models combined with projections of future climate to predict changes in population growth rate from 2008 to 2099 for an uncommon alpine plant species, Douglasia alaskana, in a rapidly warming location, southcentral Alaska USA. We dissect the causes of among-population variation in climate change impacts, including magnitude of climate change in each population and nonlinearities in population response to climate change. We show that much of the variation in climate change impacts across D. alaskana's range arises from nonlinearities in population response to climate. Our results highlight the critical role of nonlinear responses to climate change impacts, suggesting that current responses to increases in temperature or changes in precipitation may not continue indefinitely under continued changes in climate. Further, our results suggest the degree of nonlinearity in climate responses and the shape of responses (e.g., convex or concave) can differ substantially across populations, such that populations may differ dramatically in responses to future climate even when their current responses are quite similar.
气候变化的影响在物种的地理分布范围内可能有很大差异,而且对特定种群的影响很难准确预测。一种常用的气候变化对种群增长率影响的近似方法是将每个气候变量(不同种群之间可能有所不同)的局部变化与敏感性(种群增长率相对于该气候变量的导数)相乘,然后将所有气候变量相加。然而,这种近似方法可能无法准确预测地理分布范围内种群增长率的变化,因为不同种群对气候变量的敏感性或气候变化的速度可能不同。此外,尽管这种近似方法假设种群增长率对气候的线性响应,但种群增长率通常是气候变量的非线性函数。在这里,我们使用气候驱动的积分预测模型结合未来气候的预测,来预测美国阿拉斯加中南部一个快速变暖的地点的罕见高山植物 Douglasia alaskana 从 2008 年到 2099 年的种群增长率变化。我们剖析了气候变化影响在种群间存在差异的原因,包括每个种群的气候变化幅度和种群对气候变化的非线性响应。我们表明,Douglasia alaskana 分布范围内气候变化影响的大部分差异来自于种群对气候变化的非线性响应。我们的研究结果强调了气候变化影响的非线性响应的关键作用,表明在气候持续变化的情况下,目前对温度升高或降水变化的响应可能不会无限期地持续下去。此外,我们的研究结果表明,气候响应的非线性程度和响应的形状(例如凸或凹)在种群间可能有很大差异,即使当前的响应非常相似,种群对未来气候的响应也可能有很大差异。