Biology Department, Kenyon College, Gambier, OH, USA.
Biology Department, Bates College, Lewiston, ME, USA.
Glob Chang Biol. 2018 Apr;24(4):1599-1613. doi: 10.1111/gcb.13982. Epub 2017 Dec 15.
The salient feature of anthropogenic climate change over the last century has been the rise in global mean temperature. However, global mean temperature is not used as an explanatory variable in studies of population-level response to climate change, perhaps because the signal-to-noise ratio of this gross measure makes its effect difficult to detect in any but the longest of datasets. Using a population of Leach's storm-petrels breeding in the Bay of Fundy, we tested whether local, regional, or global temperature measures are the best index of reproductive success in the face of climate change in species that travel widely between and within seasons. With a 56-year dataset, we found that annual global mean temperature (AGMT) was the single most important predictor of hatching success, more so than regional sea surface temperatures (breeding season or winter) and local air temperatures at the nesting colony. Storm-petrel reproductive success showed a quadratic response to rising temperatures, in that hatching success increased up to some critical temperature, and then declined when AGMT exceeded that temperature. The year at which AGMT began to consistently exceed that critical temperature was 1988. Importantly, in this population of known-age individuals, the impact of changing climate was greatest on inexperienced breeders: reproductive success of inexperienced birds increased more rapidly as temperatures rose and declined more rapidly after the tipping point than did reproductive success of experienced individuals. The generality of our finding that AGMT is the best predictor of reproductive success in this system may hinge on two things. First, an integrative global measure may be best for species in which individuals move across an enormous spatial range, especially within seasons. Second, the length of our dataset and our capacity to account for individual- and age-based variation in reproductive success increase our ability to detect a noisy signal.
上个世纪人为气候变化的显著特征是全球平均温度的上升。然而，在研究人口对气候变化的反应时，全球平均温度并未被用作解释变量，这也许是因为这种总测量的信噪比使得在任何数据集（除了最长的数据集）中都难以检测到其效果。利用在芬迪湾繁殖的蛎鹬种群，我们检验了在物种在季节之间和内部广泛迁徙的情况下，局部、区域或全球温度指标是否是气候变化下繁殖成功的最佳指标。通过 56 年的数据集，我们发现年全球平均温度（AGMT）是孵化成功率的唯一最重要的预测指标，比区域海表温度（繁殖季节或冬季）和巢地的当地空气温度更重要。蛎鹬的繁殖成功率对气温升高呈二次响应，即孵化成功率在达到某个临界温度之前会增加，然后当 AGMT 超过该温度时会下降。AGMT 开始持续超过该临界温度的年份是 1988 年。重要的是，在这个已知年龄个体的种群中，气候变化的影响对没有经验的繁殖者最大：随着温度升高，没有经验的鸟类的繁殖成功率增加得更快，而在临界点之后下降得更快，而有经验的个体的繁殖成功率则下降得更快。我们发现 AGMT 是该系统繁殖成功率最佳预测指标的普遍性可能取决于两件事。首先，对于个体在巨大空间范围内移动的物种，特别是在季节内，综合的全球测量可能是最佳的。其次，我们的数据集的长度和我们对繁殖成功率的个体和年龄差异的解释能力提高了我们检测噪声信号的能力。
