Centre for Tropical Biodiversity and Climate Change, School of Marine and Tropical Biology, James Cook University, Townsville, Queensland, Australia.
PLoS One. 2013 Jul 31;8(7):e69393. doi: 10.1371/journal.pone.0069393. Print 2013.
Among birds, tropical montane species are likely to be among the most vulnerable to climate change, yet little is known about how climate drives their distributions, nor how to predict their likely responses to temperature increases. Correlative models of species' environmental niches have been widely used to predict changes in distribution, but direct tests of the relationship between key variables, such as temperature, and species' actual distributions are few. In the absence of historical data with which to compare observations and detect shifts, space-for-time substitutions, where warmer locations are used as analogues of future conditions, offer an opportunity to test for species' responses to climate. We collected density data for rainforest birds across elevational gradients in northern and southern subregions within the Australian Wet Tropics (AWT). Using environmental optima calculated from elevational density profiles, we detected a significant elevational difference between the two regions in ten of 26 species. More species showed a positive (19 spp.) than negative (7 spp.) displacement, with a median difference of ∼80.6 m across the species analysed that is concordant with that expected due to latitudinal temperature differences (∼75.5 m). Models of temperature gradients derived from broad-scale climate surfaces showed comparable performance to those based on in-situ measurements, suggesting the former is sufficient for modeling impacts. These findings not only confirm temperature as an important factor driving elevational distributions of these species, but also suggest species will shift upslope to track their preferred environmental conditions. Our approach uses optima calculated from elevational density profiles, offering a data-efficient alternative to distribution limits for gauging climate constraints, and is sensitive enough to detect distribution shifts in this avifauna in response to temperature changes of as little as 0.4 degrees. We foresee important applications in the urgent task of detecting and monitoring impacts of climate change on montane tropical biodiversity.
在鸟类中,热带高山物种可能是最容易受到气候变化影响的物种之一,但人们对气候如何驱动它们的分布知之甚少,也不知道如何预测它们对温度升高的可能反应。物种环境生态位的相关模型已被广泛用于预测分布的变化,但对关键变量(如温度)与物种实际分布之间关系的直接测试却很少。在没有历史数据可以比较观测结果和检测变化的情况下,时间替代空间(即使用较温暖的地点作为未来条件的类比)提供了一个检验物种对气候反应的机会。我们在澳大利亚湿热带(AWT)的北部和南部子区域的海拔梯度上收集了雨林鸟类的密度数据。利用从海拔密度分布中计算出的环境最优值,我们在 26 个物种中的 10 个物种中检测到两个区域之间存在显著的海拔差异。更多的物种表现出正(19 个物种)而非负(7 个物种)的位移,在所分析的物种中,中位数差异约为 80.6 米,与由于纬度温度差异而预期的差异(约 75.5 米)一致。从广泛的气候表面推导的温度梯度模型与基于现场测量的模型表现相当,表明前者足以进行建模影响。这些发现不仅证实了温度是驱动这些物种海拔分布的重要因素,还表明物种将向上坡移动以追踪其偏好的环境条件。我们的方法使用从海拔密度分布中计算出的最优值,为衡量气候限制提供了一种比分布极限更高效的数据替代方法,并且足够敏感,可以检测到这个鸟类群对温度变化的分布变化,其幅度小至 0.4 度。我们预见到,在检测和监测气候变化对高山热带生物多样性的影响方面,这一方法具有重要的应用前景。