North Carolina State University, Department of Biology, David Clark Labs, Campus Box 7617, Raleigh, North Carolina 27695-7617 USA.
Ecology. 2012 Nov;93(11):2305-12. doi: 10.1890/11-2296.1.
Physiological tolerance of environmental conditions can influence species-level responses to climate change. Here, we used species-specific thermal tolerances to predict the community responses of ant species to experimental forest-floor warming at the northern and southern boundaries of temperate hardwood forests in eastern North America. We then compared the predictive ability of thermal tolerance vs. correlative species distribution models (SDMs) which are popular forecasting tools for modeling the effects of climate change. Thermal tolerances predicted the responses of 19 ant species to experimental climate warming at the southern site, where environmental conditions are relatively close to the ants' upper thermal limits. In contrast, thermal tolerances did not predict the responses of the six species in the northern site, where environmental conditions are relatively far from the ants' upper thermal limits. Correlative SDMs were not predictive at either site. Our results suggest that, in environments close to a species' physiological limits, physiological trait-based measurements can successfully forecast the responses of species to future conditions. Although correlative SDMs may predict large-scale responses, such models may not be accurate for predicting site-level responses.
生理上对环境条件的耐受能力会影响物种对气候变化的反应。在这里,我们利用物种特有的耐热性来预测北美东部温带阔叶林北部和南部边界的森林地面变暖实验中蚂蚁物种的群落反应。然后,我们比较了耐热性与相关物种分布模型(SDM)的预测能力,SDM 是用于模拟气候变化影响的流行预测工具。耐热性预测了 19 种蚂蚁在南部实验地点对实验气候变暖的反应,南部的环境条件相对接近蚂蚁的上限热极限。相比之下,耐热性不能预测北部实验地点的 6 种蚂蚁的反应,北部的环境条件相对远离蚂蚁的上限热极限。相关 SDM 在两个地点都没有预测能力。我们的结果表明,在接近物种生理极限的环境中,基于生理特征的测量可以成功地预测物种对未来条件的反应。虽然相关 SDM 可以预测大规模的反应,但对于预测现场反应,此类模型可能不够准确。