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A physiological trait-based approach to predicting the responses of species to experimental climate warming

机译:基于生理特征的方法来预测物种对实验性气候变暖的响应

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摘要

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 sitelevel responses.
机译:环境条件的生理耐受性可能影响物种对气候变化的反应。在这里,我们使用特定于物种的热容忍度来预测蚂蚁物种对北美东部温带硬木森林的北部和南部边界的实验性森林地暖的反应。然后,我们比较了热耐受性与相关物种分布模型(SDM)的预测能力,相关模型是用于模拟气候变化影响的流行预测工具。热容限预测了南部地区的19种蚂蚁对实验性气候变暖的响应,该地区的环境条件相对接近蚂蚁的热上限。相反,在环境条件距离蚂蚁的热上限相对较远的北部站点,热容忍度无法预测这六个物种的反应。相关的SDM在两个部位均不能预测。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预测物种对未来条件的响应。尽管相关SDM可能会预测大规模响应,但此类模型对于预测站点级别响应可能并不准确。

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