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Low predictability of energy balance traits and leaf temperature metrics in desert, montane and alpine plant communities

机译:在沙漠,蒙烷和高山植物社区中的能量平衡性状和叶温度量的低可预测性

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摘要

Leaf energy balance may influence plant performance and community composition. While biophysical theory can link leaf energy balance to many traits and environment variables, predicting leaf temperature and key driver traits with incomplete parameterizations remains challenging. Predicting thermal offsets (delta,T-leaf - T(air)difference) or thermal coupling strengths (beta,T(leaf)vs.T(air)slope) is challenging. We ask: (a) whether environmental gradients predict variation in energy balance traits (absorptance, leaf angle, stomatal distribution, maximum stomatal conductance, leaf area, leaf height); (b) whether commonly measured leaf functional traits (dry matter content, mass per area, nitrogen fraction, delta C-13, height above ground) predict energy balance traits; and (c) how traits and environmental variables predict delta and beta among species. We address these questions with diurnal measurements of 41 species co-occurring along a 1,100 m elevation gradient spanning desert to alpine biomes. We show that (a) energy balance traits are only weakly associated with environmental gradients and (b) are not well predicted by common functional traits. We also show that (c)delta and beta can be partially approximated using interactions among site environment and traits, with a much larger role for environment than traits. The heterogeneity in leaf temperature metrics and energy balance traits challenges larger-scale predictive models of plant performance under environmental change. A freePlain Language Summarycan be found within the Supporting Information of this article.
机译:叶能平衡可能影响植物性能和社区组成。虽然生物物理理论可以将叶能平衡链接到许多特征和环境变量,但预测叶片温度和具有不完整参数化的关键驱动程序性状仍然具有挑战性。预测热偏移(Delta,T-Leaf-T(空气)差异)或热耦合强度(β,T(叶)Vs.T(空气)斜率)是具有挑战性的。我们问:(a)环境梯度是否预测能量平衡性状的变化(吸收率,叶角,气孔分布,最大气孔电导,叶面积,叶高度); (b)是否常见测量的叶功能性状(干物质含量,每面积,质量,氮馏分,δC-13,高度高于地面)预测能量平衡性状; (c)物种之间的特征和环境变量如何预测Delta和Beta。我们通过沿1,100米升高跨度跨越Alpine BioMes的41种物种的昼夜测量来解决这些问题。我们表明(a)能量平衡性状仅与环境梯度弱相关,并且(b)不受常用功能性的很好地预测。我们还表明(C)可以使用站点环境和特征之间的相互作用部分地近似(c)Δ和测试版,而不是特征的环境具有更大的作用。叶温度量和能量平衡特征的异质性挑战环境变化下的植物性能的大规模预测模型。在本文的支持信息中找到FreePlain语言SummaryCan。

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