Low predictability of energy balance traits and leaf temperature metrics in desert, montane and alpine plant communities
Low predictability of energy balance traits and leaf temperature metrics in desert, montane and alpine plant communities
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DOI：
10.1111/1365-2435.13643
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发表时间：
2020-08-21
影响因子：
5.2
通讯作者：
Michaletz, Sean T.
中科院分区：
文献类型：
--
作者：
Blonder, Benjamin;Escobar, Sabastian;Michaletz, Sean T.
叶子能量平衡可能影响植物性能和群落组成。虽然生物物理理论可以将叶片能量平衡与许多性状和环境变量联系起来，但通过不完整的参数化来预测叶片温度和关键驱动性状仍然具有挑战性。预测热偏移（δ，T 叶 - T（空气）差）或热耦合强度（β，T（叶）与 T（空气）斜率）具有挑战性。我们问：（a）环境梯度是否预测能量平衡性状（吸收率、叶角、气孔分布、最大气孔导度、叶面积、叶高）的变化； (b) 常用测量的叶片功能性状（干物质含量、单位面积质量、氮分数、δ C-13、离地高度）是否可以预测能量平衡性状； (c) 性状和环境变量如何预测物种间的 delta 和 beta。我们通过对 41 个物种的昼夜测量来解决这些问题，这些物种沿着横跨沙漠到高山生物群落的 1,100 米海拔梯度共存。我们表明（a）能量平衡特征与环境梯度的相关性很弱，（b）不能通过常见的功能特征很好地预测。我们还表明，可以使用场地环境和性状之间的相互作用来部分近似 (c)delta 和 beta，其中环境的作用比性状的作用大得多。叶片温度指标和能量平衡特征的异质性对环境变化下植物性能的大规模预测模型提出了挑战。可以在本文的支持信息中找到免费的简单语言摘要。
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.