Guangdong Provincial Key Laboratory of Remote Sensing and Geographical Information System, Guangdong Open Laboratory of Geospatial Information Technology and Application, Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou, 510070, China.
Department of Forest and Wildlife Ecology, University of Wisconsin-Madison, 1630 Linden Drive, Madison, WI, 53706, USA.
New Phytol. 2022 Aug;235(3):923-938. doi: 10.1111/nph.18204. Epub 2022 May 24.
Concurrent measurement of multiple foliar traits to assess the full range of trade-offs among and within taxa and across broad environmental gradients is limited. Leaf spectroscopy can quantify a wide range of foliar functional traits, enabling assessment of interrelationships among traits and with the environment. We analyzed leaf trait measurements from 32 sites along the wide eco-climatic gradient encompassed by the US National Ecological Observatory Network (NEON). We explored the relationships among 14 foliar traits of 1103 individuals across and within species, and with environmental factors. Across all species pooled, the relationships between leaf economic traits (leaf mass per area, nitrogen) and traits indicative of defense and stress tolerance (phenolics, nonstructural carbohydrates) were weak, but became strong within certain species. Elevation, mean annual temperature and precipitation weakly predicted trait variation across species, although some traits exhibited species-specific significant relationships with environmental factors. Foliar functional traits vary idiosyncratically and species express diverse combinations of leaf traits to achieve fitness. Leaf spectroscopy offers an effective approach to quantify intra-species trait variation and covariation, and potentially could be used to improve the characterization of vegetation in Earth system models.
同时测量多个叶片特征，以评估分类群内和分类群之间以及跨越广泛环境梯度的权衡关系是有限的。叶片光谱学可以定量测量广泛的叶片功能特征，从而能够评估特征之间以及与环境之间的相互关系。我们分析了美国国家生态观测网（NEON）所涵盖的广泛生态气候梯度上 32 个地点的叶片特征测量值。我们探讨了 1103 个个体中 14 个叶片特征之间以及与环境因子之间的关系。在所有汇总的物种中，叶片经济特征（叶面积质量、氮）与防御和耐受胁迫特征（酚类、非结构性碳水化合物）之间的关系较弱，但在某些物种中变得较强。尽管某些特征与环境因子具有特定的显著关系，但海拔、年平均温度和降水对物种间的特征变化的预测作用较弱。叶片功能特征具有独特的变化，物种表现出不同的叶片特征组合以实现适应性。叶片光谱学提供了一种有效方法来量化种内特征变化和协同变化，并有可能用于改善地球系统模型中植被的特征描述。
