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Functional traits shape tree species distribution in the Himalayas
Journal of Ecology ( IF 5.5 ) Pub Date : 2021-08-05 , DOI: 10.1111/1365-2745.13759
Surya Kumar Maharjan 1, 2, 3 , Frank J. Sterck 1 , Bishnu Prasad Dhakal 1, 4 , Marina Makri 1 , Lourens Poorter 1
Affiliation  

  1. Plant functional traits determine plant performance and have therefore the potential to shape and predict species distributions along environmental gradients. This study analyses how traits affect tree species distribution along an elevational gradient in the Himalayas, Nepal. We addressed three questions: (a) what plant strategies can be distinguished among tree species? (b) how are plant traits and strategies associated with elevation? and (c) what plant traits are the best predictors of species positions along elevational gradient?
  2. We quantified for 31 tree species a set of 39 plant traits related to resource uptake, use and conservation. We analysed how traits cluster into separate functions using a cluster analysis, and how traits and clusters associate into distinct plant strategies using a principal component analysis.
  3. The cluster analysis showed five clusters of traits, reflecting (a) efficiency in vertical expansion, (b) efficiency in horizontal expansion, (c) efficiency in metabolism, (d) physical defence and (e) tree functional groups (conifers vs. broadleaf species). The first PCA axis reflects trade-offs in traits and clusters linked to elevation: highland species had trait values that increase safety against freezing induced cavitation, high solar radiation and strong wind, and that increase resource conservation. In contrast, lowland species had trait values that increase efficiency of resource acquisition, metabolism and expansion. Additionally, a bivariate analysis showed that the first PCA axis is more strongly related to elevation than the individual traits, indicating that the combination of traits is more important than the individual traits. An all subsets regression analysis showed that a small set of traits best explain species distribution: highland species had smaller size (low basal area), safer hydraulics (low conduit diameter) and lower leaf and branch display efficiency (low leaf area per xylem area, specific branch length) that increase persistence under harsh conditions. Remarkably, leaf traits were poor predictors of species' elevational positions.
  4. Synthesis. Multiple trade-offs in plant size, hydraulics and light competitiveness shape species distribution along the elevational gradient. Along this extreme environmental gradient, stem and branch traits that integrate multiple plant organs and functions are better predictors of species' elevational distributions than leaf traits.


中文翻译:

功能性状塑造喜马拉雅山的树种分布

  1. 植物功能性状决定植物性能,因此具有塑造和预测沿环境梯度的物种分布的潜力。本研究分析了特性如何影响尼泊尔喜马拉雅山脉沿海拔梯度的树种分布。我们解决了三个问题:(a) 在树种之间可以区分哪些植物策略?(b) 植物性状和策略与海拔有何关联?(c) 哪些植物性状是沿海拔梯度的物种位置的最佳预测因子?
  2. 我们对 31 种树种进行了与资源吸收、利用和保护相关的 39 种植物性状的量化。我们使用聚类分析分析了性状如何聚类为单独的函数,以及性状和聚类如何使用主成分分析与不同的植物策略相关联。
  3. 聚类分析显示了五个性状聚类,反映了 (a) 垂直扩张效率,(b) 水平扩张效率,(c) 代谢效率,(d) 物理防御和 (e) 树木功能群(针叶树与阔叶树)物种)。第一个 PCA 轴反映了与海拔相关的特征和集群的权衡:高地物种具有的特征值可以提高对冷冻引起的空化、高太阳辐射和强风的安全性,并增加资源保护。相比之下,低地物种具有提高资源获取、代谢和扩张效率的特性值。此外,双变量分析表明,与个体性状相比,第一个 PCA 轴与海拔的相关性更强,表明性状组合比个体性状更重要。全子集回归分析表明,一小组性状最能解释物种分布:高地物种的体型较小(基部面积低)、水力学更安全(导管直径低)和较低的叶和枝展示效率(每个木质部面积的叶面积低,特定的分支长度)在恶劣条件下增加持久性。值得注意的是,叶片性状是物种海拔位置的不良预测因子。
  4. 合成。植物大小、水力学和光照竞争力的多重权衡塑造了沿海拔梯度的物种分布。沿着这种极端的环境梯度,整合了多种植物器官和功能的茎和枝性状比叶性状更能预测物种的海拔分布。
更新日期:2021-08-05
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