Using phylogeny and functional traits for assessing community assembly along environmental gradients: A deterministic process driven by elevation.
Using phylogeny and functional traits for assessing community assembly along environmental gradients: A deterministic process driven by elevation.
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使用系统发育和功能特征评估沿环境梯度的群落组装：由海拔驱动的确定性过程
DOI：
10.1002/ece3.3068
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发表时间：
2017-07
影响因子：
2.6
通讯作者：
Yue M
中科院分区：
文献类型：
--
作者：
Xu J;Chen Y;Zhang L;Chai Y;Wang M;Guo Y;Li T;Yue M
群落组装过程是群落生态学的主要焦点。联合使用基于系统发育和基于功能性状的方法沿着环境梯度探索这些过程是解释不断变化的世界下组装机制变化的有用方法。我们的研究结合了这些方法来测试大范围海拔梯度和其他栖息地环境因素的组装过程。我们在中国太白山的 40 个样地收集了数据，研究区域海拔差异超过 2,300 米，然后测量了性状和环境因素。采用方差划分方法区分了40个样地中导致系统发育和性状变化的主要环境因素。应用主成分分析（PCA）来综合其他环境因素。基于系统发育和功能方法，研究了沿着环境梯度的群落组装模式，以探索组装机制。沿着环境梯度计算每个群落的系统发育信号，以检测系统发育上性状表现的变化。对于系统发育和大多数性状的变异，海拔比其他环境因素具有更好的解释力。系统发育和多种功能结构在高海拔地区聚集，而一些保守性状过度分散。根据功能特征检测可能由沿海拔的过滤或竞争引起的趋同趋势。与海拔上显示的模式相比，沿 PCA 1 轴的叶片干物质含量 (LDMC) 和叶片氮含量显示出相互矛盾的模式。 LDMC表现出最强的系统发育信号。只有最大植物高度的系统发育信号显示出沿环境梯度的可解释的变化。合成。海拔是预测系统发育和性状变化的最佳环境因子。植物的系统发育和某些功能结构在高寒地区表现出环境过滤作用，而在中低海拔地区则通过不同的性状/系统发育表现出不同的组装过程。结果强调了确定性过程在大规模环境梯度中主导群落组装。系统发育和性状沿梯度的表现可能彼此独立。我们在本研究中使用的计算功能结构的新方法以及系统发育信号沿梯度变化的焦点可能为检测群落组装机制提供更有用的方法。
Community assembly processes is the primary focus of community ecology. Using phylogenetic‐based and functional trait‐based methods jointly to explore these processes along environmental gradients are useful ways to explain the change of assembly mechanisms under changing world. Our study combined these methods to test assembly processes in wide range gradients of elevation and other habitat environmental factors. We collected our data at 40 plots in Taibai Mountain, China, with more than 2,300 m altitude difference in study area and then measured traits and environmental factors. Variance partitioning was used to distinguish the main environment factors leading to phylogeny and traits change among 40 plots. Principal component analysis (PCA) was applied to colligate other environment factors. Community assembly patterns along environmental gradients based on phylogenetic and functional methods were studied for exploring assembly mechanisms. Phylogenetic signal was calculated for each community along environmental gradients in order to detect the variation of trait performance on phylogeny. Elevation showed a better explanatory power than other environment factors for phylogenetic and most traits’ variance. Phylogenetic and several functional structure clustered at high elevation while some conserved traits overdispersed. Convergent tendency which might be caused by filtering or competition along elevation was detected based on functional traits. Leaf dry matter content (LDMC) and leaf nitrogen content along PCA 1 axis showed conflicting patterns comparing to patterns showed on elevation. LDMC exhibited the strongest phylogenetic signal. Only the phylogenetic signal of maximum plant height showed explicable change along environmental gradients. Synthesis. Elevation is the best environment factors for predicting phylogeny and traits change. Plant's phylogenetic and some functional structures show environmental filtering in alpine region while it shows different assembly processes in middle‐ and low‐altitude region by different trait/phylogeny. The results highlight deterministic processes dominate community assembly in large‐scale environmental gradients. Performance of phylogeny and traits along gradients may be independent with each other. The novel method for calculating functional structure which we used in this study and the focus of phylogenetic signal change along gradients may provide more useful ways to detect community assembly mechanisms.
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