Da Rihan, Hao Minhui, Qiao Xuetao, Zhang Chunyu, Zhao Xiuhai
Research Center of Forest Management Engineering of State Forestry and Grassland Administration, Beijing Forestry University, Beijing, China.
Front Plant Sci. 2022 May 30;13:907839. doi: 10.3389/fpls.2022.907839. eCollection 2022.
Understanding the trait-environment relationships has been a core ecological research topic in the face of global climate change. However, the strength of trait-environment relationships at the local and regional scales in temperate forests remains poorly known. In this study, we investigated the local and regional scale forest plots of the natural broad-leaved temperate forest in northeastern China, to assess what extent community-level trait composition depends on environmental drivers across spatial scales. We measured five key functional traits (leaf area, specific leaf area, leaf carbon content, leaf nitrogen content, and wood density) of woody plant, and quantified functional compositions of communities by calculating the "specific" community-weighted mean (CWM) traits. The sum of squares decomposition method was used to quantify the relative contribution of intraspecific trait variation to total trait variation among communities. Multiple linear regression model was then used to explore the community-level trait-environment relationships. We found that () intraspecific trait variation contributed considerably to total trait variation and decreased with the spatial scale from local to regional; () functional composition was mainly affected by soil and topography factors at the local scale and climate factor at the regional scale, while explaining that variance of environment factors were decreased with increasing spatial scale; and () the main environment driver of functional composition was varied depending on the traits and spatial scale. This work is one of the few multi-scale analyses to investigate the environmental drivers of community functional compositions. The extent of intraspecific trait variation and the strength of trait-environment relationship showed consistent trends with increasing spatial scale. Our findings demonstrate the influence of environmental filtering on both local- and regional-scale temperate forest communities, and contribute to a comprehensive understanding of trait-environment relationships across spatial scales.
面对全球气候变化，了解性状与环境的关系一直是生态学的核心研究课题。然而，温带森林在局部和区域尺度上性状与环境关系的强度仍鲜为人知。在本研究中，我们调查了中国东北天然阔叶温带森林的局部和区域尺度森林样地，以评估群落水平的性状组成在多大程度上依赖于不同空间尺度上的环境驱动因素。我们测量了木本植物的五个关键功能性状（叶面积、比叶面积、叶碳含量、叶氮含量和木材密度），并通过计算“特定”群落加权平均（CWM）性状来量化群落的功能组成。采用平方和分解方法量化种内性状变异对群落间总性状变异的相对贡献。然后使用多元线性回归模型来探索群落水平的性状与环境的关系。我们发现：（1）种内性状变异对总性状变异有相当大的贡献，并且随着空间尺度从局部到区域而降低；（2）功能组成在局部尺度上主要受土壤和地形因素影响，在区域尺度上主要受气候因素影响，同时表明环境因素的方差随着空间尺度的增加而减小；（3）功能组成的主要环境驱动因素因性状和空间尺度而异。这项工作是为数不多的多尺度分析之一，旨在研究群落功能组成的环境驱动因素。种内性状变异程度和性状与环境关系的强度随着空间尺度的增加呈现出一致的趋势。我们的研究结果证明了环境过滤对局部和区域尺度温带森林群落的影响，并有助于全面理解不同空间尺度上的性状与环境关系。
