功能特征对热带山区苔藓功能多样性和群落结构的海拔模式具有中介作用

IF 4.3 3区 材料科学 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC ACS Applied Electronic Materials Pub Date : 2024-10-18 DOI:10.1016/j.gecco.2024.e03259
Liqin Fu , Chengxiu Zhan , Haozhe Wang , Shikai Song , Peng Xu , Lina Zhang , Jiancheng Zhao , De Gao
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引用次数: 0

摘要

功能多样性是指群落中功能特征的价值、范围和分布,如物种的形态、生理和行为特征,这些特征决定了物种在生态系统中扮演的角色。评估功能多样性海拔模式的驱动因素对于预测全球变化对功能多样性和群落结构的影响至关重要。在研究中,我们收集了 65 个采样点的苔藓物种数据,并测量了与其生态功能相关的 11 种功能特征。我们采用双对应分析法(DCCA),根据物种的性状分析物种对环境条件的反应。我们应用具有高斯方差函数的广义加性模型来确定功能性状组成、多样性和群落结构的海拔模式。我们应用并比较了不考虑功能性状的助推回归树(BRT)和以功能性状为中介的片断结构方程模型(SEM),分别将环境变量与功能多样性和功能群落结构联系起来。我们发现,第一个 DCCA 轴在两组物种之间的差异最大,并且主要与水利用性状相关。虽然功能多样性和群落结构沿海拔梯度均呈现负偏斜模式,但栖息地复杂性和气候变量对其各自模式的贡献不同。在解释功能多样性和群落结构的变化方面,SEM方法一直优于BRT方法。我们的研究结果凸显了功能特征在调解环境与功能多样性指标之间关系中的重要作用。生物和非生物过程在群落组合的形成过程中都发挥了重要作用,而环境变量则具有不同的影响。研究发现,与结构维持、水分吸收、细胞水合和营养获取相关的性状是功能多样性的主要驱动因素,而水分利用性状则主要负责调节功能群落结构。
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Functional traits mediate the elevational patterns of functional diversity and community structure of mosses in a tropical mountain area
Functional diversity refers to the value, range, and distribution of functional traits within a community, such as the morphological, physiological and behavioral characteristics of species that determine the role a species plays in an ecosystem. Assessing the drivers of elevational pattern of functional diversity is crucial to predict the effects of global change on functional diversity and community structure. In our research, we collected mosses species data from 65 sampling sites and measured 11 functional traits that are related to their ecological functions. We applied double canonical correspondence analysis (DCCA) to analyze species responses to environmental conditions based on their traits. We applied generalized additive models with a Gaussian function of variance to determine the elevational patterns of functional trait composition, diversity and community structure. We applied and compared boosted regression trees (BRT) without considering functional traits and piecewise structural equation modelling (SEM) mediated with functional traits to relate environmental variables with functional diversity and functional community structure, respectively. We found the first DCCA axis accounted for the largest dissimilarities between the two groups of species and correlated mainly with the water-utilization traits. Although both functional diversity and community structure displayed negatively skewed pattern along the elevational gradient, habitat complexity and climatic variables contributed differently to their respective patterns. The SEM approach consistently outperformed the BRT approach in explaining the variations in both functional diversity and community structure. Our findings highlight the important role of functional traits in mediating the relationship between the environment and functional diversity metrics. Both biotic and abiotic processes play a significant role in shaping the community assemblages, with environmental variables having distinct impacts. Traits related to structure maintenance, water absorption, cell hydration, and nutrient acquisition were found to be key drivers of functional diversity, while water-utilization traits were mainly responsible for regulating functional community structure.
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