Trait correlation network analysis identifies biomass allocation traits and stem specific length as hub traits in herbaceous perennial plants

Correlations among plant traits often reflect important trade‐offs or allometric relationships in biological functions like carbon gain, support, water uptake, and reproduction that are associated with different plant organs. Whether trait correlations can be aggregated to “spectra” or “leading dimensions,” whether these dimensions are consistent across plant organs, spatial scale, and growth forms are still open questions.
To illustrate the current state of knowledge, we constructed a network of published trait correlations associated with the “leaf economics spectrum,” “biomass allocation dimension,” “seed dimension,” and carbon and nitrogen concentrations. This literature‐based network was compared to a network based on a dataset of 23 traits from 2,530 individuals of 126 plant species from 381 plots in Northwest Europe.
The observed network comprised more significant correlations than the literature‐based network. Network centrality measures showed that size traits such as the mass of leaf, stem, below‐ground, and reproductive tissues and plant height were the most central traits in the network, confirming the importance of allometric relationships in herbaceous plants. Stem mass and stem‐specific length were “hub” traits correlated with most traits. Environmental selection of hub traits may affect the whole phenotype. In contrast to the literature‐based network, SLA and leaf N were of minor importance. Based on cluster analysis and subsequent PCAs of the resulting trait clusters, we found a “size” module, a “seed” module, two modules representing C and N concentrations in plant organs, and a “partitioning” module representing organ mass fractions. A module representing the plant economics spectrum did not emerge.
Synthesis. Although we found support for several trait dimensions, the observed trait network deviated significantly from current knowledge, suggesting that previous studies have overlooked trait coordination at the whole‐plant level. Furthermore, network analysis suggests that stem traits have a stronger regulatory role in herbaceous plants than leaf traits.

植物性状间的关联往往反映了不同植物器官所关联的生物学功能（如碳获取、结构支撑、水分吸收与繁殖）间的重要权衡关系或异速生长关系。目前关于以下问题尚无定论：性状关联能否被整合为“谱”或“核心维度”，以及这些维度在不同植物器官、空间尺度和生长型之间是否保持一致。

为阐明当前的认知现状，我们构建了与叶片经济谱（Leaf Economics Spectrum）、生物量分配维度、种子维度以及碳氮浓度相关的已发表性状关联网络，并将该基于文献的网络与另一网络进行对比：后者源自西北欧381个样地中126种植物的2530个个体的23个性状数据集。

观测得到的网络相较于基于文献的网络，包含更多显著性状关联。网络中心性分析结果显示：叶片、茎秆、地下组织、生殖组织的干质量以及株高等个体大小性状，是该网络中连接性最强的核心性状，这证实了异速生长关系在草本植物中的重要性。茎秆质量与茎比长为枢纽性状，与绝大多数性状存在关联，对枢纽性状的环境筛选可能会影响植株的整体表型。与基于文献的网络不同，比叶面积（Specific Leaf Area, SLA）与叶片氮含量在该网络中仅发挥次要作用。基于聚类分析及后续对所得性状模块的主成分分析，我们识别出五类性状模块：分别为大小模块、种子模块、代表植物器官碳氮浓度的两个模块，以及代表器官质量分配的分配模块，但并未发现代表植物经济谱的模块。

综合结论：尽管本研究为多个性状维度提供了支持证据，但观测得到的性状网络与当前主流认知存在显著偏差，这表明以往研究忽视了整株水平上的性状协同关系。此外，网络分析结果显示，相较于叶片性状，茎秆性状在草本植物中发挥着更强的调控作用。