We studied the differentiation among plant communities of deciduous broadleaved and mountain coniferous forests in terms of functional diversity and identity at a regional scale (northern and central Greece). We asked if patterns of functional differentiation among communities are consistent between the overstorey and understorey layers and if they can be influenced by deep past environmental conditions. Functional Richness (FRic) and Functional Dispersion (FDis), as well as their standardized effect sizes, were employed to assess the multivariate functional diversity of the community types. In contrast, single-trait Community Weighted Means (CWMs) were used as surrogates of functional identity. The aforementioned indices were calculated for three datasets, namely all the vascular plant taxa found in individual vegetation plots (total community), all phanerophyte (tree and shrub) taxa (overstorey) and all non-phanerophyte vascular plant taxa (understorey). We found that community types and especially four broad forest types (beech, ravine, pine and oak forests) are well differentiated in terms of functional composition (identity), as indicated by Non-Metric Multidimensional Scaling (NMDS). After conducting an NMDS for the three datasets, functional identity based on the total floristic composition was found to be the best discriminator of the studied communities. However, contrasting patterns were found for some specific traits or their categories between overstorey and understorey layers. The patterns of functional diversity of the community types (based on multivariate indices), revealed by calculating the standardized effect sizes of FRic and FDis based on the richness null model, did not differ substantially from random expectations for most of the studied community types when the dataset of all the vascular plant taxa was analyzed. However, the patterns revealed for the overstorey layer differed from those for the understorey layer. For the latter layer, the clustered structure was revealed in many community types based on the ses.FDis metric. Indications of deep past influence on the functional composition were found for certain community types (i.e. ravine forests) based on single-trait metrics, but no indication of such influence was found based on multivariate indices. Our findings highlight the complementarity and the additive explanatory value of the simultaneous use of single- and multi-trait approaches and their application to different layers in forests.

我们在区域尺度（希腊北部和中部）研究了落叶阔叶林和山地针叶林植物群落在功能多样性和特性方面的分化。我们询问了社区之间的功能分化模式在上层和下层之间是否一致，以及它们是否会受到过去深层环境条件的影响。功能丰富度（FRic）和功能分散度（FDis），以及它们的标准化效应大小，被用来评估群落类型的多元功能多样性。相比之下，单性状社区加权平均值 (CWM) 被用作功能身份的替代品。上述指数是针对三个数据集计算的，即在单个植被区（总群落）中发现的所有维管植物分类群，所有显形植物（乔木和灌木）类群（层上）和所有非显形维管植物类群（层下）。我们发现群落类型，尤其是四种广泛的森林类型（山毛榉、沟壑、松树和橡树林）在功能组成（同一性）方面有很好的区分，如非度量多维尺度 (NMDS) 所示。在对三个数据集进行 NMDS 后，发现基于总植物区系组成的功能标识是所研究群落的最佳鉴别器。然而，在上层和下层层之间发现了一些特定特征或其类别的对比模式。通过基于丰富度零模型计算 FRic 和 FDis 的标准化效应大小，揭示了群落类型的功能多样性模式（基于多元指数），当分析所有维管植物分类群的数据集时，对大多数研究的群落类型的随机预期没有显着差异。但是，上层显示的模式与下层显示的模式不同。对于后一层，基于 ses.FDis 度量在许多社区类型中揭示了聚类结构。基于单性状指标发现某些群落类型（即沟谷森林）对功能组成有深刻的过去影响的迹象，但基于多元指数没有发现这种影响的迹象。我们的研究结果强调了同时使用单性状和多性状方法的互补性和附加解释价值及其在森林中不同层次的应用。