Leaf Trait-Environment Relationships in a Subtropical Broadleaved Forest in South-East China

Abstract

Although trait analyses have become more important in community ecology, trait-environment correlations have rarely been studied along successional gradients. We asked which environmental variables had the strongest impact on intraspecific and interspecific trait variation in the community and which traits were most responsive to the environment. We established a series of plots in a secondary forest in the Chinese subtropics, stratified by successional stages that were defined by the time elapsed since the last logging activities. On a total of 27 plots all woody plants were recorded and a set of individuals of every species was analysed for leaf traits, resulting in a trait matrix of 26 leaf traits for 122 species. A Fourth Corner Analysis revealed that the mean values of many leaf traits were tightly related to the successional gradient. Most shifts in traits followed the leaf economics spectrum with decreasing specific leaf area and leaf nutrient contents with successional time. Beside succession, few additional environmental variables resulted in significant trait relationships, such as soil moisture and soil C and N content as well as topographical variables. Not all traits were related to the leaf economics spectrum, and thus, to the successional gradient, such as stomata size and density. By comparing different permutation models in the Fourth Corner Analysis, we found that the trait-environment link was based more on the association of species with the environment than of the communities with species traits. The strong species-environment association was brought about by a clear gradient in species composition along the succession series, while communities were not well differentiated in mean trait composition. In contrast, intraspecific trait variation did not show close environmental relationships. The study confirmed the role of environmental trait filtering in subtropical forests, with traits associated with the leaf economics spectrum being the most responsive ones.

Tree phylogenetic diversity promotes host–parasitoid interactions

“…To obtain a variable referring to some functional aspects of the tree community, leaf functional diversity was calculated as Rao's Q from the 26 leaf traits analysed in [31]. The trait matrix included a comprehensive set of morphological (e.g.…”

Tree diversity promotes predator but not omnivore ants in a subtropical Chinese forest

“…Mean leaf functional diversity was also calculated using Rao's Q, with the morphological and chemical leaf traits measured by Kröber et al (2012) considering the weighted abundances of tree species. To include the effect of soil on epigeic ants, total organic C, total organic N, C:N ratio, soil moisture and pH of the mineral soil were measured per plot.…”

“…As discussed earlier, predator ants are mainly nesting in leaf litter and are therefore more likely than omnivore ants to benefit from increased leaf-litter heterogeneity and quantity (dos Santos Bastos & Harada, 2011). The leaf traits used for calculating leaf functional diversity were, in addition to morphological leaf traits, predominately leaf nutrients and other chemical leaf traits that were measured on freshly collected, living young leaves (Kröber et al, 2012). This effect was independent of the community evenness of trees, which had a positive influence only on omnivore species that are more dependent on plant-based resources (Blüthgen & Feldhaar, 2010).…”

Local neighborhood competition following an extraordinary snow break event: implications for tree-individual growth

“…One was based on CPAs of 2008 (CI08) and refers to the situation immediately after the snow break event. The other competition index was based on CPA measurements of iForest (2014) Local and plot functional diversity was calculated as Rao's quadratic entropy (Rao's Q -Rao 1982, Botta-Dukat 2005 of eight functional leaf traits (these were specific leaf area; leaf dry matter content; content of nitrogen, aluminium, calcium and phosphorus; C/N ratio; stomata density) of either all neighboring trees of a target group (local functional diversity) or all individuals >1 m height of the plot (plot functional diversity, for trait data description see Kröber et al 2012). A detailed description of the calculation of Rao's Q is provided by Lang et al (2012b).…”