39 research outputs found
Leaf Trait-Environment Relationships in a Subtropical Broadleaved Forest in South-East China
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
Frontal Theta Cordance Predicts 6-Month Antidepressant Response to Subcallosal Cingulate Deep Brain Stimulation for Treatment-Resistant Depression: A Pilot Study
High phylogenetic diversity is preserved in species-poor high-elevation temperate moth assemblages
Phylogenetic conservatism of functional traits in microorganisms
A central question in biology is how biodiversity influences ecosystem functioning. Underlying this is the relationship between organismal phylogeny and the presence of specific functional traits. The relationship is complicated by gene loss and convergent evolution, resulting in the polyphyletic distribution of many traits. In microorganisms, lateral gene transfer can further distort the linkage between phylogeny and the presence of specific functional traits. To identify the phylogenetic conservation of specific traits in microorganisms, we developed a new phylogenetic metric—consenTRAIT—to estimate the clade depth where organisms share a trait. We then analyzed the distribution of 89 functional traits across a broad range of Bacteria and Archaea using genotypic and phenotypic data. A total of 93% of the traits were significantly non-randomly distributed, which suggested that vertical inheritance was generally important for the phylogenetic dispersion of functional traits in microorganisms. Further, traits in microbes were associated with a continuum of trait depths (τ(D)), ranging from a few deep to many shallow clades (average τ(D): 0.101–0.0011 rRNA sequence dissimilarity). Next, we demonstrated that the dispersion and the depth of clades that contain a trait is correlated with the trait's complexity. Specifically, complex traits encoded by many genes like photosynthesis and methanogenesis were found in a few deep clusters, whereas the ability to use simple carbon substrates was highly phylogenetically dispersed. On the basis of these results, we propose a framework for predicting the phylogenetic conservatism of functional traits depending on the complexity of the trait. This framework enables predicting how variation in microbial composition may affect microbially-mediated ecosystem processes as well as linking phylogenetic and trait-based patterns of biogeography