Associations among taxonomic diversity, functional diversity and evolutionary distinctiveness vary among environments

Abstract

Diversity metrics are commonly used to measure or quantify species-level biodiversity in a given area. In recent decades, ecologists developed many measures and indices in order to quantify a larger proportion of information about communities or species assemblages. Commonly these measures are based on species richness or species evenness, in relation to their relative abundance. Among the most common diversity metrics are the indices of taxonomic diversity, functional diversity and phylogenetic diversity. These metrics are often used to assess effectiveness of conservation planning.One concern on the use of many diversity metrics, especially in modeling, is the potential redundancy among these indices and measures. Many scientists explored the associations among different diversity metrics, finding clear patterns. For instance, functional richness and the functional diversity (FD) index are both positively correlated with species richness, while functional evenness should be unrelated to species richness. Furthermore, explorations focusing on associations between phylogenetic diversity and taxonomic or functional diversity metrics are few. However, despite the importance of the types of environment has on biotic assemblage rules, there are no studies comparing the association among diversity metrics across different type of environments.Here, we found higher values of taxonomic diversity, functional richness and Rao’s quadratic entropy (RaoQ) in farmland than in forests and grasslands. Forest bird communities were characterized by a large amount of evolutionary history as reflected by community evolutionary distinctiveness (CED). Furthermore, associations among diversity and community metrics in bird communities differ across types of environments. Within functional diversity metrics, associations between functional richness and RaoQ as well as associations between functional evenness and divergence were always positive, independently of the type of environment. The associations between functional richness and evenness or divergence, as well as functional evenness and RaoQ, changed strength and direction of correlation between different types of environment.In conclusion, a) large scale conservation planning strategies have to consider that different environments support different dimensions of bird diversity, and b) when modeling many diversity metrics, associations among diversity and community metrics can also change across environments.