Login / Signup

Clade composition of a plant community indicates its phylogenetic diversity.

Martin BitomskýPavla MládkováRobin J PakemanMartin Duchoslav
Published in: Ecology and evolution (2020)
Phylogenetic diversity quantification is based on indices computed from phylogenetic distances among species, which are derived from phylogenetic trees. This approach requires phylogenetic expertise and available molecular data, or a fully sampled synthesis-based phylogeny. Here, we propose and evaluate a simpler alternative approach based on taxonomic coding. We developed metrics, the clade indices, based on information about clade proportions in communities and species richness of a community or a clade, which do not require phylogenies. Using vegetation records from herbaceous plots from Central Europe and simulated vegetation plots based on a megaphylogeny of vascular plants, we examined fit accuracy of our proposed indices for all dimensions of phylogenetic diversity (richness, divergence, and regularity). For real vegetation data, the clade indices fitted phylogeny-based metrics very accurately (explanatory power was usually higher than 80% for phylogenetic richness, almost always higher than 90% for phylogenetic divergence, and often higher than 70% for phylogenetic regularity). For phylogenetic regularity, fit accuracy was habitat and species richness dependent. For phylogenetic richness and divergence, the clade indices performed consistently. In simulated datasets, fit accuracy of all clade indices increased with increasing species richness, suggesting better precision in species-rich habitats and at larger spatial scales. Fit accuracy for phylogenetic divergence and regularity was unreliable at large phylogenetic scales, suggesting inadvisability of our method in habitats including many distantly related lineages. The clade indices are promising alternative measures for all projects with a phylogenetic framework, which can trade-off a little precision for a significant speed-up and simplification, such as macroecological analyses or where phylogenetic data is incomplete.
Keyphrases
  • climate change
  • healthcare
  • magnetic resonance imaging
  • mental health
  • rna seq
  • cell wall