UC Davis

Increasingly, studies of community assembly and ecosystem function combine trait data and phylogenetic relationships to gain novel insight into the ecological and evolutionary constraints on community dynamics. However, the key to interpreting these two types of information is an understanding of the extent to which traits are phylogenetically conserved. In this study, we develop the necessary framework for community phylogenetics approaches in a system of marine crustacean herbivores that play an important role in the ecosystem functioning of seagrass systems worldwide. For 16 species of amphipods and isopods, we (1) reconstructed phylogenetic relationships using COI, 16S, and 18S sequences and Bayesian analyses, (2) measured traits that are potentially important for assembling species between and within habitats, and (3) compared the degree to which each of these traits are evolutionarily conserved. Despite poor phylogenetic resolution for the order Amphipoda as a whole, we resolved almost all of the topology for the species in our system, and used a sampling of ultrametric trees from the posterior distribution to account for remaining uncertainty in topology and branch lengths. We found that traits varied widely in their degree of phylogenetic signal. Body mass, fecundity, and tube building showed very strong phylogenetic signal, and temperature tolerance and feeding traits showed much less. As such, the degree of signal was not predictable based on whether the trait is related to environmental filtering or to resource partitioning. Further, we found that even with strong phylogenetic signal in body size, (which may have large impacts on ecosystem function), the predictive relationship between phylogenetic diversity and ecosystem function is not straightforward. We show that patterns of phylogenetic diversity in communities of seagrass mesograzers could lead to a variety of interpretations and predictions, and that detailed study of trait similarities and differences will be necessary to interpret these patterns.