My laboratory investigates the ecology and evolution of sponge-microbe symbioses. Microbial symbionts can constitute half of the biomass of many marine sponges, while photosynthetic symbionts can supply up to 80% of a sponge's energetic needs. We use sponges and their symbiotic microbial communities as model systems to study coevolution among hosts and symbionts, the evolution of community structure, and the evolution of mutualistic interactions.
Taxonomy and systematics build the foundation for studying relationships among organisms and provide the phylogenetic context required by comparative biology. Current funding from the National Science Foundation’s (NSF) Assembling the Tree of Life program supports our efforts to construct the Porifera Tree of Life (PorToL.org), a definitive phylogeny of sponges. My lab group integrates morphological and molecular approaches to systematics, using a variety of laboratory techniques, such as histology, electron microscopy, digital image analysis, DNA extraction, PCR amplification of targeted genes, and high-throughput DNA sequencing.
Additional funding from NSF supports the development of a novel software package for comparative evolutionary analyses. Our software is designed to place phylogenetic tools into the hands of scientists across diverse disciplines, enabling rapid advances in integrative and comparative biology at multiple phylogenetic and spatiotemporal scales. This project incorporates a variety of bioinformatic approaches to ecological and evolutionary data analysis in collaboration with computer scientists and informatics professionals.
A third NSF-sponsored project aims to rapidly characterize phenotypes. We are combining text mining, image analysis, and machine learning software to automate taxonomic character discovery and scoring from digital collections of natural history texts and images. My lab’s primary contribution to this project consists of the thousands of histological sections of sponges generated by PorToL. We are imaging these sections and using novel phenomics algorithms to discover new morphological characters that improve sponge systematics.