Research

The Effects of Deforestation on Genetic Structure in Lemurs and the Evolution of their Parasites and Pathogens. This is work in collaboration with Dr. Sarah Zohdy from Forestry and Wildlife and Dr. Jamie Oaks, and Dr. Tony Goldberg from University of Michigan, along with PhD student (Samantha Smoot) and undergraduate (Emma Hale). In recent decades global habitat loss has led to the emergence of infectious diseases of wildlife origins into human populations; however, the mechanisms driving the association between habitat degradation and disease emergence remain unclear.  We propose a novel mechanism, the Coevolution Effect, to explain this pattern and propose a model system and study design to test it. Through interdisciplinary collaborations in disease ecology, population/evolutionary genetics, phylogenetic theory, and ecological modeling, we aim to test this new hypothesis; which has the potential to fill a necessary knowledge gap and explain the underlying mechanisms of zoonotic emerging infectious diseases in a dynamic world. To test our Coevolution Effect hypothesis as a mechanism for spillover in fragmented habitats, we utilize a well-established study system in Madagascar, a biodiversity hotspot where forest loss is among the highest in the world (> 94% of the original forests), has a diverse array of mosquito-borne viruses, and is home to the most critically endangered endemic animals. Our system includes two host species, three vector species, and RNA viral pathogens. We are quantifying the effect of habitat fragmentation on the population structure of wildlife host and vectors, using population genomic data with GIS data across the landscape of continuous to fragmented habitat. We will determine the effect of habitat fragmentation on pathogen diversity within hosts and vectors using pathogen-metagenomics to characterize RNA viral diversity in each species through our collaborator Tony Goldberg. For each viral pathogen, we will test for a relationship between the degree of habitat fragmentation and genetic diversity using phylogenetic models. Ultimately these data will allow us to test of the Coevolution Effect hypothesis by classifying the viral strains into types of transmission cycles based on the presence of the RNA virus variants across species.