Disease outbreaks are a major threat to agricultural systems. We use surveillance data to estimate contact networks due to transmission from multiple routes (e.g. livestock shipments, local spread) and simulations to determine which transmission routes have greatest risk and which control methods would be most effective. Additional work with an international collaborative network is to develop ensemble methods for livestock disease prediction. Livestock diseases of interest include avian influenza, bovine tuberculosis and foot and mouth disease. For more information on this work, please see the web page for the USAMM/USDOS project.
In our disease research, we focus on the ecology and evolution of wildlife disease reservoirs with implications for human and domestic animal health. Highly virulent diseases induce high mortality in their hosts and thus decimate host populations. How do such virulent diseases persist and spread despite wiping out the hosts they rely upon? Our work investigates how ecological and evolutionary mechanisms, particularly spatial and temporal host refuges and pathogen reservoirs, enhance persistence using plague, bat diseases, and avian influenza as example systems.
Global change is intensifying efforts to predict how species composition will respond to environmental change and modify ecosystem function. Trait-based approaches are receiving considerable attention as they potentially provide badly needed improvements in prediction for community composition and ecosystem function. However, realization of this potential requires statistical and modeling tools that are in their infancy. We work in a number of different systems (e.g. grasslands, forests, fisheries, microbial communities) to determine how trait-based approaches can be generally informative. We are interested in how many traits and environmental drivers are needed to describe a system, which types of traits are most informative, and how biodiversity patterns impact the usefulness of trait-based approaches.