College of Food, Ag & Nat Res Sci
Agro-ecological landscapes are complex systems and their management requires understanding interactions of numerous species and processes that influence production of both crops and ecosystem services. The dual nature of weeds in these systems as both detrimental to crop yields and also potentially beneficial for ecosystem services offers a particular example of the challenging issues faced by decision-makers in these systems. Spatially explicit and landscape-scale models that incorporate local community dynamics can offer a strategy to address these issues in an objective, evidence-based manner. Thoughtful decision-making incorporating multiple costs and benefits will be necessary but these challenges require a fundamentally landscape-level perspective as spatial heterogeneity, non-equilibrium dynamics, and the impacts of uncommon events can all play important roles creating multiple layers of complexity. However, few tools are available that consider such spatially explicit dynamics in realistic scenarios. These researchers will explore management strategies for maintaining beneficial non-crop flora in agricultural landscapes, thereby supporting the provision of highly-valued ecosystem services in these landscapes. To do so, they will leverage and integrate current empirical understanding and expert opinion, using this information to drive landscape-scale dynamic models to evaluate the effect of non-crop flora on ecosystem service and crop production. They will use these simulation models to systematically assess impacts of agricultural land-use and management (e.g., use of herbicide-tolerant crops) on non-crop flora and associated ecosystem services at landscape scale. This will shed light, via simulation, on a critical knowledge gap: linkages between local-scale processes and landscape-scale distribution of non-crop flora, ecosystem services, and crop yield. Through simulation, analysis, and consultation with experts, the researchers will determine benefits and costs of management strategies to maintain non-crop flora in agricultural landscapes.
This group is also exploring the risks posed by emerging infectious diseases (EIDs) to human, livestock, and wildlife populations. Since the majority of EIDs that affect humans originate in wildlife, it is imperative to understand the conditions under which pathogens spread and persist in wildlife populations. However, there has been limited theoretical investigation into how animal behavior interacts with the spatial organization of resources (e.g., clustered, random, uniform, etc.) across a landscape to affect infectious disease dynamics. Importantly, spatial heterogeneity can sometimes lead to non-linear or counterintuitive outcomes depending on the host and pathogen system. There is a clear need to develop a general theoretical framework that could be used to create testable predictions for specific host-pathogen systems. The researchers are using an individual-based model integrated with movement ecology approaches to investigate how individual movement behaviors interact with landscape heterogeneity (in the form of various levels of resource abundance and clustering) to affect pathogen dynamics.