Chicago, IL 60611 United States
Overview
Where organisms live, how they move, and how environments vary across space shape population abundance, ecosystem productivity, and the spread of disease. Mathematicians have developed a rich theory for spatially structured models, including reaction-diffusion equations, patch and metapopulation models, and integro-difference equations. Much of this theory involves quantities such as principal eigenvalues, basic reproduction numbers, and properties of dispersal operators. A central challenge is connecting these results to quantities that biologists and managers care about: total population size, productivity, disease prevalence, and sustainable yield. When does movement increase or decrease total abundance? How does spatial heterogeneity in transmission alter the burden of disease? Which spatial management strategies maximize yield or minimize prevalence?
Answering these questions also requires confronting data. Parameterizing spatial models raises distinctive statistical problems, from estimating movement kernels and connectivity to inferring spatially varying demographic and transmission rates. At the same time, high-resolution data from animal tracking, remote sensing, human mobility records, and genomics create new opportunities to test and refine theory.
The workshop will focus on four interconnected areas:
- Effects of movement and spatial heterogeneity on population size, productivity, and disease prevalence and spread.
- Optimization and control in spatial settings, including reserve design, harvesting, invasive species control, and the allocation of disease interventions.
- Analytical and computational tools for high-dimensional and spatially heterogeneous systems.
- Statistical methods and data sources for parameterizing spatial models.
The workshop will bring together mathematicians, ecologists, epidemiologists, and statisticians to identify key open problems and foster lasting interdisciplinary collaborations.
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