2014-15 Program on Mathematical and Statistical Ecology (ECOL)

Ecological modeling has developed in two quite different ways. On the one hand, theoretical ecologists develop mathematical models that are analyzed using traditional tools of applied mathematics, such as PDEs and dynamical systems. These models are then used to establish properties such as resilience (the ability of a system to withstand perturbations) or tipping points (conditions under which a system is transformed permanently into a new state). On the other hand, statisticians and data analysts have developed increasingly sophisticated statistical tools, such as Bayesian hierarchical models applied to large spatio-temporal datasets, but often without delatiled consideration of nonlinear dynamics. Statistical tools used by ecologists are often different from those used by statisticians and there is a need for a transfer of expertise in both directions. This program will bring together three groups of researchers – statisticians, mathematicians and theoretical ecologists – to study and develop the interactions among these different approaches. Many of the important issues are multi-scale, e.g. models developed based on their fine-scale behavior are then used to study large-scale behavior of the system. This in turn raises questions about model misspecification, model selection or model averaging, and uncertainty quantification. Finally there is the possibility if using statistical and mathematical tools for management of ecosystems and the formulation of public policy.

Planned working groups are as follows:

Please contact the organizers at [email protected] if you would like to join one of these working groups or if you have other suggestions for working groups that could be organized in connection with this program.

The Opening Workshop will be held August 18-22, 2014.

Poster

Questions: email [email protected]