OPUS: Synthesizing Recent Developments in Sensitivity Analysis for Use in Population Ecology

Woods Hole Oceanographic Institution, Woods Hole MA

Investigators

Abstract

The Opportunities for Promoting Understanding through Synthesis program (OPUS) supports the synthesis of research results produced over an extended period by a single individual or a group of collaborating researchers. This OPUS project will produce a book integrating a series of journal publications by the Principal Investigator on the sensitivity analysis of population models. Sensitivity analysis, the focus of this project, answers the fundamental question, "what would happen if some specified aspect of a system was to change"? Sensitivity analysis is essential to the development of robust models in ecology used to study e.g., natural environmental changes, anthropogenic impacts, the benefits of management strategies, and the response to evolutionary modifications. Although our ability to model ecological phenomena is good, it will never be perfect; even if it was, it would not be sufficient. There is always the possibility that things could be different, and the certainty that at some point they will be different. It is only through an analysis of model sensitivity that we judge the significance of our uncertainty. This OPUS project will increase the dissemination of powerful new mathematical methods for sensitivity analysis, with applications to linear, nonlinear, stochastic, deterministic, spatial, and subsidized population models. The book to be produced on this project will make these new methods accessible to students, researchers, and managers concerned with the conservation, demography and population dynamics of species, greatly extending the range of models and questions that can be addressed and their value in application. This project also will have broader impacts in the area of education, both through the use of the book in university courses, and through the presentation of workshops to ecologists, conservation biologists, and human demographers.