This Faculty Early Career Development Program (CAREER) award will contribute to the national health, prosperity, and welfare by improving decision-making in conservation planning through new theory, models, algorithms, and visual analytics tools for landscape and conservation ecology. Biodiversity has been declining at rapid rates during the last several decades due to habitat loss, landscape deterioration, environmental change, and human-related activities that directly and indirectly affect natural habitats. In addition to its economic and cultural value, biodiversity plays an important role in keeping an environment’s ecosystem in balance. Disrupting such processes can reduce the provision of natural resources such as food and water, which in turn yields a direct threat to human health. Protecting natural areas is fundamental to preserving biodiversity and to mitigate the effects of ongoing environmental change. This award will contribute quantitative methods to support informed decisions on conservation design and effective land use to support species sustainability. These methods integrate realistic ecological features, specific spatial properties of the selected reserves (e.g., connectivity), population dynamics within the spatial assets, and the impact of current and future threats. The educational plan will improve the skills and diversity of future generations of engineers via technical training and engagement in transdisciplinary research. The outreach activities aim to increase the students’ awareness of current biodiversity and conservation challenges.
This award supports fundamental research on the design of portfolios of land or marine patches to support species sustainability. These design problems result in very large mixed-integer linear programs whose solutions require innovative formulations and new large-scale optimization methods. The new models and specialized algorithms will allow decision-makers to solve a variety of realistic large-scale corridor and reserve design problems that include patch-specific conservation decisions under spatial, operational, ecological, and biological requirements. These models will feature realistic objectives faced by practitioners, such as maximization of the protected area or the number of species covered and minimization of the conservation cost. The design models will embed stochastic processes to capture the species’ spatiotemporal movement across the landscape and to assess the effectiveness of conservation plans, including extinction risks, mortality, and ecosystem disturbances. New bi-level and stochastic optimization models and algorithms will support the design of robust conservation areas, i.e., areas that provide acceptable levels of ecological benefits even under future extreme and adverse events affecting the landscape. A visual analytics tool will integrate the developed tools, facilitating the discussion of optimal conservation plans with practitioners, advocates, and experts.
This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.