CAREER: Quantifying Environmental-Ecological Relationships for Watershed Sustainability Analysis

University Of Illinois At Urbana-Champaign, Urbana IL

Investigators

Abstract

Abstract 0747276 (Cai). This CAREER award focuses on sustainable watershed management (SWM) using quantitative interdisciplinary analysis to understand the inter-relationships and ecological thresholds within complex watershed systems characterized by hydrological-ecological-socioeconomic relationships. Explicit ecological target equations (ETEs) that quantify the relationships between fish community diversity and abundance and ecologically relevant environmental indicators (EREIs, e.g., streamflow and water quality metrics) will be developed. A multiple agent system (MAS) model combining heterogeneous agent behaviors, watershed hydrology, and quantitative environmental-ecological relationships will be implemented. Scientifically meaningful ecological thresholds will be identified and validated. A problem oriented, demand-driven mutual learning approach to research and education, which facilitates critical thinking and assimilates reflective experiences and lessons into quantitative analysis, will be created. Intellectual Merit. The ETE concept and tool will explicitly address the relevance of environmental variables to the target ecosystem. Identifying the EREIs from hundreds of metrics will resolve the indicator redundancy problem that hinders both the scientific understanding of ecology-hydrology connectedness and engineering design for watershed restoration. Fundamental questions, such as how human interference forces watershed ecosystems across thresholds, will be addressed through MAS-based modeling. The discovery and understanding of ecological thresholds is the key to early warning of irreversible transitions in watersheds. Broader Impacts. This project paves the way for five broad impacts: 1) ETEs and EREIs will be effective tools for both ecologists and hydrologists, and the findings on ecology-hydrology connectedness are expected to stimulate wider and deeper scientific research, 2) the MAS-based virtual model will provide a communication among the education, research, and practice sectors of SWM for a wide range of problems related to scientific understanding, management policy evaluation, and decision making support, 3) the concepts, procedures, and tools to be developed will be generalizable enough to be extendible to non-fish ecosystem indicators such as riparian vegetation and habitats, 4) virtual tool exercises will provide guidelines for more efficient sensing and monitoring system design and for cyberinfrastructure development in watersheds,, and 5) the mutual learning program will enhance long-term sustainability by intentionally connecting stakeholder groups, providing new opportunities to increase involvement and participation of minority and underrepresented stakeholders.