Multi-Objective Analysis for Ecosystem Reconciliation on an Engineered Floodplain: The Yolo Bypass in California's Central Valley

Using Multi-Objective Analysis for Ecosystem Reconciliation on an Engineered Floodplain: the Yolo Bypass in California's Central Valley Abstract Floodplains in California and elsewhere are extremely productive habitats with high levels of biodiversity, yet they are often permanently disconnected from rivers by urban or agricultural development. This poses a potential threat to the many native fish, bird and other species that evolved to take advantage of seasonal floodplain inundation. The traditional restoration approach to this problem would recreate historical floodplain in some places by restoring natural hydrologic and successional processes. However levees, dams, and development prevent this approach in much of California. Reconciliation ecology recognizes this limitation, and encourages instead the re-engineering of human dominated landscapes so that native species and human uses can sustainably co-exist. Flood control bypasses are a particularly promising location for reconciling historical fish and bird uses of floodplain habitats with human uses. However the reconciliation approach requires nuanced management of a complex multi-purpose system. This study proposes the use of formal multi-objective optimization to help planners choose management options that best improve habitat quality for fish and birds with minimal costs to farmers or wetland managers. Models like the one developed here can integrate large amounts of data and knowledge, and explicitly account for the relationships and tradeoffs among different objectives. This is especially useful in reconciliation planning where many uses and variables interact on a landscape, and deliberate re-engineering requires considering many decisions simultaneously. Results suggest several land use changes and inundation management strategies on the Yolo Bypass that can significantly improve seasonal bird and fish habitat at very little cost to farmers and other human uses. The model applications herein demonstrate the usefulness of multi-objective optimization in reconciling managed floodplains, and provide a framework for integrating new knowledge and testing varying assumptions to improve management over time.