Multi-Purpose Optimization for Reconciliation Ecology on an Engineered Floodplain: Yolo Bypass, California

Floodplains in California and elsewhere are productive natural habitats with high levels of biodiversity, yet today they are often permanently disconnected from rivers by urban or agricultural development and flood management structures. This disconnection poses a threat to many native fish, bird and other species that evolved to take advantage of seasonal floodplain inundation. The traditional restoration approach to this problem is to recreate historical floodplain by restoring natural hydrologic and successional processes. However levees, dams, and development have made this largely impossible in much of the developed world. Reconciliation ecology recognizes this limitation, and encourages instead the re-engineering of human dominated landscapes to allow for coexistence of native species and human uses. Flood control bypasses are particularly promising places to reconcile historical fish and bird uses of floodplain habitats with human uses. However, the reconciliation approach requires nuanced management of a complex system. Using the Yolo Basin flood bypass in California’s Central Valley as an example, this study develops formal multi-objective optimization to help planners identify 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 offer an explicit accounting of relationships and trade-offs between different objectives. This is especially useful in reconciliation planning, where many uses and variables interact on a landscape, and deliberate re-engineering requires consideration of many decisions simultaneously. Initial results suggest that modest land-use changes and inundation management strategies can significantly improve seasonal bird and fish habitat quality at little cost to farmers or other human land uses. The model applications 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