Anticipatory Ecosystem Management of Regime Shifts in Social Ecological Systems: Navigating Trade-Offs in Public Investments Across Farms, Forests and Cities

Anthropogenic climate change could induce regime shifts from oligotrophic to eutrophic states in shallow bays of the Lake Champlain due to more frequent and more intense flooding events in Lake Champlain Basin (LCB) as well as reduced ice cover internally in the lake system. It is, however, not clear how anticipation of these climatic change induced extreme events, coupled with anticipated impact of land-use land cover change (LULCC) on the water quality of freshwater lakes, will lead to anticipatory governance of provisioning versus non-provisioning ecosystem services, inducing proactive policy changes to mitigate nutrient pollution across transboundary LCB. The nutrient abatement costs are relatively higher for downstream urban areas than upstream farming and forest areas, yet the downstream urban areas experience more benefits from the clean water through tourism revenues, higher water front property values and drinking water supplies. Climate change has added another layer of complexity in this debate.

This paper presents an integrated assessment model (IAM) that couples climate change induced temperature and precipitation variability scenarios with human-system induced LULCC scenarios on the nutrient flows through the hydrological system of the Missisquoi Watershed and its socio-economic impacts on mitigating the water quality in the Missisquoi bay, a transboundary fresh water body in the north-eastern portion of Lake Champlain. We will present a suite of scenarios of current versus alternate public investment strategies in agriculture vs urban vs forest lands for mitigating nutrient pollution in the Missisquoi bay under different climatic and LULCC scenarios. We draw broad theoretical implications for anticipatory versus reactive ecosystem management of regime shifts in social ecological systems, with an emphasis on navigating trade-offs among rural and urban populations through foresight generated by IAMs.