Vermont proposes to support physical, human and cyberinfrastructure improvements in the state’s research infrastructure with a transdiciplinary research theme of adaptation to climate change that integrates the interactions of climate, environment, society and land use policy. The State EPSCoR Committee selected this theme as having the best potential too improve the future R&D competitiveness of the jurisdiction because it builds on core strengths and aligns with national and state priorities. We propose to create a center for Research on Adaptation to Climate Change (RACC) that supports transdisciplinary studies with complex systems modeling incorporated throughout. Application of genetic algorithms, artificial neural networks, and agent based modeling allow us to address the nonlinear dynamics of and identify emergent properties in a complex system like the Lake Champlain Basin among its many non-linear drivers and actors.
Investigators from academia and the private sector have joined together with our stakeholders, students and teachers to organize around three questions and the IAModel
Overarching Question: How will the interaction of climate change and land use alter hydrological processes and nutrient transport from the landscape, internal processing and eutrophic state within the lake and what are the implications for adaptive management strategies?
Lake Processes (Q1): What is the relative importance of endogenous in-lake processes (e.g. internal loading, ice cover, hydrodynamics) versus exogenous to-lake processes (e.g. land use change, snow/rain timing, storm frequency and intensity, land management) to lake eutrophication and algal blooms? This question broadens current research on the Lake Champlain Basin, by focusing on coupled human and natural system aspects. Research on both questions 1 and 2 utilizes the information flowing from the CSYS group on new computational tools, best temporal and spatial sampling regimes, uncertainties, scale dependencies, and gaps in data sets.
Watershed Processes (Q2): Which alternative stable states can emerge in the watershed and lake resulting from non-linear dynamics of climate drivers, lake basin processes, social behavior, and policy decisions? This question springs very directly from lessons learned by CSYS modelers of the Lake Champlain watershed data. Complex systems models will assist us in identifying the available stable states that lose resilience; recovery from some states (e.g complete eutrophication) could be very difficult through land use management policies if they come to pass.
Policy & Governance (Q3): In the face of uncertainties about alternate climate change, land use and lake response scenarios, how can adaptive management interventions (e.g. regulation, incentives, treaties) be designed, valued and implemented in the multi-jurisdictional Lake Champlain Basin? Adaptive management on a local scale will be addressed through scenario testing and complex systems modeling, in particular agent-based models of policy actors. We will work closely with our stakeholders and use mediated modeling, participatory planning and consensus building to understand the processes of policy implementation and the attitudes of the public and managers toward climate change and to steer the watershed governance toward proactive adaptive management interventions for sustaining high-valued alternate stable states in the lake.
Integrated Assessment Model (IAM): RACC researchers study the Lake Champlain Basin as a coupled human and natural system with climate-change and human drivers. The novel and potentially transformational methodology in this work is the use of complex systems tools across all spheres, from the research on the Lake and working landscape of the watershed to the policies for management of the Basin. In this effort, social and natural scientists work with stakeholders in hypothesis-driven research to create ecosystem scenarios and an Integrated Assessment Model (IAModel) for basin management – a need recognized in regional and national studies and specifically requested by our local and regional stakeholders. We collaborate with climate change researchers to test the extensibility of our complex systems models by carrying out a comparative analysis of modeling approaches including the IAModel.
Members from each team collaborate to create an IAModel for regional management for adaptive capacity. This model’s general applicability to ecosystem service assessment will be tested with collaborators. To improve existing data sets for use in all three questions and the IAModel, we collect higher spatial and temporal resolution data on nutrient loading in the watershed and Lake through a series of novel under-ice sensors, instrumented moorings and watershed sensors.