My research is united by the notion that we must recognize and appreciate the complexity and changing nature of human-natural systems, while accepting that people and organizations must still make choices in the face of that complexity — whether the decisions at stake are household purchases, implementation details of a local environmental stewardship project, or national policies about global pollutants. Therefore, the overarching theme of my work is to conduct multi-disciplinary science and analysis that tempers hubris and motivates appreciation of complexity and change, while simultaneously providing decision-oriented tools to address the challenges they create.
I do this by modeling the complexity, uncertainty, and multiple drivers of change in different problem contexts, with a particular focus on water and working landscapes. Methodologically, I frequently rely on economics, decision analysis, and ecosystem services as helpful lenses to considering problems. My research projects tend to involve building, harnessing, or extending simulation models, and running the models many times (hundreds to many thousands) in carefully chosen ways that reflect their adequacy for particular policy questions or decision contexts. I then use a variety of analytical techniques to characterize the model results in a way that provides a better assessment of what can and cannot be claimed given the relationship between model structure, data availability, and problem context. This includes an assessment of how well modeled metrics relate to objectives people actually care about, how those metrics and people’s concerns are represented in the decision processes, and how overlooking these subtleties can lead to erroneous conclusions for the sustainability problem at hand.
Most of my current work involves understanding how land management (eg forest or agricultural practices) affects water resources and related ecosystem service co-benefits, or how water resource management affects terrestrial ecosystem services (including agricultural provisioning). For example, one project works with a local water agency (as well as a civil engineer, ecohydrologist, and ecologist) to examine the impact of forest management on their reservoir inflows and the attending impacts on hydropower production and environmental flows for aquatic species. This informs a broader agenda of assessing and improving the state of science to support realistic goals for environmental impact investing. My work within this broader agenda includes liaising with private capital, brokers, utilities, and government agencies to align modeling and monitoring needs.
Another project examines proactively considering how groundwater scarcity will drive land use change in California’s agriculturally dominated San Joaquin Valley, and how conservation actors can work with the ag community to proactively shape that land use change to enhance habitat and other environmental benefits while helping farmers adapt. This work deploys state-of-the-art spatial optimization techniques within a broader workflow touching on economic and ecological considerations.
My methodological work includes enhancing techniques for decision making under uncertainty with NatCap’s decision support tools, simple land change modeling to inform corporate sourcing decisions, and (when I have time), working on techniques for managing deep uncertainty.
There are a number of topics which occupy a good deal of mental attention but which I have not yet formalized into research projects, some of which I describe below (in decreasing order of existing knowledge). These include:
- Bridging between micro-level decision support with macro-level sustainability assessments that tell us if we’re on the right track, especially in the context of creating locally and globally resilient food systems (“How do we facilitate local sovereignty and equitable local management while ensuring regional and planetary boundaries are not crossed?”);
- Knowledge management for sustainability, especially with respect to claims on sustainable agricultural practices (“How do we reframe and improve the quality of simplistic debates like ‘can [organic/vegan/GMOs] feed the world?’ so that we can base debates on knowledge claims and their implications for multi-faceted decisions?”);
- The relationships between economic valuation, social choice processes, and multi-criteria decision analysis (“What is a ‘good’ decision metric and process in light of socially constructed and evolving preferences and power relationships?”);
- (Computational) Knowledge representation and reasoning to better screen and characterize the robustness of context-dependence of knowledge claims relevant for decisions (eg, “Can we use natural language processing of academic corpora, news, blogs, comment streams to conduct systematic reviews, build issue maps or identify potential policy failure modes for further consideration?”)
Thoughts and potential collaborations welcome!