CNH2-S: Testing the strength of coupling among climate, natural, and human systems using big data

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Climate variations cause economic losses every year, but adaptations built into resource and supply systems, such as agriculture and food, energy, water resources, and manufacturing supply chains, buffer these impacts. Although management strategies and adaptation have been examined in many case studies, systematic analysis that can add up to fundamental insight has been limited. To fill this gap, this project undertakes a big-data, hypothesis-driven, assessment of the sensitivity of a variety of socio-environmental systems to historical fluctuations in climate across the continental United States. The analytical challenge is to do this empirically, with evidence from diverse sources, across multiple sectors, at high resolution, and at the national scale. By contrasting systems under different management intensities experiencing similar climate conditions, this research expects to constrain changes in system sensitivity due to management. The project thus bridges theoretical approaches from the biophysical, social, and information sciences in ways that can be used to evaluate the effects of climate variability and change, the effectiveness of adaptations in the U.S. economy, and strategies for sustainability under changing conditions. Streamflow, vegetation, and wildfire dynamics are interconnected through water and energy limits and demands which are, in turn, regulated by climate. Management goals for water resources, agricultural productivity, and hazard mitigation ultimately aim to minimize the impact of disturbances on water availability, food production, and safety. Adaptation strategies typically focus on minimizing sensitivity to climate fluctuations, albeit in ways constrained by cost, technology, and competing needs across systems. This project will leverage the climatological diversity and long history of management and adaptation in the contiguous United States to conduct a big-data, hypothesis-driven analysis for how the strength of coupling between climate and socio-environmental systems varies as a function of management intensity. The conceptual framework for analyzing and interpreting the effects of management is based on complex-systems theory, whereby impact can be viewed as an emergent property. The degree of coupling between climate and systems under contrasting styles and intensities of management can be characterized as the sensitivity of system indicators (streamflow, reservoir levels, vegetation productivity, wildfire, crop yields, and economic activity) to changes in the statistical properties of the climate forcing (mean, variance, entropy, and determinism), and quantify it with dose-response functions. Results will be used to identify natural experiments where comparisons between heavily- managed systems adjacent to those that are managed minimally can constrain how management and adaptation affect system sensitivity.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.