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

气候变化每年都造成经济损失，但资源和供应系统（如农业和粮食、能源、水资源和制造业供应链）内建的适应措施可以缓冲这些影响。虽然在许多案例研究中已经审查了管理战略和适应情况，但能够形成基本见解的系统分析仍然有限。为了填补这一空白，该项目进行了一项大数据、假设驱动的评估，评估了美国大陆各种社会环境系统对历史气候波动的敏感性。分析方面的挑战是根据来自不同来源、跨多个部门、高分辨率和国家范围的证据，从经验上做到这一点。通过对比不同管理强度下经历相似气候条件的系统，本研究期望约束管理导致的系统敏感性变化。因此，该项目将生物物理、社会和信息科学的理论方法结合起来，可用于评估气候变率和变化的影响、美国经济适应的有效性以及变化条件下的可持续性战略。水流、植被和野火动态是通过水和能源的限制和需求相互联系的，而这些限制和需求又受到气候的调节。水资源、农业生产力和减灾管理目标的最终目标是尽量减少干扰对水资源供应、粮食生产和安全的影响。适应战略通常侧重于尽量减少对气候波动的敏感性，尽管其方式受到成本、技术和跨系统竞争需求的限制。该项目将利用美国邻近地区的气候多样性和长期的管理和适应历史，对气候和社会环境系统之间的耦合强度如何随管理强度的变化进行大数据、假设驱动的分析。分析和解释管理效果的概念框架是基于复杂系统理论的，因此影响可以被视为一种紧急属性。在不同管理方式和强度下，气候与系统之间的耦合程度可以表征为系统指标（流量、水库水位、植被生产力、野火、作物产量和经济活动）对气候强迫统计性质（均值、方差、熵和决定论）变化的敏感性，并使用剂量响应函数对其进行量化。结果将用于确定自然实验，在这些实验中，管理严格的系统与管理最低的系统之间的比较可以约束管理和适应如何影响系统敏感性。该奖项反映了美国国家科学基金会的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.