CNH: People, Water, and Climate: Adaptation and Resilience in Agricultural Watersheds

自然和人类系统的复原力被定义为应对干扰的能力。适应能力是指当系统受到超过其弹性能力的扰动时，其基本结构或功能发生变化的能力。可持续性、恢复力和适应性的概念显然是相关的，但很少有研究系统地分析它们之间的相互作用如何影响系统级的动态、脆弱性、不确定性或风险。这一跨学科研究项目将调查区域耦合的自然和人类系统如何应对气候、经济和政策条件的变化，这些变化在更大的地理和时间尺度上运行。研究人员将在以农业为基础的中西部分水岭(爱荷华州的爱荷华州/雪松河分水岭)，在可持续性、复原力和适应性的背景下探索这些概念。他们将使用埃尔金顿的三重底线概念(人、星球、利润)来定义可持续发展，在该概念中，社会和环境价值被添加到传统的成功经济衡量标准中。在这项具体研究中，他们将考虑不会受到污染或收回的地表水和地下水资源，以便不再支持预期的农业用途，以及不会耗尽土壤或地下水，并至少支持现有经济活动水平的农业做法。研究人员将评估传统的最优指标之间存在的多维权衡，例如环境质量和经济回报最大化，以及弹性、适应性和可持续性指标。为了进行这项分析，他们将开发模型，模拟景观如何随着自然和社会经济因素的变化而变化。土地利用决策将被模拟为模拟人类如何应对不断变化的条件，这些模型将与地表水和地下水质量模型联系起来，以量化对环境的影响。进化计算技术将被开发来产生生产可能性边界，以量化相互竞争的目标之间的权衡。将通过焦点小组征求利益相关者对不同目标的偏好，并将开发调查和网络基础设施来支持这项研究的重大计算需求。虽然景观处于不断变化的状态，但目前影响中西部景观的全国和全球范围的因素是前所未有的。在这种情况下，产生对未来条件的准确预测是一个不切实际的目标。因此，该项目将评估一系列看似合理的方案，以确定最有可能产生可持续农业景观的战略。研究人员假设，可持续的结果是由具有适应变化和不确定条件的能力，并具有应对意外和重大扰动所需的弹性的系统产生的。自然(如气候)和人类(如政策和经济)过程可限制或加强系统适应和应对变化和不确定性的能力。重要的是要推动增强可持续性的进程，避免产生制约因素的进程。该项目将通过构建模型，将适应性、恢复力和可持续性与更传统的经济和环境最优化措施联系起来，从而推动可持续发展科学的理论和实践。从更实际的角度来看，该项目将对中西部的政策和土地管理产生影响，因为它将为决策者提供更好的数据和分析工具，因为他们正在解决复杂的问题和完善政策。该项目还将提供信息和范例，帮助广大公众了解在气候和经济条件不断变化的背景下实现可持续性的必要性。由于与区域、国家和国际变化的规模和时空格局相关的不确定性，旨在限制不确定性、记录看似合理的自然和社会经济结果以及分析替代适应战略的影响的研究可能特别及时和重要。该项目得到了美国自然与人类耦合系统动力学(CNH)计划的支持。

Resilience in natural and human systems is defined as the capacity to cope with disturbance. Adaptive capacity refers to a system's ability to change in basic structure or function when it is perturbed beyond its capacity for resilience. The concepts of sustainability, resilience, and adaptability are clearly related but few studies have systematically analyzed how interactions among them affect system-level dynamics, fragility, uncertainty, or risk. This interdisciplinary research project will investigate how regional coupled natural and human systems respond to changes in climate, economic, and policy conditions that operate over larger geographic and temporal scales. The investigators will explore these concepts in an agriculturally based Midwestern watershed (the Iowa/Cedar River Watershed in Iowa) within the context of sustainability, resilience, and adaptability. They will define sustainability using Elkington's Triple Bottom Line concept (people, planet, profit) in which social and environmental values are added to the traditional economic measures of success. In the context this particular study, they will consider surface and groundwater resources that will not be polluted or withdrawn so that intended agricultural uses can no longer be supported and agriculture practices that do not deplete the soil or groundwater, and, at a minimum, supports existing levels of economic activity. The investigators will evaluate the multidimensional tradeoffs that exist among traditional measures of optimality, such as maximization of environmental quality and economic return, and measures of resilience, adaptability, and sustainability. To conduct this analysis, they will develop models that simulate how landscapes change in response to changes in natural and socioeconomic factors. Land-use decision making will be modeled to simulate how humans respond to changing conditions, and these models will be linked to models of surface and ground water quality to quantify environmental impact. Evolutionary computation techniques will be developed to produce production possibility frontiers that quantify tradeoffs among competing objectives. Stakeholder preferences for various objectives will be solicited through focus groups, and surveys and cyberinfrastructure will be developed to support the significant computational needs of this study.While landscapes are in a continual state of change, the national and global-scale factors that currently affect landscapes in the Midwest are without precedent. The generation of precise predictions regarding future conditions is an unrealistic goal under such conditions. This project therefore will evaluate a suite of plausible scenarios to identify those strategies that are most likely to result in sustainable agricultural landscapes. The investigators hypothesize that sustainable outcomes are produced by systems that have an ability to adapt to changing and uncertain conditions and that possess the resiliency needed to respond to unexpected and significant perturbations. Natural (e.g., climate) and human (e.g., policy and economic) processes can constrain or enhance the ability of systems to adapt and respond to change and uncertainty. It is important to promote processes that enhance sustainability, and avoid those that produce constraints. This project will advance the theory and practice of sustainability science by constructing models that link adaptability, resilience, and sustainability to more traditional measures of economic and environmental optimality. From a more practical perspective, the project will have an impact on policy and land management in the Midwest by providing better data and analytical tools to decision makers as they address complex problems and refine policy. The project also will provide information and examples that help the general public understand the imperative of sustainability in the context of changing climatic and economic conditions. Because of the uncertainty associated with the magnitude and spatiotemporal pattern of regional, national, and international changes, research designed to bound uncertainty, to document plausible natural and socioeconomic outcomes, and to analyze the impact of alternative adaptation strategies can be especially timely and important. This project is supported by the NSF Dynamics of Coupled Natural and Human Systems (CNH) Program.