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科普干扰的能力。 适应能力是指一个系统在受到超出其恢复能力的干扰时改变基本结构或功能的能力。 可持续性，弹性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层面的动态，脆弱性，不确定性或风险。 这个跨学科的研究项目将研究区域耦合的自然和人类系统如何应对在更大的地理和时间尺度上运行的气候，经济和政策条件的变化。 调查人员将探讨这些概念，在农业为基础的中西部流域（爱荷华州/雪松河流域在爱荷华州）的可持续性，弹性和适应性的背景下。 他们将使用Elkington的三重底线概念（人，地球，利润）来定义可持续性，其中社会和环境价值被添加到传统的成功经济措施中。 在这一特定研究的范围内，他们将考虑不会被污染或抽取的地表水和地下水资源，从而不再支持预定的农业用途，以及不会耗尽土壤或地下水，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性措施之间存在的多维权衡，例如环境质量和经济回报的最大化，以及弹性，适应性和可持续性的措施。为了进行这种分析，他们将开发模型，模拟景观如何响应自然和社会经济因素的变化而变化。 将对土地使用决策进行建模，以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相联系，以量化环境影响。 将开发进化计算技术，以产生生产可能性边界，量化竞争目标之间的权衡。 利益相关者的偏好将通过焦点小组征求各种目标，调查和网络基础设施将开发，以支持本study.While景观的显着计算需求是在一个持续的变化状态，目前影响景观的国家和全球尺度的因素在中西部是没有先例的。 在这样的条件下，生成关于未来条件的精确预测是不现实的目标。 因此，本项目将评估一套合理的方案，以确定最有可能导致可持续农业景观的战略。 研究人员假设，可持续的结果是由系统产生的，这些系统具有适应不断变化和不确定条件的能力，并且具有应对意外和重大扰动所需的弹性。 自然（例如，气候）和人类（例如，政策和经济）过程可能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，要促进加强可持续性的进程，避免产生制约因素的进程。该项目将通过构建将适应性，弹性和可持续性与经济和环境最佳性的传统措施联系起来的模型来推进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，为决策者解决复杂问题和完善政策提供更好的数据和分析工具。 该项目还将提供信息和实例，帮助公众了解在不断变化的气候和经济条件下可持续发展的必要性。 由于与区域、国家和国际变化的幅度和时空模式相关的不确定性，旨在约束不确定性、记录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。 该项目由NSF耦合自然和人类系统动力学（CNH）计划支持。

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In the context this particular study, they will consider surface and groundwater resources that will not be polluted or withdrawn so that intended agricultural uses can no longer be supported and agriculture practices that do not deplete the soil or groundwater, and, at a minimum,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.