CNH: Co-Evolution of Upstream Human Behavior and Downstream Ecosystem Services in a Changing Climate

上游农业生产的非点源养分和沉积物径流正在损害全球沿海生态系统服务，包括五大湖、切萨皮克湾、墨西哥湾北部和其他具有经济、娱乐和文化重要性的地区。随着持续的气候变化，这种退化预计将加剧，因为更多的暴雨向下游输送更多的营养物质和沉积物，其影响包括水的透明度降低，有害藻类大量繁殖，以及高价值鱼类种群的损失。为了解决这些问题，已经确定了许多可以减少泥沙和养分径流的农业管理措施。然而，鼓励采用有效农业管理做法的政策的有效设计受到关于人类对生态系统条件的行为反应的重要知识差距的限制。这一跨学科研究项目将以茂名河流域和西部伊利湖为模型生态系统，量化上游人类行为与下游生态系统服务之间的协同进化。研究人员将模拟公众态度如何与下游生态系统条件共同演变，并塑造对影响农业管理实践的政策的支持，进而影响农民对这些政策和公众态度的反应。他们还将把研究区域的生物物理模型与公共政策和农民决策的行为模型结合起来，以预测未来可能出现的情景下公共政策、农民行为和下游生态系统之间的协同进化。这种上游人类行为与下游生态系统服务双向耦合的模型将解决上游公众态度、政策和农民行为的变化是否会抵消气候变化对下游生态系统服务的预期负面影响的问题。本项目将开发一个人-自然耦合系统模型，重点关注上游人类行为响应和下游生态系统变化之间的动态反馈。它将评估农民行为反应如何调节具体政策和不断变化的生态条件之间的相互作用，并将加强对州和地方政策制定者以可能抵消气候变化预期负面影响的方式影响农民行为和下游生态系统条件的能力的理解。虽然大量研究集中于上游养分输入和通量对流域功能和下游生态系统服务的单向影响，但影响公众、政策和农民对生态变化反应的关键反向联系却受到的关注要少得多。综合模型将为评估人类态度和行为与下游生态条件之间的动态联系提供理论基础，并将改进对行为活动和气候变化对下游生态系统服务可获得性和质量的动态影响的预测。这种预测性知识与社会关切有关，因为它将提高沿海流域决策者的能力，以适应管理，以应对气候变化的负面影响。该项目还将为本科生、研究生和博士后研究人员提供教育、培训和指导。调查人员将直接与茂密分水岭农村学区的6-12年级教师合作，开发分水岭科学课程，他们将通过与俄亥俄州海洋赠款学院计划合作，开发和分发针对决策者和普通公众的材料，更广泛地传播结果。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。

Non-point source nutrient and sediment runoff from upstream agricultural production is impairing coastal ecosystem services across the globe, including the Great Lakes, Chesapeake Bay, the northern Gulf of Mexico, and other regions of economic, recreational, and cultural importance. This degradation is projected to worsen with continued climate change, as more intense rains transport more nutrients and sediments downstream with impacts that include reduced water clarity, increases in harmful algal blooms, and a loss of high-valued fish stocks. To address these problems, many agricultural management practices have been identified that can reduce sediment and nutrient runoff. Effective design of policies to encourage adoption of effective agricultural management practices is limited by an important knowledge gap concerning human behavioral responses to ecosystem conditions, however. This interdisciplinary research project will use the Maumee River watershed and western Lake Erie as a model ecosystem to quantify the co-evolution between upstream human behavior and downstream ecosystem services. The investigators will model how public attitudes co-evolve with downstream ecosystem conditions and shape support for policies that impact agricultural management practices, and in turn, how farmers respond to these policies and public attitudes. They also will integrate biophysical models of the study region with behavioral models of public policy and farmer decision making to predict the co-evolution among public policies, farmer behavior, and downstream ecosystems under possible future scenarios. This modeling of the two-way coupling between upstream human behavior and downstream ecosystem services will address the question of whether changes in upstream public attitudes, policies, and farmer behavior will offset anticipated negative impacts of climate change on downstream ecosystem services.This project will develop a coupled human-natural system model that focuses on the dynamic feedback between upstream human behavioral responses and downstream ecosystem change. It will provide an assessment of how farmer behavioral responses mediate the interactions between specific policies and changing ecological conditions, and it will enhance understanding regarding the capacity of state and local policy makers to influence farmer behavior and downstream ecosystem conditions in ways that may counteract the expected negative impacts of climate change. While substantial research has focused on the one-way impacts of upstream nutrient inputs and fluxes on watershed functioning and downstream ecosystem services, key reverse linkages that shape public, policy, and farmer responses to ecological changes have received much less attention. The integrated model will provide the theoretical foundation for assessing the dynamic linkages between human attitudes and behaviors and downstream ecological conditions and will improve predictions of the dynamic effect of changing behavioral activities and climate on the availability and quality of downstream ecosystem services. This predictive knowledge is relevant to societal concerns because it will improve the ability of decision makers in coastal watersheds to manage adaptively to address negative impacts of climate change. The project also will provide education, training, and mentoring for undergraduate and graduate students and post-doctoral researchers. The investigators will work directly with Grade 6-12 teachers within rural school districts in the Maumee watershed to develop watershed science curriculum, and they will disseminate results more broadly by working with the Ohio Sea Grant College Program to develop and distribute materials targeted at decision makers and the general public. This project is supported by the NSF Dynamics of Coupled Natural and Human Systems (CNH) Program.