CNH: Collaborative Research: Spatial Land-Use Change and Ecological Effects (SLUCE): Interactions of Exurban Land Management and Carbon Dynamics

CNH：合作研究：空间土地利用变化和生态效应（SLUCE）：远郊土地管理与碳动态的相互作用

• 批准号: 0814542
• 负责人: DANIEL BROWN
• 金额: $ 116.61万
• 依托单位: Regents of the University of Michigan - Ann Arbor
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2008
• 资助国家: 美国
• 起止时间: 2008-09-01 至 2014-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0814542&HistoricalAwards=false
• 关键词: CNH; Collaborative; Research; Spatial; Land

Exurban residential development is widespread, constituting one of the major forms of land-use and land-cover changes in the Eastern US and elsewhere. This sprawl has large impacts on natural and rural landscapes, ecosystem services, and quality of life for millions of people. This project investigates the processes linking dynamics of land-atmosphere carbon budgets in exurban residential areas, preferences for land-cover types and patterns on these lands, and land-management activities of residents and developers. The goal of the project is to obtain a clearer understanding of the relationships between carbon dynamics, land-management activities, and market and non-market values of land-uses and land-covers ? focusing on how carbon dynamics might respond in a non-linear fashion to various management and policy options for land-cover management. Building on the extensive data resources developed under a precursor project, the researchers will use dynamic agent-based models (including a new land-market sub model) to examine a range of exurban land-cover patterns that might be expected to result from market and policy drivers These models will be linked to homeowner preferences and landscape management behaviors from surveys. The outputs of the models will be coupled with a spatially explicit model of biogeochemistry, with inputs derived from remote sensing and field-based sampling within Southeastern Michigan. The researchers will explore the relationship between decision processes by various actors and the resulting changes in biogeochemical processes. We will look for the existence of ecologically significant thresholds (e.g., large, nonlinear land-atmosphere carbon exchange in response to small changes in policy, preferences or behaviors) that are revealed in the coupled system. The study will identify both modeled micro-level dynamics and macro-level patterns in space and time, building on data and model resources developed from previous projects, while creating a complementary new dataset to support modeling of land-market interactions that includes land transactions, biogeochemical processes, cultural preferences and management practices affecting land covers, The complex feedbacks explored in this project, that both drive and result from exurban sprawl, will provide new insights into how policy can be used to guide and manage this landscape change. Coupled computer models will be used to evaluate policy scenarios that may be spatially-targeted (e.g., zoning) or aspatial (e.g., carbon credits) and are designed to affect carbon dynamics through mechanisms built on an understanding of the incentives created by markets and preferences and behaviors of residents, developers, and local governments. Field and modeling work on soil and vegetation carbon dynamics will provide much needed insights into the effects of exurban development on carbon storage, which, given the growth of exurban development, has important implications for the atmospheric carbon budget. The project strengthens scientific capacity and integration by bringing together scientists from a wide range of fields including landscape architecture, ecosystem science, economics, geographic information science, and complex systems science. The project will produce results that improve our ability to model (a) carbon cycling in the heterogeneous landscapes that humans inhabit, (b) the economic incentives inherent in our management exurban landscapes, and (c) the linkages between peoples? preferences and their behaviors and ecological landscape function. Models developed for the project will be used to generate both formal and informal educational materials for both graduate and undergraduate instruction on environmental science, policy, and design, in order to improve student understanding of how complex coupled human-environment dynamics can complicate decision making about ecosystem services, and how spatial and dynamic modeling can improve our understanding of alternative options in such settings.

城郊住宅开发非常普遍，构成了美国东部和其他地区土地利用和土地覆盖变化的主要形式之一。这种蔓延对自然和农村景观、生态系统服务以及数百万人的生活质量产生了巨大影响。该项目调查了城郊居民区土地-大气碳收支的动态、对这些土地上土地覆盖类型和模式的偏好以及居民和开发商的土地管理活动之间的联系。该项目的目标是更清楚地了解碳动态、土地管理活动以及土地利用和土地覆盖的市场和非市场价值之间的关系。侧重于碳动态如何以非线性方式对土地复盖管理的各种管理和政策选择作出反应。在前身项目开发的大量数据资源的基础上，研究人员将使用基于动态代理的模型(包括新的土地市场子模型)来检查一系列可能由市场和政策驱动因素导致的郊区土地覆盖模式。这些模型将与调查中的房主偏好和景观管理行为联系起来。模型的输出将与一个空间上明确的生物地球化学模型相结合，输入来自密歇根州东南部的遥感和野外采样。研究人员将探索不同行为者的决策过程与由此导致的生物地球化学过程变化之间的关系。我们将寻找在耦合系统中揭示的具有生态意义的阈值的存在(例如，响应政策、偏好或行为的微小变化的大的、非线性的陆地-大气碳交换)。这项研究将在以前项目开发的数据和模型资源的基础上，确定空间和时间上的建模微观一级动态和宏观一级模式，同时创建一个补充的新数据集，以支持对土地-市场相互作用的建模，其中包括土地交易、生物地球化学过程、文化偏好和影响土地覆盖的管理做法，该项目探索的复杂反馈，既是城郊蔓延的驱动因素，也是其结果，将为如何利用政策来指导和管理这种地貌变化提供新的见解。耦合的计算机模型将用于评估政策情景，这些政策情景可能是空间目标(例如，分区)或空间(例如，碳信用)，并被设计为通过建立在理解市场以及居民、开发商和地方政府的偏好和行为所创造的激励机制的基础上影响碳动态的机制。关于土壤和植被碳动态的实地工作和建模工作将对城郊发展对碳储量的影响提供亟需的见解，鉴于城郊发展的增长，这对大气碳收支具有重要影响。该项目通过汇集来自风景园林、生态系统科学、经济学、地理信息科学和复杂系统科学等广泛领域的科学家来加强科学能力和集成。该项目将产生的成果将提高我们模拟以下方面的能力：(A)人类居住的不同景观中的碳循环；(B)我们管理郊区景观所固有的经济激励；以及(C)人与人之间的联系？偏好及其行为与生态景观功能。为该项目开发的模型将用于为环境科学、政策和设计方面的研究生和本科生教学生成正式和非正式的教育材料，以提高学生对复杂的耦合人-环境动力学如何使关于生态系统服务的决策复杂化的理解，以及空间和动态建模如何提高我们对此类环境下的替代选择的理解。