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

在美国东部和其他地方，郊区住宅开发是土地利用和土地覆盖变化的主要形式之一。这种扩张对自然和乡村景观、生态系统服务以及数百万人的生活质量产生了巨大影响。本项目研究了城郊住宅区的土地-大气碳预算动态、对这些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过程。该项目的目标是更清楚地了解碳动态、土地管理活动、土地用途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覆盖管理的各种管理和政策选择作出反应。在前驱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主体的模型（包括一个新的土地市场子模型）来研究一系列可能由市场和政策驱动因素导致的城郊土地覆盖模式。这些模型将与房主偏好和景观管理行为联系起来。模型的输出将与空间上明确的生物地球化学模型相结合，输入来自密歇根东南部的遥感和实地抽样。研究人员将探讨各种行为者的决策过程与由此产生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（例如，响应政策、偏好或行为的微小变化的大型非线性陆地-大气碳交换）的存在。该研究将在以前项目开发的数据和模型资源的基础上，确定空间和时间上微观层面的动态和宏观层面的模式，同时创建一个互补的新数据集，以支持土地市场相互作用的建模，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实践。将为如何利用政策来指导和管理这种格局变化提供新的见解。耦合计算机模型将用于评估可能有空间针对性（如分区）或无空间性（如碳信用额）的政策情景，这些政策情景旨在通过建立在对市场产生的激励以及居民、开发商和地方政府的偏好和行为的理解基础上的机制来影响碳动态。土壤和植被碳动态的实地和建模工作将为了解城郊发展对碳储量的影响提供急需的见解，鉴于城郊发展的增长，这对大气碳预算具有重要意义。该项目通过汇集来自景观建筑学、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，加强了科学能力和整合。该项目将产生的结果将提高我们的建模能力：(a)人类居住的异质景观中的碳循环，(b)我们管理郊区景观中固有的经济激励，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、政策和设计的研究生和本科生提供正式和非正式的教育材料，以提高学生对复杂的人-环境耦合动力学如何使生态系统服务决策复杂化的理解，以及空间和动态建模如何提高我们对这种环境下备选方案的理解。

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.