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

郊区住宅开发很普遍，是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。 本项目研究了远郊居民区土地-大气碳收支动态、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过程。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覆盖管理的各种管理和政策选择作出反应。 在一个前体项目下开发的广泛数据资源的基础上，研究人员将使用基于动态代理的模型（包括一个新的土地市场子模型）来研究一系列郊区土地覆盖模式，这些模式可能是由市场和政策驱动因素导致的。该模型的输出将与一个空间上明确的地球化学模型相结合，输入来自密歇根州东南部的遥感和实地采样。研究人员将探索各种行为者的决策过程与地球化学过程中产生的变化之间的关系。我们将寻找存在的生态上重要的阈值（例如，大的、非线性的陆地-大气碳交换，对政策、偏好或行为的微小变化作出反应）。该研究将在之前项目开发的数据和模型资源的基础上，识别建模的微观动态和宏观空间和时间模式，同时创建一个补充的新数据集来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、影响土地覆盖的文化偏好和管理实践，该项目中探索的复杂反馈，这两个驱动力和结果从郊区蔓延，将提供新的见解，如何政策可以用来指导和管理这种景观变化。 耦合的计算机模型将用于评估可能以空间为目标的政策情景（例如，分区）或无空间（例如，碳信用额），并旨在通过建立在对市场和居民，开发商和地方政府的偏好和行为所产生的激励措施的理解基础上的机制来影响碳动态。 土壤和植被碳动力学的实地和建模工作将提供急需的见解郊区发展对碳储存的影响，其中，考虑到郊区发展的增长，对大气碳收支有重要影响。该项目通过汇集来自景观设计、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整合。 该项目将产生的结果，提高我们的能力，模型（a）在人类居住的异质景观碳循环，（B）在我们的管理郊区景观固有的经济激励，（c）人与人之间的联系？偏好及其行为和生态景观功能。 为该项目开发的模型将用于为研究生和本科生的环境科学，政策和设计教学生成正式和非正式的教育材料，以提高学生对复杂的人类-环境耦合动态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此类环境中替代方案的理解。

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.