CNH: Collaborative Research: Explaining Socioecological Resilience Following Collapse: Forest Recovery in Appalachian Ohio

许多人都知道导致森林丧失的过程，这种理解必须辅之以关于影响森林恢复和可持续性的社会生态因素的新知识。这一知识对于预测第二代和第三代森林可能出现的地点和时间以及了解维护它们所需的条件至关重要。此外，迫切需要这样的知识来为全球气候模型、气候变化缓解情景和一系列其他环境问题提供信息。这一跨学科研究项目将侧重于产生特定森林形式(包括森林面积、物种组成和土地覆盖格局)和功能(包括森林的木材、娱乐、隐私和野生动物栖息地等效益)的人类和生态联系。研究人员将审查这些联系和由此产生的森林在多大程度上导致社会生态系统发生不可逆转的变化。他们将把注意力集中在俄亥俄州的阿巴拉契亚地区，该地区的森林已经恢复，有足够的时间深度来研究产生这些森林的潜在社会生态过程。作为19世纪和20世纪初遭到破坏的前采掘外围地区，其广袤的森林在上个世纪以令人惊讶的方式出现。项目目标是：(1)比较定居前森林和当代森林的森林构成；(2)描述恢复森林的社会和生态形式和功能；(3)解释森林随着时间的推移而出现的原因；(4)预测这些社会生态系统今后将如何发挥作用。所使用的方法包括基于主体的土地利用决策和实施模型，以及模拟森林演替和更新的景观干扰和演替模型。为了给模型提供经验数据，研究人员将收集关于森林结构和组成的现场数据，生成遥感图像的时间序列分类，并利用档案和现场数据调查政治、经济、基础设施和文化动态。该项目将对理解动态耦合社会生态系统的理论和方法做出重要贡献。该项目将通过侧重于森林复原力，从而将森林恢复视为复杂社会生态系统的紧急性质，从而促进对森林过渡的基本理解。该项目将关注大规模干扰前后生态系统属性的差异，表明人类和生态系统共同创造了意想不到的生态环境。该项目将展示森林形式和功能应对当地力量和远距离社会和生态冲击的具体方式。在方法上，该项目将通过使用创新的衡量标准来纳入社会不平等和权力动态，并将社会模拟与景观水平的森林生长模型结合起来，从而推动基于代理人的建模科学。作为俄亥俄州两所大学和美国林务局的合作项目，该项目将提供有关俄亥俄州阿巴拉契亚地区紧迫的社会和环境问题的实用信息，包括农村贫困、生态变化以及公共和私人森林的管理。这一可移植框架的全球应用包括加强学者和政策制定者理解、规划和帮助促进生态恢复的方式，特别是通过提请注意社会不平等在形成社会生态复原力方面的作用。这项研究的发现也可以为气候建模和缓解提供参考。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。

Much is known about the processes leading to forest loss, that understanding must be complemented with new knowledge regarding the socioecological factors that influence forest recovery and sustainability. This knowledge is critical for predicting where and when second- and third-generation forests might emerge and for understanding the conditions necessary to maintain them. Furthermore, such knowledge is urgently required to inform global climate models, climate change mitigation scenarios, and a suite of other environmental issues. This interdisciplinary research project will focus on the human and ecological linkages that give rise to specific forest forms (including forest extent, species composition, and land-cover patterns) and functions (including benefits of the forest like timber, recreation, privacy, and wildlife habitat). The investigators will examine the extent to which those linkages and the forests emergent from them lead to irreversible changes in socioecological systems. They will focus their attention on Appalachian Ohio, an area whose which forests have returned and where there is sufficient time depth to examine the underlying socioecological processes that give rise to them. A former extractive periphery devastated in the 19th and early 20th centuries, its extensive forests have emerged in surprising ways over the last century. Project goals are (1) to compare forest composition between pre-settlement forests and contemporary forests; (2) to describe the social and ecological form and function of recovered forests; (3) to explain the emergence of the forest over time; and (4) to predict how these socioecological systems will function in the future. The methods to be used include an agent-based model representing land-use decision-making and implementation coupled with the landscape disturbance and succession model, which simulates forest succession and regrowth. To inform the models with empirical data, the researchers will collect field data on forest structure and composition, generate time-series classifications of remotely sensed images, and investigate political, economic, infrastructural, and cultural dynamics using archival and field-derived data.This project will make important contributions to theory and methods for understanding dynamically coupled socioecological systems. The project will advance basic understanding of forest transitions by focusing on forest resilience, thus treating forest recovery as an emergent property of complex socioecological systems. The project will focus attention on differences in ecosystem attributes before and long after massive disturbance, showing that humans and ecosystems have together created unexpected ecologies. The project will demonstrate specific ways that forest form and function respond to local forces and distant shocks that are both social and ecological. Methodologically, the project will advance agent-based modeling science by using innovative metrics to incorporate social inequality and power dynamics and by coupling social simulation with landscape-level forest growth models. As a collaborative project between two Ohio-based universities and the U.S. Forest Service, the project will provide practical information regarding pressing social and environmental issues in Appalachian Ohio, including rural poverty, ecological change, and management of public and private forests. Global applications of this portable framework include enhancing the ways that scholars and policy makers understand, plan for, and help to foster ecological recovery, in particular by drawing attention to the role of social inequalities in shaping socioecological resilience. The findings of this research can also inform climate modeling and mitigation. This project is supported by the NSF Dynamics of Coupled Natural and Human Systems (CNH) Program.