Doctoral Dissertation Research: Simulating Social and Land-Use Adaptations to Climate Change on Mount Kenya

世界各地的社会都将受到未来气候变化的挑战。适应能力将取决于集体行动克服这些挑战的能力。生计与生态系统服务直接相关的社区，例如那些依靠农业维持生计的社区，被认为是最脆弱的。由于获得农业化学品投入和现代技术的机会有限，这些社区将需要依靠集体行动来适应气候变化。本博士论文研究项目的重点是研究土地利用多样性、社会资本和制度设置在适应肯尼亚肯尼亚山东坡气候变化中的相对贡献。这个项目是围绕着一个普遍的假设来组织的，即在气候变化的背景下，当地社会资本的丰富程度和土地利用多样性水平决定了适应的第一阶段。在随后的阶段，通过制定新的土地使用规则和传播技术创新的强有力机构来维持对气候变化的长期适应。本研究结合定性、定量、空间明确的方法和计算机模型来分析对气候变化的适应。为了验证这一假设，博士候选人将把定性研究方法（如角色扮演游戏、调查和访谈）与定量工具（如基于智能体和神经网络模型）结合起来。基于主体的模型和本研究的其他结果将用于检验各种适应情景的鲁棒性。国际科学界把发展中国家适应气候变化作为一项重大的人类和科学挑战。这项工作将提高对发展中国家农村农业生态系统适应气候变化机制的认识。这个项目也将有利于社会生态学研究的方法论、理论和实践方面。首先，从方法论的角度来看，该研究将构成少数深入的案例研究之一，使用定性的、空间明确的和基于经验的基于主体的建模技术来分析对气候变化的适应。其次，从理论的角度来看，研究适应气候变化将加强地理学、生态学、政治学和社会学中提出的社会生态框架。最后，了解土地利用在气候变化适应中的作用可能有助于发展中国家应对这些复杂问题的自然资源管理者和决策者。作为博士论文研究改进奖，该奖项还将提供支持，使有前途的学生建立一个强大的独立研究生涯。该奖项由美国国家科学基金会地理与区域科学项目和美国国家科学基金会国际科学与工程办公室共同资助。

Societies around the world will be challenged by future climate change. Adaptive capacity will be a function of the ability to act collectively at overcoming those challenges. Communities with livelihoods tied directly to ecosystem services, such as those that rely on agriculture for sustenance, are thought to be most vulnerable. With limited access to agricultural chemical inputs and modern technologies, those communities will need to rely on collective action to adapt to climate change. The focus of this doctoral dissertation research project is to examine the relative contribution of land-use diversity, social capital, and institutional settings in adaptation to climate change along the Eastern slopes of Mount Kenya, Kenya. This project is organized around the general hypothesis that asserts that in a context of climate change, the richness of local social capital and level of land-use diversity determines the first phase of adaptation. In the subsequent phase, long-term adaptations to climate change are sustained by robust institutions developing new land-use rules and diffusing technological innovations. This research combines qualitative, quantitative, spatially explicit methods with computer models to analyze adaptations to climate change. To test this hypothesis, the doctoral candidate will couple qualitative research methods, such as role-playing games, surveys, and interviews, with quantitative tools, such as agent-based and neural network models. The agent-based model and other results of this research will be used to test the robustness of various adaptation scenarios.Adaptation to climate change in developing countries has been targeted by the international scientific community as a major human and scientific challenge. This work will improve the understanding of the mechanisms of adaptation to climate change in rural agro-ecosystems of developing countries. This project will also benefit methodological, theoretical, and practical aspects of socioecological research. First, from a methodological standpoint, the research will constitute one of the few in-depth case studies that analyze adaptations to climate change using qualitative, spatially explicit, and empirically grounded agent-based modeling techniques. Second, from a theoretical point of view, examining adaptation to climate change will enhance socioecological frameworks proposed in geography, ecology, political science, and sociology. Finally, understanding the role of land-use in climate change adaptation is likely to aid natural resource managers and decision makers in developing countries that grapple with these complex issues. As a Doctoral Dissertation Research Improvement award, this award also will provide support to enable a promising student to establish a strong independent research career. This award is jointly supported by the NSF Geography and Regional Science Program and the NSF Office of International Science and Engineering.