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

世界各地的社会将受到未来气候变化的挑战。 适应能力将取决于采取集体行动克服这些挑战的能力。 生计直接与生态系统服务相关的社区，例如那些依靠农业维持生计的社区，被认为是最脆弱的社区。 由于获得农业化学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。 这个博士论文研究项目的重点是研究土地利用的多样性，社会资本和机构设置在适应气候变化沿着肯尼亚山，肯尼亚东部斜坡的相对贡献。 这个项目是围绕一个一般性假设组织的，该假设认为，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的水平决定了适应的第一阶段。 在随后的阶段，对气候变化的长期适应是由制定新的土地使用规则和推广技术创新的强有力的机构来维持的。 该研究结合定性，定量，空间明确的方法与计算机模型来分析适应气候变化。 为了验证这一假设，博士生将结合定性研究方法，如角色扮演游戏，调查和访谈，与定量工具，如基于代理和神经网络模型。 基于主体的模型和这项研究的其他成果将用于测试各种适应情景的稳健性，发展中国家适应气候变化一直被国际科学界视为人类和科学的一项重大挑战。 这项工作将增进对发展中国家农村农业生态系统适应气候变化机制的了解。 该项目也将有利于社会生态学研究的方法，理论和实践方面。 首先，从方法论的角度来看，这项研究将构成为数不多的深入的案例研究，分析适应气候变化使用定性，空间明确，并以经验为基础的代理建模技术之一。 其次，从理论的角度来看，研究气候变化的适应性将加强地理学，生态学，政治学和社会学中提出的社会生态框架。 最后，了解土地利用在适应气候变化方面的作用，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的研究生涯。 该奖项由NSF地理和区域科学计划以及NSF国际科学与工程办公室共同支持。

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.