Knowledge Co-Production for Collaborative Environmental Management

该奖项的全部或部分资金来自《2021年美国救援计划法案》(公法117-2)。该奖项是作为NSF社会、行为和经济学博士后研究奖学金(SPRF)计划的一部分提供的。SPRF计划的目标是为学术界、工业界或私营部门和政府的科学职业生涯培养有前途的、早期职业博士水平的科学家。SPRF奖项包括在知名科学家的赞助下进行两年的培训，并鼓励博士后研究员进行独立研究。国家科学基金会致力于促进科学界所有阶层的科学家参与其研究方案和活动，包括那些来自代表性不足的群体的科学家；博士后阶段被认为是实现这一目标的专业发展的一个重要水平。每个博士后研究员都必须解决推动各自学科领域向前发展的重要科学问题。在康奈尔大学卡里姆-阿里·卡萨姆博士的赞助下，这一博士后奖学金奖项支持一名早期职业科学家调查知识联合生产过程以及这些过程如何促进或限制社会学习，目的是为协作环境管理的更多经验主义理论做出贡献。随着全球环境变化继续加速和加剧，科学和社会正在转向协作性环境管理，以促进向可持续发展的过渡。知识联合生产等合作办法将来自社会不同部门的不同行为者聚集在一起，为解决社会生态问题而努力。知识联合生产过程已被证明通过在管理团队的不同成员之间建立信任和促进沟通，促进社会学习，培养适应能力，并支持集体行动成果。本研究的目的是整合当地、土著和科学知识，共同创造对过去和未来环境变化的整体理解。案例研究位于一个保护区内和周围，该保护区正在经历因修建大坝而发生的快速、大规模的变化。这项工作将结合复杂的遥感分析和人种学调查，审查(1)不同群体(例如，政府、科学、土著群体)对保护区的看法和评价，(2)为应对那里发生的变化而出现的预期战略，以及(3)参与者在整个知识联合生产过程中如何体验社会学习。这项研究将对不同的社会文化群体如何对其环境进行概念化和评价产生新的理解，这可以帮助我们理解该系统和世界各地环境变化的关键人为驱动因素。第二，我们将把当地对变化的描述与遥感分析得出的测量结果进行比较和对比，揭示相互理解的领域以及科学知识和土著知识之间的严重差距。第三，我们将使用认知建模练习与参与式情景规划相结合，共同生成预测和应对未来环境变化的策略-从而改进这些方法，以便在其他系统中使用。最后，这个项目将提高我们对社会学习进行概念化和测量的能力，而这方面的方法是迫切需要的。与社区成员一起举办的研讨会、关于跨学科科学的开放获取的教育案例研究、一份项目报告以及至少两篇同行评议的期刊文章将有助于实现这些目标。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). This award was provided as part of NSF's Social, Behavioral and Economic Sciences Postdoctoral Research Fellowships (SPRF) program. The goal of the SPRF program is to prepare promising, early career doctoral-level scientists for scientific careers in academia, industry or private sector, and government. SPRF awards involve two years of training under the sponsorship of established scientists and encourage Postdoctoral Fellows to perform independent research. NSF seeks to promote the participation of scientists from all segments of the scientific community, including those from underrepresented groups, in its research programs and activities; the postdoctoral period is considered to be an important level of professional development in attaining this goal. Each Postdoctoral Fellow must address important scientific questions that advance their respective disciplinary fields. Under the sponsorship of Dr. Karim-Aly Kassam at Cornell University, this postdoctoral fellowship award supports an early career scientist investigating knowledge co-production processes and how they enable or constrain social learning, with the aim of contributing to more empirically-informed theories of collaborative environmental stewardship. As global environmental change continues to accelerate and intensify, science and society are turning to collaborative environmental management to facilitate transitions to sustainability. Collaborative approaches such as knowledge co-production bring together diverse actors from different sectors of society to work towards solutions for social-ecological problems. Knowledge co-production processes have been shown to facilitate social learning, foster adaptive capacity, and support collective action outcomes by building trust and enabling communication among the diverse members of a management team.The purpose of this research is to integrate local, Indigenous, and scientific knowledge to co-create a holistic understanding of past and future environmental change. The case study is located in and around a protected area that is experiencing rapid, large scale change from the construction of a dam. Using a combination of sophisticated remote sensing analyses and ethnographic inquiry, this work will examine (1) how different groups think about and value the protected area (e.g., governmental, scientific, Indigenous groups), (2) what anticipatory strategies emerge for addressing the changes occurring there, and (3) how participants experience social learning throughout the knowledge co-production process. This research will generate new understanding of how different socio-cultural groups conceptualize and value their environment, which can help us understand critical anthropogenic drivers of environmental change in this system and around the world. Second, we will compare and contrast local narratives of change with measurements derived from remote sensing analyses, revealing areas of complementary understanding as well as critical gaps between scientific and Indigenous knowledge. Third, we will employ cognitive modeling exercises in conjunction with participatory scenario planning to co-generate strategies for anticipating and responding to future environmental change – thus refining these methods for use in other systems. Finally, this project will advance our ability to conceptualize and measure social learning, for which methods are urgently needed. Workshops with community members, an open-access educational case study on transdisciplinary science, a project report, and at least two peer-reviewed journal articles will contribute to achieving these objectives.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.