Knowledge Co-Production for Collaborative Environmental Management

该奖项全部或部分根据2021年美国救援计划法案（公法117-2）资助。该奖项是作为NSF的社会，行为和经济科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，工业或私营部门和政府的科学事业准备有前途的早期职业博士级科学家。SPRF的奖励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。NSF致力于促进来自科学界各部门的科学家，包括来自代表性不足的群体的科学家参与其研究计划和活动;博士后期间被认为是实现这一目标的专业发展的重要水平。每个博士后研究员必须解决推进各自学科领域的重要科学问题。在康奈尔大学Karim-Aly Kassam博士的赞助下，该博士后奖学金支持早期职业科学家调查知识共同生产过程以及它们如何实现或限制社会学习，目的是为合作环境管理的更精确的理论做出贡献。随着全球环境变化的不断加速和加剧，科学和社会正在转向协作环境管理，以促进向可持续发展的过渡。知识共同生产等协作办法将社会不同部门的各种行为者聚集在一起，共同努力解决社会生态问题。知识共同生产过程已被证明可以促进社会学习，培养适应能力，并通过建立信任和促进管理团队的不同成员之间的沟通来支持集体行动成果。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全面理解。该案例研究位于一个保护区内及其周围，该保护区正在经历大坝建设带来的快速，大规模的变化。利用复杂的遥感分析和人种学调查相结合，这项工作将研究（1）不同群体如何看待和评价保护区（例如，政府、科学、原住民团体），（2）出现了哪些预期战略来应对那里发生的变化，以及（3）参与者在整个知识共同生产过程中如何体验社会学习。 这项研究将产生新的理解不同的社会文化群体如何概念化和重视他们的环境，这可以帮助我们了解这个系统和世界各地的环境变化的关键人为驱动因素。其次，我们将比较和对比当地的变化叙述与来自遥感分析的测量，揭示互补的理解以及科学和土著知识之间的关键差距。第三，我们将采用认知建模练习与参与式情景规划，以共同生成预测和应对未来环境变化的策略-从而改进这些方法用于其他系统。最后，这个项目将提高我们的能力，概念化和衡量社会学习，方法是迫切需要的。与社区成员的研讨会，一个开放获取的跨学科科学教育案例研究，一个项目报告，以及至少两个同行评审的期刊文章将有助于实现这些目标。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

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.