CNH: Social-Ecological Complexity and Adaptation in Marine Systems

CNH：海洋系统的社会生态复杂性和适应

• 批准号: 1211972
• 负责人: Simon Levin
• 金额: $ 149.89万
• 依托单位: Princeton University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-09-01 至 2018-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1211972&HistoricalAwards=false
• 关键词: CNH; Social; Ecological; Complexity; Adaptation

The oceans are one of the most dynamic environments on Earth, presenting a profound challenge for understanding the complex social, ecological, and physical interactions that occur within them. Fishers are naturally tuned to this complexity and meet their individual goals by targeting their efforts towards particular locations and types of catch, and by adapting their social interactions. Yet we - the scientific community - lack an understanding of how social behavior and ecological dynamics are coupled. Further, these feedbacks are largely ignored in present management approaches. We aim to fill this knowledge gap by answering three questions: (1) How does fisher social behavior (defined as the level to which individual fishers share information) change in response to ecological, technological and management factors? (2) What effect does social behavior have on fisher spatial dynamics and on the social structure of the fishing community? (3) How can management strategies be designed to account for the social behavior of fishers? To answer these questions we will conduct a comprehensive research project involving data gathering and analysis, theoretical modeling and the development of novel mathematical theory. This project will have direct implications for agencies responsible for managing marine resources along the west coast of the U.S. and in Hawaii, some of whom are collaborating in the research. By increasing our understanding of how humans using a natural resource interact with one another and how this in turn affects that resource, the results of this study will be relevant to fields as diverse as finance and global food security. We propose to gather data on the spatial and behavioral dynamics of fishers along the U.S. west coast, in Brazil and in Fiji - three marine systems with contrasting social, ecological, technological and management characteristics. U.S. data will come from collaborations with the NOAA National Marine Fisheries Service, and data from Brazil and Fiji will be obtained using economic field experiments. All three data sources will be used to develop agent-based models that simulate both the dynamics of fish and individual fishers. We will distinguish ourselves from traditional modeling approaches by adopting a Complex Adaptive Systems (CAS) perspective. With a CAS perspective the spatial dynamics of fish and fishers and the social structure of fisher communities, along with other macroscopic properties, emerge from processes operating at low levels of organization, namely the actions of individual fishers and their target species. Our agent-based models will have the CAS perspective at heart, with fisher agents able to adapt and learn different behavioral strategies (e.g. sharing or not sharing information). A combination of variation, fitness and reproduction will create a selective mechanism whereby fisher behaviors converge to evolutionary stable types. We will complement our agent-based modeling with evolutionary game theory and investigate why certain social behaviors are evolutionarily stable in some marine systems and not in others. Last, we will use mechanism design theory to develop management strategies that account for changes in fisher social behavior.

海洋是地球上最具活力的环境之一，对理解其中复杂的社会、生态和物理相互作用提出了深刻的挑战。渔民自然适应这种复杂性，并通过将其努力针对特定的地点和捕获类型以及调整其社会互动来实现其个人目标。然而，我们--科学界--缺乏对社会行为和生态动态如何耦合的理解。此外，在目前的管理方法中，这些反馈在很大程度上被忽视。我们的目标是通过回答三个问题来填补这一知识空白：（1）渔民的社会行为（定义为个体渔民分享信息的水平）如何响应生态、技术和管理因素而变化？(2)社会行为对渔民空间动态和渔业社区的社会结构有什么影响？(3)如何设计管理策略来解释渔民的社会行为？为了回答这些问题，我们将进行一个全面的研究项目，涉及数据收集和分析，理论建模和新的数学理论的发展。该项目将对负责管理美国西海岸沿着和夏威夷海洋资源的机构产生直接影响，其中一些机构正在合作进行研究。通过增加我们对人类如何利用自然资源相互作用以及这反过来如何影响该资源的理解，这项研究的结果将与金融和全球粮食安全等不同领域相关。我们建议收集数据的空间和行为动态的渔民沿着美国西海岸，在巴西和斐济-三个海洋系统的对比社会，生态，技术和管理特点。美国的数据将来自与NOAA国家海洋渔业局的合作，巴西和斐济的数据将通过经济实地实验获得。所有这三个数据源都将用于开发基于代理的模型，模拟鱼类和个体渔民的动态。我们将通过采用复杂适应系统（CAS）的观点来区分自己与传统的建模方法。从复杂适应系统的角度来看，鱼类和渔民的空间动态以及渔民社区的社会结构，沿着其他宏观性质，都是在低层次组织下运作的过程，即个体渔民及其目标物种的行动。我们基于代理的模型将以CAS为核心，Fisher代理能够适应和学习不同的行为策略（例如共享或不共享信息）。变异、适应性和繁殖的结合将创造一种选择机制，使渔民的行为收敛到进化稳定的类型。我们将用进化博弈论来补充我们基于代理的建模，并研究为什么某些社会行为在某些海洋系统中是进化稳定的，而在其他系统中则不是。最后，我们将使用机制设计理论来发展管理策略，以解释渔民社会行为的变化。