CNH: Social-Ecological Complexity and Adaptation in Marine Systems

海洋是地球上最具活力的环境之一，这对理解海洋中发生的复杂的社会、生态和物理相互作用提出了深刻的挑战。渔民自然而然地适应了这种复杂性，并通过将他们的努力瞄准特定地点和类型的渔获物以及通过调整他们的社会互动来实现他们的个人目标。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，这些反馈在目前的管理方法中很大程度上被忽视了。我们旨在通过回答三个问题来填补这一知识空白：(1)渔民社会行为(定义为渔民共享信息的水平)如何随着生态、技术和管理因素的变化而变化？(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，我们将进行一项全面的研究项目，包括数据收集和分析、理论建模和新数学理论的发展。该项目将对负责管理美国西海岸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这项研究。通过增加我们对使用自然资源的人类如何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多个领域相关。我们建议收集美国西海岸、巴西和斐济三个海洋系统的渔民的空间和行为动态数据，这三个海洋系统具有不同的社会、生态、技术和管理特征。美国的数据将来自与NOAA国家海洋渔业局的合作，来自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，以模拟鱼类和个体渔民的动态。我们将从复杂适应系统(CAS)的角度将自己与传统的建模方法区分开来。从CAS的角度来看，鱼类和渔民的空间动态、渔民群体的社会结构以及其他宏观性质，都是在低组织水平上运作的过程，即个体渔民及其目标物种的行动。我们基于代理的模型将从CAS的角度出发，使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、适应度和繁殖的结合将创造一种选择性机制，使费舍尔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，并调查为什么某些社会行为在一些海洋系统中进化稳定，而在另一些海洋系统中不稳定。最后，我们将使用机制设计理论来制定管理策略，以应对费舍尔社会行为的变化。

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.