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The sustainable governance and management of small-scale fisheries (SSF) is challenging, largely due to their dynamic and complex nature. Agent-based modeling (ABM) is a computational modeling approach that can account for the dynamism and complexity in SSF by modeling entities as individual agents with different characteristics and behavior, and simulate how their interactions can give rise to emergent phenomena, such as over-fishing and social inequalities. The structurally realistic design of agentbased models allow stakeholders, experts, and scientists across disciplines and sectors to reconcile different knowledge bases, assumptions, and goals. ABMs can also be designed using any combination of theory, quantitative data, or qualitative data. In this publication we elaborate on the untapped potential of ABM to tackle governance and management challenges in SSF, discuss the limitations of ABM, and review its application in published SSF models. Our review shows that, although few models exist to date, ABM has been used for diverse purposes, including as a research tool for understanding cooperation and over-harvesting, and as a decision-support tool, or participatory tool, in case-specific fisheries. Even though the development of ABMs is often time-and resource intensive, it is the only dynamic modeling approach that can represent entities of different types, their heterogeneity, actions, and interactions, thus doing justice to the complex and dynamic nature of SSF which, if ignored can lead to unintended policy outcomes and less sustainable SSF.

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Alphabetical order core team starting here. ‡ Alphabetically senior team.

A thorough understanding of long-term temporal social-ecological dynamics at the national scale helps to explain the current condition of a country's ecosystems and to support environmental policies to tackle future sustainability challenges. We aimed to develop a methodological approach to understand past long-term (1960-2010) social-ecological dynamics in Spain. First, we developed a methodical framework that allowed us to explore complex social-ecological dynamics among biodiversity, ecosystem services, human well-being, drivers of change, and institutional responses. Second, we compiled 21 long-term, national-scale indicators and analyzed their temporal relationships through a redundancy analysis. Third, we used a Bayesian change point analysis to detect evidence of past social-ecological thresholds and historical time periods. Our results revealed that Spain has passed through four socialecological thresholds that define five different time periods of nature and society relationships. Finally, we discussed how the proposed methodological approach helps to reinterpret national-level ecosystem indicators through a new conceptual lens to develop a more systems-based way of understanding long-term social-ecological patterns and dynamics.

Local and regional trade networks in small-scale fisheries are important for food security and livelihoods across the world. Such networks consist of both economic flows and social relationships, which connect different production regions to different types of fish demand. The structure of such trade networks, and the actions that take place within them (e.g., people fishing, buying, selling), can influence the capacity of small-scale fisheries to provide sufficient fish in a changing social and ecological context. In this study, we aim to understand the importance of networks between different types of traders that access spatially-distinct fish stocks for the availability and variability of fish provision. We deployed a mixed-methods approach, combining agent-based modelling, network analysis and qualitative data from a small-scale fishery in Baja California Sur, Mexico. The empirical data allowed us to investigate the trade processes that occur within trade networks; and the generation of distinct, empirically-informed network structures. Formalized in an agent-based model, these network structures enable analysis of how different trade networks affect the dynamics of fish provision and the exploitation level of fish stocks. Model results reveal how trade strategies based on social relationships and species diversification can lead to spillover effects between fish species and fishing regions. We found that the proportion of different trader types and their spatial connectivity have the potential to increase fish provision. However, they can also increase overexploitation depending on the specific connectivity patterns and trader types. Moreover, increasing connectivity generally leads to positive outcomes for some individual traders, but this does not necessarily imply better outcomes at the system level. Overall, our model provides an empirically-grounded, stylized representation of a fisheries trading system, and reveals important trade-offs that should be considered when evaluating the potential effect of future changes in regional trade networks.

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