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Meeting the objectives of sustainable fisheries management requires attention to the complex interactions between humans, institutions and ecosystems that give rise to fishery outcomes. Traditional approaches to studying fisheries often do not fully capture, nor focus on these complex interactions between people and ecosystems. Despite advances in the scope and scale of interactions encompassed by more holistic methods, for example ecosystem‐based fisheries management approaches, no single method can adequately capture the complexity of human–nature interactions. Approaches that combine quantitative and qualitative analytical approaches are necessary to generate a deeper understanding of these interactions and illuminate pathways to address fisheries sustainability challenges. However, combining methods is inherently challenging and requires understanding multiple methods from different, often disciplinarily distinct origins, demanding reflexivity of the researchers involved. Social–ecological systems' research has a history of utilising combinations of methods across the social and ecological realms to account for spatial and temporal dynamics, uncertainty and feedbacks that are key components of fisheries. We describe several categories of analytical methods (statistical modelling, network analysis, dynamic modelling, qualitative analysis and controlled behavioural experiments) and highlight their applications in fisheries research, strengths and limitations, data needs and overall objectives. We then discuss important considerations of a methods portfolio development process, including reflexivity, epistemological and ontological concerns and illustrate these considerations via three case studies. We show that, by expanding their methods portfolios, researchers will be better equipped to study the complex interactions shaping fisheries and contribute to solutions for sustainable fisheries management. [ABSTRACT FROM AUTHOR]

Small‐scale fisheries often involve weak management regimes with limited top‐down enforcement of rules and minimal support from legal institutions, making them useful model systems for investigating the role of social influence in determining economic and environmental outcomes. In such regimes, interpersonal relationships are expected to have a strong effect on a fisher's catch portfolio, the set of fish species targeted by an individual fisher. Here, we test three competing hypotheses about social influence using belief propagation network models and show that a peer‐to‐peer information‐sharing social network is key to explaining catch portfolios at a small‐scale fishery in Jamaica. We find that experience dictates the direction of influence among fishers in the social network, with older fishers and information brokers having distinct roles in shaping catch patterns for large‐ and small‐sized fish species, respectively. These findings highlight concrete opportunities for harnessing social networks in natural resource management. Our new approach to modelling social influence is applicable to many social–ecological systems with minimal legal and institutional support or those that rely heavily on bottom‐up participatory processes. [ABSTRACT FROM AUTHOR]