The interplay between top-down interventions and bottom-up self-organization shapes opportunities for transforming self-governance in small-scale fisheries.

Small-scale fisheries (SSF) contribute substantially to global food security, sustainable marine ecosystems and poverty alleviation. Yet many SSF face problems of overexploitation and poverty calling for novel governance approaches that enhance human-wellbeing, equity and ecological sustainability. External policies and interventions to support such governance transformations, however, need to take their often self-governed nature into account. Common practices based on informal arrangements between different fishery actors can make existing, mal-adapted structures very persistent and hence difficult to overcome. Here we combine multi-method empirical research on SSF in Mexico with agent-based modeling to analyze if and under which conditions interventions can shift ongoing self-organizing dynamics into directions that support the new governance form. We are particularly interested in the effectiveness of two different types of interventions, financial and social, and their performance under variable social and ecological conditions as commonly found in SSF. Our analysis reveals that a combination of financial and social support during extended periods of time is necessary to ensure persistence of new governance forms in face of competition with established forms, as well as environmental and social uncertainty. The findings highlight the importance of understanding the endogenous self-organizing dynamics created by the interplay between social (e.g. the dynamics of trust) and ecological (e.g. resource dynamics) processes in order to devise policies and measures to initiate a shift towards more sustainable pathways. • Combination of financial and social support needed for transforming governance. • Interventions need to be applied over extended periods of time. • Additional actions are needed to build resilience in uncertain world. • Combining empirical research with agent-based modelling allowed studying dynamic complexity. • Reinforcing feedbacks are particularly critical for overcoming lock-ins and accelerating adoption. [ABSTRACT FROM AUTHOR]