Small-scale fisheries (SSF), such as the sea urchin (Paracentrotus lividus) fishery along Mediterranean coasts, are complex and diverse social-ecological systems (SES) undergoing major pressures including climate change, biodiversity loss, and changes to social and economic drivers. SSF require multi- and transdisciplinary research approaches to understand the complex dynamics between humans and nature and to design actionable management measures tackling both ecological and socio-economic sustainability. Social-ecological network (SEN) analysis represents a promising tool to model these systems. Through its capacity to visualize and analyse interactions among actors within a particular system, it allows to combine knowledge from natural and social scientists and co-create system knowledge to jointly disentangle complexity in ecosystems and fisheries value chains. Here, we build social-ecological networks of two sea urchin fisheries case studies (Sardinia in Italy, Catalonia in Spain). Interdisciplinary knowledge on different SES sub-systems based on local experts in ecological and social science field work in the focal regions was assembled through workshops and surveys. The resulting networks represent the multi-trophic dynamics among macroalgae, sea urchins and fish predators, as well as their fisheries value chains and their governance systems. These two Mediterranean SES share similar ecological components and trophic interactions. Our hypothesis is that the observed differences in system outcomes (low vs. high sea urchin abundances, occurrence of barrens) result from differences in the human dimension of the SESs. SEN metrices show the network differ in density, and highlight diverse role across actors in shaping the flow pathways that connect humans with nature in each region. The identification of central figures within complex SES helps to identify leverage points for management interventions and can serve as a discussion baseline with stakeholders to facilitate participative decision-making. This work shows the utility of using SENs as a tool to advance co-learning in multidisciplinary teams.