Specialization of fishers leads to greater impact of external disturbance: Evidence from a social-ecological network modelling exercise for Sechura Bay, northern Peru

Coastal marine resources provide livelihoods to human communities around the world. The interactions in respective social-ecological systems are usually of complex nature, due to a wide range of different fisheries interacting with the ecosystem. Understanding connectivity within these systems (i.e. among social and ecological actors) helps in establishing meaningful management strategies for sustainable use of marine resources. This work uses the value chain analysis of different fisheries sectors to construct a qualitative social-ecological network (SEN) model of the Sechura Bay in North Peru. Here, a diverse ensemble of small-scale fisheries co-exists with a flourishing mariculture sector, though the respective production chains partially overlap. Directed and unweighted links between actors were defined based on the transfer of biomass (trophic interactions) and money (economic interactions). Several analytical network tools were applied (e.g. degree centrality, dominator tree) to identify the most important nodes of the social-ecological network and to understand interdependencies. Results of the network analysis suggest position of system's components being related to their vulnerability in the face of external disturbances. Fisher groups with a high specialization with respect to fisheries target species were stronger impacted by the last strong El Niño event (the Coastal El Niño 2017), with drastic consequences for actors of the respective production chains. The present approach is envisioned to be applicable beyond this particular case study and to nourish on-going scientific discussions on the use of social-ecological network analysis to describe human-nature interactions. This study allows (i) estimating node (actor) susceptibilities to natural and anthropogenic disturbances, and (ii) reconciling sustainable resource use and nature conservation by enhancing the understanding of the functionality of the respective social-ecological system.