The Merits of Loop Analysis for the Qualitative Modeling of Social-Ecological Systems in Presence of Offshore Wind Farms

Introduction The 2020’s will probably stand out as the decade when offshore wind farms (OWF) were developed worldwide (GWEC, 2020) as a response toward sustainability goals. Today, global OWF capacity represents 29.1 GW, which in end of 2019 accounted for 5% of total global wind capacity (GWEC, 2020). Since the world's first offshore wind turbine was installed in Denmark in 1991, Europe has taken the lead in offshore wind development. By 2019, 5,047 offshore wind turbines were installed along the European coasts, corresponding to 110 OWF producing 22.1 GW (WindEurope, 2019). OFW developments are often located on densely populated coastlines and races questions about human-environment interactions, spatial planning, and cumulated impacts with other human activities, fisheries in particular (Berkenhagen et al., 2010). OWF constructions have consequences on the marine ecosystems and dwellers of coastal areas, which depend on the complex network of ecological, socio-economic and political variables. Energy is indeed a vital issue for our future and requires the development of interdisciplinary research to interpret and drive the choices and responses to the climate challenge faced by our society (Labussière and Nadaï, 2015). A better understanding of the functioning and evolutionary trajectory of social-ecological systems (SES) following the choices in the energy sector is very useful for the governance (Mazé, 2020). SES provides the conceptual framework for the analysis of these intertwined social and natural systems. Berkes and Folke (1998) developed the ideas around SES in a context of resilience, even if this notion was already present in other fields (e.g., epidemiological context, Cherkasskii, 1988). They underlined the need to balance the “social” and “ecological” subsystems when considering them together, and to connect them through non-linear ecological and knowledge of human dynamics. Studying SES using systems science brings highly valuable answers to numerous questions concerning their interactions and their role in either transmitting or attenuating perturbations. These are theoretical as well as practical questions useful for decision. Several authors have proposed the development of SES models to understand the resilience, vulnerability, and adaptability of these systems (Young et al., 2006), or to answer management questions within a context of resilience-based decision (e.g., Anthony et al., 2013). They emphasize the need of an approach that tackles explicitly the structure of the interactions between the social and ecological components (Walker et al., 2006). Qualitative models facilitate the study of complex systems without being hampered by the need of accurately measure behavior and relationships between variables (Justus, 2006). Based on loop analysis as developed in the 1970's by Richard Levins (Levins, 1974, 1975; Lane and Levins, 1977), SES can be modeled as signed, directed graphs (signed digraph), where each relationship is described as 0, +, or –, according to the direct effect from one variable to another. The aim of this opinion paper is to emphasize the uniqueness of SES that stem from OWF, and to address how some challenges typically encountered when modeling SES linked with OWF can be resolved through Levin's loop analysis.