An integral approach to address socio-ecological systems sustainability and their uncertainties

Sci Total Environ. 2021 Mar 25:762:144457. doi: 10.1016/j.scitotenv.2020.144457. Epub 2020 Dec 15.

Abstract

The analysis of the sustainability should be addressed with a holistic approach that facilitates an integral analysis of the social, economic, institutional and environmental factors and their interactions characterizing complex socio-ecological systems (SES). Nevertheless, despite the increasing acknowledgment about the need for such systemic approaches, their application in real SES are less frequent than desirable. Among the difficulties behind this, the need for a new conceptual perspective concerning the relationships between science and the management of real SES, as well as the lack of tools to manage the inherent complexity of such systems should be emphasized. In this work, we further discuss these difficulties and propose an integral methodological framework for the assessment of SES sustainability, with the following key components: i) The hierarchical definition of sustainability goals and indicators. ii) A dynamic system model taking into account the key socio-economic and environmental factors and their interactions, in which the most representative indicators and their sustainability thresholds are integrated. iii) The analysis of vulnerabilities to exogenous drivers (scenario analysis) and the exploration of available management and planning options (policy assessment). iv) An uncertainty assessment concerning system behavior and model outcomes to guide decisions for an improved sustainability in complex SES. The whole framework highlights the need to integrate a participative approach, above all at the initial and final steps. In this work, these components are exemplified by means of their application to a real socio-ecological system: Fuerteventura island (The Canary Islands, Spain).

Keywords: Dynamic models; Indicators; Participatory approaches; Policy assessment; Science for sustainability; Uncertainty analysis.