From Representation to Intervention: System Change and Threshold Effects and Cross-scale dynamics in Social-ecological Systems

Authors

  • Yiyu Liu China

Keywords:

social-ecological systems; resilience; representation and intervention; soft systems methodology; threshold effect

Abstract

The concept of social-ecological systems (SES) is very well accepted, but there are many unanswered questions about the way SES behave. Many of the main concepts, such as thresholds and tipping points, come from ecological understanding, and do not appear to apply so clearly in the social parts of the systems. Thus, it is difficult to assess vulnerabilities and resilience, and to promote interventions to avert reaching critical thresholds. This paper considers some of these theoretical points. The challenges identification of thresholds in SES stems from such factors as the complexity of the systems, the unobservability of resilience, and the dual difficulty of identifying critical states of ecosystems and social systems. The identification of thresholds is one of the frontier problems in the current research of resilience for social-ecological systems. The traditional representational approaches of threshold-identification (such as use of resilience surrogates) focus on transplanting the measurement methods of ecosystem resilience to social-ecological systems. This results in a fundamental dilemma in ability to cope with the challenges of human action.

One of the possible approaches to solve this dilemma lies in the approach of soft systems methodology. I will argue that soft systems analysis and intervention approaches based on social constructivism offer a better way to understand thresholds and tipping points (severe risk points for system change), in order to build system and community resilience. Soft systems interventions(SSI) can include intervention on specific conditions, adaptive collaboration learning, and inducing self-organization. SSI can promote methodological change from interpretation-prediction isomorphism to action-prediction isomorphism under threshold conditions, and help us further identify focal issue and key uncertainties to intervene the initial conditions, then intervene in the implementation process based on boundary judgement, and further promote to generate similar understanding based on nudge and boost. I explore a case study of collaborative soft systems analysis and intervention in China, to illustrate how such methods can be used to identify thresholds as well as guiding intervention while involving the actors responsible for the many parts of the system. At the same time, I discuss philosophical issues in collective action, and knowledge production, systems practice and social construction.

Published

2022-02-24 — Updated on 2022-02-24

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