Ambiguity in social ecological system understanding: Advancing modelling of stakeholder perceptions of climate change adaptation in Kenya. (July 2021)

• Record Type: Journal Article
• Authors: de Jong, Charlotte Esmeralda; Kok, Kasper
• Is Part Of: Environmental modelling & software. Volume 141(2021)
• Publication Date: 2021-07
• Subjects: Ambiguity -- Social ecological systems -- Fuzzy cognitive maps -- Climate change adaptation -- Participatory modelling; ABA Ambiguity based aggregation; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2021.105054
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: Climate change adaptation requires understanding of complex social ecological systems (SESs). One source of uncertainty in complex SESs is ambiguity, defined as the range and variety of existing perceptions in and of an SES, which are considered equally valid, resulting in a lack of a unique or single system understanding. Current modelling practices that acknowledge the presence of ambiguity in SESs focus on finding consensus with stakeholders; however, advanced methods for explicitly representing and aggregating ambiguity in SESs are underdeveloped. Moreover, understanding the influences of ambiguity on SES representation is limited. This paper demonstrates the presence and range of ambiguities in endogenous and exogenous system drivers and internal relationships based on individual fuzzy cognitive maps derived from stakeholder perceptions of climate change adaptation in Kenya and introduces an ambiguity based modelling process. Our results indicate that acknowledging ambiguity fundamentally changes SES representation and more advanced methods are required. Highlights: Ambiguity is an important aspect of social ecological system understanding. Fuzzy cognitive maps elucidate a range of ambiguities among stakeholders. Ambiguity based aggregation was used to quantify ambiguity. We found the greatest ambiguity in the presence (or lack of) of relationships. More advanced ambiguity based modelling practices are needed.