Measuring Environmental Resilience Using Q-Methods: A Malaysian Perspective

Autor: Hisham Tariq, Chaminda Pathirage, Terrence Fernando, Noralfishah Sulaiman, Umber Nazir, Siti Kursiah Kamalia Abdul Latib, Haidaliza Masram
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Sustainability; Volume 14; Issue 22; Pages: 14749
ISSN: 2071-1050
DOI: 10.3390/su142214749
Popis: Communities increasingly need tools that can help them assess the environmental risks they face to understand better their capacities in mitigation, preparedness, response, and recovery. Environmental resilience (ER) is a crucial feature of community resilience that is not adequately covered in the literature. This paper proposes an inclusive, participatory approach to achieve stakeholder engagement on the definitions, objectives, and indicators for measuring ER at the community level. This study uses a 5-step approach utilising Q-methods to contextualise a resilience index for Environmental Resilience (ER). An initial set of 57 indicators from 13 frameworks from the literature was reduced to 25 by combining the indicators of similar type, format and terminology. A total of 10 participants from two groups (academics and practitioners) took part in the interviews and Q-sort workshops in Malaysia in this study. Both stakeholder groups identified Ecosystem monitoring as one of the most critical indicators to understand ER, closely followed by rapid damage assessments and an effective communication system. The exercise also revealed marked differences between them regarding the importance of fair access to basic needs and services for citizens, a priority for academics, and the value of building green infrastructure, a priority for practitioners, with the most significant difference between the two groups on the importance of measuring the natural defences of a community. The Environmental Resilience Capacity Assessment Tool (ER-CAT), proposed in this paper, can be used by local governments and communities for engagement, discussion and consensus building to select the resilience indicators that are most relevant to them in their contexts.
Databáze: OpenAIRE