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Resilience and malleability:New directions for socio-metabolic research in times of multiple crises
Haberl, Helmut Giljum, Stefan Krausmann, Fridolin Schaffartzik, Anke Staritz, Cornelia Thurner, Stefan Bruckner, Martin Streeck, Jan Wiedenhofer, Dominik Pachauri, Shonali
Haberl, Helmut
Giljum, Stefan
Krausmann, Fridolin
Schaffartzik, Anke
Staritz, Cornelia
Thurner, Stefan
Bruckner, Martin
Streeck, Jan
Wiedenhofer, Dominik
Pachauri, Shonali
Title / Series / Name
Ecological Economics
Publication Volume
243
Publication Issue
Pages
Editors
Keywords
Climate impacts
Complex adaptive systems
Disruptions
Keywords
Malleability
Provisioning systems
Resilience
Social metabolism
Tipping points
General Environmental Science
Economics and Econometrics
SDG 13 - Climate Action
Complex adaptive systems
Disruptions
Keywords
Malleability
Provisioning systems
Resilience
Social metabolism
Tipping points
General Environmental Science
Economics and Econometrics
SDG 13 - Climate Action
Files
URI
https://hdl.handle.net/20.500.14018/28958
Abstract
The world faces multiple crises and disruptions, such as climate impacts, pandemics, geopolitical tension and competition, conflicts, and wars. Socio-metabolic research (SMR), the study of stocks and flows of materials and energy associated with socioeconomic activities, is not well equipped to address these challenges. SMR methods are predominantly descriptive, static or linear. They treat disruptions as exogenous and are ill-equipped to capture abrupt non-linear changes evident today and likely to intensify in the future. They lack the granularity needed to analyze how stocks and flows of resources relate to actors, institutions, and power relations characterized by vast inequalities. SMR relies primarily on quantitative data, which is often inadequate to understand qualitative system properties and mechanisms. These shortcomings hinder understanding resilience, the ability of social metabolism to recover from shocks, and malleability, the extent to which social metabolism can be transformed to promote sustainable wellbeing for all. SMR can respond through linkages with big data models treating economies as complex networked systems that allow analyzing system resilience, non-linearities, feedback mechanisms, and tipping points. Enhanced granularity in terms of higher resolution quantitative data and rigorous understanding of qualitative system properties can help connect actors' decision-making with their biophysical implications. This is a prerequisite for generating transformative knowledge through SMR. Linking complexity science, political ecology, and SMR is imperative for addressing pressing contemporary issues.
Topic
Publisher
Place of Publication
Type
Journal article
Date
2026-05
Language
ISBN
Identifiers
10.1016/j.ecolecon.2026.108938