Resilience and malleability: New directions for socio-metabolic research in times of multiple crises
本文指出社会代谢研究在应对多重危机时的不足，提出通过结合大数据模型、复杂系统科学和政治生态学，增强对系统韧性和可塑性的理解，以促进可持续福祉的转型知识生成。
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.