Deforestation remains one of the greatest obstacles to limiting global warming, yet the economic mechanisms linking global supply chains to final consumers are poorly understood. Fine-scale satellite monitoring tracks where forests are lost, but rarely reveals who ultimately drives this loss through consumption. We further apply machine learning techniques to identify key socioeconomic drivers behind consumption-induced forest loss. Our results indicate that 38.15% of global forest loss—equating to approximately 5.01 Mha of the 13.12 Mha total in 2022—is embodied in international final demand, with five countries (Brazil, the United States, China, Indonesia, and Russia) accounting for 48.16% of global deforestation. China and Russia exhibit polarizing trends that amplify global forest pressures. Among the evaluated socioeconomic determinants, urbanization, manufacturing intensity, and domestic economic and conservation capacities emerge as the primary factors characterizing cross-national patterns of forest loss. This integrated framework offers a robust, data-driven foundation for advancing global forest conservation and promoting equitable responsibility across international supply chains. More than one third of global forest loss is embodied in international demand, with urbanization and manufacturing emerging as key predictors, according to a study that combined satellite observations with trade modeling and machine learning.
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Liu et al. (2026) studied this question.
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