Revealing Hidden Biodiversity Footprints Embedded in Global Mining Supply Chains

Driven by digitalization, infrastructure expansion, and the clean energy transition, global mining has grown rapidly over the past two decades, intensifying land-use pressure and sharpening trade-offs between resource extraction and biodiversity conservation. However, spatially explicit assessments of mining-related biodiversity impacts and the tracing of these impacts along mining supply chains remain limited. Here, we present a spatially explicit assessment framework that links local biodiversity intactness loss, expressed as mean species abundance, to global potential species loss, and we couple this framework with a multiregional input-output model to trace consumption-driven impacts along global mining supply chains. We find that biodiversity loss impacts associated with global mining land use are nearly twice as high as those of previous global estimates. Hotspots in Indonesia, New Caledonia, Australia, Brazil, and Peru account for 57% of the global mining-related biodiversity impacts. Coal, precious metals, nickel, iron, and copper extraction together contribute 82% of the total impact. Due to international trade, 77% of mining-related biodiversity footprints occur outside the countries of final consumption, with demand from China, Europe, Japan, and the United States accounting for 58% of the total footprints. Our results improve the transparency of biodiversity impacts embedded in global mining supply chains and support hotspot-oriented biodiversity conservation and supply chain governance.

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Publication Details

Journal
Environmental Science & Technology
Published
2026-06-09
DOI
https://doi.org/10.1021/acs.est.6c01834
Primary Topic
Mining and Resource Management
Type
article
Field-Weighted Citation Impact
0.00

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article

Revealing Hidden Biodiversity Footprints Embedded in Global Mining Supply Chains

Yue Yu, Shuntian Wang, Livia Cabernard, Stephan Pfister
Environmental Science & Technology
Mining and Resource Management
article

Revealing Hidden Biodiversity Footprints Embedded in Global Mining Supply Chains

Yue Yu, Shuntian Wang, Livia Cabernard, Stephan Pfister
article en

Abstract

Driven by digitalization, infrastructure expansion, and the clean energy transition, global mining has grown rapidly over the past two decades, intensifying land-use pressure and sharpening trade-offs between resource extraction and biodiversity conservation. However, spatially explicit assessments of mining-related biodiversity impacts and the tracing of these impacts along mining supply chains remain limited. Here, we present a spatially explicit assessment framework that links local biodiversity intactness loss, expressed as mean species abundance, to global potential species loss, and we couple this framework with a multiregional input-output model to trace consumption-driven impacts along global mining supply chains. We find that biodiversity loss impacts associated with global mining land use are nearly twice as high as those of previous global estimates. Hotspots in Indonesia, New Caledonia, Australia, Brazil, and Peru account for 57% of the global mining-related biodiversity impacts. Coal, precious metals, nickel, iron, and copper extraction together contribute 82% of the total impact. Due to international trade, 77% of mining-related biodiversity footprints occur outside the countries of final consumption, with demand from China, Europe, Japan, and the United States accounting for 58% of the total footprints. Our results improve the transparency of biodiversity impacts embedded in global mining supply chains and support hotspot-oriented biodiversity conservation and supply chain governance.

Environmental Science & Technology
ETH Zurich (CH), Ecological Engineering Institute (SI), Sustainability Institute (ZA)
Staatssekretariat für Bildung, Forschung und Innovation, HORIZON EUROPE Food, Bioeconomy, Natural Resources, Agriculture and Environment
Industry, innovation and infrastructure
Openalex Percentile: Top 10%
Mining and Resource Management
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