Abstract

Recently it has been estimated that one third of biodiversity threats are driven by consumer demand from outside the country in which the threat occurs. This occurs when the production of export goods exerts pressure on vulnerable populations. While population biologists have in cases been able to establish links between species threats and the causative industry(s), little has been done to trace this biodiversity footprint from the directly implicated industry out to final consumers, a step that would open a wider variety of policy responses. Here we investigate the suitability of multi-region input–output (MRIO) analysis for tracing out links between particular species threats, directly implicated industries, and the countries and consumer goods sectors ultimately driving these industries. Environmentally extended MRIO models are understood to provide reliable results at a macroeconomic level but uncertainty increases as the models are used to investigate individual sectors, companies, and products. In this study we examine several case studies (nickel mining in New Caledonia, coltan from the Democratic Republic of Congo, cut flowers from Kenya, and forestry in Papua New Guinea) in order to understand how and when MRIO techniques can be useful for studying biodiversity implicated supply chains. The study was conducted using the Eora global input–output database that documents >5 billion global supply chains. Calculating the biodiversity footprint at this level of detail, between specific threats, supply chains, and consumer goods, has not been done before. These case studies provide interesting insights in their own right and also serve to highlight the strengths and weaknesses of using input–output analysis techniques to calculate detailed biodiversity footprints. We conclude that MRIO analysis, while no panacea, can be useful for outlining supply chains and identifying which consumption sectors and trade and transformation steps can be subjected to closer analysis in order to enable remedial action.

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