D6.4 Biodiversity interdependencies with environmental and socio-economic indicators

Agricultural production is associated with land use change, greenhouse gas emissions, and other environmental degradation, which, in turn, are drivers of biodiversity loss. Most of these effects are exacerbated by increasing agri-food exports, causing the displacement of environmental and socioeconomic pressures throughout supply chains. To understand these interdependencies, quantitative assessments benefit from the combination of both detailed trade data and subnational environmental and socioeconomic indicators assessed using a life cycle approach. In Deliverable D6.3, we developed a bottom-up life cycle assessment (LCA) framework based on regionalized supply chain data and impact assessment methods to derive spatially-explicit indicators of biodiversity loss embodied in Brazilian soybean exports and derivatives to the EU. In addition, a new set of indicators for biodiversity impacts was derived for South America and Africa and implemented in the GLOBIOM modeling framework to derive biodiversity loss trajectories under alternative Shared Socioeconomic Pathways (SSPs) until 2050. This deliverable (D6.4) aims to derive quantitative indicators on agricultural commodity exports' environmental and socioeconomic impacts by combining detailed trade data and LCA approaches. The indicators assess the interdependencies between biodiversity loss and other sustainability dimensions along the supply chain. Specifically, a dedicated case study on Brazilian soy supply chains arriving in the EU in 2022 has been developed using one ton of soy equivalent arriving in the importing EU countries and the total amount of soy equivalents traded as reference units. To this aim, the supply chains' biodiversity, carbon, and water footprints, and four socioeconomic indicators are estimated: eco-efficiency, land deforestation footprint, soybean export dependence ratio, and impact on human health. The selected indicators are closely aligned with several Sustainable Development Goals (SDGs), particularly SDGs 2, 3, 6, 8, 9, 11, 12, 13, 15, and 17, reflecting the interconnected nature of environmental sustainability, economic development, and human well-being. The case study of Brazilian soy supply chains in the year 2022 allows the main drivers of the environmental impacts to be identified, namely the demand for land resources (i.e., land transformation and occupation) in the biodiversity footprint, and the farming stage, specifically the production of fertilizers, in the carbon and water footprints. In addition, the producing states and the importing EU countries with the highest environmental footprint have been highlighted. As for the socioeconomic indicators, the eco-efficiency of the carbon footprint per USD-FOB1 showed that the most eco-efficient municipalities are also those with the lowest carbon footprint and relatively low production, namely the ones located in Roraima, Tocantins, and Santa Catarina. The most eco-efficient municipalities in terms of biodiversity footprint are in Mato Grosso, Bahia, and Goiás, which are the states that cause a relatively low biodiversity loss per ton of soy-eq. and are among the primary producers of soy commodities generating higher revenues.