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Commodity trade is central to the global economy but is also associated with socio-environmental impacts, for example, deforestation, especially in producer countries. It is crucial to understand how geographic sourcing patterns of commodities and commercial relationships between places and actors influence land-use dynamics, socio-economic development, and environmental degradation. Here, we propose a concept and methodological approach to analyze the geographic stickiness of commodity supply chains, which is the maintenance of supply network configurations over time and across perturbations. We showcase policy-relevant metrics for all Brazilian soy exports between 2003 and 2017, using high-resolution supply chain data fromwww.trase.earth. We find that the Brazilian soy traders with the largest market share exhibit stickier geographic sourcing patterns, and that the supply network configurations between production places and traders become increasingly sticky in subsequent years. Understanding trade stickiness is crucial for supply chain accountability, because it directly affects the effectiveness of zero-deforestation commitments.

Though the international trade in agricultural commodities is worth more than $1.6 trillion/year (1), we still have a poor understanding of the supply chains connecting places of production and consumption and the socio-economic and environmental impacts of this trade (2). In this study, we provide the first wall-to-wall subnational map of the origin and supply chain of Brazilian meat, offal, and live cattle exports from 2015 to 2017, a trade worth more than $5.4 billion/year. Brazil is the world's largest beef exporter, exporting approximately one-fifth of its production, and the sector has a notable environmental footprint, linked to one-fifth of all commodity-driven deforestation across the tropics (3). By combining official per-shipment trade records, slaughterhouse export licenses, subnational agricultural statistics, and data on the origin of cattle per slaughterhouse, we mapped the flow of cattle from more than 2,800 municipalities where cattle were raised to 152 exporting slaughterhouses where they were slaughtered, via the 204 exporting and 3,383 importing companies handling that trade, and finally to 152 importing countries. We find stark differences in the subnational origin of the sourcing of different actors and link this supply chain mapping to spatially explicit data on cattle-associated deforestation, to estimate the 'deforestation risk' (in hectares/year) of each supply chain actor over time. Our results provide an unprecedented insight into the global trade of a deforestation-risk commodity.

Meteorological extreme events such as El Niño events are expected to affect tropical forest net primary production (NPP) and woody growth, but there has been no large-scale empirical validation of this expectation. We collected a large high temporal resolution dataset (for 1–13 years depending upon location) of more than 172 000 stem growth measurements using dendrometer bands from across 14 regions spanning Amazonia, Africa and Borneo in order to test how much month-to-month variation in stand-level woody growth of adult tree stems (NPPstem) can be explained by seasonal variation and interannual meteorological anomalies. A key finding is that woody growth responds differently to meteorological variation between tropical forests with a dry season (where monthly rainfall is less than 100 mm), and aseasonal wet forests lacking a consistent dry season. In seasonal tropical forests, a high degree of variation in woody growth can be predicted from seasonal variation in temperature, vapour pressure deficit, in addition to anomalies of soil water deficit and shortwave radiation. The variation of aseasonal wet forest woody growth is best predicted by the anomalies of vapour pressure deficit, water deficit and shortwave radiation. In total, we predict the total live woody production of the global tropical forest biome to be 2.16 Pg C yr−1, with an interannual range 1.96–2.26 Pg C yr−1 between 1996–2016, and with the sharpest declines during the strong El Niño events of 1997/8 and 2015/6. There is high geographical variation in hotspots of El Niño-associated impacts, with weak impacts in Africa, and strongly negative impacts in parts of Southeast Asia and extensive regions across central and eastern Amazonia. Overall, there is high correlation (r = −0.75) between the annual anomaly of tropical forest woody growth and the annual mean of the El Niño 3.4 index, driven mainly by strong correlations with anomalies of soil water deficit, vapour pressure deficit and shortwave radiation.This article is part of the discussion meeting issue ‘The impact of the 2015/2016 El Nino on the terrestrial tropical carbon cycle: patterns, mechanisms and implications’.

Consumption of globally traded agricultural commodities like soy and palm oil is one of the primary causes of deforestation and biodiversity loss in some of the world's most species-rich ecosystems. However, the complexity of global supply chains has confounded efforts to reduce impacts. Companies and governments with sustainability commitments struggle to understand their own sourcing patterns, while the activities of more unscrupulous actors are conveniently masked by the opacity of global trade. We combine state-of-the-art material flow, economic trade, and biodiversity impact models to produce an innovative approach for understanding the impacts of trade on biodiversity loss and the roles of remote markets and actors. We do this for the production of soy in the Brazilian Cerrado, home to more than 5% of the world´s species. Distinct sourcing patterns of consumer countries and trading companies result in substantially different impacts on endemic species. Connections between individual buyers and specific hot spots explain the disproportionate impacts of some actors on endemic species and individual threatened species, such as the particular impact of European Union consumers on the recent habitat losses for the iconic giant anteater (Myrmecophaga tridactyla). In making these linkages explicit, our approach enables commodity buyers and investors to target their efforts much more closely to improve the sustainability of their supply chains in their sourcing regions while also transforming our ability to monitor the impact of such commitments over time.