WWF research maps out palm oil trade flows from six key landscapes in Asia, in bid to improve traceability

Posted on September, 17 2021

Establishing traceability in palm oil supply chains is a notoriously difficult exercise, but is essential if companies want to ensure the palm oil they source comes from sustainable sources.
To promote supply chain visibility and transparency, a new study by WWF aims to shed light on palm oil volumes and flows from six key palm oil producing landscapes in Asia. Palm oil trade flows from key landscapes in Asia: Risks and opportunities for sustainability action provides insight into the global palm oil value chain linked to six major landscapes that are rich in biodiversity and where palm oil production is prevalent: Tabin, Tawau, Lower Sugut in Sabah, Malaysia; and Tesso Nilo, Sintang and South Papua in Indonesia. 

Protecting these landscapes is a WWF priority based on the wealth and variety of life they support: they hold some of the richest and most biodiverse tropical forests on the planet, giving shelter to many rare species and providing livelihoods for millions of people. Companies sourcing palm oil from these landscapes therefore have a unique opportunity and responsibility to positively impact forests, habitats and local communities by ensuring that their supply chain is sustainable and does not contribute to deforestation and ecosystem conversion 

For each landscape, WWF’s study identifies key companies involved in the production, trade and purchase of palm oil, and assesses their level of exposure – or the likelihood they are sourcing from the considered landscape. The result is greater visibility and traceability into palm oil supply chains linked to landscapes rich in biodiversity, bringing into sharp focus the supply chain connections that can be leveraged to drive better sustainability and transparency outcomes in parts of the global palm oil industry. 
 
 
WWF study maps out palm oil trade flows from six landscapes in Indonesia and Malaysia to buyers and consumer markets
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