Cacao Deforestation Risk Assessment
EUDR Context
| Field | Value |
|---|---|
| eudr_commodity | cacao |
| country_focus | Colombia |
| eudr_article9_field | deforestation_risk_assessment |
| eudr_evidence_type | satellite_verification |
| deforestation_risk | medium |
| last_updated | 2026-05-26 |
Overview
Under the EUDR, operators must assess whether the cacao they source is deforestation-free, meaning no forest loss or degradation occurred on the plot of production after 31 December 2020. The risk assessment must consider factors including: the prevalence of deforestation and forest degradation in the sourcing country and region, the reliability of land-use and forest-cover data, governance indicators including corruption and rule-of-law indices, the complexity of the supply chain, and the presence of indigenous peoples or local communities whose rights may be affected.
For cacao specifically, deforestation risk profiles vary dramatically by origin. West African cocoa (Cote d'Ivoire, Ghana) is historically associated with high deforestation rates driven by shade-tree removal for full-sun monoculture. Latin American origins, including Colombia, present a more nuanced risk profile: cacao itself is not a primary deforestation driver, but cacao expansion can occur in landscapes already fragmented by cattle ranching, coca cultivation, and illicit land clearing.
The EU country benchmarking system will classify producing countries and sub-national regions as high, standard, or low risk. This classification directly affects the level of due diligence scrutiny required: operators sourcing from high-risk regions face enhanced checks, while those sourcing from low-risk regions may benefit from simplified procedures. Colombia's benchmarking outcome will significantly impact the compliance burden on its cacao exporters.
Colombian Context
Colombia's deforestation dynamics are complex. A CIAT baseline study found that cacao cultivation is not a significant direct driver of deforestation in Colombia. However, cacao-growing regions overlap with active deforestation fronts driven by other forces. The Catatumbo region (Norte de Santander), bordering Venezuela, experiences forest loss from coca cultivation and armed-group land clearing. The Pacific coast (Tumaco, Nariño) faces deforestation from illegal mining, coca, and logging. The Amazon arc (Caqueta, Guaviare, Putumayo) has seen post-peace-agreement deforestation driven by cattle ranching expansion, land speculation, and in-migration.
Santander, the largest cacao-producing department, has relatively lower deforestation risk because most cacao there is grown in established agroforestry systems on land that was converted long before the 2020 cutoff date. Arauca and parts of Antioquia present moderate risk due to proximity to the agricultural frontier. The most sensitive areas for EUDR risk assessment are emerging cacao zones in Caqueta and Putumayo, where cacao is promoted as a peace-crop substitute for coca but is expanding into recently deforested landscapes.
Satellite monitoring of Colombian cacao areas is supported by national systems including IDEAM's Forest and Carbon Monitoring System and international platforms like Global Forest Watch. Fairtrade has partnered with Satelligence to scale up satellite monitoring of forested areas around Fairtrade cocoa farms across Latin America, with full georeferencing data targeted for completion by end of 2025.
Cleantech Taxonomy Nodes
Key existing nodes: CT-AF-002 (Forests and Woodlands — deforestation monitoring and forest preservation technology), CT-EX-014 (Remote sensing and satellite deforestation monitoring — the primary technical infrastructure for EUDR deforestation risk assessment), CT-AF-001 (Land and Soil — land-use change detection on cacao plots).
Proposed new node: CT-EX-027 (Cacao landscape-level deforestation risk scoring) — covers tools and methodologies for assessing deforestation risk at the landscape scale around cacao production areas, integrating satellite data, land-tenure information, governance indicators, and proximity to deforestation fronts. This is distinct from plot-level geolocation (CT-EX-022) because it addresses the contextual risk of the broader landscape rather than the specific farm boundary.
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