Fingerprinting wood to fight illegal timber trade

Site mean relative wood elemental concentrations of the five most important variables in the random forest models A4 (A, Central Africa) and A3 (B, Borneo) respectively. Site mean concentrations are scaled within each element, therefore the size of the circles indicates relative abundance per element at each site. (Courtesy:

Researchers from the Utrecht University and Wageningen University and Research in the Netherlands have developed a method to “fingerprint” where wood was taken to verify the claims of the origin of wood.

According to Laura Boeschoten, Assistant Professor at Utrecht University and lead author of the research paper, to effectively reduce illegal timber trade, law enforcers need forensic methods to independently verify claims of wood origin.

“The most important motivation to undertake the research was to improve small-scale tracing,” said Boeschoten, data scientist. “But in the end, mostly to reduce illegal timber trade.”

Current methods of timber tracing do not consistently narrow a sample’s origin to areas smaller than 100 km, the distance that would be needed to accurately identify wood illegally logged.

Multi-element analysis of traded plant material has the potential to be used to trace the origin of commodities. Whereas for timber, it has not been tested at relevant large scales, states the research.

New method

A new method for the timber tracing toolbox has been introduced which includes applying multi-element analysis to determine wood origin. “Here, we put this method to the test, by evaluating its tracing accuracy for three economically important tropical timbers: Azobé and Tali in Central Africa (22 sites) and Red Meranti on Borneo (nine sites).” adds Boeschoten.

Wood samples from 991 trees were measured using inductively coupled plasma mass spectrometry and element concentrations were analysed to chemically group similar sites and assess the accuracy of tracing samples to their origin (random forest models).

They noted down the GPS coordinates of the trees, which were located within forest concessions – government-designated forest areas, where logging is administered by a private entity.

At each site, 20–30 heartwood trees per timber species were sampled. These trees were located between 100 metres and 5 km apart, and were either standing or recently felled. The trees were of at least 30 cm diameter at breast height.

All samples were taken 10–20 cm into the tree. This resulted in a geo-located database of 179 Red meranti, 420 Azobé and 394 Tali samples. For every tree, soil variables at their growth locations were obtained from

The researchers found distinct spatial differences in chemical composition for all three timbers. In Central Africa, tracing accuracy for regional clusters was 86%-98%, with accuracy depending on the tracing question.

These clusters were 50–800 km apart and tracing accuracy was highest when combining the two timbers.

The results illustrated a high potential for multi-element analysis to be developed into a timber tracing tool that can identify the origin of multiple species and can do so at a within-country scale.

To reach this potential, reference databases need to cover wider geographic areas and represent more timbers.



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