A new method for the timber tracing toolbox: applying multi-element analysis to determine wood origin

Abstract

To effectively reduce illegal timber trade, law enforcers need forensic methods to independently verify claims of wood origin. Multi-element analysis of traded plant material has the potential to be used to trace the origin of commodities, but for timber it has not been tested at relevant large scales. 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 (9 sites). Wood samples from 991 trees were measured using Inductively Coupled Plasma Mass Spectrometry and element concentrations were analysed to chemically group similar sites (clustering) and assess accuracy of tracing samples to their origin (Random Forest models). For all three timbers, we found distinct spatial differences in chemical composition. In Central Africa, tracing accuracy was 86%–98% for regional clusters of chemically similar sites, with accuracy depending on the tracing question. These clusters were 50–800 km apart and tracing accuracy was highest when combining the two timbers. Tracing accuracy of Red Meranti on Borneo was 88% at the site level. This high accuracy at a small scale may be related to the short distances at which differences in soil type occur on Borneo. A blind sample analysis of 46 African timber samples correctly identified the origin of 70%–72% of the samples, but failed to exclude 70% of the samples obtained from different species or outside the study area. Overall, these results illustrate a high potential for multi-element analysis to be developed into a timber tracing tool which can identify origin for 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.

A framework for tracing timber following the Ukraine invasion

“…Determination methods can leverage larger data sets from wider ranges to infer the likely harvest location. Elemental tracing outperforms SIRA when looking at finer spatial scales 15 , and previous work using TEA to trace timber sample origin could differentiate concessions 50 km apart 15 . Our best TEA model has an average error of 199.82 km.…”

“…Our best TEA model has an average error of 199.82 km. It is crucial to highlight that, unlike in the study by Boeschoten et al 15 , our research treats the determination problem as a regression problem within a continuous space compared to a classification problem with fixed options.…”

“…Although SIRA has been successful in origin prediction, its wider applicability is limited by the lack of (1) extensive reference data and (2) resolving power at small spatial scales 14 . Trace element analysis (TEA) has been proposed as an alternative 15 , as the trace element composition of forest biomass reflects the bio-available and mobilized macro- and micro-nutrients present in soils 16 , providing a spatial signal to trace timber back to harvest location. Empirical studies performed in Africa and Borneo differentiated timber from country or cluster/site level origins based on TEA 16 , 17 .…”

“…Studies using SIRA or TEA to address timber origin queries have framed the determination problem as a classification task 15 , 16 , 18 , wherein the objective is predicting the origin of a sample from a finite set of defined locations. While this approach may yield satisfactory results in scenarios with limited spatial range, it introduces several challenges once the range of interest expands.…”

Timber tales: tracing the origin and species identity of African timbers using plastid genomes

“…Therefore, we conclude that the sequence data generated through the strategy employed here effectively allows verification of taxonomic claims. Correctly excluding blind samples from other species was identified as a barrier for the application of multi-element analysis for timber tracing of Tali and Azobé (Boeschoten et al, 2023). Our results show that using DNA barcoding, these barriers can be overcome, after which multi-element analyses could be performed to verify geographic origin.…”