Scientists in Sweden have made a groundbreaking discovery that could revolutionize the timber industry in Europe. By combining traditional field work with cutting-edge computer modeling, researchers have found a way to trace a single beam of lumber back to the forest where it originated.
This new method, detailed in a recent paper in the prestigious journal Nature Plants, has the potential to significantly reduce the sale of illegal Russian timber in the European Union. Despite sanctions prohibiting the import of Russian lumber due to the conflict in Ukraine, birch, oak, pine, and other types of wood from Russia continue to find their way into European markets.
The innovative approach was put to the test last month in Belgium, where it successfully identified large shipments of illegal Russian lumber. The study involved analyzing the chemical composition of 900 wood samples collected from 11 countries in Eastern Europe. By inputting this data into a machine learning model, researchers were able to predict the geographic origin of the samples with impressive accuracy.
Lead author Victor Deklerck and his team from Preferred by Nature, a nonprofit organization based in Copenhagen, collected tree samples using a non-invasive method that extracts wood tissue without harming the tree. These samples were then analyzed for minerals and elements absorbed from the soil and rainfall, creating a unique “chemical fingerprint” for each tree.
The model developed by machine-learning expert Jakub Truszkowski at the University of Gothenburg was able to extrapolate chemical profiles for vast areas of forest across Eastern Europe, even where no samples had been taken. While the model was successful in identifying the origin of wood samples from Russia, it faced challenges with samples from neighboring countries like Belarus.
Despite these challenges, the researchers are optimistic about the potential of this technology to combat illegal logging and trade in other industries. The study serves as a proof of concept for using science to address real-world issues in a timely manner, and the researchers believe this approach could be applied to track a variety of other products, such as shrimp and palm oil.
Overall, this study highlights the power of combining traditional field work with advanced computer modeling to tackle complex issues and make sense of vast amounts of data. As Dr. Deklerck noted, the future of research lies in our ability to extract meaning from the ever-increasing amount of data available to us.
