A framework for tracing timber following the Ukraine invasion.

Area of Science:

• Environmental Science
• Forensic Science
• Geochemistry

Background:

• Scientific testing like stable isotope ratio analysis (SIRA) and trace element analysis (TEA) is vital for verifying plant origin, combating deforestation, and enforcing economic sanctions.
• Existing methods lack robust models that integrate SIRA and TEA for comprehensive origin verification and determination.

Purpose of the Study:

• To develop and validate integrated models combining SIRA and TEA for timber origin verification and harvest location determination.
• To create a large Eastern European timber reference database for key species (Betula, Fagus, Pinus, Quercus).
• To establish statistical tests for verifying claimed timber origins and probabilistic models for determining harvest locations.

Main Methods:

• Development of a large Eastern European timber reference database.
• Application of a statistical test for origin verification against claimed sources.
• Implementation of a probabilistic model using Gaussian processes, integrating SIRA, TEA, and genus distribution data for location determination.

Main Results:

• The verification method successfully rejects 40-60% of simulated false origin claims, with a low rate of rejecting correct claims.
• The determination method predicts timber harvest locations with an accuracy of 180 to 230 km.
• Demonstrated effectiveness of combining multiple data types with probabilistic modeling for timber traceability.

Conclusions:

• The developed integrated approach significantly enhances the ability to verify timber origin and determine harvest locations.
• This methodology provides a powerful tool for regulatory bodies to combat illegal timber trade and enforce sanctions.
• Combining diverse datasets and advanced statistical modeling is key to improving timber provenance investigations.