The study presents an innovative framework that combines stable isotope ratio analysis (SIRA) and trace element analysis (TEA) to develop models for the verification and determination of timber origin. Its results showcase the power of combining different data types and probabilistic modelling to identify and scrutinize timber harvest location claims. Here are the primary contributions of the research:

1. Advanced Analytical Techniques: The integration of SIRA and TEA enables the creation of a detailed and reliable database of timber characteristics. These techniques allow for the precise identification of the geographic origin of timber, enhancing the ability to trace its provenance accurately.

   
   

2. Development of Statistical Models: The research introduces sophisticated statistical models that can verify timber samples against their claimed origins. This capability is essential for distinguishing between legitimate and false origin claims, ensuring that timber from sanctioned regions does not enter the market under false pretenses.

   
   

3. Probabilistic Origin Determination: Utilizing AI and probabilistic modeling, the framework predicts the harvest location of timber within within 180 to 230 km of true location. This tool significantly improves the precision of origin determination, making it a valuable asset for enforcement agencies and the timber industry.