Timber isoscapes. A case study in a mountain area in the Italian Alps

BACKGROUND: Local timber is still one of the main sources of work and income for mountain communities. However, illegal logging is a major cause of deforestation in many countries and has significant impacts on local communities and biodiversity. Techniques for tracing timber would provide a useful tool to protect local timber industries and contribute to the fight against illegal logging. Although considerable progress has been made in food traceability, timber provenance is still a somewhat neglected research area. Stable isotope ratios in plants are known to reflect geographical variations. This study reports accurate spatial distribution of δ(18)O and δ(2)H in timber from north-eastern Italy (Trentino) in order to trace geographical origin. METHODOLOGY AND PRINCIPAL FINDINGS: We tested the accuracy of four kriging methods using an annual resolution of δ(18)O and δ(2)H measured in Picea abies. Pearson’s correlation coefficients revealed altitude to be the most appropriate covariate for the cokriging model, which has ultimately proved to be the best method due to its low estimation error. CONCLUSIONS: We present regional maps of interpolated δ(18)O and δ(2)H in Picea abies wood together with the 95% confidence intervals. The strong spatial structure of the data demonstrates the potential of multivariate spatial interpolation, even in a highly heterogeneous area such as the Alps. We believe that this geospatial approach can be successfully applied on a wider scale in order to combat illegal logging.