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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 δ18O and δ2H 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 δ18O and δ2H 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 δ18O and δ2H 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.

Background: Tracking timber is necessary in order to prevent illegal logging and protect local timber production, but there is as yet no suitable analytical traceability method. Stable isotope ratios in plants are known to reflect geographical variations. In this study we analysed four stable isotope ratios in order to develop a model able to identify the geographic origin of Norway spruce in the European Alps., Methodology and Principal Findings: δ18O, δ2H, δ13C and δ15N were measured in bulk needles of Picea abies sampled in 20 sites in and around the European Alps. Environmental and spatial variables were found to be related to the measured isotope ratios. An ordinary least squares regression was used to identify the most important factor in stable isotope variability in bulk needles. Spatial autocorrelation was tested for all isotope ratios by means of Moran's I. δ18O, δ2H and δ15N values differed significantly between sites. Distance from the coast had the greatest influence on δ2H, while latitude and longitude were strongly related to δ18O. δ13C values did not appear to have any relationship with geographical position, while δ15N values were influenced by distance from the motorway. The regression model improved the explanatory power of the spatial and environmental variables. Positive spatial autocorrelations were found for δ18O and δ2H values., Conclusions: The δ 18O, δ2H and δ15N values in P. abies bulk needles are a suitable proxy to identify geographic origin as they vary according to geographical position. Although the regression model showed the explanatory variables to have significant power and stability, we conclude that our model might be improved by multivariate spatial interpolation of the δ 18O and δ2H values.