Forest ecosystems are threatened by unsustainable and illegal logging, which contributes to climate change by releasing greenhouse gasses, increases impoverishment of rural communities depending forest products, and creates market disadvantages for sustainable forestry products.  The timber from such unsustainable or illicit harvest is sold on domestic markets and overseas, where timber trade occurs in a complex network of forest owners, timber processing companies, and traders. Although various measures have been established to counter illegal logging and the subsequent trade, we lack practicable mechanisms to identify the origin of timber and wood products.  Knowledge about the place of timber harvest is indispensable to identifying the compliance of harvest with laws, regulations, and certification standards (including the US Lacey Act).  Existing tracking systems are usually based on marks externally applied to timber (e.g. ink, metal bands, barcodes) at the place of harvest.  These risk fraud since they can be applied to any piece of timber, and do not provide an independent check for timber origin.  Using eight nuclear microsatellites as DNA-fingerprints, we created an independent genetic reference database for determining the geographic origin of mahogany timber in Latin America.  Leaves were sampled from 1589 trees from 26 stands from Bolivia to Mexico.

Results/Conclusions

Preliminary analysis on 10 out of 26 populations sampled indicate there are more than 150 different genetic variants (alleles), strong genetic differentiation among the populations (Fst = 0.21, standardised F_ST of Hedrick = 0.65), and a strong correlation between genetic and spatial distances among stands (R²= 0.79).  In order to control for the declared origin of wood probes, we screened the same nuclear microsatellites as we did for the reference data base.  Based on multilocus allele frequencies, the reference data were then used in a Bayesian approach to assign or exclude individuals and groups to or from the declared population and country of origin.  The statistical power of the method was tested with self-assignment test which revealed a very high proportion of correctly assigned /excluded individuals and groups of individuals.  Using anonymous wood samples from timber traders we also demonstrated the power of DNA-fingerprints to determine geographic origin.  We are further testing the general applicability of this technique to the tropical timber trade.