Cargando…

Oxygen and Hydrogen Stable Isotope Ratios of Bulk Needles Reveal the Geographic Origin of Norway Spruce in the European Alps

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 isotop...

Descripción completa

Detalles Bibliográficos
Autores principales: Gori, Yuri, Wehrens, Ron, La Porta, Nicola, Camin, Federica
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4351073/
https://www.ncbi.nlm.nih.gov/pubmed/25742601
http://dx.doi.org/10.1371/journal.pone.0118941
Descripción
Sumario: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: δ(18)O, δ(2)H, δ(13)C and δ(15)N 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. δ(18)O, δ(2)H and δ(15)N values differed significantly between sites. Distance from the coast had the greatest influence on δ(2)H, while latitude and longitude were strongly related to δ(18)O. δ(13)C values did not appear to have any relationship with geographical position, while δ(15)N 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 δ(18)O and δ(2)H values. CONCLUSIONS: The δ (18)O, δ(2)H and δ(15)N 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 (18)O and δ(2)H values.