Daniela Diaconu, Marc Wassenberg, Heinrich Spiecker. Variability of European beech wood density as influenced by interactions between treering growth and aspect[J]. Forest Ecosystems, 2016, 3(1): 6-6. DOI: 10.1186/s40663-016-0065-8
Citation: Daniela Diaconu, Marc Wassenberg, Heinrich Spiecker. Variability of European beech wood density as influenced by interactions between treering growth and aspect[J]. Forest Ecosystems, 2016, 3(1): 6-6. DOI: 10.1186/s40663-016-0065-8

Variability of European beech wood density as influenced by interactions between treering growth and aspect

  •   Background  Wood density is considered to be the most important predictor of wood quality but despite its importance, diffuse-porous tree species have been the subject of only a limited number of studies. The importance of European beech forests for Central Europe calls for profound research to examine the potential impact of a warmer climate on the quality of beech timber.
      Methods  In this study we analysed the influence of tree-ring width and tree-ring age on the wood density of beech, and whether the wood density response to these two parameters is modified by aspect. A linear mixed-effects model for wood density was constructed for mean density data measured with high frequency densitometry on stem discs from 72 beech trees sampled from two different aspects (northeast -NE and southwest -SW) of a valley in southwestern Germany.
      Results  Part of the variability of mean annual wood density was explained by cambial age: an increase in cambial age resulted in an increase in mean wood density. Tree-ring width and aspect had only a small influence on wood density. Wood density on the SW aspect was lower than on the NE with a difference of approximately 0.006 g/cm3. The between-tree variability was very high.
      Conclusions  The significant interaction between cambial age and aspect reflects the importance of site conditions at older tree ages: with increasing cambial age the difference between aspects becomes stronger. Our results give a better understanding of the importance of site conditions on the wood quality
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