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<p>Adapting forest management to future climate conditions requires an understanding of how environmental factors affect wood quality. Wood traits like the microfibril angle (MFA), that influences tree stem stiffness and strength, are sensitive to changes in environmental conditions. Our study investigated the relationship between environmental variables and MFA in mature black spruce (<i>Picea mariana</i>) and jack pine (<i>Pinus banksiana</i>). Five black spruce and five jack pine trees were sampled from the boreal forest of Quebec, Canada. The MFA measurements were obtained with Silviscan-3. Generalized additive mixed models were used to link MFA to environmental data obtained from ground plots established by the FLUXNET Research Network for the period of 2004–2010. The model for black spruce described MFA as a function of wind direction in the previous month, Standardized Precipitation-Evapotranspiration Index (SPEI) and minimum depth to water table, explaining 49.6% of the MFA deviance. For jack pine, mean soil temperature and SPEI were the best predictors, with the model explaining 82.2% of MFA deviance. Nonlinear effects of day of year and tree-specific responses highlighted seasonal and individual variability. These findings provide insights for forest management and tree improvement programmes targeting climate resilience and wood quality in boreal forests.</p>

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Microfibril angle as an environmental fingerprint in wood

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月7日

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  • Mariana Hassegawa,
  • Philippe Riel,
  • Lisa Wingate,
  • Alexis Achim

摘要

Adapting forest management to future climate conditions requires an understanding of how environmental factors affect wood quality. Wood traits like the microfibril angle (MFA), that influences tree stem stiffness and strength, are sensitive to changes in environmental conditions. Our study investigated the relationship between environmental variables and MFA in mature black spruce (Picea mariana) and jack pine (Pinus banksiana). Five black spruce and five jack pine trees were sampled from the boreal forest of Quebec, Canada. The MFA measurements were obtained with Silviscan-3. Generalized additive mixed models were used to link MFA to environmental data obtained from ground plots established by the FLUXNET Research Network for the period of 2004–2010. The model for black spruce described MFA as a function of wind direction in the previous month, Standardized Precipitation-Evapotranspiration Index (SPEI) and minimum depth to water table, explaining 49.6% of the MFA deviance. For jack pine, mean soil temperature and SPEI were the best predictors, with the model explaining 82.2% of MFA deviance. Nonlinear effects of day of year and tree-specific responses highlighted seasonal and individual variability. These findings provide insights for forest management and tree improvement programmes targeting climate resilience and wood quality in boreal forests.