期刊
CANADIAN JOURNAL OF FOREST RESEARCH
卷 51, 期 10, 页码 1512-1520出版社
CANADIAN SCIENCE PUBLISHING
DOI: 10.1139/cjfr-2020-0475
关键词
paper birch; wood discoloration; wood properties; regional variation; climate
类别
资金
- Ministere des Forets, de la Faune et des Parcs du Quebec
This study investigated wood discoloration in paper birch trees across Quebec, Canada, and found that the impact of discoloration on trees was limited, with regional variations observed. Higher proportions of discolored basal area were found in warmer and drier southwestern areas, while lower proportions were found in eastern regions with more snowfall. This research confirms the feasibility of large-scale mapping of wood discoloration in standing trees based on forest inventory and climate data.
Wood discoloration was investigated in 721 paper birch (Betula papyrifera Marsh.) trees from 146 sites across the managed forest of Quebec, Canada. Discoloration was present at breast height in 85% of trees, but its impact was limited in terms of tree basal area and volume, with proportions of 6.4% and 3.6%, respectively. These two measures were strongly correlated. Discoloration changed wood appearance but had no effect on microfibril angle and modulus of elasticity. Discolored wood was nevertheless denser, probably due to the accumulation of colored extractives. Predictive models were also developed and applied to 415 711 paper birch trees from 51 689 inventory plots across the province to study regional variation. Higher proportions of discolored basal area were obtained in the southwestern areas of the province where the climate is warmer and drier. In these areas, paper birch trees are larger and, likely, support bigger branches which can cause larger columns of discoloration when broken. Lower proportions were found in eastern regions where snowfall is more abundant. Smaller, more flexible branches in trees growing in these areas could explain this result. This study confirms the feasibility of large-scale mapping of wood discoloration in standing trees based on forest inventory and climate data.
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