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Performing a complete silvicultural diagnosis before a silvicultural treatment generally requires assessing the state of regeneration with the help of an inventory by sampling, particularly for stands dominated by sugar maple (Acer saccharum Marsh.) or yellow birch (Betula alleghaniensis Britt.), in which partial cuts are recommended. This inventory may then be compared to the standard or used in a growth model for saplings (trees for which the diameter measured at 1.3 m above the ground (DBH) varies from 1.1 cm to 9.0 cm). Some of these tools are based on sapling density, while others are based on the stocking of the saplings or on the stocking of total regeneration (combining saplings and seedlings with a DBH ≤ 1.0 cm). We assessed the number of plots required to estimate the density and the stocking of saplings with a given margin of error in 28 stands. The results show that more plots are required than usual in practice to inventory sapling density. The stocking is much easier to estimate precisely.
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The temperate mixedwood forests of eastern North America have been managed by partial cutting for several decades. To ensure that regeneration contributes to replacing the commercial-size stems that are removed by partial cutting, forest managers need to anticipate how saplings (i.e., regenerating trees with a diameter at breast height >1.0 cm) develop in terms of number and diameter. Using up to 20 years of monitoring data from three study sites, we developed a transition matrix model to predict the future number of saplings and their diameter distribution for mixed yellow birch ( Betula alleghaniensis Britton) – conifer stands. Our results show that partial cutting allowed yellow birch, red maple ( Acer rubrum L.), red spruce ( Picea rubens Sarg.), and balsam fir ( Abies balsamea (L.) Mill.) saplings to reach merchantable size faster and in greater numbers than in untreated control plots. We also found that fewer hardwood saplings (yellow birch and red maple) than softwood saplings (red spruce and balsam fir) were required to produce 1 m 2 ·ha −1 of merchantable basal area after 20–40 years. Finally, our model provides a tool for forest managers to predict sapling development in mixed hardwood and softwood stands over a full cutting cycle.
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Individual tree recruitment is an important element needed to understand stand dynamics, as it influences both stand composition and productivity. Forest growth simulators usually include recruitment models. The quality of recruitment predictions can have long-term impacts on estimations of forest growth, ecosystem health and the commercial utility of managed forests. The main objective of this study was to develop a recruitment model for commercial-size trees (i.e., trees with a diameter at breast height > 9 cm) of 10 species groups using different dendrometric and environmental variables. The resulting model will be included in a growth simulator used to support forest management planning. We hypothesized that accounting for sapling density as a covariate would improve the recruitment model's predictive performance. Using empirical data from periodically measured permanent sample plots (1982–2019) located throughout the managed mixed hardwood forests of Quebec, we constructed models with and without sapling-related covariates and compared them on the basis of cross-validation model performance statistics. Our results show that including sapling density significantly improved model performance. From this, we conclude that adding sapling density as a covariate can significantly improve a recruitment model's predictive power for eastern mixed hardwood forests.