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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.

Abstract In northern hardwood forests, tree markers select the trees to be harvested during logging operations using classification systems that assign harvest priorities based on the presence of a wide range of individual defects. According to the most recent advances in our understanding of the impact of defects on both tree vigour (the risk of mortality or decline in growth) and quality (the potential for recovering valuable sawlogs), tree markers should adopt a simpler classification system that considers fewer defects than the current operational practice, and they should prioritize the removal of trees with crown dieback. Since the probability of developing defects and dying increases substantially with tree diameter, tree markers should also favour the removal of larger trees that have maintained their quality. However, these recommendations were developed based on tree-level analyses. To provide further validation at the stand scale, we compared stand improvement and value recovery under three tree marking regimes: a new, simplified regime based on the recommendations above, and two regimes used in the province of Quebec, Canada. To do so, we conducted tree marking simulations and value recovery assessments in 14 managed stands distributed across the northern hardwood range of Quebec. Our results confirmed that the simplified tree marking regime not only facilitated stand improvement by removing a greater proportion of low-vigour trees, but also recovered significantly more value (17% on average) at the stand scale. By prioritizing the removal of trees with crown dieback, the simplified regime was superior at salvaging the current value of low-vigour trees before they die or decline in quality. Based on our results, we propose simplified and empirically-validated tree marking guidelines for northern hardwood forests.

Northern hardwoods are susceptible to a wide range of defects that can reduce the amount of sound wood with desirable qualities, such as the clear sapwood of sugar maple trees. Yet, the rate at which trees decline in quality due to the development of such defects has never been quantified in northern hardwood forests due to a dearth of repeat inventories that record the appearance of defects over time. As a result, it remains uncertain whether, and how, selection management reduces the probability of decline in quality. In this study, we quantify the rate at which trees decline in quality due to the development of defects, and we test several hypotheses regarding the influence of selection management on quality. Our results show that (1) the probability of decline in quality increases as trees grow larger; (2) crown dieback also increases the probability of decline in quality; (3) the probability of decline in quality is slightly lower in managed stands than in unmanaged stands, and (4) the probability of decline in quality increases with the mean annual temperature of the site. Finally, we combined our estimates of the probability of decline in quality with previous estimates of the probability of mortality to assess the overall risk associated with retaining trees of different species, sizes, and vigour profiles. The resulting metric can inform efforts to improve the management of northern hardwood forests by providing an integrated estimate of the risk that the value of a tree will be reduced, or eliminated, due to mortality or decline in quality.

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.

Multi-cohort forest management in northern hardwood stands may well be the best way to successfully regenerate tree species of intermediate shade tolerance, such as yellow birch (Betula alleghaniensis Britt.). The creation of large enough gaps in the canopy favors increased light availability within the opening, while soil scarification provides suitable germination seedbeds. Evidence of these methods’ success nonetheless remains mostly the purview of experimental studies rather than operational tests. In Quebec, Canada, the multi-cohort methods promoted include group selection cutting and patch cutting. The present study tested their implementation at an operational scale and over a large territory in both hardwood-dominated and mixedwood stands. We assessed their efficacy in promoting natural regeneration of commercial hardwood trees, notably yellow birch and sugar maple (Acer saccharum Marsh.). We conducted regeneration surveys at 2, 5, 10, and 15 years after harvest. Overall, group selection and patch cuttings were successful in regenerating the target species. Yellow birch, for instance, showed a mean stocking around 60% and a mean sapling density around 3400 stems ha−1 after 15 years. We compared several variables for measuring regeneration in early years, and found that the relative abundance, the stocking based on one stem per sampling unit, and the mean maximum height were good predictors of the relative presence of yellow birch and sugar maple in 15-year-old canopy openings. Using smaller sampling units (6.25 m2 rather than 25 m2) and waiting until year 5 may be more useful for making such predictions. In addition, there was an important turnover in vertical dominance in these openings. Non-commercial woody competitors were frequently dominant in early years but were often replaced by commercial hardwoods, notably yellow birch. We propose certain thresholds for assessing the success of post-harvest regeneration and for evaluating the need for a cleaning treatment.

The 2023 wildfire season in Québec set records due to extreme warm and dry conditions, burning 4.5 million hectares and indicating persistent and escalating impacts associated with climate change. This study reviews the unusual weather conditions that led to the fires, discussing their extensive impacts on the forest sector, fire management, boreal caribou habitats, and particularly the profound effects on First Nation communities. The wildfires led to significant declines in forest productivity and timber supply, overwhelming fire management resources, and necessitating widespread evacuations. First Nation territories were dramatically altered, facing severe air quality issues and disruptions. While caribou impacts were modest across the province, the broader ecological, economical, and social repercussions were considerable. To mitigate future extreme wildfire seasons, the study suggests changes in forest management practices to increase forest resilience and resistance, adapting industrial structures to changes in wood type harvested, and enhancing fire suppression and risk management strategies. It calls for a comprehensive, unified approach to risk management that incorporates the lessons learned from the 2023 fire season and accounts for ongoing climate change. The studyunderscores the urgent need for detailed planning and proactive measures to reduce the growing risks and impacts of wildfires in a changing climate.

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.