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The formation of a single species, recalcitrant understory vegetation layer can limit tree regeneration and, in the long term, modify the composition of forests. Few studies have investigated how recalcitrant vegetation influences competition for water resources although the formation of a dense understory is likely to modify the forest water balance. In eastern North American hardwood forests, the development of a dense understory layer of American beech (Fagus grandifolia) has been observed in stands dominated by sugar maple (Acer saccharum), a phenomenon that shares many characteristics associated with recalcitrant vegetation. Given that water availability is generally negatively correlated with stand density, we hypothesized that the formation of a dense understory beech layer increased competition for water resources, thus leading to reduced water use by sugar maple trees in beech‐dominated stands. Using thermal dissipation sensors, we measured sap flux density (Fd) of two sugar maple trees at three beech‐dominated sites and three control sites. During the growing season, Fd of sugar maple trees was significantly larger at beech‐dominated sites compared to control sites, indicating a greater rate of water use by sugar maples in stands with a dense understory beech layer. We provide two hypotheses to explain our results at the tree scale: (i) reduced cover by forest floor vegetation could limit transpiration by this layer, thus allowing increased water availability to supply transpiration by overstory trees, or (ii) increased tree transpiration rate could be a mechanism to satisfy nutrient requirements in beech‐dominated stands often associated with lower soil fertility. [ABSTRACT FROM AUTHOR]

Process-based forest growth models with spatially explicit representation are relevant tools to investigate innovative silviculture practices and/or climate change effects because they are based on key ecophysiological processes and account for the effects of local competition for resources on tree growth. Such models are rare and are often calibrated for a very limited number of species and rarely for mixed and/or uneven-aged stands, and none are suitable for the temperate forests of Québec. The aim of this study was to calibrate and evaluate HETEROFOR (HETEROgeneous FORest), a process-based and spatially explicit model based on resource sharing, for 23 functionally diverse tree species in forest stands with contrasting species compositions and environmental conditions in southern Quebec. Using data from the forest inventory of Quebec, we evaluated the ability of HETEROFOR to predict the short-term growth (5–16 years) of these species at the tree and stand levels and the long-term dynamics (120 years) of red and sugar maple stands. The comparison between the prediction quality of the calibration and evaluation datasets showed the robustness of the model performance in predicting individual-tree growth. The model reproduced correctly the individual basal area increment (BAI) of the validation dataset, with a mean Pearson's correlation coefficient of 0.56 and a mean bias of 18 %. Our results also highlighted that considering tree position is of importance for predicting individual-tree growth most accurately in complex stands with both vertically and horizontally heterogeneous structures. The model also showed a good ability to reproduce BAI at the stand level, both for monospecific (bias of - 3.7 %; Pearson's r=0.55) and multi-species stands (bias of - 9.1 %; Pearson's r=0.62). Long-term simulations of red maple and sugar maple showed that HETEROFOR was able to accurately predict the growth (basal area and height) and mortality processes from the seedling stage to the mature stand. Our results suggest that HETEROFOR is a reliable option to simulate forest growth in southern Quebec and to test new forestry practices under future climate scenarios. [ABSTRACT FROM AUTHOR]

An increase in the frequency and magnitude of drought events threatens the health of forests and the economic, ecological, and societal services they provide. It has been widely demonstrated that trees undergoing a succession of stresses may accumulate lesions that in turn lead to a decrease in their vigor and eventually to death. However, recent studies have shown that a nonlethal stress should also initiate a stress memory, which triggers a faster and stronger plant defensive response when a new stress occurs. Although this mechanism is well understood in many herbaceous plants, a better understanding in trees is needed. The aim of our study was to explore the capacity of two forest tree species to develop a stress memory. A greenhouse experiment was conducted to evaluate the tree seedlings' vigor after one or two consecutive droughts separate from a rehydration period during the same growing season. No stress memory pattern was observed for the two tree species as, on the contrary, we even observed a stress accumulation pattern in sugar maple. It remains possible that some individuals in our study developed stress memory, but that we were not able to detect it. The fine‐tuning of experimental parameters and the conducting of longitudinal studies would be helpful to detect individual capacity in stress memory activation. [ABSTRACT FROM AUTHOR]

Process-based forest growth models with spatially explicit representation are a relevant tool to investigate innovative silviculture practices and/or climate change effects because they are based on key ecophysiological processes and account for the effects of local competition for resources on tree growth. Such models are rare, often calibrated for a very limited number of species and rarely in mixed and/or uneven-aged stands, and none are suitable for the temperate forests of Québec. The aim of this study was to calibrate and evaluate HETEROFOR, a process-based and spatially explicit model based on resource sharing, for 23 functionally diverse tree species in forest stands with contrasting species compositions and environmental conditions in southern Québec. Using data from the forest inventory of Québec, we evaluated the ability of HETEROFOR to predict the short-term growth (5-16 years) of these species at the tree and stand levels, and the long-term dynamics (120 years) of red and sugar maple stands. The comparison between the prediction quality for the calibration and evaluation datasets showed the robustness of the model performance in predicting individual tree growth. The model reproduced correctly individual basal area increment (BAI) of the validation dataset with a mean Pearson’s correlation coefficient of 0.56 and a mean bias of 18%. Our results also highlighted that considering tree position is of importance for predicting individual tree growth most accurately in complex stands with both vertical and horizontal heterogeneous structure. The model also showed a good ability to reproduce BAI at the stand level, both for monospecific (bias of -3.7%, Pearson’s r = 0.55) and multi-species stands (bias of -9.1%, Pearson’s r = 0.62). Long-term simulations of red maple and sugar maple showed that HETEROFOR was able to accurately predict the growth (basal area and height) and mortality processes from the seedling stage to the mature stand. Our results suggest that HETEROFOR is a reliable option to simulate forest growth in southern Québec and test new forestry practices under future climate scenarios. [ABSTRACT FROM AUTHOR]