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The evolutionary dynamics of tree species are influenced by their specific climatic environments, and their ability to persist is determined by adaptive strategies such as broad climate tolerance, phenotypic plasticity or genetic differentiation. Biogeographical predictions indicate that populations located at the edges of their ranges are more likely to experience heightened vulnerability to climatic fluctuations due to approaching tolerance limits. However, if local phenotypic acclimation or genetic adaptation has taken place, trees near the edge of their range could demonstrate comparable sensitivity to freeze and drought as the rest of the sampled population. Nevertheless, there remains uncertainty regarding the extent of developmental and evolutionary adjustments in climate sensitivity across the entire ranges of many tree species.Here, we document the biogeography of tree growth sensitivity to freeze and soil water and vapour pressure deficits during 1950–2018 using an extensive multi‐species tree‐ring dataset of 35,784 trees at 4535 sites covering boreal, temperate conifer and temperate deciduous forests of Canada. We quantify the relationships between tree radial growth increment and seasonal climate variables and explore factors driving the observed patterns of annual growth and climate sensitivity such as species, regional climate and local site conditions, and tree age and size.Freeze and drought had widespread impacts on tree growth that were contingent on the presence of focal species in interaction with tree size. An indirect growth thermal limitation towards cold/wet edges, occurring through the site moisture conditions, was observed in seven widespread species (e.g. Picea glauca, Picea mariana and Larix laricina). Moreover, six species had negative drought impacts more strongly expressed towards their warm/dry edges (e.g. Abies balsamea, Betula papyrifera and Pseudotsuga menziesii). However, widespread Picea, Pinus and Populus species showed no indication of increased sensitivity to soil water conditions at these edges.Synthesis. Our findings support the idea of evolutionary or acclimatization adjustments in the development of populations in response to long‐term climate conditions experienced in their respective locations. This underscores the importance of incorporating phenotypic and genomic data into future analyses of climate change impacts, which would enhance our ability to predict potential ecological shifts. [ABSTRACT FROM AUTHOR]

Under climate change circumstances, increasing studies have reported the temporal instability of tree growth responses to climate, which poses a major challenge to linearly extrapolating past climate and future growth dynamics using tree‐ring data. Space‐for‐time substitution (SFTS) is a potential solution to this problem that is widely used in the dendrochronology field to project past or future temporal growth response trajectories from contemporary spatial patterns. However, the projected accuracy of the SFTS in the climate effects on tree growth remains uncertain. Here, we empirically test the SFTS method by comparing the effect of spatial and temporal climate variations on climate responses of white spruce (Picea glauca), which has a transcontinental range in North America. We first applied a response surface regression model to capture the variations in growth responses along the spatial climate gradients. The results showed that the relationships between growth and June temperature varied along spatial climate gradients in a predictable way. And their relationships varied mainly along with local temperate condition. Then, the projected correlation coefficients between growth and climate using SFTS were compared against the observed. We found that the growth response changes caused by spatial versus temporal climate variations showed opposite trends. Moreover, the projected correlation coefficients using the SFTS were significantly lower than the observed. This finding suggests that applying the SFTS to project the growth response of white spruce might lead to an overestimation of the degree of tree maladaptation in future climate scenarios. And the overestimation is likely to get weaker from Alaska and Yukon Territory in the west to Quebec in the east. Although this is only a case study of the SFTS method for projecting tree growth response, our findings suggest that direct application of the SFTS method may not be applicable to all regions and all tree species. [ABSTRACT FROM AUTHOR]

With climate change, increasingly intense and frequent drought episodes will be affecting water availability for boreal tree species, prompting tree breeders and forest managers to consider adaptation to drought stress as a priority in their reforestation efforts. We used a 19‐year‐old polycross progeny test of the model conifer white spruce (Picea glauca) replicated on two sites affected by distinct drought episodes at different ages to estimate the genetic control and the potential for improvement of drought response in addition to conventional cumulative growth and wood quality traits. Drought response components were measured from dendrochronological signatures matching drought episodes in wood ring increment cores. We found that trees with more vigorous growth during their lifespan resisted better during the current year of a drought episode when the drought had more severe effects. Phenotypic data were also analyzed using genomic prediction (GBLUP) relying on the genomic relationship matrix of multi‐locus gene SNP marker information, and conventional analysis (ABLUP) based on validated pedigree information. The accuracy of predicted breeding values for drought response components was marginally lower than that for conventional traits and comparable between GBLUP and ABLUP. Genetic correlations were generally low and nonsignificant between drought response components and conventional traits, except for resistance which was positively correlated to tree height. Heritability estimates for the components of drought response were slightly lower than for conventional traits, but similar single‐trait genetic gains could be obtained. Multi‐trait genomic selection simulations indicated that it was possible to improve simultaneously for all traits on both sites while sacrificing little on gain in tree height. In a context of rapid climate change, our results suggest that with careful phenotypic assessment, drought response may be considered in multi‐trait improvement of white spruce, with accelerated screening of large numbers of candidates and selection at young age with genomic selection. [ABSTRACT FROM AUTHOR]

Increasing air temperatures and changing precipitation patterns due to climate change can affect tree growth in boreal forests. Periodic insect outbreaks affect the growth trajectory of trees, making it difficult to quantify the climate signal in growth dynamics at scales longer than a year. We studied climate‐driven growth trends and the influence of spruce budworm (Choristoneura fumiferana Clem.) outbreaks on these trends by analyzing the basal area increment (BAI) of 2058 trees of Abies balsamea (L.) Mill., Picea glauca (Moench) Voss, Thuja occidentalis L., Populus tremuloides Michx., and Betula papyrifera Marsh, which co‐occurs in the boreal mixedwood forests of western Quebec. We used a generalized additive mixed model (GAMM) to analyze species‐specific trends in BAI dynamics from 1967 to 1991. The model relied on tree size, cambial age, degree of spruce budworm defoliation, and seasonal climatic variables. Overall, we observed a decreasing growth rate of the spruce budworm host species, A. balsamea and P. glauca between 1967 and 1991, and an increasing growth rate for the non‐host, P. tremuloides, B. papyrifera, and T. occidentalis. Our results suggest that insect outbreaks may offset growth increases resulting from a warmer climate. The observation warrants the inclusion of the spruce budworm defoliation into models predicting future forest productivity. [ABSTRACT FROM AUTHOR]

Merging robust statistical methods with complex simulation models is a frontier for improving ecological inference and forecasting. However, bringing these tools together is not always straightforward. Matching data with model output, determining starting conditions, and addressing high dimensionality are some of the complexities that arise when attempting to incorporate ecological field data with mechanistic models directly using sophisticated statistical methods. To illustrate these complexities and pragmatic paths forward, we present an analysis using tree‐ring basal area reconstructions in Denali National Park (DNPP) to constrain successional trajectories of two spruce species (Picea mariana and Picea glauca) simulated by a forest gap model, University of Virginia Forest Model Enhanced—UVAFME. Through this process, we provide preliminary ecological inference about the long‐term competitive dynamics between slow‐growing P. mariana and relatively faster‐growing P. glauca. Incorporating tree‐ring data into UVAFME allowed us to estimate a bias correction for stand age with improved parameter estimates. We found that higher parameter values for P. mariana minimum growth under stress and P. glauca maximum growth rate were key to improving simulations of coexistence, agreeing with recent research that faster‐growing P. glauca may outcompete P. mariana under climate change scenarios. The implementation challenges we highlight are a crucial part of the conversation for how to bring models together with data to improve ecological inference and forecasting. [ABSTRACT FROM AUTHOR]