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Climate change projections forecast most significant impacts on high-latitude forest ecosystems. Particularly, climate warming in boreal regions should increase fire severity and shorten its return interval. These processes can change the dynamics of boreal forests as younger stands become more dominating with a shift from gymnosperm to angiosperm. However, despite angiosperm’s phenological and physiological traits have a high potential for ecophysiological and dendroclimatological studies in Siberia, they have been rarely investigated due to their short-term lifespan in comparison with gymnosperm. Modeling tree growth is a common way to understand tree growth responses to environmental changes since it allows using available experiment or field data to interpret observed climate–growth relationships based on the biological principles. In our study, we applied the process-based Vaganov–Shashkin (VS) model of tree-ring growth via a parameterization approach VS-oscilloscope for the first time to an angiosperm tree species (Betula pubescens Ehrh.) from continuous permafrost terrain to understand its tree-radial growth dynamic. The parameterization of the VS model provided highly significant positive correlations (p < 0.05) between the simulated growth curve and initial tree-ring chronologies for the period 1971–2011 and displayed the average duration of the growing season and intra-seasonal key limiting factors for xylem formation. Modeled result can be valid at the regional scale for remote birch stands, whereas, justification of the local non-climatic input data of the model provided precise site-specific tree growth dynamic and their substantiated responses to driving factors.

Significant alterations of cambial activity might be expected due to climate warming, leading to growing season extension and higher growth rates especially in cold-limited forests. However, assessment of climate-change-driven trends in intra-annual wood formation suffers from the lack of direct observations with a timespan exceeding a few years. We used the Vaganov-Shashkin process-based model to: (i) simulate daily resolved numbers of cambial and differentiating cells; and (ii) develop chronologies of the onset and termination of specific phases of cambial phenology during 1961–2017. We also determined the dominant climatic factor limiting cambial activity for each day. To asses intra-annual model validity, we used 8 years of direct xylogenesis monitoring from the treeline region of the Krkonoše Mts. (Czechia). The model exhibits high validity in case of spring phenological phases and a seasonal dynamics of tracheid production, but its precision declines for estimates of autumn phenological phases and growing season duration. The simulations reveal an increasing trend in the number of tracheids produced by cambium each year by 0.42 cells/year. Spring phenological phases (onset of cambial cell growth and tracheid enlargement) show significant shifts toward earlier occurrence in the year (for 0.28–0.34 days/year). In addition, there is a significant increase in simulated growth rates during entire growing season associated with the intra-annual redistribution of the dominant climatic controls over cambial activity. Results suggest that higher growth rates at treeline are driven by (i) temperature-stimulated intensification of spring cambial kinetics, and (ii) decoupling of summer growth rates from the limiting effect of low summer temperature due to higher frequency of climatically optimal days. Our results highlight that the cambial kinetics stimulation by increasing spring and summer temperatures and shifting spring phenology determine the recent growth trends of treeline ecosystems. Redistribution of individual climatic factors controlling cambial activity during the growing season questions the temporal stability of climatic signal of cold forest chronologies under ongoing climate change.

New insights into the intra-annual dynamics of tree-ring formation can improve our understanding of tree-growth response to environmental conditions at high-resolution time scales. Obtaining this information requires, however, a weekly monitoring of wood formation, sampling that is extremely time-intensive and scarcely feasible over vast areas. Estimating the timing of cambial and xylem differentiation by modeling thus represents an interesting alternative for obtaining this important information by other means. Temporal dynamics of cambial divisions can be extracted from the daily tree-ring growth rate computed by the Vaganov–Shashkin (VS) simulation model, assuming that cell production is tightly linked to tree-ring growth. Nonetheless, these predictions have yet to be compared with direct observations of wood development, i.e., via microcoring, over a long time span. We tested the performance of the VS model by comparing the observed and predicted timing of wood formation in black spruce [Picea mariana (Mill.)]. We obtained microcores over 15 years at 5 sites along a latitudinal gradient in Quebec (Canada). The measured variables included cell size and the timing of cell production and differentiation. We calibrated the VS model using daily temperature and precipitation recorded by weather stations located on each site. The predicted and observed timing of cambial and enlarging cells were highly correlated (R2 = 0.8); nonetheless, we detected a systematic overestimation in the predicted timing of cambial cells, with predictions delayed by 1–20 days compared with observations. The growth rate of cell diameter was correlated with the predicted growth rate assigned to each cambial cell, confirming that cell diameter developmental dynamics have the potential to be inferred by the tree-ring growth curve of the VS model. Model performances decrease substantially in estimating the end of wood formation. The systematic errors suggest that the actual relationships implemented in the model are unable to explain the phenological events in autumn. The mismatch between the observed and predicted timing of wood formation in black spruce within our study area can be reduced by better adapting the VS model to wet sites, a context for which this model has been rarely used.