Abstract

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 (R 2 = 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.

Highlights

  • Modeling permits the description of complex biogeochemical processes that occur in nature (Danis et al, 2012), as a suite of factors drive tree-growth response to climate

  • We compared the predictions of intra-annual treering formation dynamics estimated by the Vaganov–Shashkin (VS) model with field observations based on a 15 years-long monitoring of xylogenesis across a latitudinal gradient

  • Our results show that the model successfully describes the influence of climate variables on black spruce tree-ring growth

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Summary

Introduction

Modeling permits the description of complex biogeochemical processes that occur in nature (Danis et al, 2012), as a suite of factors drive tree-growth response to climate. Tools such as MAIDENiso, TreeRing2000, and the Vaganov–Shashkin (VS) model are mechanistic models for predicting tree growth that account for the endogenous and exogenous factors shaping tree growth and productivity (Vaganov et al, 2006; Danis et al, 2012). The VS model requires the smallest number of inputs These inputs include data that are widely used and available, such as tree-ring width chronologies and daily mean precipitation and temperature. The intra-annual predictions of the VS model continue to lack validation with long-term field observations that, unlike tree-ring chronologies, are scarce

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