Modeled Tracheidograms Disclose Drought Influence on Pinus sylvestris Tree-Rings Structure From Siberian Forest-Steppe

Popkova, Margarita; Vaganov, Еugene А.; Shishov, Vladimir V.; Babushkina, Еlena А.; Rossi, Sergio; Fonti, Marina V.; Fonti, Patrick

doi:10.3389/fpls.2018.01144

Cited by 45 publications

(51 citation statements)

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“…Addition of a cell growth module could produce cell anatomical simulations that could be compared to emerging observations (c.f. Fonti et al, 2010;Cuny et al, 2015;von Arx et al, 2016;Ziaco et al, 2016;Popkova et al, 2018). Finally, the model may also be ported to other open source languages, as has been done for the monthly resolution 'lite' version of the Vaganov-Shashkin model (VSL;Tolwinski-Ward et al, 2011 Vaganov et al (2011).…”

Section: Discussionmentioning

confidence: 99%

An interpreted language implementation of the Vaganov–Shashkin tree-ring proxy system model

et al. 2020

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We describe the implementation of the Vaganov-Shashkin tree-ring growth model (VSM) in MATLAB. VSM, originally written in Fortran, mimics subdaily and daily resolution processes of cambial growth as a function of soil moisture, air temperature, and insolation, with environmental forcing modeled as the principle of limiting factors. The re-implementation in a high level interpreted language, while sacrificing speed, provides opportunities to systematically evaluate model parameters, generate large ensembles of simulated tree-ring chronologies, and embed proxy system modeling within data assimilation approaches to climate reconstruction. We provide a versioned code repository and examples of model applications which permit process-level understanding of tree ring width variations in response to environmental variations and boundary conditions.

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Section: Discussionmentioning

confidence: 99%

An interpreted language implementation of the Vaganov–Shashkin tree-ring proxy system model

et al. 2020

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“…The core of tree-ring growth is cambial activity, and the VS model has been developed to establish not only the start and end of the growing season but also the timing of xylem cell production and the final size of these cells (Popkova et al, 2018). This particular aspect of the VS model has heightened interest in its application with the abundance of literature discussing intra-annual tree-ring dynamics within the cambial zone and xylem; these dynamics are related to both endogenous (developmental patterns and hormones) and exogenous (weather and seasonality) factors (Buttò et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Comparing the Cell Dynamics of Tree-Ring Formation Observed in Microcores and as Predicted by the Vaganov–Shashkin Model

et al. 2020

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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 treering 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

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“…The model verification shows significant similarity (R=0.55, S=70%, p<0.001) between simulated and actual chronologies over 1936-1959. To provide the best fit of simulated tree-growth values with the actual treering chronology, the adjustment parameters of the model were obtained (see more in [3], [15]).…”

Section: Results and Conclusionmentioning

confidence: 99%

“…A significant number of papers convincingly show that the anatomical tree-ring structure reflects the seasonal dynamics of external conditions, for instance, intra annual density fluctuations, frost rings, or multiple rings, reduction of cell number in the latewood as a reaction to the early growth cessation [2].The main anatomical characteristics of tree-ring structure, e.g. number of cells, radial cell size and cell walls thickness, are closely related to the kinetic characteristics of seasonal tree-ring formation, especially to the kinetics of cell production [3]. There are a number of publications disclosing an impact of cell differentiation rate on anatomical structure of tree rings [4], [5].…”

Section: Introductionmentioning

confidence: 99%

“…The calculated growth rate curve can be interpreted as an impact of climate on seasonal growth variability excluding other external and internal factors forcing tree-ring growth. The modeling is an extremely important step because the simulated daily tree-ring growth rate Gr(t) is a basis to evaluate intra-seasonal variation of new cells [3]. This paper presents an innovative two-steps approach combining the VS-model used for growth rate simulation and an automatic timing procedure of cell production.…”

Section: Introductionmentioning

confidence: 99%

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Timing of Cell Production in Tree Rings: An Automatic Two-Step Procedure in R

Belousova¹

2018

SGEM International Multidisciplinary Scientific GeoConference EXPO Proceedings

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The study of intra-annual dynamic of wood formation is one of the most progressive and fast-growing fields in plant sciences. The main anatomical characteristics of treering structure, e.g. number of cells and radial cell size, are closely related to the kinetics of cell production. In this case, the timing of seasonal production is a fundamental aspect of plant development and functioning. To better assess the impact of specific climatic events to the timing and dynamic of growth, a process-based modeling can be a very useful tool. The Vaganov-Shashkin model was proved to provide reliable estimates of tree growth under strong limited conditions. Based on the assumption that climate conditions are determining cell differentiation mostly in the cambial zone, the model computes daily growth rate and converts it into the rate of cell production. In this work we present a two-steps approach combining the process-based VS-modeling and the timing procedure for cell production. An automatic method to identify the formation time of new cell transfer to the enlargement zone of tree ring was developed in R. The main advantage of a new approach was the ability to estimate daily values of growth rates and timing of cell formation in the forest-steppe zone in southern Siberia over a long period of direct climate observations without labour-intensive field measurements. The significant correlation between the original algorithm and its updated automatic version proves correctness and reliability of the new method.

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Modeled Tracheidograms Disclose Drought Influence on Pinus sylvestris Tree-Rings Structure From Siberian Forest-Steppe

Cited by 45 publications

References 60 publications

An interpreted language implementation of the Vaganov–Shashkin tree-ring proxy system model

An interpreted language implementation of the Vaganov–Shashkin tree-ring proxy system model

Comparing the Cell Dynamics of Tree-Ring Formation Observed in Microcores and as Predicted by the Vaganov–Shashkin Model

Timing of Cell Production in Tree Rings: An Automatic Two-Step Procedure in R

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