Stem growth and stem sap flow measurements of three conifer tree species in Siberia

Abstract This work is targeted to evaluate the reaction of individual trees against periodic and punctual environmental stressing events with a network of long-term monitoring of tree water/growth-related processes in various geographic and climatic areas. Instrumental measurements of stem circumfer...

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Bibliographic Details
Published in:IOP Conference Series: Earth and Environmental Science
Main Authors: Rubtsov, Alexey, Arzac, Alberto, Knorre, Anastasia, Shashkin, Alexander, Benkova, Vera, Vaganov, Eugene
Format: Article in Journal/Newspaper
Language:unknown
Published: IOP Publishing 2020
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Online Access:http://dx.doi.org/10.1088/1755-1315/611/1/012028
https://iopscience.iop.org/article/10.1088/1755-1315/611/1/012028/pdf
https://iopscience.iop.org/article/10.1088/1755-1315/611/1/012028
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Summary:Abstract This work is targeted to evaluate the reaction of individual trees against periodic and punctual environmental stressing events with a network of long-term monitoring of tree water/growth-related processes in various geographic and climatic areas. Instrumental measurements of stem circumferential/radial size changes (dRc/dR) using band/point dendrometers and stem sap flow rates ( Q ) using a trunk segment heat balance method in Scots pine, Siberian larch, and Dahurian larch trees have been carried out at three research sites in Krasnoyarsk Krai, Russia. Analysis of perennial dRc/dR and seasonal Q data obtained in 2015-2019 allows us to characterize the seasonality and features of the tree stem growth and stem water transport rates specific for each of the studied conifer species and on different temporal scales (diurnal, inter/intra-seasonal, and annual). The archived in-situ data are used to verify the efficiency of some process-based BS-and stochastic VS-tree growth and phenology models for Siberian larch and Scots pine trees. The results have confirmed the realistic nature of the simulation and have shown certain drawbacks of these models.