TIMING OF CELL PRODUCTION IN TREE RINGS: AN AUTOMATIC TWO-STEP PROCEDURE IN R
Кафедра математических методов и информационных технологий
Journal Name:WATER RESOURCES, FOREST, MARINE AND OCEAN ECOSYSTEMS CONFERENCE PROCEEDINGS, SGEM 2018
Journal Quartile in Web of Science:без квартиля
Bibliographic Citation:Daria, Belousova. TIMING OF CELL PRODUCTION IN TREE RINGS: AN AUTOMATIC TWO-STEP PROCEDURE IN R [Текст] / Belousova Daria, Popkova Margarita, Babushkina Elena, Shishov Vladimir // WATER RESOURCES, FOREST, MARINE AND OCEAN ECOSYSTEMS CONFERENCE PROCEEDINGS, SGEM 2018: Book Series: International Multidisciplinary Scientific GeoConference-SGEM. — 2018. — Т. 3. — С. 1053-1060
Текст статьи не публикуется в открытом доступе в соответствии с политикой журнала.
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.