7 research outputs found
Comprehensive Hydrological Survey of Glukhoye Lake, a Typical Forest Lake on Kunashir Island (Kuril Islands)
In order to study a typical forest lake on Kunashir Island, which is Glukhoye Lake, a bathymetric mapping was conducted using a Lowrance echo sounder, during which 25 transects and 3 longitudinal tacks were measured. According to the results of bathymetric mapping, 5 points of hydrological and hydrochemical synchronous survey were carried out, within the framework of which hydrochemical indicators were measured and 9 water samples were taken for further analysis. At the same locations, 5 sediment samples were collected and described during the ground survey. Based on these studies, a comprehensive hydrological characterization of Glukhoye Lake, a typical forest lake on Kunshir Island, has been formulated. It is located in a forested area between the hills, has a shallow basin, few tributaries and slow water exchange. The lake is characterized by very little variability in hydrochemical parameters in depth and in plan. The predominance of hydrocarbonate and sodium ions is quite typical for surface water bodies of volcanic massifs. The hypothesis of a continuing close link between the lake and the ocean has not been confirmed
Strain and Friction Effect on the Stress-Strain State in the Deformation Zone during Cold Rolling of Thin Beryllium and Aluminum Foils
A Modified Algorithm for Estimating the Radial Cell Size in the Vaganov-Shashkin Simulation Model
ΠΠΎΠ½ΠΈΠΌΠ°Π½ΠΈΠ΅ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΠ° ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΡΠΎΡΡΠ° Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ Π΄ΡΠ΅Π²Π΅ΡΠ½ΡΡ
ΡΠ°ΡΡΠ΅Π½ΠΈΠΉ ΠΏΠΎΠ΄
Π²Π»ΠΈΡΠ½ΠΈΠ΅ΠΌ Π²Π΅Π΄ΡΡΠΈΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ² Π²Π½Π΅ΡΠ½Π΅ΠΉ ΡΡΠ΅Π΄Ρ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΠ΄Π½ΠΎΠΉ ΠΈΠ· ΡΠ°ΠΌΡΡ
Π°ΠΊΡΡΠ°Π»ΡΠ½ΡΡ
ΠΏΡΠΎΠ±Π»Π΅ΠΌ
ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ Π΄Π΅Π½Π΄ΡΠΎΡΠΊΠΎΠ»ΠΎΠ³ΠΈΠΈ. Π£ΡΠΊΠΎΡΠ΅Π½ΠΈΠ΅ ΠΈΠ»ΠΈ Π·Π°ΠΌΠ΅Π΄Π»Π΅Π½ΠΈΠ΅ ΡΠΊΠΎΡΠΎΡΡΠΈ ΡΠΎΡΡΠ° Π΄Π΅ΡΠ΅Π²Π° Π² ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΠ΅
ΠΈΠ½ΡΠ΅ΡΠ²Π°Π»Ρ ΡΠ΅Π·ΠΎΠ½Π° ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ΅ΡΡΡ ΡΠΎΠ²ΠΌΠ΅ΡΡΠ½ΡΠΌ Π²Π»ΠΈΡΠ½ΠΈΠ΅ΠΌ ΡΠ°ΠΊΠΈΡ
ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ²,
ΠΊΠ°ΠΊ ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΠ° ΠΈ Π²Π»Π°ΠΆΠ½ΠΎΡΡΡ ΠΏΠΎΡΠ²Ρ. Π‘ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΌΠΎΠ΄ΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ°
ΠΈΠΌΠΈΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΡΠΎΡΡΠ° Π΄ΡΠ΅Π²Π΅ΡΠ½ΡΡ
ΡΠ°ΡΡΠ΅Π½ΠΈΠΉ ΠΠ°Π³Π°Π½ΠΎΠ²Π°-Π¨Π°ΡΠΊΠΈΠ½Π° β VS-ΠΎΡΡΠΈΠ»Π»ΠΎΠ³ΡΠ°ΡΠ° β
Π² ΡΠ°Π±ΠΎΡΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΡΠ΅ΡΡΡ ΡΠ΅Π·ΠΎΠ½Π½ΡΠΉ ΡΠΎΡΡ ΠΊΠ»Π΅ΡΠΎΠΊ Π² Π³ΠΎΠ΄ΠΈΡΠ½ΠΎΠΌ ΠΊΠΎΠ»ΡΡΠ΅. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ Π½ΠΎΠ²ΡΠΉ
ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ ΠΊ ΠΎΡΠ΅Π½ΠΊΠ΅ ΠΊΠ°ΠΌΠ±ΠΈΠ°Π»ΡΠ½ΠΎΠΉ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ Ρ
Π²ΠΎΠΉΠ½ΡΡ
ΠΈ ΡΠ΅Π·ΠΎΠ½Π½ΠΎΠΉ ΠΊΠ»Π΅ΡΠΎΡΠ½ΠΎΠΉ
ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠΈ, ΠΊΠΎΡΠΎΡΡΠΉ Π±ΡΠ» ΠΏΡΠΎΡΠ΅ΡΡΠΈΡΠΎΠ²Π°Π½ Π½Π° ΠΎΠ±ΡΠ°Π·ΡΠ΅ ΡΠΎΡΠ½Ρ ΠΎΠ±ΡΠΊΠ½ΠΎΠ²Π΅Π½Π½ΠΎΠΉ (Pinus sylvestris L.),
ΠΎΡΠΎΠ±ΡΠ°Π½Π½ΠΎΠΌ Π² Π₯Π°ΠΊΠ°ΡΠΈΠΈ, Π·Π° ΠΏΠ΅ΡΠΈΠΎΠ΄ Ρ 1969 ΠΏΠΎ 2008 Π³Π³. ΠΠ»Π°Π³ΠΎΠ΄Π°ΡΡ Π΄Π°Π½Π½ΠΎΠΌΡ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Ρ ΡΠ΄Π°Π»ΠΎΡΡ
ΡΠ°Π·Π΄Π΅Π»ΠΈΡΡ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈ Π½Π΅ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π²Π½Π΅ΡΠ½ΠΈΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ² Π½Π° ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅
ΠΊΠ»Π΅ΡΠΎΠΊ Π² Π³ΠΎΠ΄ΠΈΡΠ½ΠΎΠΌ ΠΊΠΎΠ»ΡΡΠ΅ Π΄ΡΠ΅Π²Π΅ΡΠ½ΡΡ
ΡΠ°ΡΡΠ΅Π½ΠΈΠΉTo describe the mechanism of tree-ring formation in woody plants influencing by the leading
environmental factors is one of the most urgent problems of modern dendroecology. Changing of
the tree-ring growth rate at selected intervals in the growing season is determined by the complex
influence of climatic factors (e.g. temperature and soil moisture). Using the modified algorithm of the
simulation model of growth Vaganov-Shashkin β VS-oscilloscope seasonal growth of cells in tree ring
is simulated in the work. New mathematical approach is developed to estimate a cambial activity
and seasonal cell production of conifer species. The approach is tested on tree-ring sample of Pinus
sylvestris for Khakassian region over 1969-2008. The obtained approach allows to separate a treering
growth signal on two components caused by climatic and non-climatic factor
Visual Parameterization of Vaganov-Shashkin Simulation Model and its Application in Dendroecological Research
Π Π΄Π΅Π½Π΄ΡΠΎΡ
ΡΠΎΠ½ΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅ΡΡΡ Π±ΠΎΠ»ΡΡΠΎΠ΅ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²ΠΎ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
Π°Π½Π°Π»ΠΈΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ΠΎΠ²
Π΄Π»Ρ Π°Π½Π°Π»ΠΈΠ·Π° Π΄Π°Π½Π½ΡΡ
, ΠΎΠ΄Π½ΠΈΠΌ ΠΈΠ· ΠΊΠΎΡΠΎΡΡΡ
ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅. ΠΡΠΈ ΡΠΎΠ·Π΄Π°Π½ΠΈΠΈ Π»ΡΠ±ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ
ΠΎΠ΄Π½ΠΈΠΌ ΠΈΠ· Π³Π»Π°Π²Π½ΡΡ
Π²ΠΎΠΏΡΠΎΡΠΎΠ² Π²ΡΡΡΡΠΏΠ°Π΅Ρ Π²ΡΠ±ΠΎΡ Π³Π»Π°Π²Π½ΡΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ². Π‘Π°ΠΌΡΠ΅ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½Π½ΡΠ΅ ΠΈ
Π΄ΠΎΡΡΡΠΏΠ½ΡΠ΅ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π΄Π°Π½Π½ΡΠ΅ β ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΠ° ΠΈ ΠΎΡΠ°Π΄ΠΊΠΈ.
ΠΠ° ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠΈ ΠΈΠΌΠΈΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΠ°Π³Π°Π½ΠΎΠ²Π°-Π¨Π°ΡΠΊΠΈΠ½Π° ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ Π½ΠΎΠ²ΡΠΉ Π°Π»Π³ΠΎΡΠΈΡΠΌ
Π²ΠΈΠ·ΡΠ°Π»ΡΠ½ΠΎΠΉ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈΠ·Π°ΡΠΈΠΈ ΡΠΎΡΡΠ° Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ Ρ
Π²ΠΎΠΉΠ½ΡΡ
Π΄Π΅ΡΠ΅Π²ΡΠ΅Π², Π½Π°Π·Π²Π°Π½Π½ΡΠΉ Β«VS-
ΠΎΡΡΠΈΠ»Π»ΠΎΠ³ΡΠ°ΡΒ», ΠΈ ΠΎΠΏΠΈΡΠ°Π½Π° Π΅Π³ΠΎ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½Π°Ρ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΡ. ΠΠΎΠ»ΡΡΠ΅Π½Π½ΡΠΉ Π°Π»Π³ΠΎΡΠΈΡΠΌ Π±ΡΠ»
Π°ΠΏΡΠΎΠ±ΠΈΡΠΎΠ²Π°Π½ Π½Π° Π΄Π²ΡΡ
ΠΏΠΎΡΠΎΠ΄Π°Ρ
Π΄ΡΠ΅Π²Π΅ΡΠ½ΡΡ
ΡΠ°ΡΡΠ΅Π½ΠΈΠΉ β Larix gmelini ΠΈ Picea obovata. ΠΠΎΠ²ΡΠΉ ΡΠΏΠΎΡΠΎΠ±
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈΠ·Π°ΡΠΈΠΈ ΠΈ Π°Π½Π°Π»ΠΈΠ· ΠΌΠΎΠ΄Π΅Π»ΠΈΡΡΠ΅ΠΌΡΡ
ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡ ΠΎΡΠ΅Π½ΠΈΡΡ Π»ΠΎΠΊΠ°Π»ΡΠ½ΡΠ΅ ΡΡΠ»ΠΎΠ²ΠΈΡ
ΠΏΡΠΎΠΈΠ·ΡΠ°ΡΡΠ°Π½ΠΈΡ Π΄ΡΠ΅Π²Π΅ΡΠ½ΡΡ
ΡΠ°ΡΡΠ΅Π½ΠΈΠΉ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ Π΄Π²ΡΡ
ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
:
ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΡ ΠΈ ΠΎΡΠ°Π΄ΠΊΠΎΠ², Π±Π΅Π· ΠΏΡΠΈΠ²Π»Π΅ΡΠ΅Π½ΠΈΡ Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΎ ΠΌΠ΅ΡΡΠΎΠΎΠ±ΠΈΡΠ°Π½ΠΈΠΈThere are many different methods and tools for data analysis in dendrochronology. Modeling is one of
them. One of the main issues in modeling is a choice of the main factors. Π‘limatic data (temperature
and precipitation) are the most common and affordable of them. Based on Vaganov β Shaskin model
the new algorithm of visual parameterization of three-ring growth β VS-oscilloscope was developed.
Algorithm was tested on different species of woody plants β Larix gmelini and Picea obovata. A new
parameterization and analysis of modeling results help to evaluate conditions of area of growth of
woody plants, based on dynamic of two climate variables: temperature and precipitation, without
adding information about area of growt
Visual Parameterization of Vaganov-Shashkin Simulation Model and its Application in Dendroecological Research
Π Π΄Π΅Π½Π΄ΡΠΎΡ
ΡΠΎΠ½ΠΎΠ»ΠΎΠ³ΠΈΠΈ ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅ΡΡΡ Π±ΠΎΠ»ΡΡΠΎΠ΅ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²ΠΎ ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
Π°Π½Π°Π»ΠΈΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ΠΎΠ²
Π΄Π»Ρ Π°Π½Π°Π»ΠΈΠ·Π° Π΄Π°Π½Π½ΡΡ
, ΠΎΠ΄Π½ΠΈΠΌ ΠΈΠ· ΠΊΠΎΡΠΎΡΡΡ
ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅. ΠΡΠΈ ΡΠΎΠ·Π΄Π°Π½ΠΈΠΈ Π»ΡΠ±ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ
ΠΎΠ΄Π½ΠΈΠΌ ΠΈΠ· Π³Π»Π°Π²Π½ΡΡ
Π²ΠΎΠΏΡΠΎΡΠΎΠ² Π²ΡΡΡΡΠΏΠ°Π΅Ρ Π²ΡΠ±ΠΎΡ Π³Π»Π°Π²Π½ΡΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ². Π‘Π°ΠΌΡΠ΅ ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½Π½ΡΠ΅ ΠΈ
Π΄ΠΎΡΡΡΠΏΠ½ΡΠ΅ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π΄Π°Π½Π½ΡΠ΅ β ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΠ° ΠΈ ΠΎΡΠ°Π΄ΠΊΠΈ.
ΠΠ° ΠΎΡΠ½ΠΎΠ²Π°Π½ΠΈΠΈ ΠΈΠΌΠΈΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΠ°Π³Π°Π½ΠΎΠ²Π°-Π¨Π°ΡΠΊΠΈΠ½Π° ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ Π½ΠΎΠ²ΡΠΉ Π°Π»Π³ΠΎΡΠΈΡΠΌ
Π²ΠΈΠ·ΡΠ°Π»ΡΠ½ΠΎΠΉ ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈΠ·Π°ΡΠΈΠΈ ΡΠΎΡΡΠ° Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ Ρ
Π²ΠΎΠΉΠ½ΡΡ
Π΄Π΅ΡΠ΅Π²ΡΠ΅Π², Π½Π°Π·Π²Π°Π½Π½ΡΠΉ Β«VS-
ΠΎΡΡΠΈΠ»Π»ΠΎΠ³ΡΠ°ΡΒ», ΠΈ ΠΎΠΏΠΈΡΠ°Π½Π° Π΅Π³ΠΎ ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½Π°Ρ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΡ. ΠΠΎΠ»ΡΡΠ΅Π½Π½ΡΠΉ Π°Π»Π³ΠΎΡΠΈΡΠΌ Π±ΡΠ»
Π°ΠΏΡΠΎΠ±ΠΈΡΠΎΠ²Π°Π½ Π½Π° Π΄Π²ΡΡ
ΠΏΠΎΡΠΎΠ΄Π°Ρ
Π΄ΡΠ΅Π²Π΅ΡΠ½ΡΡ
ΡΠ°ΡΡΠ΅Π½ΠΈΠΉ β Larix gmelini ΠΈ Picea obovata. ΠΠΎΠ²ΡΠΉ ΡΠΏΠΎΡΠΎΠ±
ΠΏΠ°ΡΠ°ΠΌΠ΅ΡΡΠΈΠ·Π°ΡΠΈΠΈ ΠΈ Π°Π½Π°Π»ΠΈΠ· ΠΌΠΎΠ΄Π΅Π»ΠΈΡΡΠ΅ΠΌΡΡ
ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡ ΠΎΡΠ΅Π½ΠΈΡΡ Π»ΠΎΠΊΠ°Π»ΡΠ½ΡΠ΅ ΡΡΠ»ΠΎΠ²ΠΈΡ
ΠΏΡΠΎΠΈΠ·ΡΠ°ΡΡΠ°Π½ΠΈΡ Π΄ΡΠ΅Π²Π΅ΡΠ½ΡΡ
ΡΠ°ΡΡΠ΅Π½ΠΈΠΉ Π½Π° ΠΎΡΠ½ΠΎΠ²Π΅ Π΄ΠΈΠ½Π°ΠΌΠΈΠΊΠΈ Π΄Π²ΡΡ
ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
:
ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΡ ΠΈ ΠΎΡΠ°Π΄ΠΊΠΎΠ², Π±Π΅Π· ΠΏΡΠΈΠ²Π»Π΅ΡΠ΅Π½ΠΈΡ Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΎ ΠΌΠ΅ΡΡΠΎΠΎΠ±ΠΈΡΠ°Π½ΠΈΠΈThere are many different methods and tools for data analysis in dendrochronology. Modeling is one of
them. One of the main issues in modeling is a choice of the main factors. Π‘limatic data (temperature
and precipitation) are the most common and affordable of them. Based on Vaganov β Shaskin model
the new algorithm of visual parameterization of three-ring growth β VS-oscilloscope was developed.
Algorithm was tested on different species of woody plants β Larix gmelini and Picea obovata. A new
parameterization and analysis of modeling results help to evaluate conditions of area of growth of
woody plants, based on dynamic of two climate variables: temperature and precipitation, without
adding information about area of growt
A Modified Algorithm for Estimating the Radial Cell Size in the Vaganov-Shashkin Simulation Model
ΠΠΎΠ½ΠΈΠΌΠ°Π½ΠΈΠ΅ ΠΌΠ΅Ρ
Π°Π½ΠΈΠ·ΠΌΠ° ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΡ ΠΈ ΡΠΎΡΡΠ° Π³ΠΎΠ΄ΠΈΡΠ½ΡΡ
ΠΊΠΎΠ»Π΅Ρ Π΄ΡΠ΅Π²Π΅ΡΠ½ΡΡ
ΡΠ°ΡΡΠ΅Π½ΠΈΠΉ ΠΏΠΎΠ΄
Π²Π»ΠΈΡΠ½ΠΈΠ΅ΠΌ Π²Π΅Π΄ΡΡΠΈΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ² Π²Π½Π΅ΡΠ½Π΅ΠΉ ΡΡΠ΅Π΄Ρ ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΠ΄Π½ΠΎΠΉ ΠΈΠ· ΡΠ°ΠΌΡΡ
Π°ΠΊΡΡΠ°Π»ΡΠ½ΡΡ
ΠΏΡΠΎΠ±Π»Π΅ΠΌ
ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ Π΄Π΅Π½Π΄ΡΠΎΡΠΊΠΎΠ»ΠΎΠ³ΠΈΠΈ. Π£ΡΠΊΠΎΡΠ΅Π½ΠΈΠ΅ ΠΈΠ»ΠΈ Π·Π°ΠΌΠ΅Π΄Π»Π΅Π½ΠΈΠ΅ ΡΠΊΠΎΡΠΎΡΡΠΈ ΡΠΎΡΡΠ° Π΄Π΅ΡΠ΅Π²Π° Π² ΠΎΡΠ΄Π΅Π»ΡΠ½ΡΠ΅
ΠΈΠ½ΡΠ΅ΡΠ²Π°Π»Ρ ΡΠ΅Π·ΠΎΠ½Π° ΠΎΠΏΡΠ΅Π΄Π΅Π»ΡΠ΅ΡΡΡ ΡΠΎΠ²ΠΌΠ΅ΡΡΠ½ΡΠΌ Π²Π»ΠΈΡΠ½ΠΈΠ΅ΠΌ ΡΠ°ΠΊΠΈΡ
ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ²,
ΠΊΠ°ΠΊ ΡΠ΅ΠΌΠΏΠ΅ΡΠ°ΡΡΡΠ° ΠΈ Π²Π»Π°ΠΆΠ½ΠΎΡΡΡ ΠΏΠΎΡΠ²Ρ. Π‘ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ ΠΌΠΎΠ΄ΠΈΡΠΈΡΠΈΡΠΎΠ²Π°Π½Π½ΠΎΠ³ΠΎ Π°Π»Π³ΠΎΡΠΈΡΠΌΠ°
ΠΈΠΌΠΈΡΠ°ΡΠΈΠΎΠ½Π½ΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΡΠΎΡΡΠ° Π΄ΡΠ΅Π²Π΅ΡΠ½ΡΡ
ΡΠ°ΡΡΠ΅Π½ΠΈΠΉ ΠΠ°Π³Π°Π½ΠΎΠ²Π°-Π¨Π°ΡΠΊΠΈΠ½Π° β VS-ΠΎΡΡΠΈΠ»Π»ΠΎΠ³ΡΠ°ΡΠ° β
Π² ΡΠ°Π±ΠΎΡΠ΅ ΠΌΠΎΠ΄Π΅Π»ΠΈΡΡΠ΅ΡΡΡ ΡΠ΅Π·ΠΎΠ½Π½ΡΠΉ ΡΠΎΡΡ ΠΊΠ»Π΅ΡΠΎΠΊ Π² Π³ΠΎΠ΄ΠΈΡΠ½ΠΎΠΌ ΠΊΠΎΠ»ΡΡΠ΅. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ Π½ΠΎΠ²ΡΠΉ
ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄ ΠΊ ΠΎΡΠ΅Π½ΠΊΠ΅ ΠΊΠ°ΠΌΠ±ΠΈΠ°Π»ΡΠ½ΠΎΠΉ Π°ΠΊΡΠΈΠ²Π½ΠΎΡΡΠΈ Ρ
Π²ΠΎΠΉΠ½ΡΡ
ΠΈ ΡΠ΅Π·ΠΎΠ½Π½ΠΎΠΉ ΠΊΠ»Π΅ΡΠΎΡΠ½ΠΎΠΉ
ΠΏΡΠΎΠ΄ΡΠΊΡΠΈΠΈ, ΠΊΠΎΡΠΎΡΡΠΉ Π±ΡΠ» ΠΏΡΠΎΡΠ΅ΡΡΠΈΡΠΎΠ²Π°Π½ Π½Π° ΠΎΠ±ΡΠ°Π·ΡΠ΅ ΡΠΎΡΠ½Ρ ΠΎΠ±ΡΠΊΠ½ΠΎΠ²Π΅Π½Π½ΠΎΠΉ (Pinus sylvestris L.),
ΠΎΡΠΎΠ±ΡΠ°Π½Π½ΠΎΠΌ Π² Π₯Π°ΠΊΠ°ΡΠΈΠΈ, Π·Π° ΠΏΠ΅ΡΠΈΠΎΠ΄ Ρ 1969 ΠΏΠΎ 2008 Π³Π³. ΠΠ»Π°Π³ΠΎΠ΄Π°ΡΡ Π΄Π°Π½Π½ΠΎΠΌΡ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Ρ ΡΠ΄Π°Π»ΠΎΡΡ
ΡΠ°Π·Π΄Π΅Π»ΠΈΡΡ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
ΠΈ Π½Π΅ΠΊΠ»ΠΈΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΡ
Π²Π½Π΅ΡΠ½ΠΈΡ
ΡΠ°ΠΊΡΠΎΡΠΎΠ² Π½Π° ΡΠΎΡΠΌΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅
ΠΊΠ»Π΅ΡΠΎΠΊ Π² Π³ΠΎΠ΄ΠΈΡΠ½ΠΎΠΌ ΠΊΠΎΠ»ΡΡΠ΅ Π΄ΡΠ΅Π²Π΅ΡΠ½ΡΡ
ΡΠ°ΡΡΠ΅Π½ΠΈΠΉTo describe the mechanism of tree-ring formation in woody plants influencing by the leading
environmental factors is one of the most urgent problems of modern dendroecology. Changing of
the tree-ring growth rate at selected intervals in the growing season is determined by the complex
influence of climatic factors (e.g. temperature and soil moisture). Using the modified algorithm of the
simulation model of growth Vaganov-Shashkin β VS-oscilloscope seasonal growth of cells in tree ring
is simulated in the work. New mathematical approach is developed to estimate a cambial activity
and seasonal cell production of conifer species. The approach is tested on tree-ring sample of Pinus
sylvestris for Khakassian region over 1969-2008. The obtained approach allows to separate a treering
growth signal on two components caused by climatic and non-climatic factor
Forward Modeling Reveals Multidecadal Trends in Cambial Kinetics and Phenology at Treeline
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 1961β2017. 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 KrkonoΕ‘e 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 0.28β0.34 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