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The Influence of the Forest Factors on the Variability of the Tree-ring Chronologies of the common Pine in the conditions of the Muromtsevo District Forestry of the Vladimir Region

Rumyantsev Denis Evgenievich

ORCID: 0000-0001-9871-9504

Doctor of Biology

Professor, Department of Forestry, Ecology and Forest Protection, Mytishchi Branch of the Bauman Moscow State Technical University

141005, Mytischi, Moscow region, Russia,1st Institutskaya street, 1, LT2

dendro15@list.ru
Other publications by this author
 

 
Epishkov Anton Alekseevich

individual entrepreneur

141005, Russia, Moscow region, Mytishchi, Iaya Institutskaya str., 1, of. LT2

kam_ant1983@mail.ru

DOI:

10.7256/2453-8809.2022.1.38494

EDN:

WRPIPN

Received:

22-07-2022


Published:

25-08-2022


Abstract: Comparative analysis of tree-ring chronologies on the variability of the short-term component is based on the calculation of synchronicity coefficients. The study of the regularities of the variability of tree-ring chronologies on this basis in natural cenopopulations is important for establishing the reaction rate of this indicator. This is significant for the further progress of dendrochronological and dendroclimatic studies, improving the methods of forensic botanical examination using dendrochronology methods. In the study, this issue was studied on the basis of chronologies from different phytocenoses with the predominance of scots pine in the stand. The trial areas were located on the territory of the Muromtsevo forestry of the Vladimir region. The study was carried out as part of the implementation of R&D Rosleskhoz (2008-2011). The main parameters of the frequency of occurrence of different variants of the values of the synchronicity coefficient were established. The regularities of the frequency of occurrence of different values of the synchronicity coefficient depending on the type of forest are also established: The range of variation of values between groups from different types of forest is small and amounts to several percent. The data obtained are important for solving the following practical tasks: monitoring the accuracy of measurements of annual rings on individual wood samples; establishing the date of termination of cambial activity in the trunk of a tree; establishing the date of construction of wooden buildings; dating of archaeological wood; dating the time of creation of art objects; diagnostics of the condition of the tree at the time of cutting; establishing the time of cutting the tree; establishing the drying time a tree.


Keywords:

dendrochronology, dendroecology, annual rings, synchronicity coefficient, cross-dating, forensic botanical examinations, common pine, Muromtsevo forestry, radial gain, dendrochronological information

This article is automatically translated. You can find original text of the article here.

Introduction The method of cross-dating of tree-ring chronologies was first formulated by Andrew Douglass, it was based on a visual qualitative analysis of the conjugacy of short-term (one-year) fluctuations in the width of annual rings in different tree organisms [10].

  At the same time, only the years of local growth extremes were taken into account. The method was further developed in the works of the German forester and botanist Bruno Huber. He came to the conclusion that in the temperate climate of Europe, it is more efficient to use the variability of all annual rings of the time series for cross-dating and proposed to conduct a statistical assessment of the similarity between dendrochronological series by calculating the "coefficient of parallel variability" [12],[13]. The Huber similarity coefficient between two dendrochronological series was calculated as the ratio of the number of time intervals dissimilar in response to the increment to the total number of time intervals. The domestic dendrochronological school, as a rule, used another indicator similar to it, proposed in the dissertation of T.T. Bitvinskas [1],[2] – the synchronicity coefficient. It was calculated already as the ratio of time intervals similar in reaction to the total number of time intervals. Currently, this approach has become more widespread in the world dendrochronological practice compared to Huber's approach.Relatively unimportant due to the rare frequency of occurrence of such cases and, accordingly, their small influence on the magnitude of the calculated value of the similarity coefficients remained the question of situations with equality in the reaction of radial increment.

To resolve it on an objective basis, most dendrochronologists currently use the GLK coefficient (gleichl?ufigkeit coefficient) for dating, which characterizes the similarity between two dendrochronological series, taking into account such cases, not by a score of "1" or a score of "0", but by a score of 0.5. In particular, it can be calculated using the TSAP-Win program (RINNTECH) [7].

 Currently, the method of cross-dating is used to solve the following practical tasks: monitoring the accuracy of measurements of annual rings on individual wood samples;  establishment of the date of termination of cambial activity in the trunk of a tree; establishment of the date of construction of wooden buildings; dating of archaeological wood; dating of the time of creation of art objects; diagnosis of the condition of the tree at the time of felling; establishment of the time of felling of the tree; establishment of the time of drying of the tree.

The last two tasks are primarily relevant for forestry. They make it possible to monitor the legality of the turnover of round timber and to identify violations of forest legislation by methods of forensic botanical examination [3],[5],[6],[8],[11],[15]. There is no effective alternative to these methods for solving the set range of issues.

T.T. Bitvinskas (1972) was the first to study the variability of the synchronicity coefficient in natural cenopopulations. At the II All-Union Meeting on Dendrochronology and Dendroclimatology held in Kaunas in 1972, he expressed the following: "It is of great interest to study the question of how much the variability of the width of the annual layers of individual trees for certain calendar years coincides with the variability of the average width of the annual layer of planting." One of the concepts introduced by Bitvinskas into the practice of estimating the group variability of radial increment was the general convergence of a number of curves. Initially, an average chronology was calculated for each sample area based on individual time series of radial increment. Then the synchronicity coefficient between the average chronology and each of the individual chronologies was calculated. Then, from the totality of the obtained values of the synchronicity coefficient, the average value was calculated.

The study of the group variability of time series of radial increment in terms of synchronicity is of practical interest for the development of methods of forensic botanical examination, improving them to such an extent that they become available to a wide range of forestry specialists. At the same time, such studies are of fundamental interest from the point of view of the genetics of the population of forest-forming breeds and the development of breeding methods for productivity and sustainability. The purpose of this work is to study the variation of the synchronicity coefficient in the cenopopulations of Scots pine depending on the types of forest on the material of tree-ring chronologies from the Muromtsevo forestry of the Vladimir region.Materials and methods The object of the study was the pine forests of the Muromtsevo forestry of the Vladimir region.

Materials for the study were collected as part of the R&D of the Federal Forestry Agency (2008-2011).

The selection of wood samples on the territory of the Muromtsevo district forestry was carried out in August 2009. Temporary trial areas were laid within the limits of separate taxing allotments, in which stands of the I-III bonitet were located. In nature, the test areas were not beaten off, but for each accounting tree, geographical coordinates were determined using the GPS navigator GPSMAP 60Cx. A geobotanical description and a description of the parameters of the accounting trees were performed on each test area.

Wood samples were taken using a Pressler drill from trees of the I-III growth class according to Kraft at a height of 1.3 m. Wood samples were taken from 20 accounting trees, one drill core from each accounting tree.

The measurement of the width of the annual rings on the wood samples was carried out using the LINTAB device. During the work, the accuracy of measurements was constantly monitored based on the use of the visual cross-dating procedure in the TSAP-Win program. The TSAP-Win software package provides a calculation of the synchronicity coefficient called the GLK coefficient (gleichl?ufigkeit coefficient), which characterizes the similarity between two dendrochronological series and is calculated as follows:

 

?i= (Xi+1 - Xi )if ?i >0; Gix = +1/2 if ?i =0; Gix = 0 (very rare)

if ?i <0; Gix = -1/2 for two curves G(x,y) = (1/n-1)

  n-1?i=1 |Gix + Giy|

 

where G = GLK, X and Y are dendrochronological series; n is the length of dendrochronological series, years; i is the moment of time [14].

The resulting measurement results using the TSAPWin program were saved as a file in Excel CSV format and subsequently data was processed in a Microsoft Excel spreadsheet processor.

It is appropriate to explain separately that in the work they operate with ideas about two types of average values of the synchronicity coefficient. First, the average chronology for the trial area is calculated by the width of the annual ring. Next, the synchronicity coefficient of each individual chronology with the average chronology is calculated. The average value is calculated from the resulting set of values (the number of which corresponds to the number of scientific trees on the test area). As a result, we get the indicator that T.T. Bitvinskas [2] called "the general convergence of a number of curves". Based on the average breakdown area (the total convergence of a number of curves), group averages can be calculated, for example, averages for the type of forest.

The work was carried out on the basis of a database (a bank of dendrochronological data) created on the instructions of the Federal Forestry Agency by MGULES scientists in 2009.

Results and discussion To study the variation of the synchronicity coefficient, 33 test areas located in the Vladimir region of the Muromtsevo forestry were analyzed.

The trial areas were located in different forest growing conditions. Geographical coordinates of the first test area (MPP2): latitude 55°55.349’00’; longitude 040°58.348’00’.

 In order to exclude trees growing in unfavorable conditions from the analysis, green–mossy pine forests were mainly selected for analysis, since the annual layers of oppressed trees growing on soils with excessive waterlogging (sphagnum pine forests, long-mossy pine forests) contain false or fallen annual rings, which complicates the procedure of experimental data processing. Based on the materials of the taxation description, an array of data was collected for each test area, presented in Table 1. Typical undergrowth species in the test areas were common mountain ash and brittle buckthorn, goat willow, long-eared willow, gray alder, common juniper, common bird cherry were also found. Spruce and birch were the most common in the forest, linden, pine, oak, maple, aspen were also found.

 

Table 1 Characteristics of trial plazastable 1characteristics of trial plots Code PPKvartal, excl.

 

The age of the composition of the forests is 276,4vii4c4e2bsosnyakkislichnympp 36154.2

V8C2E+Bsosnyak Blueberry 610,21V5C4E1B+

Ossosnyak blueberry 9273,5V 10C+Yesosnyak sourcepp 8937,15vi10ssosnyak raznotravnyiMPP 69

46,8VII9C1E+Bsosnyak cranberry checkpoint 1922,14 V10ssosnyak blueberry CHECKPOINT 2324,1IV10C+Bsosnyak cranberry CHECKPOINT 2526,18V8C2SOsnyak raznotravnyiMPP 85

150,1V8C2E+Bsosnyak Brusnichnyympp 70131,19IV9C1E+B+

Ossosnyak Kislichnyympp 2264,15iv8c2ossosnyak bilberry 2122,5iv9c1bsosnyak blueberry

MPP 8821.26 V10ssosnyak Lingonberry MPP 710,21V10C+E+

Bsosnyak orlyakovyMPP 7968,13VI10C+E+

Bsosnyak raznotravnyiMPP 8313,26V9C1E+2bsosnyak lingonberry

MPP 84150,6V7C3B Blueberry weed MPP 86130,6V5C3B2E+

Ossosnyak Blueberry checkpoint 9945,11V 10ssosnyak Lingonberry CHECKPOINT 14151,22IV10C+B+

Blueberry ossosnyak

MPP 9813,18V10C+Yesosnyak Lingonberry MPP 7768.3 V5C4E1B+

Ossosnyak Kislichnyympp 56123,8IV6C3E1BSOSNYAK Bilberry MPP 2022.2 V10C

Pine blueberry PPE 61127,9V6C2E2B+

Blueberry Pickle 9427,4V9C1B Sour pickle 52109,6IV4C6B+Os+

Yesosnyak Blueberry 7067.1 V10C

Sosnyak Kislichnyympp 57130,11V8C2BSOSNYAK Bilberry 1579,12iii7c3bsosnyak Bilberry 2426,6IV7C3B+

Yesosnyak Blueberries 7467.1V 

10 Grass-mixed grass As can be seen from the data in Table 1, the stands on the laid test areas are not homogeneous in composition and vary from 10C (pure pine plantation) to 5C4E1B + Os (mixed stands of pine, spruce, birch and aspen).

 

The types of forest are dominated by pine forests of the green-mossy group of forest types. This is important from the point of view of conducting calculations, since to a certain extent they unify the sample according to the criterion of the type of forest, which eliminates errors in measurements if this process depends on the type of forest. The influence of the forest type on the variation of the synchronicity coefficient was considered separately by us.The following species were mainly found in the living ground cover.

Blueberry pine: blueberries, lingonberries, hairy ozhika, European hoof, meadow marjanica, double-leaved mayberry, common sour, hard-leaved starling, raspberry, Schreber's pleurocium, European weekling, ivy budra, flattened planus, May lily of the valley and others. Lingonberry pine: cowberry, blueberry, male cowberry, Schreber's pleurocium, cladonia, common heather and others. Sour pine: common sour, forest boneberry, blueberry, raspberry, male cowberry, hairy sedge, ground strawberry, wild strawberry, yellow green, hard-leaved star and others. Mixed pine: meadowsweet, dioecious nettle, female stalk, common vine, pungent buttercup, mother and stepmother, forest horsetail. Based on the data obtained, as a result of processing wood samples in the TSAP-Win program, for each sample area characterizing a separate cenopopulation of pine, the coefficients of synchronicity between the average group chronology and individual chronologies were calculated.

  These data made up an array of values of the synchronicity coefficient. It included 595 values.  Then the average value of the synchronicity coefficient, the maximum value of the synchronicity coefficient and the minimum value of the synchronicity coefficient were calculated. Further, the data for each test area were recorded in a general table, and the number of occurrence of each coefficient for all test areas was calculated. For the obtained arrays of values of the synchronicity coefficient, the values of the frequency of occurrence in the sample were calculated.

The obtained data is reflected in the graph in Figure 1. Figure 1. The values of the frequency of occurrence of the synchronicity coefficients between the individual chronology and the average chronology of the STANDFIG.

1. Values of the frequency of occurrence of synchronicity coefficients between the individual chronology and the average chronology of the standard, after analyzing the graph presented in Figure 1, we can conclude that the values of the synchronicity coefficient in the test areas have high indicators.

 

The distribution graph of the frequency of occurrence of values visually corresponds to the normal distribution graph.  With the correct dating of tree-ring chronologies, the values of the synchronicity coefficient are most in the range of 47% - 89%.  Lower and higher values are rare. The data obtained can be used for cross-dating of tree-ring chronologies to monitor the accuracy of measurements.

For dendrochronology, the question of whether the average, maximum and minimum values of the synchronicity coefficient in the cenopopulation are related in their variation is of theoretical interest. Based on the material we received, we performed this kind of analysis. Its result is reflected in Figure 2 and in Table 2. Fig. 2 Graphs of variation of average, maximum and minimum values of synchronicity coefficients Fig.

2 Graphs of variation of average, maximum and minimum values of synchronicity Coefficients Figure 2 shows the average, minimum and maximum values of the synchronicity coefficient for each of the sample areas analyzed by us.

 

As a result, we observe the coefficient dynamics series on the test areas. As can be seen from the data in Figure 2, there are coincidences in the fluctuations of the coefficient dynamics series: smaller average values of the synchronicity coefficient on the test area often correspond to smaller minimum and maximum values of the synchronicity coefficient, and vice versa: large – large.

In order to give a quantitative assessment of the pattern we found, we used the correlation analysis procedure in the MS Excel program. The results of the performed calculations reflect the data in Table 3.Table 2. Values of correlation coefficients between the series of synchronicity coefficients between chronologiesTable 2. Values of correlation coefficients between series of synchronicity coefficients between chronologies

 

 

 

The average maximum minimum is 10,670,64 Maximum 0,6710,32 Minimum 0,640,321The results shown in Table 3 indicate that there is a fairly close relationship between the average value and the minimum, as well as the average value and the maximum (correlation coefficient 0.64-0.67), but it cannot be considered functional and these data in research papers in in the future, it is recommended to analyze independently.

 

The correlation relationship between the maximum and minimum values of the synchronicity coefficient is very weak, practically absent – the correlation coefficient is 0.3. The estimates for assessing the strength of the connection are given by us on the basis of the textbook by G.F. Lakin [4].

The main result of the work was the analysis of the variation of the values of the synchronicity coefficient depending on the types of forest. These data can be useful for the formation of methods of forensic botanical examination using methods of dendrochronology. As we have already noted in the introduction, this is important for answering the questions:

1. establishing the date of construction of wooden buildings?

2. dating the time of creation of art objects?

3. diagnostics of the dry condition of the tree at the time of cutting?

4 setting the time of tree felling?

The answers to these questions make it possible to monitor the legality of the turnover of round timber and to identify violations of forest legislation by methods of forensic botanical examination.

Data on the variation of the synchronicity coefficient depending on the type of forest are given in Table 3.Table 3. Variation of the values of the synchronicity coefficient in the test areas Table 3. Variation of the values of the synchronicity coefficient in the test areas

Trial Area Average value of the coefficient. Synchronismaximal value of the coefficient. synchronismimimal value of the coefficient. Synchronicity of the type of forests 2657256sosnyak Kislichnyimpp 669

7557sosnyak blueberry checkpoint 7677757sosnyak Orlyakov checkpoint 14708257

Blueberry pine tree 15728265som blueberry pine tree 19707760som blueberry pine tree 20

738366 Blueberry seedling 21698047 Blueberry seedling 227284

64sosnyak bilberry 23728459sosnyak lingonberry 24698560sosnyak blueberry

MPP 25687461sosnyak raznotravnyiMPP 36708659sosnyak Bilberry MPP 5268

7556 Blueberry seedling 56717960 blueberry seedling 57697758

Blueberry pine 61717762s Blueberry pine 69677453s cranberry pine 70

708161sosnyak Kislichnyimpp 74708151sosnyak cereal-ppt.

WFP 777581

68sosnyak kislichnyimpp 79707663sosnyak raznotravnyiMPP 83697653sosnyak lingonberry

MPP 84687758sosnyak blueberry checkpoint 85677657SOSNYAK lingonberry CHECKPOINT 8671

7863 Blueberry seedling 88707756 cranberry seedling 89727864

Sosnyak raznotravnyyMPP 92727764sosnyak kislichnyympp 94748368sosnyak Kislichnyympp 98

738965 Cranberry seedling 99677654 cranberry seedling

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

As a result, our sample of trial areas was divided into 5 groups: blueberry pine, sour pine, lingonberry pine, mixed grass pine, orlyak pine. The results of calculating averages for average coefficients, averages for maximum coefficients, averages for minimum values of the synchronicity coefficients for each of the groups by forest type reflect the diagrams in Figures 3, 4, 5.Fig. 3. Average values of the synchronicity coefficient for test areas embedded in different types of forests Fig.

3. Average values of the synchronicity coefficient for test areas laid in different types of Forests. .

 

4. Average maximum values of the synchronicity coefficient for test areas embedded in different types of forests Fig.

4. Average maximum values of the synchronicity coefficient for test areas laid in different types of forests.

 

5. Average minimum values of the synchronicity coefficient for test areas embedded in different types of forests Fig.

5. Average minimum values of the synchronicity coefficient for test areas laid in different types of FORESTS According to the diagram shown in Figure 1, it can be seen that the range of variation between different groups is not very large and is several percent.

For example, the maximum value is observed for blueberry pine (85%), the minimum value is observed for eagle pine (77%), the range of variation between them is 8%, the variation between other groups is somewhat less. Consequently, within the framework of solving the research tasks set by us, the maximum values of the synchronicity coefficients for areas from different types of forests are less correctly combined into a general sample during analysis than the average averages.

According to the diagrams presented in Figure 4, it can be seen that the range of variation is somewhat larger than for the average for the average, but also only a few percent. For example, the maximum value is observed for sour pine (63%), the minimum value is observed for lingonberry pine (57%), the range of variation between them is 6%, and the variation between other groups is even smaller. Therefore, within the framework of solving the research tasks set by us, it is incorrect to combine the minimum values of the synchronicity coefficients for areas from different types of forests into a common sample during analysis.

According to the diagram shown in Figure 5, it can be seen that the range of variation is greater than for the averages based on the average values of the synchronicity coefficients, but also amounts to several percent. For example, the maximum value is observed for sour pine (63%), the minimum value is observed for lingonberry pine (57%), the range of variation between them is 6%, the variation between other groups is even smaller. Therefore, within the framework of solving the research tasks set by us, it is incorrect to combine the minimum values of the synchronicity coefficients for areas from different types of forests into a common sample during analysis.

Conclusion Thus, studies were carried out characterizing the variation of the synchronicity coefficient in the cenopopulations of Scots pine in the conditions of the Muromtsevo district forestry of the Vladimir region.

These are unique, unparalleled data of theoretical and practical significance. It is confirmed that the synchronicity coefficient is a reliable indicator of similarity between dendrochronological series. In the course of the study, the graying main conclusions were obtained:

1) The distribution graph of the frequency of occurrence of values visually corresponds to the normal distribution graph.  With the correct dating of tree-ring chronologies, the values of the synchronicity coefficient are most often in the range of 62% - 78%. Lower and higher values are rare. The data obtained can be used for cross-dating of tree-ring chronologies to monitor the accuracy of measurements.

2) There is a fairly close relationship between the average value of the synchronicity coefficient in the cenopopulation and the minimum value of the synchronicity coefficient in the cenopopulation, as well as between the average value and the maximum (correlation coefficient 0.64-0.67), but it cannot be considered functional and these indicators in research papers are recommended to be analyzed independently in the future.

3) There is a very weak correlation between the maximum and minimum values of the synchronicity coefficient, it is practically absent – the correlation coefficient is 0.3.4) The range of variation among the averages for the average values of the synchronicity coefficients between groups from different types of forest is small and amounts to several percent.

For example, the maximum value of the coefficient is observed for sour pine (71%), the minimum value is observed for eagle pine (67%). The range of variation between them is 4%, the variation between other groups is even smaller. Therefore, in the framework of solving research problems, it is correct to combine the average values of the synchronicity coefficients for areas from different types of forests into a common sample during analysis.

 

References
1. Bitvinskas T.T. Dynamics of growth of pine plantations of the Lithuanian USSR and the possibility of its forecast. M.: TSKHA, 1966.15c.
2. Bitvinskas T.T. On some issues of synchronization (verification) in dendroclimatochronological studies and principles of classification and selection of dendrochronological material /T.T. Bitvinskas // Dendroclimatochronology and radiocarbon. Materials of the II All-Union Meeting on Dendrochronology and dendroclimatology. Kaunas: Institute of Botany of the Academy of Sciences of the Lithuanian SSR, 1972. pp.148-158.
3. Zhavoronkov Yu.M. The use of dendrochronology methods in forensic botanical examinations carried out on the basis of the ECC of the Department of Internal Affairs of the Vologda region in the investigation of crimes of illegal logging/Yu.M. Zhavoronkov//Forensic tools and methods in the detection and investigation of crimes.Official collection of works-M.: ECC of the Ministry of Internal Affairs of the Russian Federation, 2009.pp.203-206.
4. Lakin G.F. Biometrics. M.: Higher School, 1990.352 p
5. Lipatkin V.A. Possibilities of using the method of cross-dating of tree-ring chronologies in the investigation of cases related to illegal logging/ V. A. Lipatkin, S. B. Palchikov, D. E. Rumyantsev, Yu. M. Zhavoronkov //Theory and practice of forensic examination. Scientific and practical journal. №3 (19), 2010. P. 244-254.
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7. Palchikov S. B. Modern equipment for dendrochronological research / S. B. Palchikov, D. E. Rumyantsev// Bulletin of the Moscow State University of Forests – Forest Bulletin, №3 (72), 2010. pp.46-51.
8. Rozanov M.I. Theoretical foundations of the identification of the whole in parts. Diss...Candidate of Legal Sciences. M.: TSNIIISE, 1969. 320s.
9. Rumyantsev D.E. Statistical patterns of variability of time series of radial growth of scots pine on the territory of the Russian plain / Rumyantsev D.E., Epishkov A.A., Lipatkin V.A., Volkova G. L. // Modern problems of science and education, No. 5, 2015 (URL: http://www.science-education.ru/ru/article/view?id=22526 (accessed: 06.01.2016).
10. Rumyantsev D.E. History and methodology of forestry dendrochronology. Moscow: MGUL, 2010.109 p
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The subject of the study is the variation of the synchronicity coefficient in the cenopopulations of Scots pine depending on the types of forest based on the material of tree-ring chronologies from the Muromtsevo forestry of the Vladimir region. The research methodology is based on a combination of theoretical and empirical approaches using methods of analysis (including statistical), measurement, generalization, comparison, synthesis. The relevance of the study is determined by the wide application and importance of improving studies of the group variability of time series of radial growth in terms of synchronicity, including the influence of the forest typological factor on the variability of the synchronicity coefficients of the tree-ring chronologies of Scots pine in the Muromtsevo forestry of the Vladimir region. The scientific novelty of the author is associated with the empirical data obtained, as well as the formulated conclusions that the synchronicity coefficient is a reliable indicator of similarity between dendrochronological series. The data obtained can be used for cross-dating of tree-ring chronologies to monitor the accuracy of measurements. In the framework of solving research problems, the average values of the synchronicity coefficients for areas from different types of forest should be correctly combined into a general sample during analysis. The article is written in Russian literary language. The style of presentation is scientific. The structure of the manuscript includes the following sections: Introduction (method of cross-dating of tree-ring chronologies, works by E. Douglass, B. Huber, T. T. Bitvinskas, GLK coefficient, determination of the time of cutting wood, determination of the time of drying of wood, general convergence of a number of curves, the purpose of the work), Materials and methods (pine forests of the Muromtsevo forestry of the Vladimir region, sampling of wood, measurement of the width of annual rings on samples, TSAP-Win software package, two types of average values of the synchronicity coefficient), Results and discussion (33 test areas, pine forests, characteristics of test areas, composition of stands and living ground cover, values of the frequency of occurrence of synchronicity coefficients between individual chronology and average chronology by tree stand, variation of the values of the synchronicity coefficient in the test areas, the values of the correlation coefficients between the series of synchronicity coefficients between chronologies, average values, average maximum and minimum values of the synchronicity coefficient for the test areas embedded in different types of forest), Conclusion (conclusions), Bibliography. The text includes five figures and three tables. Table 3 is missing. The title ("Variation of the values of the synchronicity coefficient in the test areas") and, apparently, the contents of Figure 2 and Table 4 are duplicated, which needs to be corrected. The content generally corresponds to the title. At the same time, the subject of the study can be specified in the wording of the title – the variation of the synchronicity coefficient in the cenopopulations of Scots pine in the conditions of the Muromtsevo district forestry of the Vladimir region. To confirm the reliability of the conclusions, it is desirable to provide static criteria for differences. Attention is also drawn to the publication of the results of studies conducted in 2009, after more than 10 years, which it is desirable to clarify. The bibliography includes 16 sources of domestic and foreign authors – monographs, scientific articles, dissertations. Bibliographic descriptions of some sources require adjustments in accordance with GOST and editorial requirements, for example: 1. Bitvinskas T.T. Dynamics of growth of pine plantations of the Lithuanian USSR and the possibility of its prediction. M. : TSKHA, 1966. 15 p. 2. Bitvinskas T. T. On some issues of synchronization (verification) in dendroclimatochronological studies and principles of classification and selection of dendrochronological material // Dendroclimatochronology and radiocarbon : proceedings of the II All-Union Meeting on Dendrochronology and Dendroclimatology. Kaunas : Institute of Botany of the Academy of Sciences of the Lithuanian SSR, 1972. pp. 148-158. 3. Zhavoronkov Yu.M. The use of dendrochronology methods in forensic botanical examinations carried out on the basis of the ECC of the Department of Internal Affairs of the Vologda region in the investigation of crimes of illegal logging // Criminalistic tools and methods in the disclosure and investigation of crimes : type of collection ??? M. : ECC of the Ministry of Internal Affairs of the Russian Federation, 2009. pp. 203-206. 4. Lakin G. F. Biometrics. M. : Higher School, 1990. 352 p. 5. Possibilities of using the method of cross-dating of wood-ring chronologies in the investigation of cases related to illegal logging/ V. A. Lipatkin, S. B. Palchikov, D. E. Rumyantsev et al. //Theory and practice of forensic examination.2010. No. 3. pp. 244-254. 8. Rozanov M. I. Theoretical foundations of the identification of the whole in parts : dis. ... cand. Jurid. M. : TSNIIISE, 1969. 320c. 11. Douglass A.E. Climatic cycles and tree-growth. A study the annual rings of trees in relation to climate and solar activity. Washington : Carnegie institution, 1919. 127 p. 12. Jozsa L.A. Contributions of tree-ring dating and wood structure analysis to the forensic sciences / // Canadian Society Forensic Science Journal. 1985. Vol. 18. No. 4. P. 200-210. Appeal to opponents (Bitvinskas T. T., Zhavoronkov Y. M., Lakin G. F., Lipatkin V. A., Palchikov S. B., Rumyantsev D. E., Palchikov S. B., Rumyantsev D. E., Rozanov M. I., Epishkov A. A., Lipatkin V. A., Volkova G. L., Douglass A. E., Jozsa L. A., Rump H. H., Schweingruber F. H., Wolodarsky-Franke A., etc.) takes place mainly, in the first part. There is no discussion of the results obtained, their comparison with the data of other authors, which needs to be corrected. In general, the material is of interest to the readership, but the manuscript needs to be finalized, after which it can be considered for publication in the journal "Agriculture".

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The reviewed article is devoted to determining the influence of the forest typological factor on the variability of the synchronicity coefficients of the tree-ring chronologies of Scots pine using statistical methods. The research methodology is based on the study of literary sources on the topic of the work, the application of the method of cross-dating of tree-ring chronologies, the study of wood samples selected on the territory of the Muromtsevo district forestry of the Vladimir region. The authors of the article rightly associate the relevance of the study with the possibility of using the cross-dating method to solve many practical problems: monitoring the accuracy of measurements of annual rings on individual wood samples; establishing the date of termination of cambial activity in the trunk of a tree; establishing the date of construction of wooden buildings; dating archaeological wood; dating the time of creation of art objects; diagnosing the condition of a tree at the time of cutting; setting the time of felling the tree; setting the time of drying of the tree. The scientific novelty of the presented study, according to the reviewer, lies in the presented results of studying the variation of the synchronicity coefficient in the cenopopulations of Scots pine depending on the types of forest. The authors have identified the following structural sections in the article: Introduction, Materials and methods, Results and discussion, Conclusion, Bibliography. The authors describe in detail the source material for the study, how sampling was carried out, what scientific methods and computer programs were used to process information and convert it into research results presented in the publication. The bibliographic list includes 16 names of sources in Russian and English, to which the text contains address links indicating the presence of an appeal to opponents in the publication. The study is based on the analysis of real dendrochronological data – this, undoubtedly, should be attributed to the advantages of the reviewed work. The paper reflects the average values of the synchronicity coefficient for the sample areas laid down in different types of forest (lingonberry pine, sour pine, mixed pine, blueberry pine, orlyak pine), as well as the average minimum and maximum values of this value. The reviewed article is not without some flaws. Thus, when quoting T. T. Bitvinskas on the variability of the synchronicity coefficient in natural cenopopulations, no reference to the source is given, although this source is apparently reflected in the list of references. In addition, the text fragment in which the author says that the results "were saved as a file in the Excel CSV format" needs to be adjusted, since "Excel" and "CSV" are fundamentally different formats, providing for the possibility of converting data from one format to another and back. It is also necessary to eliminate typos, for example, "typo" (the letter is missing). The topic of the article is relevant, the material corresponds to the industry orientation of the journal, is focused on monitoring the legality of the turnover of round timber and identifying violations of forest legislation by methods of forensic botanical examination, may arouse interest among readers and is recommended for publication after the elimination of comments.
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