The correlation in the dynamics of the growth of European spruce and the dynamics of potato and winter rye yields

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     Lyapicheva Mariya Alekseevna Master's degree; Department of Forest Management, Forest Management and Geoinformation Systems; Mytishchi Branch of Bauman Moscow State Technical University 141005, Russia, Moscow region, Mytishchi, I-Th institutskaya str., 1, office LT2 melikhova2000@mail.ru Illarionov Denis Viktorovich Master's degree; Department of Forest Cultures, Breeding and Dendrology; Mytishchi branch of Bauman Moscow State Technical University 141005, Russia, Moscow region, Mytishchi, I-Th institutskaya str., 1, office LT2 X151152@yandex.ru

Lebedeva Elizaveta Maksimovna Master's degree; Department of Forest Cultures, Breeding and Dendrology; Mytishchi branch of Bauman Moscow State Technical University 141005, Russia, Moscow region, Gorod, I-Th institutskaya str., 1, office LT2 lebedevaliza2938@mail.ru

Introduction

There is a problem of identifying and investigating a drought that is physiologically significant for a plant, i.e., a drought that leads to water deficiency in the plant's body, a decrease in its productivity and stability ^[11]. Such studies can be carried out directly on the time series of crop yields. However, such information can only be obtained through direct observations over many years. An alternative is the dendrochronological method, which allows you to obtain such information within a few days in a retrospective way. Of course, this information will not be identical to information about the dynamics of crop yields, however, the time series will be based on the same variable associated with the process of drought influence on the photosynthesis process. What is its basis? Plants usually have enough water for the photosynthesis reaction itself (6CO2+6H2O= C 6H12 O ₆+6O2). But the limiting factor of this reaction is usually the lack of carbon dioxide ^[7]. To replenish it, the plant is forced to open the "gas exchange windows" - stomata located in the leaf, and let new portions of carbon dioxide into the leaf. The downside of this process is the loss of some of the moisture (which is already in short supply) during evaporation from open stomata.

Most plant species have adaptations that limit moisture loss during its deficiency, but at the same time these adaptations inhibit gas exchange and reduce the intensity of photosynthesis. The details of the ecophysiological mechanisms of photosynthesis vary among different plant species, at the same time, the described scheme is generally characteristic of all species.

In complex studies, dendroclimatic analysis was performed for different species of woody plants: Siberian fir (Abies sibirica Ledeb.), Pennsylvania ash (Fraxinus pennsylvanica Marsh.), Western thuja (Thuja occidentalis L.), Amur velvet (Phellodendron amurense Rupr.), Scots pine (Pinus sylvestris L.), red oak (Quercus rubra L.), Schrenk spruce (Picea schrenkiana Fisch. & C.A.Mey.), Weymouth pine (Pinus strobus L.), Rumelian pine (Pinus peuce Griseb.), Oriental spruce (Picea orientalis (L.) Peterm.), petiolate oak (Quercus robur L.), Pseudotsuga menziesii (Pseudotsuga menziesii (Mirb.) Franco) ^[16]. He showed that different species exhibit a different spectrum of climatic signals in chronologies and that reliable correlations were observed with 35 types of meteorological parameters out of 48 possible ones ^[16]. In general, the weather conditions in May and June directly during the formation of the annual ring have the strongest effect on the increase. What is the meaning of the resulting output? Long—term studies conducted by F. D. Skazkin ^[15] on various grain crops have shown that the period from entering the tube to earing - flowering is critical in relation to lack of moisture. In the Non–Chernozem region, this period falls on May-June. Direct studies of the yield of spring soft wheat in the conditions of the Moscow region for the period 1984-2008 showed that the most favorable years are those with an optimum GTC (> 1.3) in May–June. The lowest yield level was obtained in the years with the June GTC <1.0 ^[5]. Thus, the weather conditions of May–June are not only important for the formation of radial wood growth in woody plants, but also have a decisive influence on the formation of grain crops.

The history of domestic dendrochronological research contains a certain number of examples of attempts to identify conjugacy in time series reflecting fluctuations in the yield of agricultural crops and time series fluctuations in the width of the annual ring of woody plants ^[2,3,4,6,10]. One of the last such studies was carried out by a team of authors for the conditions of the steppe and forest-steppe regions of the Altai Territory ^[14]. The identification of similarity and synchronicity of reactions of agricultural and woody plants to climatic fluctuations makes it possible to restore the dynamics of yield based on the chronologies of the width of the annual rings. It was found that the magnitude of radial growth of Scots pine (Pinus sylvestris L.) of ribbon forests and crop yields in the steppe and forest-steppe regions of the region are limited by the same climatic factors: the precipitation of April-June (stimulate growth) and temperatures of May-July (restrain growth) are the most significant for the growth of agricultural plants and the alignment of scots. The highest correlations of crop yields in the regions of the region are observed with a group of certain tree-ring chronologies, which are confined to the border area between the forest-steppe and the steppe and are characterized by high climatic sensitivity. Significant positive correlations of tree-ring chronologies with the yield series of spring wheat, oats, buckwheat and natural hayfields and negative dependencies with potato yields were revealed. Based on the established significant relationships, the reconstruction of the yield ranges of spring wheat in the Kulundinsky district until 1871 and oats in the Rebrikhinsky district until 1830 was carried out. The restored rows allow us to identify periods of potential decrease and increase in crop yields. Thus, among the periods of declining wheat yields, one can designate the beginning of the fifties, when the virgin lands of the Altai Territory were actively developed.

Our research is devoted to the analysis of the conjugacy in yield fluctuations of winter rye (Secale cereale L.) and potatoes (Solanum tuberosum L.) obtained in the long-term experience of TLC ^[1] and in the dynamics of radial growth indices in the 200-year chronology of the European spruce (Picea abies (L.) H.Karst.) from the Alekseevskaya grove of the National Park "Moose Island" ^[13].

The object of the work and the method of work

To solve these tasks, data on the yield of winter rye and potatoes in the long-term TLC experience for the period from 1912 to 1991 were used for three options: without fertilizers, NPK, NPK + manure (permanently and in crop rotation) (Table 1).

Table 1. Characteristics of the yield ranges of winter rye and potatoes according to the variants of the experiment

For each variant of the experiment, there were time series that were approximated by a parabolic trend and annual yield deviations from the trend line were calculated. These time series given in the appendix to Abudd Leyla's dissertation ^[1] were used in our calculations. The time series was compared with the indexed chronology of the European spruce from the Alekseevskaya grove of the Losiny Ostrov National Park (Fig. 1). The Alekseevskaya grove, which arose at the turn of the XVIII–XIX centuries and located in the Losiny Ostrov NP, is a unique natural object. The wind of 2017 made it possible to select cuts in it that are of value for dendrochronological research. The following methodology was used to construct primary chronologies. The surface of the cuts was cleaned with a milling cutter along three radii located relative to each other at an angle of 120 degrees. The surface was rubbed with chalk powder to better display the structure of the annual rings. To measure the width of individual rings and the increase over decades, Led Scale Loupe 10x measuring magnifiers were used, cross-dating of chronologies was performed in the TSAP-Win program ^[13].

Figure 1 Dynamics of radial growth indices in the chronology of the European spruce

Thus, the study period covers 68 years to calculate the correlation with meteorological parameters and 80 years to calculate the correlation with the yield indices of winter rye and potatoes in different versions of the experiment. The total length of the indexed chronology of spruce is 200 years. For dendroclimatic analysis, time series were used for such meteorological parameters as average monthly temperatures, monthly precipitation amounts at the Moscow weather station (obtained on the website http://www.pogodaiklimat.ru/history/28367_3.htm .) ^[9]. The bioclimatic analysis was conducted on the basis of correlation analysis.

The results of the study

To identify the relationship between the dynamics of spruce growth indices and the dynamics of radial growth indices, a correlation analysis was performed, the results of which are shown in Table 2. Calculations were performed for the period 1950 - 2017. It is advisable to perform such calculations both for meteorological parameters in the year of the formation of the annual ring, and for meteorological parameters of the year preceding it ^[18]. The initial series of meteorological parameters contain values for 1948, which raise obvious doubts about their reliability – this was due to the choice of a specific length of the time interval used for analysis.

Table. 2 The values of the correlation coefficients between the spruce growth index and meteorological parameters

*the values of the correlation coefficients are reliable at a confidence level of 0.05

According to the results of calculations of the correlation coefficients between a number of spruce growth indices and a number of yield indices. Thus, reliable correlation coefficients were revealed with the temperature of January of the current year (correlation coefficient R=0.26); with the temperature of June of the current year (R=-0.25), with the temperature of August of last year (R=-0.25), with the temperature of December of the last calendar year (R=0.27). Therefore, for the formation of a high growth of wood spruce has favorable mild winters (with elevated temperatures in December and January), fairly cool temperatures in June (which is explained by the negative effect of elevated temperatures on transpiration and gas exchange through the effects of stomatal closure), and fairly cool conditions in August last year (the period of laying vegetative buds, in which the reformed shoots of the assimilation surface are located, providing intensive photosynthesis per year formation of the annual ring). The critical effect of precipitation on the formation of the dynamics of radial growth of spruce in this particular local habitat has not been revealed, which, apparently, is due to the specifics of the soil and soil conditions of the ecotope under consideration (moderately close groundwater occurrence, which does not create headwaters, but at the same time, provides good moisture availability for the roots of old-age spruce trees). The dynamics of the radial growth of spruce can be modeled using a linear regression equation of the form:

Y=2.1796+0.0128*T _12-1+0.0122*T _1-0.0203*T _6-0.0377*T _8-1

T _12-1 is the temperature of December in the calendar year preceding the calendar year of the formation of the annual ring, ^about C

T ₁ is the temperature of January in the calendar year of the formation of the annual ring, ^about C

T ₆ is the temperature of June in the calendar year of the formation of the annual ring, ^about C

T _8-1 is the temperature of August in the calendar year preceding the calendar year of the formation of the annual ring, ^about C

The equation describes the variability of radial growth indices with a sufficiently low coefficient of determination (0.23), while the observed correlation coefficient between the real range of values of the growth indices and the model values is 0.49 and is reliable at a confidence level of 0.01. A visual analysis of the conjugacy in the dynamics of the time series under consideration indicates a high level of conjugacy in their dynamics at a qualitative level. The calculation of the synchronicity coefficient confirms this conclusion: there is a fairly high synchronicity of fluctuations in the values in the series (the synchronicity coefficient is 69%).

Figure 2 Results of modeling the dynamics of the radial growth indices of spruce depending on the dynamics of meteorological parameters based on the linear regression equation

It is known that the growth and the nature of the influence of climatic factors on the dynamics of radial growth fluctuations have a very strong regional specificity ^[9]. Comparing the results of the analysis for different geographical areas and different forest typological conditions is of limited value. However, such a comparison cannot be completely dispensed with. In our case, the results obtained generally do not coincide with the data of Polish scientists, who found that the growth of spruce in the northern regions of Poland positively correlates with the amount of precipitation from May to July ^[19]. In the conditions of Bavaria, the chronology of spruce stands located in habitats with low altitude above sea level also demonstrated a positive relationship between the increase in growth and precipitation in March, May, June and July ^[20], which is not observed in our case. At the same time, the chronology of spruce trees from habitats located high above sea level showed a negative correlation with the amount of precipitation from May to July. A team of authors performed dendroclimatic studies in spruce crops in the Sergiev Posad district of the Moscow region ^[12]. Dendroclimatic analysis by the climagram method showed that extremely narrow rings form in years with a lack of precipitation in March, February, May, June, and July. Temperatures (with the exception of May temperatures) have almost no effect on the formation of extremely narrow annual rings. All this generally does not correspond to the picture observed on the material of the chronology obtained by us, which indicates the uniqueness of the dendrochronological material obtained in this case and the high potential for using the dendroclimatic information extracted from it.

To identify the conjugacy in the dynamics of the indices of radial growth of European spruce in the tree stand under consideration and the dynamics of the yield indices of winter rye and potatoes, correlation coefficients were calculated, the results of which are summarized in Table 3 and Table 4. The reliability of the values of the correlation coefficients was estimated at a confidence level of 0.05 ^[8]. The time series for which reliable values of the correlation coefficients with the dynamics of the indices of radial growth of spruce were found are shown in Figure 3 and Figure 4.

Table 3. Correlation of dynamics of spruce growth indices and potato yield indices in different variants of the experiment

*the values of the correlation coefficients are reliable at a confidence level of 0.05

Figure 3 Dynamics of radial growth indices in the chronology of European spruce in connection with the dynamics of potato yield indices in the experiment without lime, without crop rotation and with the introduction of a complex of NPK fertilizers and manure

Table 4. Correlation of dynamics of spruce growth indices and winter rye yield indices in different variants of the experiment

*the values of the correlation coefficients are reliable at a confidence level of 0.05

Figure 4 Dynamics of radial growth indices in the chronology of European spruce in connection with the dynamics of winter rye yield indices in the experiment without lime, without crop rotation and without fertilization

Discussion of the results

Thus, during the calculations, two reliable relationships were revealed between the dynamics of the indices of radial growth of spruce and the dynamics of crop yields: the relationship with potato yields in the experiment without lime, without crop rotation and with the application of a complex of NPK fertilizers and manure (correlation coefficient 0.22) and the relationship with rye yields in the experiment without lime, without crop rotation and without fertilization (correlation coefficient 0.23). At the same time, reliable values of correlation coefficients in yield dynamics are always observed between different variants of the experiment for both rye and potatoes, however, sometimes their relationship is weak and comparable in terms of closeness with the relationship with the dynamics of the indices of radial growth of spruce: for example, a variant of calculating the correlation coefficient between the time series of potato yields in the "without lime" variant of the experiment, in crop rotation, without fertilizers" and the variant of the experiment "without lime, permanently, NPK +manure" gave a correlation coefficient value of 0.29; and the variant of calculating the correlation coefficient between the time series of rye yields in the variant of the experiment "without lime, in crop rotation, NPK + manure" and the variant of the experiment "without lime, permanently, NPK" I gave a coefficient value of 0.36. This proves that the relationships we have identified between the dynamics of spruce growth and crop yields are biologically significant and comparable to the variation in yield dynamics at the intraspecific level.

Conclusion

Thus, during the research, the main meteorological parameters significant for the formation of spruce growth were identified: the average monthly temperatures of December and January, which determine the severity of winter conditions, the average monthly temperatures of June, apparently affecting the intensity of transpiration and, through this process, the intensity of photosynthesis, and the average monthly temperatures of August in the year preceding the calendar year of the formation of the annual rings, which apparently affect the processes of vegetative bud formation, which in turn determines the area of the developing assimilation surface and the intensity of photosynthesis in the year of formation of the annual ring. A reliable correlation has been established between crop yields in all variants of the experiment. The facts of a reliable correlation between the dynamics of spruce growth indices and crop yields have been revealed. The results of the study, in our opinion, reflect the fact that the harvest (the harvest of wood, the harvest of food agricultural products) is primarily determined by the intensity of photosynthesis. Photosynthesis is an evolutionarily conservative mechanism that works in many ways in the same way in systematic groups of plants that are far from each other. The intensity of photosynthesis, in turn, is closely related to the intensity of transpiration, which reacts sensitively to the weather conditions of the external environment and is regulated by the plant in order to prevent water deficiency. These processes occur in many ways uniformly in systematically different groups of plants.