Poly-Species Phytocenoses for Ecosystem Restoration of Degraded Soil Covers

: Agroecological studies are based on the concept that, by understanding ecological processes, it is possible to manage agroecosystems for more sustainable production of more biomass and, thus, protection of natural resources. Many studies in the field of agroecology show that some farming methods can improve soil quality and restore agroecosystems by increasing plant biodiversity. Functional characteristics of plants for the assessment of ecosystem processes and services can be used for the sustainable management of agroecosystems. The paper discusses ways to restore pastures with low biological productivity in the arid steppe of Northern Kazakhstan (Kostanay region). Grass-and-legume mixtures were selected, according to the soil and climatic conditions of this region, to increase the productivity of pastures. The authors also describe the meteorological conditions in the region in question for 2021. The data of agrochemical analysis of the soil on which the grass mixture was grown differed slightly from the soils of other sites and often even was inferior to them in some indicators that affected plant productivity, namely, the humus, phosphorus, and potassium content. In the conditions of the experiment, the highest productivity was shown by the grass-and-legume mixture consisting of crested wheatgrass- alfalfa -awn less brome (27.8 c/ha of green mass and 12.6 c/ha of dry matter). Thus, according to the information obtained during the study, it can be concluded that to restore the productivity of pastures in Northern Kazakhstan, it is necessary to select the grass-and-legume mixtures that have the highest productivity and nutritional value and are adapted to the soil and climatic conditions of this region. The algorithm of the predictive simulation model of the dynamics of the graminoid community is also presented in a general form. Problems related to the remediation of soil covers are discussed.


Introduction
The Republic of Kazakhstan is an agrarian country and ranks sixth in the world in terms of pasture area. The total pasture area occupies 187 million ha. Currently, due to prolonged unsystematic use, 48.0 million ha have been degraded, among them, 26.5 million ha have been completely worn down (Torekhanov and Alimaev, 2007;Bakhralinova et al., 2016).
For the development of animal husbandry in Kazakhstan, it is necessary to create a sustainable feed base, taking into account its potential, there are opportunities to introduce highly productive fodder crops and effective technologies into agricultural production. In Kazakhstan, the sources of providing plant feed for farm animals are pastures (187 million ha), hayfields (5.0 million ha), and fodder arable land (2.5 million ha) (BMAPA, 2009;Derpsch et al., 2010;Popov et al., 2017).
According to the Food and Agriculture Organization (FAO), the degradation of pastures leads to the loss of ecosystem functions caused by disturbances from which the system cannot fully recover (Agard et al., 2007;Pereira et al., 2018).
As a result of animal grazing, fodder grain crops and mixed herbs fall out of the herbage and low-value, weedy and poisonous plant species unsuitable for proper nutrition of livestock are introduced into its composition and begin to dominate. In addition, in previous studies (Liu et al., 2019) it was noted that animal grazing led to a decrease in biomass, resulting in the long-term destruction of pastures. In Pakistan, vegetation degradation was mainly associated with an increase in livestock (Abbas et al., 2017). In general, 21.29% of vegetation was degraded under the influence of climatic factors and anthropogenic actions, which was a serious problem (Zhao et al., 2018). In the studies by several authors (Kubenkulov et al., 2019;Oliveira et al., 2022), criteria and indicators of the degree of degradation of vegetation cover were established, where the state of pasture vegetation was assessed by four degrees of degradation: 1: Weak, 2: Medium, 3: Severe, 4: Very severe. The limiting influence of abiotic factors on the productivity of degraded pastures and the manifestation of the influence of grazing as the most important deflationary process were determined (Edwards et al., 2019;Leech et al., 2019).
The main problems of the fodder industry are low yields of pasture feed; low levels of use of pastures and hayfields (Tokusheva and Nugmanov, 2016;Tokusheva et al., 2017). To solve problems related to improving the state of pasture infrastructure, preventing the degradation of pasture lands, and preserving the ecological integrity of pasture ecosystems in the environment, as well as increase the production of environmentally friendly livestock products, so that Kazakhstan can become a global player in the production of milk and meat products .
In these works, sufficient attention was paid to the peculiarities and problems of growing perennial grasses, but they did not study the selection of legume components in the composition of pasture grass mixtures for the arid conditions of the Western Pre-Caucasian region (Bedilo, 2016).
The formation of grass-and-legume herbage on a pasture due to the replacement of technical nitrogen with a biological source helps to reduce average annual financial costs by 40% (Kutuzova, 2007). The positive effect of perennial legumes on the soil is also very great, as evidenced by numerous data obtained both in various regions of Kazakhstan and in Russia (Ganichev and Ryumin, 2018).
The relevance of our study is conditioned by the use of grass-and-legume mixtures to improve pastures without destroying the soil sod, which minimizes the degradation of pasture lands. In this aspect, this study is a popular and promising part of agricultural research, especially in Kazakhstan.
The purpose of this study was to determine the possibilities of poly-species agrophytocenoses and to develop software tools for the restoration and improvement of degraded pastures in the northern regions of Kazakhstan.

Design of the Study
During the study, the following goals were set: − To study the current state and determine the main ways of increasing the productivity of degraded pastures − To conduct agrochemical assessment of soils − To determine the productivity of poly-species agrophytocenoses during field experiments − To determine the level of plant nitrogen nutrition by the content of chlorophyll in the leaves by measuring with the N-tester device − To develop software tools for studying pasture productivity by mathematical modeling in the conditions of climate change and anthropogenic load. The location of the study, Agricultural Experimental Station Zarechnoye LLP, is located in Northern Kazakhstan, between the Ural Ridge in the west and the Kazakh hillocky area in the east, in the basins of the Tobol and Ubagan rivers. The region occupies a vast territory, about 114 thousand km 2 , which is divided into three natural and climatic zones. The study institute is located in the 2 nd soil-climatic zone. The territory is characterized as an arid steppe mainly with southern low-humus chernozems

Stages of the Study
To reach the goals set on the study topic, the following field experiments were conducted. The area of the experiment is 0.75 ha. In the degraded area where the experiments were supposed to be set, a preliminary inspection of vegetation and soil cover was carried out in the spring. In the summer, after the vegetation regrowth, a second inspection was carried out and the species composition of the vegetation was determined (Fig. 1).

Sampling
Determination of the content of organic matter was carried out by the Tyurin method in the modification of the Central Research Institute of Agrochemical Services for Agriculture (TsINAO) (CSMM, 1992b), which is based on the oxidation of organic matter with a solution of potassium bicarbonate in sulfuric acid and subsequent determination of trivalent chromium equivalent to the content of organic matter on a photoelectric colorimeter. The content of nitrate nitrogen was determined using the ionomeric method (CSMM, 1986). The method involves the extraction of nitrates with an aluminum-potassic alum solution with a mass fraction of 1% or a solution of potassium sulfate with the concentration (½ K2SO4) = 1 moL/dm 3 (1 n) with the mass ratio of soil samples and the solution volume of 1:2.5 and subsequent determination of nitrates in the extract with the help of ion-selective electrode.
The content of mobile compounds of phosphorous and potassium was determined by the Chirikov method in the modification of TsINAO (CSMM, 1992a). The method is based on the extraction of mobile compounds of phosphorus and potassium from the soil with a solution of acetic acid concentration c (CH3COOH) = 0.5 mol/dm 3 with a ratio of soil to a solution of 1:25 and subsequent determination of phosphorus in the form of a blue phosphorus-molybdenum complex on a photoelectric colorimeter and determination of potassium on a flame photometer.
The density of plant population was taken into account twice: After germination and before harvesting on specially designated sites in two repetitions. The density of plant population and the plant preservation were determined on test sites from adjacent rows of 0.5 m with subsequent counting.
The height of the plants was determined before taking into account the yield of the green mass by measuring 25 plants of each species (Fig. 2).
The botanical composition of the herbage was determined by analyzing plant samples weighing 1 kg with the release of legumes, grains, and mixed herbs, followed by weighing each component. To determine the botanical composition of the herbage, 100-250 g of airdry mass or 500-1,000 g of green freshly harvested fodder mass were taken. During species analysis, each sample was disassembled into individual types of herbs included in it. The fractions were weighed and the botanical composition of the herbage was determined as a percentage of the sample weight. The botanical composition of the herbage was determined before each grazing on pastures (Novoselov, 1983).
The accounting of the green mass harvest in the pasture ripeness phase was determined by mowing and weighing the green mass on the accounting plots with analysis of the species composition of the grass mixture and by drying the sheaves to an air-dry state (Dospekhov, 1985).
The output of the air-dry mass was determined with trial sheaves weighing 1 kg. Determination of the dry matter content is associated with the establishment of its humidity. The samples are dried to a constant mass and the calculation is carried out according to the formula: where, X1 is the initial moisture content in the fodder, %; B1 is the sample mass before drying, g; C is the sample mass after drying, g.
To determine the level of nitrogen nutrition of plants was determined by the content of chlorophyll in the leaves, directly in the field, using an N-tester portable device.
Various numbers appear on the display after 30 taps. The range of these numbers is sometimes higher or lower. The higher the nitrogen content in plants, the more intense and brighter the color of the leaves. This intensity is measured by the device and shows how much nitrogen is enough or not enough in plants.

Statistical Analysis
The data were statistically processed using variance analysis. The significance of the differences between the variants was estimated at a probability level of 0.05. Statistical analysis was carried out using Microsoft Excel 2003 and AGROS 2.11 software.

Results
The climate in the study area is sharply continental with hot and dry summers and cold winters with little snow. The annual amplitude of the air temperature averages 75°C and in some years reaches 88°C. In winter, the minimum air temperature often drops to-35-40°C and in rare cases, the temperature drops to-45-50°C. In summer, the absolute temperature equals + 41-43°C. The warm period with an average daily temperature above 0°C lasts 195 to 200 days (from the first decade of April to the third decade of October). The duration of the frost-free period ranges from 108 to 130 days. The average annual air temperature is 0.3-2.3°C and in some years it rises to 4.5-5°C or drops to 0-1.2°C. The duration of the growing season increases from north to south and equals 166 to 174 days. A characteristic feature of the continental climate is the predominance of precipitation during the warm period (May to October) when 60-80% of the annual precipitation falls. The maximum precipitation falls in the second half of summer, most often in July. The humidification index (Hydrothermal Index, HTI) in the region varies from 0.9 in the north to 0.5 in the south. Prolonged cold in spring, earlier temperature fall in autumn, and late summer precipitation are typical for the climate of the region and distinguish it from other arid regions.
Meteorological data obtained for the growing season of 2021 in the Kostanay region were characterized by the following indicators: Precipitation in May was 5.5 mm with an average annual norm of 36 mm and the air temperature was 20.0°C, which is higher than the average long-term norm by +6.3°C. In June, 13.7 mm of precipitation fell, which was 21.3 mm less than the average annual value, and the air temperature corresponded to the average annual value of 20.8°C, which favorably affected the germination and development of plants (Table 1). In July, 103.5 mm of precipitation fell, which was 47.5 mm more than the longterm norm and the air temperature was 21.3°C, i.e., slightly higher than the average long-term norm. In August, precipitation totaled 5.4 mm, which was a low indicator compared to the average annual norm of 35.0 mm and the air temperature showed a slight increase in temperature by 3.3°C. The results of the agrochemical analysis of the soil are shown in Table 2, where the humus content in the degraded pasture (control) was 3.99%, and in the other variants, it varied from 3.63 to 4.69%.
The provision of the soil with mobile forms of nitrate-nitrogen (N-NO3) was ≤2.8, the phosphorus content (P2O5 according to Chirikov) was 23-68 and 272 potassium content (K2O according to Chirikov) was 155 and more than 200 (high).
The primary indicators of vegetation productivity in herbaceous communities are the density and height of the herbage. Figure 3 shows a diagram of the average density of grass-and-legume mixtures for three experiments. At the control plot, there were such types of herbs as milfoil, milkweed, crested wheatgrass, sow thistle, sheep fescue, and cinquefoil. The average density of plants on the control plot was 67 plants/m 2 . The greatest density of legumes was noted on the variant of the crested wheatgrass-alfalfa-awnless brome, equaling 214 plants/m 2 . The greatest density of grain crops was noted on the variant of Russian wild ryealfalfa-awnless brome with 109 plants/m 2 .
As can be seen in Fig. 4, the average height of grains and legumes in three experiments varied from 45 to 70 cm. In the variants, the average height of plants was higher compared to the control plot, where it ranged from 20 to 32 cm.
According to the primary productivity indicators, some of the proposed grass mixtures are significantly higher, up to 4 times, than the mixed herbs of the degraded pasture that served as a control variant. This is confirmed by direct data on phytomass reserves.
As can be seen in Table 3, the conducted studies have shown that poly-species agrophytocenoses demonstrate the highest productivity in the variant of the grass mixture of crested wheatgrass-alfalfa-awnless brome (80.3 c/ha). Besides, compatibility is observed between grain perennial grasses and alfalfa, apparently due to their biological characteristics. There is a good combination of species and a lack of competition between them in the herbage. In the 2 nd experiment, the highest productivity was noted for the variant crested wheatgrass-common sainfoin-awnless brome. In the 3rd experiment, the productivity of all variants was lower than compared with other variants of the experiment. However, in all the experiments of the study, the productivity indicators were higher than in the control variant.
One of the most important indicators of the value of fodder crops is their nitrogen content in them, which is necessary for the proper nutrition of farm animals (Arlauskienė et al., 2021). In this regard, we conducted a study of the nitrogen content in plants proposed as structural components of experimental grass mixtures. Figure 5 shows that in experiment 1, the nitrogen content in the studied species is higher than in the other experiments. The highest nitrogen content was noted in alfalfa (553), which makes this crop and the grass mixtures in which it is included the most preferable ones from the point of view of nutritional value.
When considering the issue of restoration of degraded pastures, the issue of developing mathematical tools for predicting the dynamics of biomass in grassland communities was also considered. We propose an algorithm for describing the behavior of the hourly dynamics of organic matter carbon in grass communities of various types of Eco Grass, which is an upgraded version of the algorithm described in S.V. Mamikhin's monograph (Mamikhin, 2003). The algorithm was tested when constructing a model of carbon dynamics in the soil and vegetation cover of a particular graminoid community.
The model is deterministic with elements of stochasticity and point, i.e., the values of state variables depend only on time. The time step t in this version of the model is 1 h. The basic version of the model consists of six blocks: "Climate", "Meteo", "Hydrological", "Temperature", "Phytomass", and "Soil carbon". Figure 6 shows a diagram of the interaction of the model blocks, including an additional "Grazing" block.
In the "Meteo" block, the values of solar radiation and air temperature are calculated for each hour. The "phenological" time is also calculated here. The variable of the "phenological" time tph shows at what stage of the annual phenological cycle, characterized by the number of phenocenoses since the beginning of the year, the phytocenosis is located, which is necessary to take into account the influence of the phenological stages of the state of plants on the distribution of assimilates and other life processes. For all stages, it is accepted that in the first half of the year, the increased air temperature in comparison with the average monthly long-term accelerates the passage of the plant phenological cycle and in the second one it slows down (with a coefficient of 0.05).
In the "Hydrological" and "Temperature" blocks, the humidity and temperature of the soil horizons are calculated for each hour. Besides, the dynamics of stocks of mortmass and humus are calculated along the soil horizons. We consider the dynamics of two parts of the humus, which we can call the labile and stable parts. The first part includes nonspecific compounds and newly formed humic acids and the second one includes the mature humic acids, humin.
To assess the impact of grazing of farm animals on the productivity of a graminoid community, an additional "Grazing" block of the model can be connected, the input variables for which are the stocks of green phytomass and the number of heads of grazed animals per unit area regulated by a human, Cattle Grazing (CG). The block calculates the functions of grazing on phytomass, as well as the amount of excrement excreted by animals daily, to account for the 273 intake of organic matter into the soil. It is logical to assume that in the absence of natural fodder, for example in winter, livestock is provided with compound fodders.
Next, we will consider in more detail the structure of the "Phytomass" block of the model, which reproduces the seasonal dynamics of organic matter carbon in phytocenosis components. Table 4 shows the variables describing the dynamics of carbon stocks in the components of the phytomass of the graminoid community and Table 5 and 6 show the input and auxiliary variables necessary for the operation of the model.
The formulas used in the calculations in the listed blocks of the model are described in the aforementioned monograph (Mamikhin, 2003). The Eco Grass model is implemented in a modern freely distributed cross-platform programming environment Qb 64 (https://www.qb64.org/portal /), which allows using it in any version of Microsoft Windows (starting with Microsoft Windows XP and later versions), Linux, or Mac OS. The simulation results are displayed on the screen in text-digital and graphical form (Fig. 7), as well as in a separate text file data_gr.dat with data in a format convenient for further processing, for example statistical, in other programs.      Monthly precipitation amount cm/month

Discussion
For the practical application of the model, its localization is necessary, such as obtaining information about the dynamics of soil moisture, the intensity of photosynthesis and respiration in plants included in the grass mixture, plant phenology, animal grazing intensity, etc.
In addition, we are conducting a study on soil reclamation of spent ore deposits of the mining and metallurgical complex of Kazakhstan and adjacent territories, where soil covers require restoration for their subsequent use for economic purposes. Experiments are being conducted to study the agrochemical properties of the soil areas of the spent deposits on which these grass mixtures are grown.
Bioremediation is used, that is, plants affect the environment in different ways and three main approaches to bioremediation of soils with the help of microorganisms are being tested: Biostimulation, i.e., stimulating the development of native microflora in the contaminated area; bioadditioning, i.e. introducing biological preparations of microorganisms capable of degrading the pollutant into the soil and phytostimulation, i.e., using plants to stimulate the development of rhizosphere microorganisms. The main ones are rhizofiltration (roots absorb water and chemical elements necessary for the vital activity of plants); phytoextraction (accumulation of dangerous pollutants in the plant body (for example, heavy metals)); phytovolatilization (evaporation of water and volatile chemical elements (As, Se) by plant leaves); Phyto stabilization (conversion of chemical compounds into a less mobile and active form (which reduces the risks of contamination spread)); phytodegradation (degradation by plants and symbiotic microorganisms of the organic part of pollutants) and Phyto stimulation (stimulation of the development of symbiotic microorganisms involved in the process of cleaning soil). The results of the study are presented in subsequent papers (Valiyev et al., 2018;Bulaev et al., 2019;Kalybekov et al., 2020).

Conclusion
It was found that the highest productivity under experimental conditions was formed by a grass-andlegume mixture of crested wheatgrass-alfalfa-awnless brome (27.8 c/ha of green mass and 12.6 c/ha of dry matter). The highest nitrogen content was noted in alfalfa, which was part of the same grass mixture of crested wheatgrass-alfalfa-awnless brome. The conducted study has also revealed several issues that should be addressed for the successful implementation of new technologies for 277 the remediation of degraded pastures. It is necessary to find out how well and for how long the introduced species of fodder crops will be reproduced in conditions of natural growth, without additional human intervention. The issue related to the adaptive capabilities of artificial polyspecies phytocenoses, their ability to withstand adverse climatic conditions, such as drought, an increase in average annual temperature, etc., has not been fully clarified. This requires additional research.
The proposed predictive simulation model Eco Grass is built on the block principle, which allows embedding additional modules, expanding the functionality of the model. The algorithm can be modified. For example, if there is a lack of information on the dynamics of the water regime of the corresponding soils, regression equations or even tabular data can be used. A necessary condition for the possibility of using the model in the presented version is the availability of information on the dynamics of soil moisture and physiological parameters of plant vital activity.

Data Availability
The data used to support the findings of this study are included in the article.

Funding Statement
The study is funded by the Science Committee of the Ministry of Education and Science of the Republic of Kazakhstan (Grant No.АР09562508).