A method and system for reseeding and controlling Maowusu sandy land

Abstract

The present invention provides a reseeding and restoration method and system for the Mao Us Sandy Land, belonging to the field of sandy land restoration technology. The method comprises: measuring various characterizing indicators of reseeding plants before and after reseeding and restoration of the Mao Us Sandy Land, including changes in plant community composition and stoichiometric characteristics, changes in soil physical and chemical properties and carbon, nitrogen, and phosphorus stoichiometric characteristics, and changes in soil microbial carbon, nitrogen, and phosphorus community characteristics; using the Alpha diversity index to determine the species richness and diversity of the soil microbial community and obtain the changes in richness and diversity; analyzing the microbial species composition in the soil using a stacked bar chart to obtain information on the composition and abundance changes of dominant species in the soil microorganisms, and using the changes in richness and diversity, as well as the composition and abundance changes of dominant species, as characteristics of changes in soil microbial community structure; using the Pearson correlation analysis method to obtain correlations between the various characterizing indicators; and selecting corresponding reseeding plants based on the correlations between the various characterizing indicators to reseed and restore degraded grassland vegetation in the Mao Us Sandy Land. This method can effectively restore the Mao Us Sandy Land.

Description

Technical Field

[0001] The invention belongs to the technical field of sand land management, and particularly relates to a reseeding management method for Maowusu sand land. Background Art

[0002] After being rehabilitated, the Mu Us Desert has become an important ecological barrier in northern my country. However, due to climate change and improper utilization, grassland degradation still exists in some areas of the Mu Us Desert.

[0003] Restoration of degraded grassland vegetation is the most urgent task in my country's current grassland ecological management. No-till reseeding is a measure to restore degraded grassland vegetation. By reseeding suitable and high-quality grass species, the productivity and ecological service functions of degraded grassland can be improved.

[0004] The effects of different plant species on the Maowusu Desert vary significantly, making the selection of appropriate plant species crucial. As a unique ecosystem, the Maowusu Desert possesses unique soil structure, climatic conditions, and water regimes. Therefore, the plant species selected for reseeding must not only possess strong vitality but also possess sand-fixing capabilities, growth rates, and ecological adaptability tailored to the sandy environment.

[0005] If the selection is inappropriate, it may lead to slow plant growth, low survival rate, and even aggravate the deterioration of the sand. On the contrary, if plants with strong adaptability, rapid growth and good sand fixation effect are selected, it can not only effectively fix the sand and prevent wind erosion, but also promote the recovery of the sand ecosystem and the improvement of biodiversity. However, when selecting overseeding plants, since each plant will have multiple effects on multiple characterization indicators of the Maowusu Sandy Land after overseeding, when it is necessary to judge the overseeding effect of the Maowusu Sandy Land after overseeding, it is often necessary to collect multiple indicators to make a judgment, and the collection process is too cumbersome. Summary of the Invention

[0006] In order to overcome the deficiencies of the above-mentioned prior art, the present invention provides a method for reseeding and controlling Maowusu sandy land.

[0007] In order to achieve the above object, the present invention provides the following technical solutions:

[0008] A method for reseeding and controlling Maowusu sandy land comprises:

[0009] Various characterization indicators of the Maowusu sandy land before and after reseeding with various reseeded plants were measured, including changes in plant community composition and stoichiometric characteristics, changes in soil physical and chemical properties and carbon, nitrogen and phosphorus stoichiometric characteristics, and changes in soil microbial carbon, nitrogen and phosphorus and changes in soil microbial community structure characteristics;

[0010] Among them, the Alpha diversity index was used to determine the species richness and diversity of the soil microbial community in the Maowusu Sandy Land. A stacked bar chart was used to analyze the microbial species composition in the Maowusu Sandy Land soil to obtain the composition and abundance information of the dominant species in the soil microorganisms. The richness and diversity information, as well as the composition and abundance information of the dominant species, were used as the community structure characteristics of the soil microorganisms.

[0011] Use the Pearson correlation analysis method to obtain the correlation between various characterization indicators; select a single core indicator from the characterization indicators with high correlation, and multiple core indicators form a new characterization indicator system;

[0012] A new indicator system is used to evaluate the management effect of different reseeding species after reseeding, so as to determine the appropriate reseeding species for reseeding and restoration of degraded grassland vegetation in the Maowusu Desert.

[0013] Furthermore, the plurality of overseeding plants include:

[0014] When sowing alone, the plants to be sown include: Suaeda salsa, Calendula officinalis, Leymus chinensis, and alfalfa;

[0015] When sowing mixed seeds, the plants to be planted include: Leymus thunbergii and alfalfa.

[0016] Furthermore, the determination of the change in the plant stoichiometric characteristics includes:

[0017] Collect plant and litter samples;

[0018] The total carbon content of plant and litter samples was determined using the K2Cr2O7 heating method;

[0019] Place the fallen leaf sample in a digestion tube, add concentrated H2SO4 solution and digest it at 240℃ for one hour, then heat it to 380℃ and digest it. During the digestion process, add 30% H2O2 solution intermittently until the digestion solution becomes colorless or clear.

[0020] The total nitrogen and total phosphorus contents were determined using a continuous flow analyzer.

[0021] Furthermore, the determination of the soil physical and chemical properties includes:

[0022] Physical property determination:

[0023] Soil bulk density was measured using the knife ring method;

[0024] Measure soil moisture and pH;

[0025] Chemical property determination:

[0026] The organic carbon content of soil was determined using the K2Cr2O7 external heating method;

[0027] Total phosphorus content in soil samples was determined using a colorimetric method;

[0028] The nitrate nitrogen and ammonium nitrogen contents in the soil were measured by the extraction method.

[0029] Furthermore, the Pearson correlation analysis method is used to obtain the correlation relationship between the characterization indicators; the calculation formula is:

[0030]

[0031] Where: r represents the correlation coefficient between variables x and y, x i Indicates the x variable value of reseeding i, y i represents the y variable value of reseeding i, n represents the reseeding species, n = 28;

[0032] The significance of the correlation coefficient between variables was determined using the t-test:

[0033]

[0034] Furthermore, the community structure characteristics of soil microorganisms also include: structural differences of soil microbial communities, and calculation of structural differences of soil microbial communities, which includes:

[0035] Statistical algorithms were used to calculate the distances between communities of different microbial samples to obtain a distance matrix. NMDS analysis and ANOSIM / Adonis intergroup difference test were used to evaluate the similarity or difference of the overall community structure between different samples or groups.

[0036] Based on the Bray-Curtis distance, non-metric multidimensional analysis was used to obtain the differences in soil microbial community structure after reseeding.

[0037] Furthermore, the plant community composition was characterized by the importance value IV of each species, and the Shannon-Wiener index H, the Pilo evenness index J and the Simpson diversity index D were used to jointly characterize the community diversity;

[0038] The formula is:

[0039] IV = (relative height + relative coverage + relative density) / 3

[0040]

[0041] J=H / lnS

[0042]

[0043] Where: S is the total number of species, relative cover is the ratio of the cover of a certain species to the sum of the covers of all species, relative height is the ratio of the height of a certain species to the sum of the heights of all species, relative biomass is the ratio of the dry weight of the biomass of a certain species to the sum of the dry weight of the biomass of all species, P is the ratio of the dry weight of the biomass of a certain species to the sum of the dry weight of the biomass of all species, and P is the ratio of the dry weight of the biomass of a certain species to the sum of the dry weight of the biomass of all species. i It is the ratio of the importance value of a species to the sum of the importance values ​​of all species.

[0044] A reseeding management system for Maowusu sandy land is characterized by comprising:

[0045] The measurement module is used to measure various characterization indicators before and after the reseeding of various plants on the Maowusu Sandy Land. The characterization indicators include: changes in plant community composition and stoichiometric characteristics, changes in soil physical and chemical properties and carbon, nitrogen and phosphorus stoichiometric characteristics, and changes in soil microbial carbon, nitrogen and phosphorus and changes in soil microbial community structure characteristics;

[0046] Among them, the Alpha diversity index was used to determine the species richness and diversity of the soil microbial community in the Maowusu Sandy Land. A stacked bar chart was used to analyze the microbial species composition in the Maowusu Sandy Land soil to obtain the composition and abundance information of the dominant species in the soil microorganisms. The richness and diversity information, as well as the composition and abundance information of the dominant species, were used as the community structure characteristics of the soil microorganisms.

[0047] The correlation relationship building module is used to obtain the correlation relationship between various characterization indicators using the Pearson correlation analysis method; a single core indicator is selected from the characterization indicators with high correlation, and multiple core indicators form a new characterization indicator system;

[0048] The selection module is used to evaluate the treatment effect of different reseeding species after reseeding through a new indicator system, so as to determine the appropriate reseeding species for reseeding and restoration of degraded grassland vegetation in the Maowusu Sandy Land.

[0049] The method and system for reseeding and treating Maowusu sandy land provided by the present invention have the following beneficial effects:

[0050] This study first identified several indicators that characterize reseeding and restoration of the Maowusu Desert. Among these, the Alpha Diversity Index was used to assess species richness and diversity within the soil microbial community. Stacked bar charts were used to analyze the composition of soil microbial species, revealing changes in the structure of the soil microbial community. This information is crucial for selecting appropriate reseeding plants, as different plant species have varying effects on soil microbes, which are key factors influencing soil fertility and plant growth.

[0051] In addition, the Pearson correlation analysis method was used to obtain the correlation relationship between each characterization index. The correlation relationship characterizes the degree of mutual influence of each index. Some highly correlated indicators are affected synchronously, that is, if one index increases, all others increase. Therefore, the present invention selects a single index as the core index from the highly correlated indicators and constructs a new characterization index system. This allows for a comprehensive assessment of the effectiveness of reseeding and management of the Maowusu Desert using fewer indicators, without the need to collect a large number of characterization indicators. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] To more clearly illustrate the embodiments of the present invention and its design, the following briefly introduces the drawings required for this embodiment. The drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be derived from these drawings without inventive effort.

[0053] Figure 1 This is a schematic diagram of a reseeding treatment method for Maowusu sandy land according to the present invention;

[0054] Figure 2 This is a schematic diagram of a supplementary seeding cell design according to an embodiment of the present invention. DETAILED DESCRIPTION

[0055] In order to enable those skilled in the art to better understand the technical solution of the present invention and to be able to implement it, the present invention is described in detail below with reference to the accompanying drawings and specific embodiments. The following embodiments are only used to more clearly illustrate the technical solution of the present invention and are not intended to limit the scope of protection of the present invention.

[0056] Example:

[0057] In this example, four herbaceous plants were selected: Suaeda salsa (SG), Calamagrostis epigeios (CE), and Leymus secalinus (LS), which are salt-tolerant and drought-tolerant native species; and Medicago sativa (MS), which has strong adaptability, high yield, and high nutritional value. The experiment set up single sowing of Suaeda salsa (SG), Calamagrostis epigeios (CE), Leymus secalinus (LS), and Medicago sativa (MS), and mixed sowing of Leymus secalinus and Medicago sativa (LS+MS). The sowing rates for single sowing were 9 kg / hm-2 for Suaeda salsa, 4.5 kg / hm-2 for Calamagrostis epigeios, 25 kg / hm-2 for Leymus secalinus, and 18 kg / hm-2 for Medicago sativa. Based on the sowing rate of each grass species, the sowing rate of each grass species in the mixed sowing combination was 70% of its single sowing rate (Yao Zeying et al. 2020) (see Table 2-1 for specific sowing rates). Sowing was carried out in August 2021. When sowing, the seeds were mixed with diammonium phosphate (P2O5 ≥ 54%) in a ratio of 1:3 and then sown. A control (CK) was set up, with furrowing, fertilization, covering, and no sowing. Each treatment was repeated 3 times, with a total of 18 plots, with a plot spacing of 2m and a plot area of ​​100m. 2 (10m×10m), randomized block experiment was used for field reseeding ( Figure 2 ) Use an inverted "T"-shaped furrow opener to sow in rows, with a spacing of 30 cm between rows and a depth of 4 cm, covered with 2 cm of soil. No fertilizer or watering is required after reseeding, and the grassland will recover naturally.

[0058] Table 1 Reseeding species and seeding rates

[0059]

[0060] Step 1:

[0061] 1.1 Grassland vegetation survey

[0062] In each experimental plot, the cover of the community vegetation was visually observed. Three 1 m² (1 m × 1 m) quadrats (divided into 100 10 cm × 10 cm squares using cotton string) were randomly placed in the reseeded plots. The cover of each plant species in each 10 cm × 10 cm square was estimated, and the cover of the 100 squares was summed to obtain the total cover of the individual plant species. In addition, the number of plants of each species in the 1 m² quadrats was recorded as species abundance, and the height of each species was measured with a steel tape measure (at least five plants were measured and the average was used). All plants in the sample plot were cut flush with the ground and placed in cowhide bags. After cutting the aboveground plants, the grass litter was collected and placed in cowhide bags. The samples were brought back to the laboratory, first fixed at 105℃ for 20 minutes, then dried in an oven at 65℃ for 72 hours to constant weight, and then weighed and recorded. The aboveground biomass (AB) and litter (Litter) of each sample plot were crushed and passed through a 2mm sieve for subsequent analysis of indicators.

[0063] The species composition of the community was characterized by the importance value (IV) of each species, and the community α-diversity index was characterized by the Shannon-Winner index (H), Pielou index (J) and Simpson index (D).

[0064] IV = (relative height + relative coverage + relative density) / 3 (2-1)

[0065]

[0066] J=H / lnS (2-3)

[0067]

[0068] Where: S is the total number of species, relative cover is the ratio of the cover of a certain species to the sum of the covers of all species, relative height is the ratio of the height of a certain species to the sum of the heights of all species, relative biomass is the ratio of the dry weight of the biomass of a certain species to the sum of the dry weight of the biomass of all species, P is the ratio of the dry weight of the biomass of a certain species to the sum of the dry weight of the biomass of all species, and P is the ratio of the dry weight of the biomass of a certain species to the sum of the dry weight of the biomass of all species. i It is the ratio of the importance value of a species to the sum of the importance values ​​of all species.

[0069] 1.2 Soil sample and underground root collection

[0070] For the three 1m2 plots used to measure aboveground biomass, three random points were selected within each plot. Soil samples were first taken from 0-10 cm using a 5cm diameter soil augers and passed through a 2mm sieve. The sieved soil was divided into two portions: one portion was air-dried and stored for soil chemical property analysis; the other fresh sample was stored in a -80°C freezer for subsequent determination of soil microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), and microbial biomass phosphorus (MBP), as well as microbial community composition. Roots and soil were removed from the plot (0-50 cm) and separated. Plant roots were placed in a kraft bag, brought back to the laboratory, rinsed with clean water, and then dried at 105°C for 20 minutes. The roots were then oven-dried at 65°C for 72 hours to constant weight. The belowground biomass (UB) of each plot was then weighed and recorded. The weighed samples were then crushed and passed through a 2mm sieve for subsequent analysis of indicators.

[0071] Step 2:

[0072] 2.1 Analysis of carbon, nitrogen and phosphorus in plants and litter

[0073] Total carbon (TC), total nitrogen (TN), and total phosphorus (TP) content in plant and litter samples were determined using the K2Cr2O7 external heating method and the H2SO4-H2O2 digestion followed by continuous flow analyzer analysis. TC in crushed plant and litter samples was determined using the K2Cr2O7 heating method. Approximately 0.200 g of air-dried plant sample (containing 8 mL of K2Cr2O7 and 8 mL of H2SO4) was digested in an oil bath at 180°C for 5 min, followed by titration with FeSO4. TN and TP content in crushed plant and litter samples was determined using a flow analyzer. Approximately 0.200 g of leaf litter sample was placed in a 100 mL digestion tube, followed by the addition of 5 mL of concentrated H2SO4 solution and digestion at 240°C for one hour. The digestion was then heated to 380°C, with 30% H2O2 solution added intermittently during the digestion process until the digestion solution became colorless or clear. After fixing the volume to 50 mL with distilled water, the total nitrogen and total phosphorus contents were determined separately using a continuous flow analyzer with different standard curves and base solutions.

[0074] 2.2 Determination of soil physical and chemical properties

[0075] Soil bulk density (SBD) was measured using the ring knife method. Soil water content (SMC) was determined by drying secondary samples in an oven (105°C) to a constant weight. The weight difference before and after drying was used to calculate soil water content. Soil pH was determined by adding 50 mL of distilled water to a flask containing 10 g of soil. The suspension was shaken for 30 minutes, and then the soil pH was measured using a pH meter.

[0076] Soil organic carbon (OC) was determined using the K2Cr2O7 external heating method. Approximately 0.500 g of air-dried soil was digested at 180°C for 5 min using an oil bath and then titrated with FeSO4. The TN content in the soil was determined using a flow analyzer. Approximately 0.500 g of air-dried soil was digested with 1.85 g of a mixed catalyst (K2SO4:CuSO4·5H2O = 10:1) and 5 mL of H2SO4 at 380°C for 60 min. The volume was fixed to 100 mL with distilled water and then measured using a continuous flow analyzer (AA3, Germany). A colorimetric method was used to determine the TP content in the soil samples. Approximately 0.5 g of air-dried soil was digested with 2 mL of HClO4 and 8 mL of H2SO4 at 250°C for 60 min. After diluting to 20 mL with water, 5 mL of the supernatant was aspirated and added to 5 mL of molybdenum antimony reagent. The solution was then made up to 50 mL with water and measured at 880 nm using a UV spectrophotometer (UV2300, Japan). Nitrate nitrogen (NO₃⁻ -N) and ammonium nitrogen (NH₄⁺ -N) in the soil were measured using an extraction method. 5.00 g of soil was extracted with 50 mL of 1 mol·L⁻¹ KCl. After filtration, the solution was analyzed using a flow analyzer (AA3, Germany). To measure microbial biomass carbon (MBC), microbial biomass nitrogen (MBN), and microbial biomass phosphorus (MBP), a chloroform fumigation method was used. After extraction with 0.5 mol·L⁻¹ K₂SO₄, a TOC meter was used to determine dissolved carbon and nitrogen in the extract. Among them, part of the samples after chloroform fumigation were used to measure soil MBP. After extraction with 0.5 mol·L-1 NaHCO3, the molybdenum antimony colorimetric method was used to determine the phosphorus content in the extract.

[0077] 2.3 Determination of soil extracellular enzyme activity

[0078] Soil extracellular enzyme activity was measured using a 96-well microplate fluorescence assay. The assay steps were as follows: 1.000 g of fresh soil was weighed into a conical flask, sodium acetate buffer was added, and the mixture was homogenized by shaking. The soil was then added to a 96-well opaque microplate. The corresponding enzyme substrate was added, and standard and control groups were set up. After incubation at 25°C in the dark for 4 hours, sodium hydroxide solution was added to terminate the enzyme reaction. Fluorescence was measured using a microplate reader, with excitation at 365 nm and fluorescence at 460 nm. Finally, enzyme activity characteristics were calculated and analyzed. Detailed information on the carbon, nitrogen, and phosphorus-derived enzymes and their corresponding substrates measured in this study is shown below (Table 2-2).

[0079] Table 2-2 Basic information of extracellular enzymes

[0080]

[0081] Calculation of ecological stoichiometry of soil extracellular enzymes (LeBauer and STreseder 2008):

[0082] Carbon and nitrogen acquisition enzyme stoichiometric ratio = ln(CBH+BG):ln(NAG+LAP) (2-5)

[0083] Carbon and phosphorus acquisition enzyme stoichiometric ratio = ln(CBH+BG):ln(ALP) (2-6)

[0084] Stoichiometric ratio of nitrogen and phosphorus acquisition enzymes = ln(NAG+LAP):ln(ALP) (2-7)

[0085] Enzyme activity vector analysis:

[0086] VectorLength=√[ln(CBH+BG):ln(NAG+LAP)] 2 +[ln(CBH+BG):lnALP] 2 (2-8)

[0087] Vector Angle=Degrees{ATAN2[ln(CBH+BG):ln ALP,(ln(CBH+BG):ln(NAG+LAP))]}(2-9)

[0088] The vector length and angle of extracellular enzyme activity in soil after overseeding were calculated using soil enzyme activity ratios. The vector length indicates the degree of microbial carbon limitation; a longer vector indicates greater carbon limitation. The vector angle indicates microbial nitrogen or phosphorus limitation. An angle greater than 45° indicates phosphorus limitation, while an angle greater than 45° indicates nitrogen limitation.

[0089] 2.4 Soil microbial diversity sequencing

[0090] Sequencing analysis of soil microbial community structure and diversity: Sequencing was performed using the Illumina Miseq PE300 platform. Specific experimental operations and testing were completed by Shanghai Major Biotechnology Co., Ltd. (https: / / www.majorbio.com).

[0091] 2.5 Data Analysis

[0092] The Shapiro-Wilk test was used to test the distribution of all data, and all data followed a normal distribution. The homogeneity of variance in the one-way ANOVA analysis was used to test the variance of the different grass seed reseeding samples, and all sample variances were homogeneous.

[0093] The significance of the same index (plant AB, UB, TC, TN, TP, C:N, C:P, N:P; soil OC, TN, TP, C:N, C:P, N:P, MBC, MBN, MBP, microbial biomass C:N, microbial biomass C:P, microbial biomass N:P; enzyme activities CBH, BG, NAG, ALP, LAP) among different grass species (SG, CE, LS, MS, LS+MS, CK) was tested by one-way ANOVA (LSD) (P < 0.05);

[0094] Pearson correlation analysis was used to explore and analyze the correlation between the above indicators. Microbial alpha diversity is mainly used to study the diversity of a reseeded community. By evaluating a series of alpha diversity indices, information on species richness and diversity in the microbial community can be obtained.

[0095] Based on the species annotation results, stacked bar charts were used to analyze the microbial species composition in each reseeded plot (abundance ≥ 0.5%), and information such as the composition and abundance changes of the dominant species in each sample was obtained.

[0096] Differences in microbial community structure between samples can be quantified using statistical distance analysis. Statistical algorithms are used to calculate distances between samples, generating a sample distance matrix. NMDS analysis, combined with ANOSIM / Adonis intergroup difference tests, assesses similarities or differences in overall community structure between samples / groups. Nonmetric multidimensional analysis, based on the Bray-Curtis distance, was used to analyze differences in soil microbial community structure after reseeding.

[0097] This study was based on Person correlation analysis to show the correlation between different variables. Mantel Test was used to explore the correlation between the microbial community composition and diversity matrix and the environmental variable matrix. The calculation formula is as follows:

[0098]

[0099] Where r represents the correlation coefficient between variables x and y, xi represents the value of the x variable at reseeding i, yi represents the value of the y variable at reseeding i, and n represents the reseeding species. In this study, n = 28.

[0100] The significance of the correlation coefficient between variables was determined using the t-test:

[0101]

[0102] The data in this study were collated and calculated using Microsoft Excel 2019, the data were analyzed using SPSS (version 20.0), and the figures in the article were drawn using Origin 2022 and R (4.0.5).

[0103] in conclusion:

[0104] This study selected degraded grasslands in the Maowusu region and, based on previous research, selected Suaeda salsa, Imperata truncatula, Leymus chinensis, Medicago truncatula, and Leymus chinensis + Medicago truncatula for reseeding. Through field surveys, sample collection, and laboratory analysis, based on ecological stoichiometry theory, we systematically analyzed the ecological stoichiometric characteristics of plants, soils, microorganisms, and extracellular enzymes, as well as the characteristics of soil microbial communities after reseeding with different species. The following conclusions were drawn:

[0105] (1) Reseeding reduced the number of grassland species, and reseeded species were the most important species in the grassland. Overall, reseeding significantly increased grassland community cover and height, reduced grassland diversity index, and increased aboveground and belowground biomass and litter content in grassland communities. The TN content in the aboveground and belowground parts of reseeded alfalfa grassland communities significantly increased, while the TP content in the aboveground parts of reseeded Suaeda salsa grassland communities significantly increased, changing the nutrient ratios of plant communities.

[0106] (2) Reseeding of Acropora truncatula, Leymus chinensis, and Leymus chinensis + Medicago truncatula significantly increased SWC, while reseeding of Suaeda salsa and Medicago truncatula significantly decreased soil pH. Reseeding did not change SBD. Reseeding significantly increased soil OC, TN, and TP contents and changed the soil nutrient ratio.

[0107] (3) After reseeding, the activities of C, N, and P acquisition enzymes in grassland soil increased, and the enzyme activity ratio changed. Reseeding significantly increased the angle and length of the C, N, and P acquisition enzyme activity vectors (P<0.05). After reseeding, grassland soil microorganisms were all limited by N.

[0108] (4) Reseeding was beneficial for the storage of soil water and soil OC. There was a significant correlation between plant and soil C:N ratios. The stoichiometry of soil extracellular enzymes was not closely related to the stoichiometry of plants and litter. Overall, reseeding significantly increased the content of MBC, MBN, and MBP in grassland soils. Microorganisms primarily utilized nutrients in the soil, and microbial stoichiometry exhibited a homeostatic mechanism.

[0109] (5) The dominant categories of soil bacteria and fungi were similar before and after reseeding. The diversity of soil bacterial communities increased and the uniformity decreased after reseeding alfalfa and Leymus sibiricus + alfalfa. The diversity of fungal communities increased after reseeding alfalfa and Leymus sibiricus + alfalfa. After reseeding, the soil bacterial community responded more to reseeding, while the soil fungal community responded less to reseeding. Fungal α diversity was sensitive to changes in plant communities, while bacterial α diversity was not sensitive to changes in plant communities. Plant community characteristics and nutrient ratios affected the composition of bacterial communities, while the composition of fungal communities was regulated by plant biomass. Whether it was fungi or bacteria, plants affected the microbial community by affecting soil properties.

[0110] In summary, reseeding alfalfa and Leymus japonicus + alfalfa are both beneficial to improving grassland productivity and nutritional quality, improving soil physical and chemical properties, increasing soil nutrient content, increasing soil nutrient circulation rate, and enhancing soil carbon sequestration capacity. In the later management process, it is necessary to appropriately increase the application of phosphorus fertilizer to alleviate the phosphorus limitation of grassland.

[0111] The above-described embodiments are only preferred specific implementation methods of the present invention, and the protection scope of the present invention is not limited thereto. Any simple changes or equivalent replacements of the technical solutions that can be obviously obtained by any technician familiar with the field within the technical scope disclosed in the present invention fall within the protection scope of the present invention.

Claims

1. A method for reseeding and controlling Maowusu sandy land, characterized in that: include: Various characterization indicators of the Maowusu sandy land before and after reseeding with various reseeded plants were measured, including changes in plant community composition and stoichiometric characteristics, changes in soil physical and chemical properties and carbon, nitrogen and phosphorus stoichiometric characteristics, and changes in soil microbial carbon, nitrogen and phosphorus and changes in soil microbial community structure characteristics; Among them, the Alpha diversity index was used to determine the species richness and diversity of the soil microbial community in the Maowusu Sandy Land. A stacked bar chart was used to analyze the microbial species composition in the Maowusu Sandy Land soil to obtain the composition and abundance information of the dominant species in the soil microorganisms. The richness and diversity information, as well as the composition and abundance information of the dominant species, were used as the community structure characteristics of the soil microorganisms. Use the Pearson correlation analysis method to obtain the correlation between various characterization indicators; select a single core indicator from the characterization indicators with high correlation, and multiple core indicators form a new characterization indicator system; A new indicator system is used to evaluate the management effect of different reseeding species after reseeding, so as to determine the appropriate reseeding species for reseeding and restoration of degraded grassland vegetation in the Maowusu Desert.

2. The method for reseeding and controlling the Maowusu sandy land according to claim 1, wherein: The various overseeding plants include: When sowing alone, the plants to be sown include: Suaeda salsa, Calendula officinalis, Leymus chinensis, and alfalfa; When sowing mixed seeds, the plants to be planted include: Leymus thunbergii and alfalfa.

3. The method for reseeding and controlling the Maowusu sandy land according to claim 1, wherein: The determination of the change in the plant stoichiometric characteristics comprises: Collect plant and litter samples; The total carbon content of plant and litter samples was determined using the K2Cr2O7 heating method; Place the fallen leaf sample in a digestion tube, add concentrated H2SO4 solution and digest it at 240℃ for one hour, then heat it to 380℃ and digest it. During the digestion process, add 30% H2O2 solution intermittently until the digestion solution becomes colorless or clear. The total nitrogen and total phosphorus contents were determined using a continuous flow analyzer.

4. The method for reseeding and controlling Maowusu sandy land according to claim 1, wherein: The determination of the soil physical and chemical properties includes: Physical property determination: Soil bulk density was measured using the knife ring method; Measure soil moisture and pH; Chemical property determination: The organic carbon content of soil was determined using the K2Cr2O7 external heating method; Total phosphorus content in soil samples was determined using a colorimetric method; The nitrate nitrogen and ammonium nitrogen contents in the soil were measured by the extraction method.

5. The method for reseeding and controlling the Maowusu sandy land according to claim 1, wherein: The Pearson correlation analysis method is used to obtain the correlation relationship between the characterization indicators; the calculation formula is: Where: r represents the correlation coefficient between variables x and y, x i Indicates the x variable value of reseeding i, y i represents the y variable value of reseeding i, n represents the reseeding species, n = 28; The significance of the correlation coefficient between variables was determined using the t-test:

6. The method for reseeding and controlling Maowusu sandy land according to claim 1, wherein: The community structure characteristics of soil microorganisms also include: structural differences of soil microbial communities, and calculation of structural differences of soil microbial communities, which includes: Statistical algorithms were used to calculate the distances between communities of different microbial samples to obtain a distance matrix. NMDS analysis and ANOSIM / Adonis intergroup difference test were used to evaluate the similarity or difference of the overall community structure between different samples or groups. Based on the Bray-Curtis distance, non-metric multidimensional analysis was used to obtain the differences in soil microbial community structure after reseeding.

7. The method for reseeding and controlling Maowusu sandy land according to claim 1, wherein: The composition of the plant community was characterized by the importance value IV of each species, and the diversity of the community was jointly characterized by the Shannon-Wiener index H, the Pilo evenness index J and the Simpson diversity index D; The formula is: IV = (relative height + relative coverage + relative density) / 3 J=H / lnS Where: S is the total number of species, relative cover is the ratio of the cover of a certain species to the sum of the covers of all species, relative height is the ratio of the height of a certain species to the sum of the heights of all species, relative biomass is the ratio of the dry weight of the biomass of a certain species to the sum of the dry weight of the biomass of all species, P is the ratio of the dry weight of the biomass of a certain species to the sum of the dry weight of the biomass of all species, and P is the ratio of the dry weight of the biomass of a certain species to the sum of the dry weight of the biomass of all species. i It is the ratio of the importance value of a species to the sum of the importance values ​​of all species.

8. A reseeding management system for Maowusu sandy land, characterized in that: include: The measurement module is used to measure various characterization indicators before and after the reseeding of various plants on the Maowusu Sandy Land. The characterization indicators include: changes in plant community composition and stoichiometric characteristics, changes in soil physical and chemical properties and carbon, nitrogen and phosphorus stoichiometric characteristics, and changes in soil microbial carbon, nitrogen and phosphorus and changes in soil microbial community structure characteristics; Among them, the Alpha diversity index was used to determine the species richness and diversity of the soil microbial community in the Maowusu Sandy Land. A stacked bar chart was used to analyze the microbial species composition in the Maowusu Sandy Land soil to obtain the composition and abundance information of the dominant species in the soil microorganisms. The richness and diversity information, as well as the composition and abundance information of the dominant species, were used as the community structure characteristics of the soil microorganisms. The correlation relationship building module is used to obtain the correlation relationship between various characterization indicators using the Pearson correlation analysis method; a single core indicator is selected from the characterization indicators with high correlation, and multiple core indicators form a new characterization indicator system; The selection module is used to evaluate the treatment effect of different reseeding species after reseeding through a new indicator system, so as to determine the appropriate reseeding species for reseeding and restoration of degraded grassland vegetation in the Maowusu Sandy Land.

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