Restoration method for degraded desert steppe soil seed bank

Abstract

The invention provides a method for restoring a degraded desert steppe soil seed bank, and belongs to the technical field of ecological restoration. The invention discloses a method for repairing a degraded desert steppe soil seed bank. The method comprises the following steps: dividing degraded desert steppes into three landscape types according to the high (greater than 0.3) vegetation coverage, the middle (0.15-0.3) vegetation coverage and the low (less than or equal to 0.15) vegetation coverage; the method comprises the following steps: respectively taking grassland sample plots of three landscape types as centers to make buffer areas with radiuses of 100-500m, and enclosing the buffer areas formed by the minimum radiuses and meeting the requirements that the aggregation degree index AI is greater than or equal to 80 and the average plaque area is greater than or equal to 2hm together with the grassland sample plots to form a soil seed remediation area; and after soil remediation is conducted on the soil seed remediation area, dominant species are introduced to increase the plant coverage degree. The method enriches the gene resources of the soil seed bank, further enhances the adaptability of plants to the ecological system, improves the survival rate of seeds, and promotes the restoration of the soil seed bank.

Description

Technical Field

[0001] This invention belongs to the field of ecological restoration technology, specifically relating to a method for restoring seed banks of degraded desert steppe soil. Background Technology

[0002] The soil seed bank comprises all viable seeds existing in the soil surface and within the soil. It forms the basis for vegetation regeneration and community succession, playing a crucial role in the restoration of degraded vegetation ecosystems, particularly in the restoration of desertified grassland ecosystems. Desertified grassland ecosystems are characterized by altered grassland community structure, reduced vegetation cover, and a pronounced trend towards landscape fragmentation. Landscape pattern significantly impacts plant communities. Severe fragmentation leads to increased habitat edge effects, interrupted matrix continuity, and the formation of discrete patch clusters, resulting in reduced patch connectivity. This, in turn, affects seed dispersal and ecological processes such as soil nutrient allocation and microbial structural characteristics, further impacting soil seed bank diversity. Therefore, constructing rationally designed soil seed bank landscape pattern restoration zones facilitates the exchange of nutrients and microorganisms in the soil, as well as pollen and seed dispersal, thereby promoting soil seed bank restoration.

[0003] Currently, methods for restoring soil seed banks in desertified grasslands mainly focus on addressing issues such as low water holding capacity, low organic matter content, and low soil fertility in desertified soils. This results in the inability to construct reasonable restoration areas during the soil seed bank restoration process, which disrupts the connectivity of the ecological environment in the restoration area, hinders the natural diffusion and dissemination of seeds, limits the introduction of new species, affects the activities of soil animals and microorganisms, and damages the integrity of the soil ecosystem. Summary of the Invention

[0004] In view of this, the purpose of this invention is to provide a method for restoring degraded desert steppe soil seed banks, which promotes the dispersal of soil seeds and the exchange of soil nutrients from the perspective of landscape pattern, thereby increasing the species richness of the soil seed bank and achieving good restoration results.

[0005] This invention provides a method for remediating degraded desert steppe soil seed banks, comprising the following steps: Degraded desert steppes are classified into three landscape types based on their vegetation coverage: high, medium, and low. High vegetation coverage is greater than 0.3, medium vegetation coverage is 0.15 to 0.3, and low vegetation coverage is ≤0.15. Using grassland plots of three different landscape types as the center, buffer zones with radii of 100-500m were constructed. The buffer zones with the smallest radii that meet the requirements of aggregation index AI≥80 and average patch area≥2hm² were enclosed together with the grassland plots to form soil seed remediation areas. After soil remediation is carried out in the soil seed remediation area, dominant species are introduced to increase plant coverage.

[0006] Preferably, the vegetation coverage is calculated based on the normalized vegetation index of degraded desert steppe using a pixel-based binary model. The calculation formula I for vegetation coverage is as follows: FVC=(NDVI-NDVI min ) / (NDVI max -NDVI min Formula I Where FVC is vegetation cover and NDVI is... min The minimum NDVI value in the study area, NDVI max This represents the maximum NDVI value in the study area. The FVC is calculated using the above formula with thresholds of 5% and 95%.

[0007] Preferably, the formula II for calculating the normalized vegetation index of the degraded desert steppe is: NDVI=(NIR+RED) / (NIR-RED) Formula II.

[0008] Wherein, NDVI represents the Normalized Difference Vegetation Index, NIR represents Landsat remote sensing image data in the near-infrared band, and RED represents Landsat remote sensing image data in the red band.

[0009] Preferably, the formula for calculating the aggregation index AI is shown in Formula III; Formula III Where gi is the number of adjacent edges between patches of each landscape type, and maxgi is the number of adjacent edges between patches of each landscape type in the most likely clustering state.

[0010] Preferably, the formula for calculating the average area of ​​the patch is shown in Formula IV; AREA_MN=A / N Formula IV Where AREA_MN represents the average area of ​​patches, A is the total area of ​​patches, and N is the number of patches. The average area of ​​patches is an indicator reflecting the degree of landscape fragmentation.

[0011] Preferably, the soil remediation includes increasing soil moisture content and organic matter content according to the landscape type: When the soil remediation area is a low-coverage grassland area, the application rate of soil remediation agent is 6.5~8 kg / m². 2 The irrigation water volume keeps the soil moisture holding capacity above 12%; When the soil remediation area is a medium-coverage grassland, the application rate of soil remediation agent is 5.5~7 kg / m².2 The irrigation water volume keeps the soil moisture holding capacity above 15%; When the soil remediation area is a high-coverage grassland, the application rate of soil remediation agent is 4-5.5 kg / m². 2 The irrigation water volume keeps the soil moisture holding capacity above 20%.

[0012] Preferably, the dominant species are obtained by sowing different plant seeds according to the landscape type: In grassland areas with low vegetation cover, annual plants with nitrogen-fixing capabilities, whose seeds are dispersed by wind or mucus, should be sown at a seed density of 30-40 g / m². 2 ; In grassland areas with medium vegetation cover, perennial plants with nitrogen-fixing capabilities and seeds dispersed by wind should be preserved, with a seed sowing density of 25-35 g / m². 2 ; In grassland areas with high vegetation cover, the sowing density for perennial plants whose seeds are dispersed by animals or through bursting is 15-30 g / m². 2 .

[0013] Preferably, the sown plants in the low vegetation cover grassland area include at least one of the following: pigweed, sand privet, and sweet clover; The sown plants in the grassland area with medium vegetation cover include at least one of the following: Caragana korshinskii, Alfalfa, and alfalfa. The plant species sown in the high vegetation coverage grassland area include at least one of the following: Astragalus membranaceus, Ilex chinensis, and Caragana korshinskii.

[0014] Preferably, the method also includes measuring the soil seed bank density and diversity before and after restoration in grassland areas of three different landscape types to assess the effectiveness of soil seed bank restoration in degraded desert grasslands.

[0015] Preferably, the formula for calculating the soil seed bank density is shown in Formula V: Soil seed bank density = area of ​​plot / total number of seeds in plot × 10000 (Formula V) The diversity of the seed bank is represented by the Shannon-Wiener diversity index, and the calculation formula is shown in Formula VI. Shannon-Wiener Diversity Index = Formula VI; Where: S is the total number of species in the quadrat; i represents the i-th species in the seed bank, P i Let i be the proportion of the number of individuals of plant species i to the total number of individuals.

[0016] This invention provides a method for remediating soil seed banks in degraded desert steppes. The method categorizes degraded desert steppes into three landscape types based on vegetation cover: high (greater than 0.3), medium (0.15-0.3), and low (≤0.15). A buffer zone with a radius of 100-500m is created centered on each of the three landscape types' steppe plots. This buffer zone, with a minimum radius meeting the requirements of an aggregation index (AI) ≥ 80 and an average patch area ≥ 2 hm², is then enclosed along with the steppe plots to form a soil seed remediation area. After soil remediation in this area, dominant species are introduced to increase plant cover. Based on the natural environmental characteristics of degraded desert steppes, this invention optimizes the landscape pattern and scale of the remediation area by establishing a reasonable soil seed bank remediation area, promoting the exchange of nutrients in the soil and the dispersal of plant seeds, thereby increasing the species richness of the soil seed bank. Meanwhile, based on the characteristics of the landscape pattern, dominant species with ecological characteristics that are compatible with the local environment and suitable for survival were introduced, which enriched the genetic resources of the soil seed bank, further enhanced the plant's adaptability to the ecosystem, improved seed survival rate, and promoted the restoration of the soil seed bank. Detailed Implementation

[0017] This invention provides a method for remediating degraded desert steppe soil seed banks, comprising the following steps: Degraded desert steppes are classified into three landscape types based on their vegetation coverage: high, medium, and low. High vegetation coverage is greater than 0.3, medium vegetation coverage is 0.15 to 0.3, and low vegetation coverage is ≤0.15. Using grassland plots of three different landscape types as the center, buffer zones with radii of 100-500m were constructed. The buffer zones with the smallest radii that meet the requirements of aggregation index AI≥80 and average patch area≥2hm² were enclosed together with the grassland plots to form soil seed remediation areas. After soil remediation is carried out in the soil seed remediation area, dominant species are introduced to increase plant coverage.

[0018] This invention classifies degraded desert steppe into three landscape types based on the degree of vegetation coverage: high, medium, and low. High vegetation coverage is greater than 0.3, medium vegetation coverage is 0.15~0.3, and low vegetation coverage is ≤0.15.

[0019] In this invention, the characteristics of the degraded desert steppe are preferably altered steppe community structure, reduced vegetation cover, and a distinct trend of landscape fragmentation. In this embodiment, the degraded desert steppe is selected from the desertified steppe of Siziwang Banner, with an experimental area of ​​not less than 10 square kilometers.

[0020] In this invention, the vegetation cover is calculated using a pixel-based binary model based on the normalized vegetation index (FVC) of degraded desert steppe; the calculation formula I for the vegetation cover (FVC) is as follows: FVC=(NDVI-NDVI min ) / (NDVI max -NDVI min Formula I Among them, NDVI min The minimum NDVI value in the study area, NDVI max This represents the maximum NDVI value in the study area. The FVC is calculated using the above formula with thresholds of 5% and 95%.

[0021] In this invention, the formula II for calculating the normalized vegetation index of the degraded desert steppe is: NDVI=(NIR+RED) / (NIR-RED) Formula II.

[0022] Wherein, NDVI represents the Normalized Difference Vegetation Index, NIR represents Landsat remote sensing image data in the near-infrared band, and RED represents Landsat remote sensing image data in the red band. The NDVI is calculated using Landsat remote sensing imagery to acquire the desert steppe imagery of the grassland to be measured, and then using remote sensing image processing software to obtain image data in the red and near-infrared bands. The preferred time to acquire the desert steppe remote sensing imagery of the grassland to be measured is July to August each year.

[0023] In this invention, to provide a restorative effect, it is preferable to also include a control area, the grassland area and landscape type of which are the same as or similar to those of the experimental area. The control area includes degraded desert steppe regions with high, medium, and low vegetation cover.

[0024] After identifying grassland plots of three different landscape types, this invention creates buffer zones with radii of 100-500m centered on each of the three types of grassland plots. The buffer zones with the smallest radii that meet the requirements of aggregation index AI≥80 and average patch area≥2hm² are then enclosed together with the grassland plots to form soil seed remediation areas.

[0025] In this invention, the calculation formula for the aggregation index AI is preferably as shown in Formula III; Formula III Where gi is the number of adjacent edges between patches of each landscape type, and maxgi is the number of adjacent edges between patches of each landscape type in the most likely clustering state. The clustering index AI is preferably calculated using the software fragstats.

[0026] In this invention, the formula for calculating the average area of ​​the patch is preferably as shown in Formula IV; AREA_MN=A / N Formula IV Where AREA_MN represents the average area of ​​patches, A is the total area of ​​patches, and N is the number of patches. The average area of ​​patches is an indicator reflecting the degree of landscape fragmentation. The aggregation index and the average area index of patches are calculated using Fragstats software.

[0027] In this invention, when a grassland area within a radius of 500 meters meets the requirements of an aggregation index AI ≥ 80 and an average patch area ≥ 2 hm², the area is fenced off according to a radius of 500 meters. The control area is fenced off with the same radius as the experimental area. This fencing facilitates the flow of substances and the dispersal of pollen and seeds within the restoration area, and fencing both the experimental and control areas with the same radius helps in observing the restoration effect.

[0028] After obtaining the soil seed remediation area, the present invention performs soil remediation on the soil seed remediation area and then introduces dominant species to increase plant coverage.

[0029] In this invention, the soil remediation preferably includes increasing soil moisture content and organic matter content according to the landscape type: when the soil seed remediation area is a low-coverage grassland area, the soil remediation agent is applied at a rate of 6.5~8 kg / m². 2 It can be 7~7.5 kg / m 2 Irrigation water should maintain soil moisture content at 12% or higher, ideally 13%–15%. When the soil remediation area is a medium-coverage grassland, the application rate of soil remediation agent should be 5.5–7 kg / m². 2 Irrigation water should maintain soil moisture content at 15% or higher, ideally 16%–20% or even 18%. When the soil remediation area is a high-coverage grassland, the application rate of soil remediation agent should be 4–5.5 kg / m². 2The irrigation water volume should be such that the soil moisture holding capacity is above 20%, specifically 21%~25% or 23%. The soil remediation agent preferably comprises the following components by mass percentage: 20%~30% clay, 30%~40% cow manure, 20%~30% straw, and 15%~30% water-retaining agent; alternatively, it can be 22%~28% clay, 32%~38% cow manure, 22%~28% straw, and 17%~25% water-retaining agent; or 25% clay, 35% cow manure, 25% straw, and 20% water-retaining agent. The water-retaining agent is preferably polyacrylate. This invention does not impose any special limitations on the preparation method of the soil remediation agent; any method well-known in the art can be used. When remediating the soil, if the soil is sandy, the soil remediation agent is applied after shallow tillage. The depth of shallow tillage is preferably 10~20cm. If the soil is uncovered, it is preferable to tillage to increase soil aeration and permeability before applying the soil remediation agent. Irrigation for different landscape types should be carried out at 80% to 120% of the actual water requirements of the subsequently introduced dominant species. Soil remediation effectively increases soil moisture content, organic carbon content, and total nitrogen content: for example, after soil remediation treatment, soil water holding capacity in low-vegetation-coverage grassland areas increases from 5% to over 12%, soil organic carbon content increases from 1% to 2% to 5%, and total nitrogen content can increase from 0.1% to 0.2% to 0.3% to 0.5%. In medium-vegetation-coverage grassland areas, soil water holding capacity increases from 8% to over 15%, soil organic carbon content increases from 1.2% to 3% to 2.5% to 6%, and total nitrogen content increases from 0.2% to 0.3% to 0.4% to 0.6%. In grassland areas with high vegetation cover, soil water holding capacity can be increased from 10% to over 20%, soil organic carbon content can be increased from 2%~4% to 3%~7%, and total nitrogen content can be increased from 0.3%~0.4% to 0.5%~0.7%. The preferred method for determining organic carbon content is volumetric analysis. The preferred method for determining total nitrogen content is the semi-micro Kjeldahl method.

[0030] In this invention, a dominant species is introduced one week after soil remediation. The dominant species are preferably different plant seeds sown according to the landscape type: in low-vegetation-coverage grassland areas, annual plants with nitrogen-fixing capabilities are sown, and their seeds are dispersed by wind or mucus, with a sowing density of 30-40 g / m². 2 It can be 32~38g / m 2 35g / m 2 In grassland areas with moderate vegetation cover, perennial plants with nitrogen-fixing capabilities and seeds dispersed by wind should be preserved, with a seed sowing density of 25-35 g / m². 2 It can be 27~32g / m 2 30g / m 2In grassland areas with high vegetation cover, for the sowing of perennial plants whose seeds are dispersed by animals or through bursting, the sowing density should be 15-30 g / m². 2 It can be 17~28g / m 2 25g / m 2 The sown plants in the low-vegetation-coverage grassland area include at least one of the following: *Salvia splendens*, *Salvia splendens*, and *Osmanthus fragrans*. The sown plants in the medium-vegetation-coverage grassland area include at least one of the following: *Caragana korshinskii*, *Alternanthera philoxeroides*, and alfalfa. The sown plants in the high-vegetation-coverage grassland area include at least one of the following: *Astragalus membranaceus*, *Ilex chinensis*, and *Caragana korshinskii*.

[0031] In this invention, it is preferable to further include assessing the effectiveness of soil seed bank restoration in degraded desert steppe by separately measuring the soil seed bank density and diversity before and after restoration in grassland areas of three different landscape types. The formula for calculating the soil seed bank density is given in Formula V: Soil seed bank density = area of ​​plot / total number of seeds in plot × 10000 (Formula V) The preferred method for calculating the total number of seeds in a quadrat is to evenly set up 20 quadrats of 1m×1m size on a grassland plot. A 10cm×10cm×10cm soil block is dug out from each quadrat. All soil samples from the 20 quadrats are mixed, air-dried, and stored in a well-ventilated and dry environment. A germination experiment is conducted for 30 days to obtain the number of seeds in the soil seed bank per unit area.

[0032] In this invention, the seed bank diversity is represented by the Shannon-Wiener diversity index, and the calculation formula is given in Formula VI; Shannon-Wiener diversity index = Formula VI; Where: S is the total number of species in the quadrat; i represents the i-th species in the seed bank, P i Let i be the proportion of the number of individuals of plant species i to the total number of individuals.

[0033] In one embodiment of the present invention, the seed density and vegetation diversity index of desert steppe areas of three landscape types were effectively improved. The seed density of the low vegetation cover steppe area increased by 6.75 times, and the diversity index increased from 0.3 to 1.5; the seed density of the vegetation cover steppe area increased by 5 times, and the diversity index increased from 0.8 to 2.1; and the seed density of the vegetation cover steppe area increased by 3 times, and the diversity index increased from 0.5 to 1.8.

[0034] The following detailed description of a method for restoring degraded desert steppe soil seed bank provided by the present invention, with reference to specific embodiments, should not be construed as limiting the scope of protection of the present invention.

[0035] Example 1 1. Divide the sample plots into different landscape types. The desertified grassland in Siziwang Banner, Inner Mongolia Autonomous Region, was selected in July and August 2022, with an experimental area of ​​10 square kilometers. Landsat remote sensing imagery was used to acquire remote sensing images of the desertified grassland in Siziwang Banner, Inner Mongolia Autonomous Region. The red band and near-infrared band of the image data were acquired using the remote sensing image processing software ENVI. The NDVI (Normalized Difference Vegetation Index) of the desert grassland was calculated according to Formula II, and an NDVI distribution map was drawn. Then, based on the NDVI index, the vegetation cover (FVC) was calculated according to Formula I based on the pixel bisection model.

[0036] NDVI=(NIR+RED) / (NIR-RED) Formula II.

[0037] Wherein, NDVI represents the Normalized Difference Vegetation Index, NIR represents Landsat remote sensing image data in the near-infrared band, and RED represents Landsat remote sensing image data in the red band.

[0038] FVC=(NDVI-NDVI min ) / (NDVI max -NDVI min Formula I Among them, NDVI min The minimum NDVI value in the study area, NDVI max This represents the maximum NDVI value in the study area. The FVC is calculated using the above formula with thresholds of 5% and 95%.

[0039] Based on the FVC (Farm Cover Value) results, grasslands were classified into three landscape types: low-coverage grassland (FVC ≤ 0.15), medium-coverage grassland (0.15 < FVC ≤ 0.3), and high-coverage grassland (FVC > 0.3). Two plots were selected for each landscape type, each with an area greater than 1 square kilometer and similar vegetation cover and species composition. These plots were numbered 1 and 2, with plot 1 serving as the experimental area and plot 2 as the control area. Soil treatments and the introduction of dominant species were implemented according to the specific landscape type to achieve seed bank remediation.

[0040] 2. Seed bank testing Soil seed bank density and diversity were measured in six sample plots across three grassland regions: low-coverage, medium-coverage, and high-coverage. In March 2023, 20 1m × 1m quadrats were evenly distributed across the sample plots. A 10cm × 10cm × 10cm soil clod was excavated from each quadrat, and all soil samples were mixed, air-dried, and stored in a well-ventilated and dry environment. Germination experiments were then conducted in the laboratory. Soil was spread evenly in germination trays, with a soil thickness of 0.5–2cm. The room temperature was controlled at 20–30℃, and appropriate soil moisture was maintained. Sufficient ventilation and light were ensured. Seed germination was recorded every two days for three months. Species identification, recording, and removal were performed regularly during the experiment. Soil seed bank density is expressed as the number of germinating seeds per unit area of ​​soil (seeds·m²). -2 The calculation formula is shown in Formula V.

[0041] Density = Area of ​​quadrat / Total number of seeds in quadrat × 10000 (unit conversion) Equation V; Seed bank diversity is represented by the Shannon-Wiener diversity index (H), and the calculation formula is given in Formula VI; Shannon-Wiener Diversity Index = Formula VI; In the formula: S is the total number of species in the quadrat; i represents the i-th species in the seed bank, P i Let i be the proportion of the number of individuals of plant species i to the total number of individuals.

[0042] 3. Enclose the seed bank restoration area Using plot number 1 in each of the three grassland zones (low cover grassland, FVC ≤ 0.15, medium cover grassland, 0.15 < FVC ≤ 0.3, and high cover grassland, FVC > 0.3) as the center, buffer zones were demarcated according to the Aggregation Index (AI) and average area of ​​patches (AREA_MN). The Aggregation Index (AI) for each buffer zone was calculated using the fragstats software, as shown in Formula III below: Formula III; Where gi is the number of adjacent edges between patches of a certain type, and max gi is the number of adjacent edges of patches of that type in the most likely clustering state.

[0043] The degree of landscape fragmentation is reflected by the average area of ​​patches (AREA_MN), and the calculation formula is shown in Formula IV: Formula IV: AREA_MN=A / N

[0044] N represents the total number of patches, and A represents the total landscape area.

[0045] The buffer zone must have an AI ≥ 80 and an AREA_MN ≥ 2 hm². The area with the smallest radius meeting both requirements should be selected as the soil seed bank remediation area for enclosure. If both requirements are met within a 500m radius area, then the 500m radius area should be enclosured accordingly. The control area of ​​plot 2 should be enclosured based on the enclosure radius set for the experimental plot 1.

[0046] 4. Increase soil moisture content and organic matter content Within the enclosed seed bank remediation area of ​​plot 1 in three landscape types, eutrophication was performed on sandy soil and unvegetated soil in June and August to improve soil fertility and water retention. Eutrophication involved applying a soil remediation agent before sowing. This agent consisted of clay, cow manure, straw, and a water-retaining agent in a mass ratio of 3:4:2:1. The water-retaining agent was a polyacrylate product. For low-coverage grassland areas (FVC ≤ 0.15), 8 kg of soil remediation agent was added per square meter; for medium-coverage grassland areas (0.15 < FVC ≤ 0.3), 7 kg of soil remediation agent was added per square meter; and for high-coverage grassland areas (FVC > 0.3), 5.5 kg of soil remediation agent was added per square meter. Sandy soil was shallowly tilled to a depth of 15 cm; simultaneously, unvegetated soil was tilled to a depth of 10-15 cm to increase soil aeration and permeability. Irrigation was then carried out in the remediation area. After soil remediation treatment, soil moisture content, organic carbon content, and total nitrogen content were measured using the following methods: (1) Soil moisture content was calculated using the drying method. Five quadrats were evenly selected from plot 1 of the three landscape types. For each quadrat, a 10cm soil layer was extracted using the S-shaped five-point method. After mixing the soil, it was dried at a constant temperature of (105±0.5)℃ until the mass remained constant. The soil mass moisture content was calculated according to formula VII: Soil moisture content (%) = (Wet soil mass - Dry soil mass) / Dry soil mass × 100% Formula VII.

[0047] Soil water holding capacity increased from 3% to 12.2% in low-coverage grassland areas, from 8.3% to 15.6% in medium-coverage grassland areas, and from 10.3% to over 21.4% in high-coverage grassland areas.

[0048] (2) Soil organic carbon content was determined using volumetric analysis. Five quadrats were evenly selected from plot 1 of the three landscape types. Soil samples from the 0-20 cm layer were collected from each quadrat using the S-shaped five-point method. After air drying, plant debris, roots, stones, and other impurities were removed. The soil was then ground using a mortar and pestle until it passed through a sieve with a 0.25 mm aperture. 0.5000 g of soil sample was accurately weighed and 10 mL of 0.8 mol / L potassium dichromate (K₂Cr₂O₇) solution was added. Then, 15 mL of concentrated H₂SO₄ (98%, density 1.84 g / cm³) was rapidly injected while shaking to prevent clumping. Insert the test tube into a preheated oil bath (175±5℃) and start timing for 5 min±10 s from boiling. Immediately remove the test tube and cool it to room temperature (approximately 40℃). Then transfer the solution in the test tube to a 250 ml Erlenmeyer flask. Rinse the test tube and funnel several times with distilled water, pouring the rinsing solution into the Erlenmeyer flask to make the total volume of the solution in the flask approximately 60-80 ml. Add 3 drops of o-phenanthroline indicator and titrate with 0.2 mol / L FeSO4 standard solution. The color change will be: orange-yellow → blue-green → brown-red (endpoint). Perform a blank test following the same steps without adding soil samples. Calculate the organic carbon content according to Formula VIII.

[0049] Formula VIII In the formula: V0 represents the volume of FeSO4 consumed in the blank titration (mL), V represents the volume of FeSO4 consumed in the sample titration (mL), C represents the concentration of the FeSO4 standard solution (mol / L), 0.003 represents the number of grams of 1 mmol of carbon, and 1.6 represents the coefficient for converting organic carbon to organic matter.

[0050] The soil organic carbon content in low-coverage grassland areas can be increased from 1.5% to 4.3%, in medium-coverage grassland areas from 2.1% to 4.9%, and in high-coverage grassland areas from 3.1% to 5.2%.

[0051] (3) The Kjeldahl method was used to determine the total nitrogen content in the soil. Five quadrats were evenly selected from plot 1 of the three landscape types. A 10 cm soil layer was collected from each quadrat using the S-shaped five-point method. After air drying, plant debris, roots, stones, and other impurities were removed. The soil was then ground in a mortar and pestle until it passed through a sieve with a 0.25 mm aperture. 1 g of soil sample was weighed and placed in a Kjeldahl flask. 5 ml of 98% H2SO4 was added and heated to digest until the solution turned a clear blue-green color. After cooling, the solution was washed into a 100 mL volumetric flask and diluted to volume. The solution was left to stand overnight. 10 mL of the diluted solution was injected into a Kjeldahl distillation apparatus and 10 mL of 40% NaOH was added to create an alkaline environment. The receiving flask was pre-filled with 20 mL of 2% boric acid + mixed indicator (methyl red-bromocresol green). Steam distillation was carried out for 5 min. The absorbance was titrated with 0.01 mol / L HCl standard solution. The endpoint was reached when the color changed from green to dark red. The same steps were followed, but without adding soil samples, to perform a blank test. Calculate the total nitrogen content according to Formula VIIII.

[0052] Formula VIII In the formula: V represents the volume of HCl consumed in the sample titration (mL), V0 represents the volume of HCl consumed in the blank titration (mL), C represents the concentration of the HCl standard solution (mol / L), m represents the soil mass (g), 0.014 represents the number of grams of 1 mmol of nitrogen, and 0.1 represents the fractionation factor (10mL / 100mL).

[0053] The total nitrogen content in soils of low-coverage grasslands can be increased from 0.1% to 0.35%, in medium-coverage grasslands from 0.23% to 0.45%, and in high-coverage grasslands from 0.35% to 0.6%.

[0054] 5. Introduction and Coverage of Dominant Species Within the enclosed seed bank remediation areas of plot 1 in three landscape types, dominant species were introduced into the unvegetated areas of different landscapes one week after soil treatment in June and August. For low-coverage grassland areas (FVC≤0.15), annual plants with strong nitrogen-fixing capabilities and whose seeds are dispersed by wind, mucilage, or from the canopy seed bank were selected, such as *Salvia splendens*, *Salvia splendens*, and *Sweet clover*, with a seed density of not less than 30-40 g / m². 2 Sowing is necessary to increase plant survival rates. For grasslands with moderate cover (0.15 < FVC ≤ 0.3), perennial seed plants with nitrogen-fixing capabilities and wind-dispersed characteristics are preferred, such as *Caragana korshinskii*, *Alfalfa*, and *Alfalfa*. The seed density should be no less than 25-35 g / m². 2To increase plant survival rate, for high-coverage grassland areas (FVC > 0.3), choose perennial plants whose seeds rely on animals or burst dispersal, such as Astragalus membranaceus, Ilex chinensis, and Caragana korshinskii. The seed density at sowing should not be less than 20 g / m². 2 To increase plant survival rate, after sowing, cover the soil surface with a 2-3 cm thick layer of organic material (such as crushed straw). This helps maintain soil moisture, regulate soil temperature, and prevents the seeds from being eaten by birds or other animals. Replant dominant species in June and August for two consecutive years, sowing at least 5 herbaceous plants and 2 shrubs each year.

[0055] 6. Repair Effectiveness Evaluation Form Two years after sowing, the seed density and diversity of the soil seed bank in the experimental area were significantly improved compared with the control area. The evaluation results are shown in Table 1 below.

[0056] Table 1. Overview of Repair Results

[0057] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for remediating degraded desert steppe soil seed banks, characterized in that, Includes the following steps: Degraded desert steppes are classified into three landscape types based on their vegetation coverage: high, medium, and low. High vegetation coverage is greater than 0.3, medium vegetation coverage is 0.15 to 0.3, and low vegetation coverage is ≤0.

15. Using grassland plots of three different landscape types as the center, buffer zones with radii of 100-500m were constructed. The buffer zones with the smallest radii that meet the requirements of aggregation index AI≥80 and average patch area≥2hm² were enclosed together with the grassland plots to form soil seed remediation areas. After soil remediation is carried out in the soil seed remediation area, dominant species are introduced to increase plant coverage.

2. The method for remediating degraded desert steppe soil seed banks according to claim 1, characterized in that, The vegetation coverage was calculated using a pixel-based binary model based on the normalized vegetation index of degraded desert steppe. The calculation formula I for vegetation coverage is as follows: FVC=(NDVI-NDVI min ) / (NDVI max -NDVI min ) Formula I Where FVC is vegetation cover and NDVI is... min The minimum NDVI value in the study area, NDVI max This represents the maximum NDVI value in the study area. The FVC is calculated using the above formula with thresholds of 5% and 95%.

3. The method for remediating degraded desert steppe soil seed banks according to claim 2, characterized in that, The formula for calculating the normalized vegetation index of the degraded desert steppe is as follows: NDVI=(NIR+RED) / (NIR-RED) Formula II Wherein, NDVI represents the Normalized Difference Vegetation Index, NIR represents Landsat remote sensing image data in the near-infrared band, and RED represents Landsat remote sensing image data in the red band.

4. The method for remediating degraded desert steppe soil seed banks according to claim 1, characterized in that, The formula for calculating the aggregation index AI is shown in Formula III; Formula III Where gi is the number of adjacent edges between patches of each landscape type, and maxgi is the number of adjacent edges between patches of each landscape type in the most likely clustering state.

5. The method for remediating degraded desert steppe soil seed banks according to claim 1, characterized in that, The formula for calculating the average area of ​​the patch is shown in Formula IV; AREA_MN=A / N Formula IV Where AREA_MN represents the average area of ​​patches, A is the total area of ​​patches, and N is the number of patches. The average area of ​​patches is an indicator reflecting the degree of landscape fragmentation.

6. The method for remediating degraded desert steppe soil seed bank according to claim 1, characterized in that, The soil remediation includes increasing soil moisture content and organic matter content according to different landscape types: When the soil seed remediation area is a low-coverage grassland area, apply 6.5~8 kg / m² of soil remediation agent. 2 The irrigation water volume keeps the soil moisture holding capacity above 12%; When the soil remediation area is a medium-coverage grassland, the application rate of soil remediation agent is 5.5~7 kg / m². 2 The irrigation water volume keeps the soil moisture holding capacity above 15%; When the soil remediation area is a high-coverage grassland, the application rate of soil remediation agent is 4-5.5 kg / m². 2 The irrigation water volume keeps the soil moisture holding capacity above 20%.

7. The method for remediating degraded desert steppe soil seed banks according to claim 1, characterized in that, The dominant species are determined by sowing different plant seeds according to the landscape type: In grassland areas with low vegetation cover, annual plants with nitrogen-fixing capabilities, whose seeds are dispersed by wind or mucus, should be sown at a seed density of 30-40 g / m². 2 ; In grassland areas with medium vegetation cover, sow perennial plants that fix nitrogen and whose seeds are dispersed by wind, with a seed sowing density of 25-35 g / m². 2 ; In grassland areas with high vegetation cover, the sowing density for perennial plants whose seeds are dispersed by animals or through bursting is 15-30 g / m². 2 .

8. The method for remediating degraded desert steppe soil seed banks according to claim 7, characterized in that, The sown plants in the low vegetation cover grassland area include at least one of the following: pigweed, sand privet, and sweet clover; The sown plants in the grassland area with medium vegetation cover include at least one of the following: Caragana korshinskii, Alfalfa, and alfalfa. The plant species sown in the high vegetation coverage grassland area include at least one of the following: Astragalus membranaceus, Ilex chinensis, and Caragana korshinskii.

9. The method for remediating degraded desert steppe soil seed banks according to claim 7, characterized in that, It also includes assessing the effectiveness of soil seed bank restoration in degraded desert steppe by separately measuring the soil seed bank density and diversity before and after restoration in grassland areas of three different landscape types.

10. The method for remediating degraded desert steppe soil seed banks according to claim 9, characterized in that, The formula for calculating the soil seed bank density is given in Formula V: Soil seed bank density = area of ​​plot / total number of seeds in plot × 10000 (Formula V) The diversity of the seed bank is represented by the Shannon-Wiener diversity index, and the calculation formula is shown in Formula VI. Shannon-Wiener Diversity Index = Formula VI; Where: S is the total number of species in the quadrat; i represents the i-th species in the seed bank, P i Let i be the proportion of the number of individuals of plant species i to the total number of individuals.

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