High and cold grassland ecosystem multifunctionality evaluation method based on multidimensional indexes

Abstract

The invention discloses an alpine grassland ecosystem multifunctionality evaluation method based on multidimensional indexes. Acquiring overground and underground biomass, species richness, diversity index and soil physical and chemical indexes of plants through field sampling; a comprehensive index system covering key ecological functions such as productivity, plant diversity and soil nutrient circulation is constructed, and the ecological system multifunctional index is calculated after dimensional difference is eliminated through normalization processing. And through variance analysis and correlation analysis in combination with a tradeoff and collaboration mechanism between identification functions, a management scheme for multi-function collaboration improvement is evaluated. According to the method, an integrated and quantitative multi-dimensional ecological function is taken as a core, the problems of single evaluation index dimension, lack of index correlation analysis, weak comprehensive decision support capability and the like in the prior art are solved, and a quantifiable and systematic ecological system state evaluation framework is established. Scientific cognition on the overall function state of the alpine grassland ecosystem is improved, and technical support is provided for sustainable management and protection of grassland resources in alpine regions.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of ecosystem comprehensive function evaluation and grassland resource management, and particularly relates to a high-cold grassland ecosystem multifunctionality evaluation method based on multi-dimensional ecological function indexes, which is suitable for sustainable management and scientific decision support of grasslands in the Qinghai-Tibet Plateau and similar ecologically fragile regions. BACKGROUND

[0002] As a typical mountain ecosystem type, high-cold grasslands are widely distributed in the Qinghai-Tibet Plateau and other regions, and have important ecological, environmental and resource values. This type of ecosystem plays a key ecological service function in water conservation, carbon sink function, biodiversity maintenance and wind erosion control. However, due to the influence of multiple factors such as harsh natural environment, increasing human activity frequency and climate change, high-cold grasslands are generally facing different degrees of degradation risk, and the integrity, stability and continuous supply capacity of their ecological functions are significantly threatened.

[0003] Currently, the evaluation methods of grassland ecosystem function mainly focus on single index or a certain specific ecological process, such as net primary productivity (NPP), species diversity or soil nutrient level. Although this kind of method can reveal local ecological characteristics, it has obvious limitations in the overall evaluation of multi-functional systems, and it is difficult to reflect the trade-off and synergistic relationship between multiple ecological functions. In addition, some studies ignore the internal relationship and systematic integration between indexes, and lack a unified quantitative comprehensive evaluation framework, which makes it difficult to effectively guide ecological restoration practice, resource optimization and policy making.

[0004] Therefore, it is urgent to develop a comprehensive evaluation method that can integrate multi-dimensional ecological function indexes, comprehensively reflect the multifunctionality state of the ecosystem, and has quantitative, scientific and operational characteristics, in order to serve the fine management and sustainable utilization of high-cold grasslands. This method should be able to clearly identify the performance intensity of each ecological function, reveal the synergistic or trade-off relationship between functions, and support the scientific judgment and optimization intervention of the health state of the ecosystem. SUMMARY

[0005] The purpose of the present application is to provide a high-cold grassland ecosystem multifunctionality evaluation method based on multi-dimensional indexes, which integrates key ecological process indexes such as plant diversity, ecological productivity and soil nutrient cycling, and establishes a comprehensive evaluation framework with clear structure and quantifiable characteristics. This method aims to solve the problems of single evaluation dimension, missing function correlation and insufficient comprehensive decision support ability in the prior art, so as to improve the scientific cognition level of the overall state of high-cold grassland ecosystem function, and provide quantitative support for ecological protection planning, grassland resource utilization and policy making.

[0006] In order to achieve the above-mentioned purpose, the present application provides the following technical solutions:

[0007] The application provides a high-cold grassland ecosystem multifunctionality evaluation method based on a multi-dimensional index, and specifically comprises the following steps:

[0008] (1) sample site layout and vegetation and soil sample collection;

[0009] (2) plant diversity index calculation;

[0010] (3) ecological function grouping and index system construction;

[0011] (4) calculation of ecosystem multifunctionality index (EMF);

[0012] (5) function trade-off and synergy analysis;

[0013] (6) comprehensive function state determination of the ecosystem;

[0014] Further, step (1) specifically comprises setting a representative sample site in a typical high-cold grassland region, randomly laying out a 1m x 1m quadrat, investigating and collecting samples of plants in the quadrat. The species richness (S) is recorded by identifying plant species, the plant coverage, height and frequency are measured, and all plant samples and their root systems in the quadrat are collected, dried, weighed to obtain the aboveground biomass (AGB) and the belowground root system biomass (BGB).

[0015] Meanwhile, after removing the surface vegetation in the 0-20cm surface layer soil of each quadrat, 3 soil samples are randomly collected and mixed into a composite sample, and the following methods are used to determine various indexes: an elemental analyzer is used to determine the total nitrogen (TN) and total carbon (TC) of the soil; a molybdenum-antimony anti-colorimetric method or an inductively coupled plasma optical emission spectrometry (ICP-OES) is used to determine the total phosphorus (TP) and available phosphorus (AP) of the soil; a continuous flow analyzer is used to determine the ammonium nitrogen (NH4 + -N) and nitrate nitrogen (NO3 - -N) of the KCl extract.

[0016] Further, step (2) specifically comprises calculating the Shannon-Wiener diversity index and the Pielou evenness index based on the data collected in step (1), and the formulas are as follows:

[0017] Pi = Ni / N (Formula 1)

[0018]

[0019] J = H / lnS (Formula 3)

[0020] Where Pi is the proportion of the number of individuals of the ith species to the total number of individuals, Ni is the number of individuals of the ith species, N is the number of individuals of all species in the community. In is the natural logarithm, S is the species richness, H is the Shannon-Wiener index, and J is the Pielou evenness index.

[0021] Further, step (3) is specifically to divide the 11 indicators in steps (1) and (2) into three functions: respectively,

[0022] Productivity function (Pro): AGB, BGB;

[0023] Plant diversity function (Div): Shannon-Wiener index, Pielou evenness index, S;

[0024] Soil nutrient cycling function (Nut): TN, TC, TP, AP, NH4 + -N, NO3 - -N;

[0025] Further, step (4) is specifically to process the 11 indicators respectively by using the maximum and minimum value normalization method, and to standardize them to the interval [0, 1] to eliminate the dimensional difference, and then to combine the standardized sub-indicators of the three functions of Pro, Div and Nut according to equal weight, to construct a comprehensive multifunctional index EMF, and the calculation formula is as follows:

[0026]

[0027] Where Fi is the transformed value of the ith function, Frawi is the untransformed value of the ith function, and Fmini and Fmaxi are the minimum and maximum untransformed values of the ith function, respectively.

[0028] Further, step (5) is specifically to evaluate the synergistic or trade-off relationship between the functions by calculating the root mean square error (RMSE) between Pro, Div, Nut and EMF, and the RMSE calculation formula is as follows

[0029]

[0030] Where B std is the relative benefit of each function index (i.e. the standardized value), and the value range is 0-1. B is each function index. B max and B min are the maximum and minimum values of each function index.

[0031]

[0032] Where RMSE represents the average deviation from the average value B, and B std represents the relative benefit of each function index, The expected return of the i-th functional index is represented. The greater the RMSE, the greater the ecological function trade-off; the smaller the RMSE, the smaller the ecological function trade-off.

[0033] Further, step (6) is specifically to combine the EMF and RMSE results, and comprehensively evaluate the multi-functionality state of the sample land ecosystem, with "high EMF + low RMSE" as the optimal goal of multi-functionality synergy.

[0034] Compared with the existing products, the present application has the following beneficial effects:

[0035] The present application effectively breaks through the problem of relying on a single index and the evaluation result being one-sided in the existing method by integrating a plurality of key ecological function indexes such as ecological productivity, plant diversity, soil nutrients, and water regulation, and constructing a comprehensive evaluation system. The ecological multi-functionality index is combined with the trade-off synergy analysis method to realize the quantitative identification of the synergy and trade-off relationship among the multi-functionality, and the accuracy and applicability of the ecological system function state evaluation are improved.

[0036] The present method can systematically reflect the overall performance of the alpine grassland ecological function, and is suitable for multiple application scenarios such as ecological monitoring, degradation evaluation and management strategy formulation. Compared with the traditional method, the comprehensive evaluation result provided by the present application is more scientific and guiding, and can provide important technical support for grassland resource management, ecological restoration and policy making in alpine regions, and has a wide application prospect. BRIEF DESCRIPTION OF DRAWINGS

[0037] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0038] Figure 1 The flowchart of the present application;

[0039] Figure 2 The multi-functionality evaluation diagram of the ecosystem under different grazing modes;

[0040] Figure 3 The trade-off / synergy analysis diagram of each function index under different grazing modes. DETAILED DESCRIPTION

[0041] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the following will clearly and completely describe the technical solutions in the embodiments of the present application with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only a part of the embodiments of the present application, rather than all the embodiments of the present application. The components of the embodiments of the present application described and shown in the drawings can be arranged and designed in various different configurations.

[0042] Therefore, the following detailed description of the embodiments of the present application provided in the drawings is not intended to limit the scope of the claimed present application, but only represents selected embodiments of the present application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present application without creative work fall within the scope of protection of the present application.

[0043] It should be noted that: similar reference numerals and letters represent similar items in the following drawings, therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0044] In the description of the present application, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer" and the like indicate the orientation or positional relationship based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship when the product of the present application is usually placed, and are only for the convenience of describing the present application and simplifying the description, and therefore cannot be understood as indicating or implying that the indicated device or element must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the present application. In addition, the terms "first", "second", "third" and the like are only used to distinguish the description and cannot be understood as indicating or implying relative importance.

[0045] In addition, the terms "horizontal", "vertical", "overhang" and the like do not mean that the components must be absolutely horizontal or overhanging, but can be slightly inclined. For example, "horizontal" only means that its direction is relatively more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly inclined.

[0046] In the description of the present application, it should also be noted that, unless otherwise explicitly specified and limited, the terms "arrangement", "installation", "connection", "connection" should be understood broadly, for example, it can be fixedly connected, or it can be detachably connected, or integrally connected; it can be mechanically connected, or it can be electrically connected; it can be directly connected, or it can be indirectly connected through an intermediate medium; it can be the communication inside two elements. For those of ordinary skill in the art, the specific meaning of the above terms in the present application can be understood according to the specific circumstances.

[0047] Some embodiments of the present application will be described in detail with reference to the drawings. The following examples and features in the examples can be combined with each other in the case of no conflict.

[0048] The embodiments of the present application will be further described in combination with cases.

[0049] This embodiment takes the alpine grassland ecosystem on the Qinghai-Tibet Plateau as the research object, and selects Tiebujia Village (37°02'N, 99°35'E) in Shennaihe Town, Gonghe County, Hainan Tibetan Autonomous Prefecture, Qinghai Province as the core test area. The average altitude of the area is 3270 meters, which belongs to the typical plateau continental climate, the annual average precipitation is about 400 millimeters, and it has typical ecological vulnerability and representativeness. The soil in the region is mainly chestnut soil, and the vegetation community is mainly composed of Cyperaceae, Poaceae and forbs, and the typical dominant species include Carex melanantha C. A. Mey, Carex alatauensis S. R. Zhang and Astragalus membranaceus (Fisch.) Bunge.

[0050] This experiment sets up five kinds of grazing management treatments: grazing prohibition (CK), light continuous grazing (LCG), moderate continuous grazing (MCG), heavy continuous grazing (HCG) and heavy rotational grazing (HRG), which are used to explore the influence of different grazing systems on the multi-functionality of the ecosystem. Each treatment sets up 3 parallel repeated plots, a total of 15 plots, and each plot area is 0.5 hectares. The layout is implemented by means of random block arrangement to reduce the interference of spatial heterogeneity on the test results. According to the estimated maximum carrying capacity of local alpine grassland (about 4 sheep units / 0.5 hectares), the carrying capacity of continuous grazing in this embodiment is set as follows: LCG, 2 sheep / 0.5 hectares; MCG, 3 sheep / 0.5 hectares; HCG, 4 sheep / 0.5 hectares. For HRG treatment, the total carrying capacity is also set to 4 sheep / 0.5 hectares, but the plot is divided into 3 equal-area sub-areas, and grazing is carried out in sequence, with a grazing duration of about 7 days for each sub-area, and a rotational grazing cycle of 21 days. This rotational grazing design helps to give each sub-area intermittent rest under the premise of maintaining consistent total grazing intensity, which is helpful for the natural recovery of soil and vegetation and reduces the risk of ecological degradation caused by excessive trampling. During the whole grazing season, the fixed grazing position of LCG, MCG and HCG treatments remains unchanged (continuous grazing), while the HRG treatment implements periodic moving grazing area rotation.

[0051] Subsequently, the alpine grassland multi-functionality evaluation method based on the multi-dimensional ecological function index constructed by the present application is used to carry out ecological function analysis on the plots under each grazing management mode, and the results are as follows:

[0052] (1) Single-factor variance analysis (ANOVA) and Duncan's test were used to compare the differences in ecological functions under different grazing modes. Normality (Shapiro-Wilk test) and homogeneity of variance (Levene test) were tested to verify the model assumptions. When significant differences were detected (P < 0.05), Duncan's test was used to analyze the relationship between different ecosystem function indicators, and the results are shown in Table 1.

[0053] Table 1. Correlation of soil physical properties and multi-functionality measurement parameters with ecosystem function indicators

[0054]

[0055] Table 1 shows that HCG Pro is significantly lower than other treatments (P < 0.05), and EMF (0.52 ± 0.1) of HRG is significantly higher than HCG (0.40 ± 0.05) and LCG (0.39 ± 0.1). Grazing (CK) has high productivity but weak nutrient cycling, and EMF is moderate (0.48 ± 0.05). The results are verified by root mean square error (RMSE), which reflects the deviation from the ideal situation where all functions are equally optimized. The higher the RMSE value, the stronger the trade-off function, and the greater the difference between the functions of each ecosystem. A lower RMSE value indicates better functional balance and potential synergy. The results show that HCG leads to the strongest trade-off (RMSE = 0.35), while LCG shows the lowest RMSE (0.21), indicating more stable multi-functionality. The measured values of EMF and RMSE under each grazing treatment are listed in Table 2, which shows that HRG has the best ecological multi-functionality (EMF = 0.52) and functional trade-off degree (RMSE = 0.25), verifying the practicality of the evaluation method of the present application.

[0056] (2) Trade-off / synergy analysis between function indices under different grazing modes as Figure 2 When the correlation coefficient between two functions is positive, it is considered to be synergistic, and negative is considered to be trade-off. The farther the point is from the 1:1 line, the stronger the trade-off effect; the closer it is, the more significant the synergy. In the pairwise trade-off relationship analysis, LCG is beneficial to the synergy of Pro and Nut, as evidenced by its closer position to the 1:1 line. CK always shows the highest level of synergy between Pro and Div. HRG and MCG are beneficial to the coordination of Div and Nut. HCG treatment has the highest multi-function trade-off effect. This indicates that under the same grazing intensity, HRG is more conducive to the synergy between multi-functionality in alpine grassland ecosystem, verifying the guidance of the evaluation method of the present application.

[0057] The patent technology breaks through the single function evaluation bottleneck by constructing a multi-dimensional ecosystem function evaluation system, comprehensively analyzes the overall state of the ecosystem through the synergistic analysis of productivity, diversity and soil nutrients, and solves the problem of missing index correlation of traditional methods. The core innovation lies in the construction of the EMF and RMSE joint evaluation system, taking "high EMF + low RMSE" as the optimization goal, realizing the visualization and identification of the synergistic and trade-off mechanism of ecological function. The method has high universality and scalability, and its index system design can adapt to global alpine and arid ecosystems (such as the Qinghai-Tibet Plateau). The application in the alpine grassland of the Qinghai-Tibet Plateau shows that the method can significantly improve the state evaluation accuracy of the multi-functionality of the ecosystem and the prediction ability of the ecological stability, and can clearly reveal the key driving factors (such as the positive contribution of soil carbon, nitrogen and phosphorus to EMF, the potential trade-off between productivity and diversity, and nutrient function), providing direct basis for optimizing grazing strategies and other management schemes, and having the value of ecological protection benefit and sustainable utilization of grassland resources, providing a solid quantitative basis for related policy making.

[0058] The above is only the preferred embodiment of the present application and is not used to limit the present application. For those skilled in the art, the present application can have various modifications and changes. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for evaluating the multifunctionality of alpine grassland ecosystems based on multidimensional indicators, characterized in that, Includes the following steps: Step 1: Plot Establishment and Vegetation / Soil Sample Collection: Establish representative independent plots within the target alpine grassland; randomly set up 1m×1m quadrats within the plots to investigate and collect the following ecological function-related data: Plant indicators include aboveground biomass (AGB), underground root biomass (BGB), and species richness (S). Soil function indicators include total nitrogen (TN), total carbon (TC), total phosphorus (TP), available phosphorus (AP), and ammonium nitrogen (NH4). + -N and nitrate nitrogen NO3 - -N; Step 2: Calculation of plant diversity indices: Based on the data collected in Step 1, calculate the Shannon-Wiener diversity index and the Pielou evenness index to reflect species composition and distribution characteristics. Step 3: Ecological Function Grouping and Indicator System Construction: The indicators from Steps 1 and 2 are divided into three functional categories: Productivity functions: aboveground biomass AGB, underground root biomass BGB; Plant diversity functions: Shannon-Wiener index, Pielou evenness index, species richness S; Soil nutrient cycling function (Nut): Total nitrogen (TN), total carbon (TC), total phosphorus (TP), available phosphorus (AP), ammonium nitrogen (NH4) + -N and nitrate nitrogen NO3 - -N; Step 4: Ecosystem Multifunctionality Index (EMF) Calculation: The 11 indicators were processed using the maximum-minimum normalization method and standardized to the [0,1] interval to eliminate dimensional differences. Then, the standardized sub-indices of the three functions, Pro, Div, and Nut, were merged with equal weights to construct the comprehensive multifunctionality index EMF. Step 5: Functional trade-offs and synergy analysis: By calculating the root mean square error (RMSE) between the three types of functions (Pro, Div, Nut) and the EMF value, the synergistic or trade-off relationships between functions are evaluated, and the impact of each function on the overall ecological performance is quantitatively characterized. Step 6: Determining the overall functional status of the ecosystem: Combining the results of the comprehensive multifunctionality index (EMF) and the root mean square error (RMSE), the multifunctional status of the sample plot ecosystem is comprehensively evaluated. The optimal goal of multifunctional synergy is "high EMF + low RMSE", providing a quantitative basis for grassland management and decision-making.

2. The method according to claim 1, characterized in that: In step 1, the plant quadrats are collected by randomly selecting three 1m×1m quadrats within each plot, recording plant cover, height, and frequency, collecting all plant samples within the quadrats and digging out the root system, drying and weighing them, measuring AGB and BGB, and recording the number of species S.

3. The method according to claim 1, characterized in that: In step 1, the method for collecting and measuring soil samples includes randomly collecting 3 soil samples from the 0-20cm soil layer of each quadrat and mixing them into a composite sample. TC and TN were determined using an elemental analyzer; TP and AP were determined using the molybdenum-antimony colorimetric method or ICP-OES; and NH4 was determined using a continuous flow analyzer. + -N and NO3 - -N.

4. The method according to claim 1, characterized in that: In step 3, the functional indicators are classified into three categories—Pro, Div, and Nut—based on their ecological function attributes, thus constructing a clear ecological function grouping system.

5. The method according to claim 1, characterized in that: In step 4, after standardizing the dimensions of each indicator, the EMF index is synthesized using a weighted average method. The three functional groups participate in the synthesis with equal weights. The EMF is used to reflect the comprehensive ecosystem function level of the sample plot.

6. The method according to claim 1, characterized in that: In step 5, RMSE is used to measure the degree of deviation between the indicators of each functional group and the EMF value, thereby determining the synergistic (low deviation) or trade-off (high deviation) relationship between functions.

7. The method according to claim 1, characterized in that: In step 6, the comprehensive evaluation uses EMF to represent the overall ecological function level and RMSE to represent the degree of functional coordination. By combining the two, an ecological function optimization judgment model of "high EMF + low RMSE" is constructed.

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