Ecological system service loss assessment method and system suitable for arid and semi-arid regions

Abstract

The invention relates to an ecological system service loss assessment method and system suitable for arid and semi-arid regions, and the method comprises the steps: employing an arthropod Shannon diversity index, a vegetation average height and the soil organic matter content as key indexes, employing a minimum-maximum standardization method to carry out the normalization processing of each index in the key indexes, introducing an entropy weight method to weight each index so as to calculate a weight value of each index; and then calculating ecological integrity indexes of the contrast region and the fragmentation region, further calculating an ecological integrity loss rate, and calculating an economic loss amount of the ecosystem in combination with a region area and a unit area ecosystem service value, thereby quantitatively evaluating an ecological service value loss condition caused by human activities. The method can comprehensively reflect the degradation path and economic consequences of the ecological system under agricultural interference, provides a scientific basis for ecological compensation, recovery priority judgment and environmental policy making, and realizes quantitative evaluation of the health condition of the ecological system.

Description

Technical Field

[0001] This invention relates to the field of ecological environment assessment and ecosystem service value quantification technology, specifically to a method and system for assessing ecosystem service loss in arid and semi-arid regions. Background Technology

[0002] Ecosystems in arid and semi-arid regions are fragile, have limited service functions, and are susceptible to human disturbance. In recent years, with the intensification of intensive agricultural activities, the degradation of ecosystem services in these regions has become increasingly serious, manifested in a variety of problems such as declining biodiversity, soil degradation, and vegetation deterioration.

[0003] However, most existing ecological degradation assessment methods focus on qualitative descriptions and lack the ability to quantify the loss of ecological integrity and economic value. This makes it difficult to support scientific ecological compensation and management decisions in practical applications. Furthermore, current technologies primarily focus on assessing ecosystem health through single-dimensional indicators (such as the NDVI vegetation index or soil nutrients), but this approach often fails to comprehensively reflect the true state of the ecosystem. For example, some traditional methods rely on expert scoring or manual weighting to determine the importance of each indicator, inevitably introducing subjective human factors and reducing the scientific rigor and reproducibility of the assessment results. In addition, current methods rarely consider the differences between different types of ecosystems, lacking adaptability and universality, and cannot be well applied to various disturbance scenarios and ecosystem types.

[0004] Therefore, there is an urgent need to develop a quantitative assessment method based on the dual dimensions of ecological integrity and system service value in order to accurately reflect the degree of ecosystem degradation and its economic consequences under agricultural disturbance. Summary of the Invention

[0005] To address the shortcomings of current assessment methods for ecosystem degradation and service loss caused by agricultural activities in arid and semi-arid regions, such as incomplete reflection of the true state of the ecosystem, low resource utilization, poor response timeliness, lack of dynamic adaptability, and high labor costs, this invention provides an ecosystem service loss assessment method suitable for arid and semi-arid regions. This method overcomes the limitations of traditional single-dimensional assessment methods, providing a more comprehensive reflection of the overall health of the ecosystem. It quantitatively assesses the loss of ecosystem service value caused by human activities, comprehensively reflects the degradation path and economic consequences of ecosystems under agricultural disturbance, and provides a scientific basis for ecological compensation, restoration priority determination, and environmental policy formulation, achieving a quantitative evaluation of ecosystem health. This invention also relates to an ecosystem service loss assessment system suitable for arid and semi-arid regions.

[0006] The technical solution of the present invention is as follows:

[0007] A method for assessing ecosystem service loss in arid and semi-arid regions, characterized by the following steps:

[0008] Key indicator selection steps: Select at least one area within an arid or semi-arid ecosystem that retains its natural ecological characteristics and has not been affected by intensive agricultural activities as a control area, and at least one area that has been ecologically degraded due to intensive agricultural activities as a fragmented area; sample the selected control area and fragmented area from multiple dimensions, including animal diversity, vegetation growth status, and soil health level, to obtain raw data of key ecosystem indicators; the key indicators include animal diversity indicators, vegetation functional trait indicators, and soil quality indicators;

[0009] Data standardization steps: The min-max standardization method is used to normalize the raw data of each indicator in the key indicators to obtain the standardized value of each indicator.

[0010] Weight calculation steps: Based on the standardized values ​​of each indicator, the weight value of each indicator is calculated using the entropy weight method.

[0011] The steps for calculating the ecological integrity index are as follows: The standardized values ​​of each indicator are weighted and summed according to their weight values ​​to obtain the ecological integrity index. Then, the ecological integrity index of the control area and the ecological integrity index of the fragmented area are calculated separately.

[0012] Steps for calculating the ecological integrity loss rate: Calculate the ecological integrity loss rate based on the ecological integrity index of the control area and the ecological integrity index of the fragmented area;

[0013] The steps for calculating the value of ecosystem services are as follows: Calculate the value of ecosystem services in the control area based on the pre-obtained area area and the value of ecosystem services per unit area of ​​each region; and calculate the value of ecosystem services in the fragmented area based on the rate of loss of ecological integrity and the value of ecosystem services in the control area.

[0014] Service loss assessment steps: Based on the ecosystem service value of the control area and the ecosystem service value of the fragmented area, the economic loss of the ecosystem is calculated, thereby realizing the service loss assessment of the ecosystem in arid and semi-arid regions.

[0015] Preferably, in the key indicator selection step, the animal diversity indicator is the Shannon diversity index of arthropods, the vegetation functional trait indicator is the average vegetation height, and the soil quality indicator is the soil organic matter content.

[0016] Preferably, in the weight calculation step, calculating the weight value of each indicator using the entropy weight method specifically includes:

[0017] Based on the standardized values ​​of each indicator and the principle of information entropy, the entropy value of each indicator is calculated, and the first weight value of the Shannon diversity index of arthropods, the second weight value of the average vegetation height, and the third weight value of the soil organic matter content are calculated according to the entropy value.

[0018] Preferably, in the ecological integrity index calculation step, the weighted summation of the standardized values ​​of each indicator based on the weight values ​​to obtain the ecological integrity index specifically includes:

[0019] The ecological integrity index is calculated by summing the standardized value of the Shannon diversity index of arthropods and the product of the first weight value, the standardized value of the average vegetation height and the product of the second weight value, and the standardized value of the soil organic matter content and the product of the third weight value.

[0020] Preferably, in the data standardization step, the calculation formula for the min-max standardization method is:

[0021] y ij =[x ij -min(x j )] / [max(x j )-min(x j )]

[0022] Where, x ij For the raw data of the j-th indicator in the i-th region, y ij For the corresponding standardized value, min(x) j ) and max(x j ) are the minimum and maximum values ​​of the j-th indicator, respectively.

[0023] Preferably, in the step of calculating the value of ecosystem services, the value of ecosystem services per unit area is calibrated using long-term monitoring data of the study area, or by referencing the value of ecosystem services per unit area of ​​similar ecosystems in arid and semi-arid regions from existing literature.

[0024] An ecosystem service loss assessment system suitable for arid and semi-arid regions is characterized by comprising, in sequence, a key indicator selection module, a data standardization module, a weight calculation module, an ecological integrity index calculation module, an ecological integrity loss rate calculation module, an ecosystem service value calculation module, and a service loss assessment module.

[0025] The key indicator selection module selects at least one area within an arid or semi-arid ecosystem that retains its natural ecological characteristics and is unaffected by intensive agricultural activities as a control area, and at least one area whose ecology has been degraded due to intensive agricultural activities as a fragmented area. It then samples the selected control area and fragmented area from multiple dimensions, including animal diversity, vegetation growth status, and soil health level, to obtain raw data on the key indicators of the ecosystem. These key indicators include animal diversity indicators, vegetation functional trait indicators, and soil quality indicators.

[0026] The data standardization module uses the min-max standardization method to normalize the original data of each key indicator to obtain the standardized value of each indicator.

[0027] The weight calculation module calculates the weight value of each indicator based on the standardized value of each indicator and using the entropy weight method.

[0028] The ecological integrity index calculation module calculates the standardized values ​​of each indicator by weighted summation according to the weight values ​​to obtain the ecological integrity index, and then calculates the ecological integrity index of the control area and the ecological integrity index of the fragmented area respectively.

[0029] The ecological integrity loss rate calculation module calculates the ecological integrity loss rate based on the ecological integrity index of the control area and the ecological integrity index of the fragmented area.

[0030] The ecosystem service value calculation module calculates the ecosystem service value of the control area based on the pre-acquired area area and ecosystem service value per unit area of ​​each region; and calculates the ecosystem service value of the fragmented area based on the ecological integrity loss rate and the ecosystem service value of the control area.

[0031] The service loss assessment module calculates the economic loss of the ecosystem based on the ecosystem service value of the control area and the ecosystem service value of the fragmented area, thereby realizing the assessment of ecosystem service loss in arid and semi-arid regions.

[0032] Preferably, in the key indicator selection module, the animal diversity indicator is the Shannon diversity index of arthropods, the vegetation functional trait indicator is the average vegetation height, and the soil quality indicator is the soil organic matter content.

[0033] Preferably, in the weight calculation module, the calculation of the weight value of each indicator using the entropy weight method specifically includes:

[0034] Based on the standardized values ​​of each indicator and the principle of information entropy, the entropy value of each indicator is calculated, and the first weight value of the Shannon diversity index of arthropods, the second weight value of the average vegetation height, and the third weight value of the soil organic matter content are calculated according to the entropy value.

[0035] Preferably, in the ecological integrity index calculation module, the standardized values ​​of each indicator are weighted and summed according to their weight values ​​to obtain the ecological integrity index, specifically including:

[0036] The ecological integrity index is calculated by summing the standardized value of the Shannon diversity index of arthropods and the product of the first weight value, the standardized value of the average vegetation height and the product of the second weight value, and the standardized value of the soil organic matter content and the product of the third weight value.

[0037] The technical effects of this invention are as follows:

[0038] This invention provides a method for assessing ecosystem service loss in arid and semi-arid regions. It can also be understood as a method for assessing ecosystem degradation and loss of service functions caused by agricultural activities in arid regions, or an ecosystem service loss assessment method based on the Ecological Integrity Index (EII) and entropy weight method. It can achieve a quantitative evaluation of the health status of the ecosystem and estimate the loss of ecosystem service value caused by human activities. It is applicable to the ecological management and monitoring of grassland / farmland ecotones in arid and semi-arid regions. Firstly, by clearly selecting control areas and fragmented areas with consistent ecosystem types within arid and semi-arid regions, ecosystem type variables are controlled to eliminate assessment interference caused by differences in ecological background. This ensures that subsequent comparative data (such as biological and soil indicators) are comparable to those of similar ecosystems. Focusing on the unique ecological background of arid and semi-arid regions, this approach adapts to the region's ecological vulnerability characteristics, making the assessment method more aligned with the actual situation of the study area and avoiding the incompatibility of general methods in specific climate-ecological zones. Sampling is conducted on the selected control and fragmented areas from multiple dimensions, including animal diversity, vegetation growth status, and soil health levels, to obtain raw data on key ecosystem indicators. Traditional methods often focus on a single dimension (such as the vegetation index NDVI or soil nutrients), failing to comprehensively reflect the true state of the ecosystem. This invention introduces three core dimensions—biodiversity (such as the Shannon diversity index for arthropods), vegetation functional traits (such as average vegetation height), and soil quality (such as soil organic matter content)—covering the core of the ecosystem's "biology-vegetation-soil" structure. This study constructs a multi-dimensional, multi-level indicator system, enabling a multi-dimensional quantitative assessment of ecosystem structure and function, and providing a more comprehensive reflection of the overall health of the ecosystem. The min-maximum standardization method is used to normalize the raw data of each key indicator, obtaining standardized values ​​for each indicator. Since different ecological indicators have inconsistent dimensions and large differences in numerical ranges, direct use in calculations may lead to biases. Therefore, min-maximum standardization eliminates dimensional differences, making various indicators comparable, improving the accuracy and consistency of subsequent analyses, and laying the foundation for multi-dimensional data fusion. Then, based on the standardized values ​​of each indicator, the entropy weight method is used to calculate the weight value of each indicator. Compared with traditional expert scoring or manual weighting methods, the entropy weight method is an objective weighting method. It automatically calculates the information entropy of each indicator, objectively determining the indicator weight, reducing subjective interference, avoiding uncertainty caused by subjective judgment, improving the scientific nature and repeatability of the assessment results, and further enhancing the credibility of the multi-dimensional evaluation system.Then, the standardized values ​​of each indicator are weighted and summed according to their respective weights to obtain the ecological integrity index (EII). The EII is then calculated separately for the control area and the fragmented area. By constructing the EII, the three key indicators of biodiversity, vegetation growth, and soil health are integrated into a quantifiable comprehensive indicator (i.e., integrating the three ecological dimensions). This not only facilitates horizontal comparison of the ecological status of different regions but also enables a quantitative assessment of the overall state of the ecosystem, overcoming the limitations of traditional single-dimensional assessment methods. Furthermore, the ecological integrity loss rate is calculated based on the EII of the control area and the fragmented area. By comparing the differences in the EII between the control area and the fragmented area, the decline in ecological integrity caused by agricultural disturbance is quantified, reflecting the degree of damage to the ecosystem caused by human activities. This process embodies the transformation from "multidimensional ecological indicators" to "systematic health assessment," providing a scientific basis for developing restoration measures. Based on the pre-obtained area and ecosystem service value per unit area of ​​each region, the ecosystem service value of the control region is calculated. Furthermore, the ecosystem service value of the fragmented region is calculated based on the ecological integrity loss rate and the ecosystem service value of the control region. By combining ecosystem integrity with service value, this method can be used for ecological compensation and restoration priority assessment, realizing the transformation from "ecological state" to "economic value." This allows the impact of ecological degradation to be measured and compensated through economic means. This service value assessment method, combining multi-dimensional ecological indicators, breaks through the limitations of previous methods that relied solely on qualitative descriptions, providing quantitative support for ecological compensation mechanisms and a decision-making basis for practical applications such as ecological compensation valuation and priority ranking for degraded land restoration. Finally, based on the ecosystem service values ​​of the control and fragmented regions, the economic loss of the ecosystem is calculated, thus achieving an assessment of ecosystem service loss. The final economic loss directly demonstrates the loss of ecosystem service functions caused by agricultural disturbance, providing strong support for the establishment of ecological compensation mechanisms, environmental policy formulation, and land use planning, enhancing the practicality and application prospects of the method.

[0039] This invention constructs a systematic and quantifiable multi-dimensional ecological integrity index system that includes biodiversity, vegetation growth, and soil health. Combined with entropy weighting, the Ecological Integrity Index (EII), and the calculation of ecosystem service value loss caused by human factors such as agricultural activities, a complete ecosystem service loss assessment process is formed, capable of comprehensively reflecting the multi-dimensional health status of the ecosystem. It has the following effects: 1) Comprehensive reflection of the multi-dimensional health status of the ecosystem: By selecting three core dimensions—animal diversity (e.g., the Shannon diversity index for arthropods), vegetation growth status (e.g., average vegetation height), and soil health level (e.g., soil organic matter content)—as key indicators, a systematic and quantifiable Ecological Integrity Index (EII) system is constructed. This multi-dimensional assessment method can more comprehensively reflect the overall health status of the ecosystem, breaking through the limitations of traditional single-dimensional assessment methods. 2) Introducing the entropy weight method to reduce subjective interference and enhance the scientific nature of the assessment: The entropy weight method calculates the entropy value of each indicator based on its standardized value and the principle of information entropy, and determines its weight value accordingly. This avoids the uncertainty caused by traditional subjective weighting, improves the scientific nature and repeatability of the assessment results, and ensures the objectivity and stability of the evaluation system. 3) Combining ecological integrity and ecosystem service value: Ecological integrity is combined with ecosystem service value. The ecological integrity loss rate is calculated by comparing the ecological integrity index of the control area and the broken area, and further converted into economic value loss. This not only realizes the transformation from "ecological state" to "economic value," but also provides a decision-making basis for practical applications such as establishing ecological compensation mechanisms and prioritizing the restoration of degraded areas. 4) Promoting scientific decision-making and management: By quantitatively assessing ecosystem service loss, this method provides strong data support for government agencies, research institutions, and relevant stakeholders, helping them make more scientific and reasonable decisions. Especially in ecological compensation and environmental governance, this method provides clear economic value references, promoting the effective allocation of resources and maximizing socio-economic benefits. In summary, this invention not only enhances the scientific rigor of ecosystem assessment but also strengthens its practicality and applicability, providing an effective tool and method for addressing ecosystem degradation caused by agricultural activities in arid and semi-arid regions.

[0040] Furthermore, the entropy weight method is used to calculate the weight value of each indicator, specifically including: calculating the entropy value of each indicator based on its standardized value and the principle of information entropy; and calculating the first weight value for animal diversity indicators, the second weight value for vegetation functional traits indicators, and the third weight value for soil quality indicators based on the entropy value. This invention introduces the entropy weight method for objective weighting, determining indicator weights based on the information content of the data itself, avoiding the uncertainty caused by traditional subjective scoring methods or experience-based weighting, and improving the scientific rigor and repeatability of the evaluation results. This method is particularly suitable for multi-dimensional ecological indicator systems, automatically identifying key sensitive factors and enhancing the stability and adaptability of the evaluation system.

[0041] Furthermore, the ecological integrity index was calculated by summing the standardized values ​​of animal diversity indicators and their first weighted values, the standardized values ​​of vegetation functional traits indicators and their second weighted values, and the standardized values ​​of soil quality indicators and their third weighted values. By weighting and integrating representative indicators of biodiversity, vegetation functional traits, and soil quality, a comprehensive ecological integrity index (EII) reflecting the health of the ecosystem was constructed. This achieved a quantitative expression of the ecosystem's state, facilitating cross-regional comparisons and providing a foundation for subsequent service value conversion, thus enhancing the intuitiveness and practicality of the assessment results.

[0042] This invention takes into account the differences between various ecosystem types from the outset, proposing a universal and flexible ecological indicator system that allows for the adjustment or replacement of key indicators based on different ecosystem types. For example, bird diversity indices can be used in forest ecosystems, while leaf area indices can be used in wetland ecosystems. This flexibility makes the method applicable not only to arid and semi-arid regions but also to other types of ecosystems, such as forests, wetlands, and farmland, demonstrating broad application prospects and ensuring the scientific rigor and applicability of the assessment results. It represents a significant technological innovation in the field of ecological assessment.

[0043] This invention also relates to an ecosystem service loss assessment system applicable to arid and semi-arid regions. This system corresponds to the aforementioned ecosystem service loss assessment method for arid and semi-arid regions and can be understood as a system that implements the aforementioned ecosystem service loss assessment method for arid and semi-arid regions. It includes a key indicator selection module, a data standardization module, a weight calculation module, an ecological integrity index calculation module, an ecological integrity loss rate calculation module, an ecosystem service value calculation module, and a service loss assessment module, all connected sequentially. These modules work collaboratively, focusing on the characteristics of ecosystems in arid and semi-arid regions. By selecting three core dimensions—animal diversity (e.g., the Shannon diversity index for arthropods), vegetation growth status (e.g., average vegetation height), and soil health level (e.g., soil organic matter content)—as key indicators, a systematic and quantifiable Ecological Integrity Index (EII) system is constructed. This multi-dimensional assessment method can more comprehensively reflect the overall health status of the ecosystem, breaking through the limitations of traditional single-dimensional assessment methods. Through controlled variables (comparison with similar ecosystems), multi-dimensional indicators, and standardization, it accurately captures the impact of fragmentation on ecosystem services, solving the problems of poor regional adaptability, one-sided indicators, and difficulty in data integration found in traditional assessment systems. This invention employs the entropy weight method to calculate the entropy value of each indicator based on its standardized value and the principle of information entropy, thereby determining its weight value. This avoids the uncertainty caused by traditional subjective weighting, improves the scientific rigor and repeatability of the assessment results, and ensures the objectivity and stability of the evaluation system. By combining ecological integrity with ecosystem service value, the ecological integrity loss rate is calculated based on the difference in ecological integrity indices between the control area and the fragmented area, and further converted into economic value loss. This not only realizes the transformation from "ecological state" to "economic value," but also provides a decision-making basis for practical applications such as establishing ecological compensation mechanisms and prioritizing the restoration of degraded areas. This invention enhances the scientific rigor of ecosystem assessment while also increasing its practicality and scalability, providing an effective tool for solving the problem of ecosystem degradation caused by agricultural activities in arid and semi-arid regions. Attached Figure Description

[0044] Figure 1 This is a flowchart of the method for assessing ecosystem service loss applicable to arid and semi-arid regions, as described in this invention.

[0045] Figure 2 This is a schematic diagram illustrating the working principle of the ecosystem service loss assessment method and system applicable to arid and semi-arid regions of this invention.

[0046] Figure 3 This is a structural block diagram of the ecosystem service loss assessment system applicable to arid and semi-arid regions according to the present invention. Detailed Implementation

[0047] The present invention will now be described with reference to the accompanying drawings.

[0048] This invention relates to a method for assessing ecosystem service loss in arid and semi-arid regions, applicable to the management and monitoring of agriculturally disturbed ecosystems in grassland / farmland ecotones in arid and semi-arid areas. The method uses arthropod diversity, vegetation functional traits, and soil organic matter as core indicators to construct an Ecological Integrity Index (EII). An entropy weighting method is introduced to assign weights to multiple indicators, eliminating anthropogenic interference. Ecological degradation rates are calculated by comparing EII values ​​between control and fragmented areas. Furthermore, by combining this with the unit ecosystem service value, the method quantitatively assesses the loss of ecosystem service value caused by human activities. This comprehensively reflects the degradation path and economic consequences of ecosystems under agricultural disturbance, providing a scientific basis for ecological compensation, restoration priority determination, and environmental policy formulation, and achieving a quantitative evaluation of ecosystem health. The flowchart of this method is shown below. Figure 1 The diagram illustrates how intensive production leads to ecological loss. Agricultural practices increase physical losses by reducing vegetation vitality, arthropod diversity, and soil health. This decline in functions results in a loss of ecological value—manifested as a reduction in supply, regulation, and other ecosystem services—through the following steps:

[0049] I. Key Indicator Selection Steps: Select at least one area within the ecosystem of arid and semi-arid regions that retains natural ecological characteristics and has not been affected by intensive agricultural activities as a control area, and at least one area that has been ecologically degraded due to intensive agricultural activities as a fragmented area; and sample the selected control area and fragmented area from multiple dimensions including animal diversity, vegetation growth status, and soil health level to obtain raw data of key ecosystem indicators; key indicators include animal diversity indicators, vegetation functional traits indicators, and soil quality indicators.

[0050] Specifically, firstly, at least one area within arid and semi-arid regions affected by varying degrees of agricultural disturbance, retaining its natural ecological characteristics and unaffected by intensive agricultural activities (meaning undisturbed or minimally affected by agricultural activities), was selected as a control area. At least one ecologically degraded area due to intensive agricultural activities (meaning significantly disturbed by agricultural activities) was selected as a fragmented area. Then, three core dimensions of the ecosystem were chosen: animal diversity (e.g., arthropods), vegetation growth status, and soil health level, serving as the basis for constructing the Ecological Integrity Index (EII). Specifically, these three categories of indicators can be flexibly selected based on the ecological characteristics of the study area and the monitoring objectives, choosing the most representative parameters. Then, sampling was conducted on the selected control and fragmented areas from the three core dimensions to obtain raw data on the key ecosystem indicators. The following indicators were selected as examples:

[0051] 1) Animal diversity indicators: Arthropod Shannon Diversity Index (AR_Shannon), representing biodiversity;

[0052] 2) Vegetation functional trait indicators: average vegetation height (GH), which represents the functional traits of vegetation;

[0053] 3) Soil quality indicators: Soil organic matter content (OM), which represents soil quality.

[0054] The aforementioned indicators are representative and universal, reflecting the three fundamental dimensions of an ecosystem: biological community structure, vegetation vitality, and basic soil functions. Understandably, these key indicators can be adjusted and replaced according to different ecosystem types, substituting them with ecological indicators corresponding to a specific ecosystem type. This means it is applicable to desert steppes, agro-vegetable ecotones, or other ecological areas significantly affected by agricultural activities. Users can replace key indicators with other ecological indicators based on research data and regional characteristics, such as insect species richness, bird diversity index, chlorophyll content, vegetation cover, leaf area index, total soil nitrogen content, soil moisture content, and soil pH, maintaining the scientific rigor and adaptability of the evaluation system. The ecosystem types include forest ecosystems, grassland ecosystems, desert ecosystems, wetland ecosystems, farmland ecosystems, and marine and coastal ecosystems.

[0055] II. Data Standardization Steps: The min-max standardization method is used to normalize the raw data of each key indicator to obtain the standardized value of each indicator, as shown in the following formula:

[0056] y ij =[x ij -min(xj )] / [max(x j )-min(x j (1)

[0057] In the above formula, x ij Let x be the original value of the j-th index in the i-th sample plot (i.e., the control area or fragmented area), min(x j ) represents the minimum value of the j-th index among all sample plots; max(x j ) represents the maximum value of the j-th index among all sample plots; y ij This represents the standardized value after normalization.

[0058] III. Weight Calculation Steps: Based on the standardized values ​​of each indicator, the weight value of each indicator is calculated using the entropy weight method.

[0059] Specifically, based on the standardized values ​​of each indicator and the principle of information entropy, the entropy value E of each indicator is first calculated. j Calculate according to the following formula:

[0060]

[0061] In the above formula, X ij Let represent the standardized value of the j-th indicator in the i-th sample plot, where n is the number of sample plots.

[0062] Then based on the entropy value E j The first weighted value W1 for the Shannon diversity index of arthropods (AR_Shannon), the second weighted value W2 for the average vegetation height (CH), and the third weighted value W3 for the soil organic matter content (OM) were calculated according to the following formula:

[0063] W j =(1-E j ) / (K-∑E j (3)

[0064] In the above formula, W j W1, W2, W3 are the weight values ​​of the j-th indicator. K refers to the total number of indicators, i.e., the number of indicators participating in the entropy weight calculation.

[0065] IV. Calculation Steps for the Ecological Integrity Index: The standardized values ​​of each indicator are weighted and summed according to their respective weights to obtain the Ecological Integrity Index (EII), which is calculated using the following formula:

[0066] EII=w1×AR std +w2×GH std +w3×OM std (4)

[0067] In the above formula, ARstd GH is the standardized value of the Shannon diversity index for arthropods. std OM is the standardized value of the average vegetation height. std This is the standardized value for soil organic matter content.

[0068] That is, based on the standardized value of the Shannon diversity index for arthropods (AR) std The product of the first weighted value W1 and the standardized value GH of the average vegetation height. std The product of the second weighted value W2 and the standardized value OM of soil organic matter content. std The ecological integrity index EII is calculated by summing the product of the third weight value W3 and the third weight value W3.

[0069] After calculating the ecological integrity index EII, the ecological integrity index EII of the control area was then calculated separately. CZ Ecological Integrity Index (EII) for Fragmented Areas FZ .

[0070] V. Steps for calculating the ecological integrity loss rate: Calculate the ecological integrity loss rate EII based on the ecological integrity index of the control area and the ecological integrity index of the fragmented area. Loss Calculate according to the following formula:

[0071] EII Loss =(EII) CZ -EII FZ ) / EII CZ (5)

[0072] VI. Steps for calculating the value of ecosystem services: Based on the pre-obtained area A and the ecosystem service value VC per unit area for each region, calculate the ecosystem service value ESVcz for the control region according to the following formula:

[0073] ESVcz=A×VC (6)

[0074] In the formula, the ecosystem service value per unit area (VC) can be calibrated using long-term monitoring data of the study area, or by referencing the unit service value data of similar ecosystems in arid and semi-arid regions from existing literature.

[0075] And based on the ecological integrity loss rate EII Loss The ecosystem service value (ESV) of the fragmented area was calculated using the ESVcz method, comparing it with the control area. FZ Calculate according to the following formula:

[0076] ESV FZ =(1-EII) Loss )×ESV cz(7)

[0077] VII. Service Loss Assessment Steps: Based on the ecosystem service value of the control area and the ecosystem service value of the fragmented area, calculate the economic loss of the ecosystem. Loss This enables the assessment of ecosystem service losses in arid and semi-arid regions (also known as monetization assessment). The process of assessing ecosystem degradation pathways and service losses is as follows: Figure 2 As shown, by constructing a process of "agricultural practice → physical losses (including vegetation growth, arthropod diversity, and soil health) → ecological value (including provisioning services, regulatory services, and cultural services) → ecological loss," this accurately presents the transmission path of agricultural practices' impact on ecosystems, clearly demonstrating the complete logical chain from agricultural intervention to the generation of ecological loss. That is, agricultural practices first lead to an increase in physical losses (including vegetation growth, arthropod diversity, and soil health), which in turn causes a decrease in ecological value (covering provisioning services, regulatory services, cultural services, and other services), ultimately resulting in increased ecological loss. This aligns with the ecological impact transmission pattern of "agricultural activities first causing damage to physical elements, then transmitting to ecological value, and finally manifesting as ecological loss."

[0078] The economic losses to the ecosystem are calculated using the following formula:

[0079] Ecological Loss =ESV CZ -ESV Fz (8)

[0080] Example:

[0081] Experimental surveys were conducted at the target research sites, and soil, biological, and vegetation samples were collected from several control areas and fragmented areas. Ecological index data and geographic information were processed using R language and ArcGIS software, respectively, and the changes in EII and ecosystem service value were calculated accordingly, ultimately achieving spatial presentation and quantitative assessment of ecosystem loss.

[0082] First, simulated plot data were set: three plots were set (plots 1 and 2 were the broken area FZ, and plot 3 was the control area CZ), as shown in Table 1.

[0083] Table 1

[0084] Sample plot number Region Type AR_Shannon GH(cm) OM (%) Sample plot 1 FZ 1.10 28 0.75 Sample plot 2 FZ 1.35 35 1.10 Sample plot 3 CZ 1.80 50 1.50

[0085] Then perform standardization (Min-Max normalization), using formula (1), i.e., y ij =[x ij -min(x j )] / [max(x j)-min(x j The standardized values ​​(also known as normalized values) of the arthropod Shannon diversity index AR_Shannon, as shown in Table 2, the standardized values ​​of average vegetation height GH, as shown in Table 3, and the standardized values ​​of soil organic matter content OM, as shown in Table 4, were calculated.

[0086] Table 2

[0087] Sample plot number Original value Normalized value Sample plot 1 1.10 0.00 Sample plot 2 1.35 0.25 Sample plot 3 1.80 1.00

[0088] Table 3

[0089]

[0090]

[0091] Table 4

[0092] Sample plot number Original value Normalized value Sample plot 1 0.75 0.00 Sample plot 2 1.10 0.35 Sample plot 3 1.50 1.00

[0093] Then, the entropy weight method is used for calculation. Step 1: Calculate the sum of the normalized values ​​for each index, as shown below:

[0094] AR_Shannon: 0+0.25+1.00=1.25

[0095] GH: 0 + 0.28 + 1.00 = 1.28

[0096] OM: 0 + 0.35 + 1.00 = 1.35

[0097] Step 2: Calculate the information entropy E j The entropy value E of AR_Shannon was calculated using formula (2). AR =0.366; the entropy value E of GH GH =0.378; and the entropy value E of OM OM =0.365. Where, ∑E j =1.109.

[0098] Step 3: Calculate the weights. Use formula (3), i.e., W. j =(1-E j ) / (3-∑E j The values ​​W1 = 0.314, W2 = 0.298, and W3 = 0.388 were calculated respectively.

[0099] Next, calculate the Ecological Integrity Index (EII) value. EII = w1 × AR std +w2×GH std +w3×OM std The ecological integrity indices of the three sample plots are shown in Table 5.

[0100] Table 5

[0101] Sample plot number Original value Sample plot 1 0.314×0+0.298×0+0.388×0＝0.000 Sample plot 2 0.314×0.25+0.298×0.28+0.388×0.35＝0.295 Sample plot 3 0.314×1.00+0.298×1.00+0.388×1.00＝1.000

[0102] Then calculate the ecological integrity loss rate EII. Loss (Also known as the ecological degradation rate). Using formula (5), i.e., EII Loss =(EII) CZ -EII FZ ) / EII CZ The ecological integrity loss rate of the fragmented areas (i.e., plot 1 and plot 2) was calculated separately, as shown in Table 6.

[0103] Table 6

[0104]

[0105]

[0106] Finally, the value of ecosystem services is estimated.

[0107] Assumption: The area of ​​each sample plot is A = 1 hm² 2 Ecosystem service value per unit area (VC) = USD 10,000 / hm² 2 Then ESV CZ =A×VC=1×10000=10000;ESV FZ =(1-EII) Loss )×ESV CZ Ecosystem service value (ESV) of fragmented areas (i.e., plot 1 and plot 2) FZ As shown in Table 7.

[0108] Table 7

[0109] Sample plot number <![CDATA[ESV FZ (USD)]]> Ecological Loss (USD) Sample plot 1 0 1000 Sample plot 2 2950 7050

[0110] Table 8 shows the information on the ecological integrity index (EII) and its loss, ecosystem service value (ESV), and economic loss of ecosystems in different sites.

[0111] Table 8

[0112] Sample plot EII value <![CDATA[EII Loss ]]> ESVcz <![CDATA[ESV FZ ]]> <![CDATA[Ecological Loss ]]> 1 0.000 1.000 10000 0 10000 2 0.295 0.705 10000 2950 7050 3 1.000 0 10000 10000 0

[0113] This invention also relates to a method and system for assessing ecosystem service loss in arid and semi-arid regions. This system corresponds to the aforementioned method for assessing ecosystem service loss in arid and semi-arid regions and can be understood as a system for implementing the aforementioned method. Figure 3As shown, the system includes, in sequence, a key indicator selection module, a data standardization module, a weight calculation module, an ecological integrity index calculation module, an ecological integrity loss rate calculation module, an ecosystem service value calculation module, and a service loss assessment module. Specifically,

[0114] The key indicator selection module selects at least one area within an arid or semi-arid ecosystem that retains its natural ecological characteristics and is unaffected by intensive agricultural activities as a control area, and at least one area whose ecology has been degraded due to intensive agricultural activities as a fragmented area. It then samples the selected control area and fragmented area from multiple dimensions, including animal diversity, vegetation growth status, and soil health level, to obtain raw data on the key indicators of the ecosystem. These key indicators include animal diversity indicators, vegetation functional trait indicators, and soil quality indicators.

[0115] The data standardization module uses the min-max standardization method to normalize the original data of each key indicator to obtain the standardized value of each indicator.

[0116] The weight calculation module calculates the weight value of each indicator based on the standardized value of each indicator and using the entropy weight method.

[0117] The ecological integrity index calculation module calculates the standardized values ​​of each indicator by weighted summation according to the weight values ​​to obtain the ecological integrity index, and then calculates the ecological integrity index of the control area and the ecological integrity index of the fragmented area respectively.

[0118] The ecological integrity loss rate calculation module calculates the ecological integrity loss rate based on the ecological integrity index of the control area and the ecological integrity index of the fragmented area.

[0119] The ecosystem service value calculation module calculates the ecosystem service value of the control area based on the pre-acquired area area and ecosystem service value per unit area of ​​each region; and calculates the ecosystem service value of the fragmented area based on the ecological integrity loss rate and the ecosystem service value of the control area.

[0120] The service loss assessment module calculates the economic loss of the ecosystem based on the ecosystem service value of the control area and the ecosystem service value of the fragmented area, thereby realizing the assessment of ecosystem service loss in arid and semi-arid regions.

[0121] Preferably, in the key indicator selection module, the animal diversity indicator is the Shannon diversity index of arthropods, the vegetation functional trait indicator is the average vegetation height, and the soil quality indicator is the soil organic matter content.

[0122] Preferably, in the weight calculation module, the calculation of the weight value of each indicator using the entropy weight method specifically includes:

[0123] Based on the standardized values ​​of each indicator and the principle of information entropy, the entropy value of each indicator is calculated, and the first weight value of the Shannon diversity index of arthropods, the second weight value of the average vegetation height, and the third weight value of the soil organic matter content are calculated according to the entropy value.

[0124] Preferably, in the ecological integrity index calculation module, the standardized values ​​of each indicator are weighted and summed according to their weight values ​​to obtain the ecological integrity index, specifically including:

[0125] The ecological integrity index is calculated by summing the standardized value of the Shannon diversity index of arthropods and the product of the first weight value, the standardized value of the average vegetation height and the product of the second weight value, and the standardized value of the soil organic matter content and the product of the third weight value.

[0126] This invention provides an objective and scientific method and system for assessing ecosystem service loss in arid and semi-arid regions. By selecting three core dimensions—animal diversity, vegetation growth status, and soil health level—as key indicators, a systematic and quantifiable ecological integrity index system is constructed. This multi-dimensional assessment approach more comprehensively reflects the overall health status of the ecosystem, overcoming the limitations of traditional single-dimensional assessment methods. The entropy weighting method is used to calculate the entropy value of each indicator and determine its weight accordingly, introducing an information entropy weighting mechanism to reduce subjective human interference and avoid the uncertainty caused by traditional subjective weighting. This improves the scientific rigor and repeatability of the assessment results, ensuring the objectivity and stability of the evaluation system. Furthermore, by combining ecological integrity with ecosystem service value, the ecological integrity loss rate is calculated based on the difference in ecological integrity indices between the control area and the fragmented area, and further converted into economic value loss. This not only realizes the transformation from "ecological state" to "economic value" but also provides a decision-making basis for practical applications such as establishing ecological compensation mechanisms and prioritizing the restoration of degraded land. This invention is applicable to remote sensing monitoring, farmland ecological management, and degraded grassland assessment scenarios, and has good scalability.

[0127] It should be noted that the specific embodiments described above enable those skilled in the art to more fully understand the present invention, but do not limit the present invention in any way. Therefore, although the present invention has been described in detail with reference to the accompanying drawings and embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the present invention. In short, all technical solutions and improvements that do not depart from the spirit and scope of the present invention should be covered within the protection scope of the present invention patent.

Claims

1. A method for assessing ecosystem service loss in arid and semi-arid regions, characterized in that, Includes the following steps: Key indicator selection steps: Select at least one area within an arid or semi-arid ecosystem that retains its natural ecological characteristics and has not been affected by intensive agricultural activities as a control area, and at least one area that has been ecologically degraded due to intensive agricultural activities as a fragmented area; sample the selected control area and fragmented area from multiple dimensions, including animal diversity, vegetation growth status, and soil health level, to obtain raw data of key ecosystem indicators; the key indicators include animal diversity indicators, vegetation functional trait indicators, and soil quality indicators; Data standardization steps: The min-max standardization method is used to normalize the raw data of each indicator in the key indicators to obtain the standardized value of each indicator. Weight calculation steps: Based on the standardized values ​​of each indicator, the weight value of each indicator is calculated using the entropy weight method. The steps for calculating the ecological integrity index are as follows: The standardized values ​​of each indicator are weighted and summed according to their weight values ​​to obtain the ecological integrity index. Then, the ecological integrity index of the control area and the ecological integrity index of the fragmented area are calculated separately. Steps for calculating the ecological integrity loss rate: Calculate the ecological integrity loss rate based on the ecological integrity index of the control area and the ecological integrity index of the fragmented area; The steps for calculating the value of ecosystem services are as follows: Calculate the value of ecosystem services in the control area based on the pre-obtained area area and the value of ecosystem services per unit area of ​​each region; and calculate the value of ecosystem services in the fragmented area based on the rate of loss of ecological integrity and the value of ecosystem services in the control area. Service loss assessment steps: Based on the ecosystem service value of the control area and the ecosystem service value of the fragmented area, the economic loss of the ecosystem is calculated, thereby realizing the service loss assessment of the ecosystem in arid and semi-arid regions.

2. The method for assessing ecosystem service loss in arid and semi-arid regions according to claim 1, characterized in that, In the key indicator selection step, the animal diversity indicator is the Shannon diversity index of arthropods, the vegetation functional trait indicator is the average vegetation height, and the soil quality indicator is the soil organic matter content.

3. The method for assessing ecosystem service loss in arid and semi-arid regions according to claim 2, characterized in that, In the weight calculation step, the entropy weight method is used to calculate the weight value of each indicator, specifically including: Based on the standardized values ​​of each indicator and the principle of information entropy, the entropy value of each indicator is calculated, and the first weight value of the Shannon diversity index of arthropods, the second weight value of the average vegetation height, and the third weight value of the soil organic matter content are calculated according to the entropy value.

4. The method for assessing ecosystem service loss in arid and semi-arid regions according to claim 3, characterized in that, In the calculation step of the ecological integrity index, the standardized values ​​of each indicator are weighted and summed according to the weight values ​​to obtain the ecological integrity index. Specifically, this includes: The ecological integrity index is calculated by summing the standardized value of the Shannon diversity index of arthropods and the product of the first weight value, the standardized value of the average vegetation height and the product of the second weight value, and the standardized value of the soil organic matter content and the product of the third weight value.

5. The method for assessing ecosystem service loss in arid and semi-arid regions according to any one of claims 1 to 4, characterized in that, In the data standardization step, the calculation formula for the min-max standardization method is as follows: y ij =[x ij -min(x j )] / [max(x j )-min(x j )] Where, x ij For the raw data of the j-th indicator in the i-th region, y ij For the corresponding standardized value, min(x) j ) and max(x j ) are the minimum and maximum values ​​of the j-th indicator, respectively.

6. The method for assessing ecosystem service loss in arid and semi-arid regions according to any one of claims 1 to 4, characterized in that, In the step of calculating the value of ecosystem services, the value of ecosystem services per unit area is calibrated using long-term monitoring data of the study area, or by referencing the value of ecosystem services per unit area of ​​similar ecosystems in arid and semi-arid regions from existing literature.

7. An ecosystem service loss assessment system suitable for arid and semi-arid regions, characterized in that, It includes, in sequence, a key indicator selection module, a data standardization module, a weight calculation module, an ecological integrity index calculation module, an ecological integrity loss rate calculation module, an ecosystem service value calculation module, and a service loss assessment module. The key indicator selection module selects at least one area within an arid or semi-arid ecosystem that retains its natural ecological characteristics and is unaffected by intensive agricultural activities as a control area, and at least one area whose ecology has been degraded due to intensive agricultural activities as a fragmented area. It then samples the selected control area and fragmented area from multiple dimensions, including animal diversity, vegetation growth status, and soil health level, to obtain raw data on the key indicators of the ecosystem. These key indicators include animal diversity indicators, vegetation functional trait indicators, and soil quality indicators. The data standardization module uses the min-max standardization method to normalize the original data of each key indicator to obtain the standardized value of each indicator. The weight calculation module calculates the weight value of each indicator based on the standardized value of each indicator and using the entropy weight method. The ecological integrity index calculation module calculates the standardized values ​​of each indicator by weighted summation according to the weight values ​​to obtain the ecological integrity index, and then calculates the ecological integrity index of the control area and the ecological integrity index of the fragmented area respectively. The ecological integrity loss rate calculation module calculates the ecological integrity loss rate based on the ecological integrity index of the control area and the ecological integrity index of the fragmented area. The ecosystem service value calculation module calculates the ecosystem service value of the control area based on the pre-acquired area area and ecosystem service value per unit area of ​​each region. The ecosystem service value of the fragmented area was calculated based on the ecological integrity loss rate and the ecosystem service value of the control area. The service loss assessment module calculates the economic loss of the ecosystem based on the ecosystem service value of the control area and the ecosystem service value of the fragmented area, thereby realizing the assessment of ecosystem service loss in arid and semi-arid regions.

8. The ecosystem service loss assessment system for arid and semi-arid regions according to claim 7, characterized in that, In the key indicator selection module, the animal diversity indicator is the Shannon diversity index of arthropods, the vegetation functional trait indicator is the average vegetation height, and the soil quality indicator is the soil organic matter content.

9. The ecosystem service loss assessment system for arid and semi-arid regions according to claim 8, characterized in that, In the weight calculation module, the entropy weight method is used to calculate the weight value of each indicator, specifically including: Based on the standardized values ​​of each indicator and the principle of information entropy, the entropy value of each indicator is calculated, and the first weight value of the Shannon diversity index of arthropods, the second weight value of the average vegetation height, and the third weight value of the soil organic matter content are calculated according to the entropy value.

10. The ecosystem service loss assessment system for arid and semi-arid regions according to claim 9, characterized in that, In the ecological integrity index calculation module, the standardized values ​​of each indicator are weighted and summed according to their weight values ​​to obtain the ecological integrity index, which specifically includes: The ecological integrity index is calculated by summing the standardized value of the Shannon diversity index of arthropods and the product of the first weight value, the standardized value of the average vegetation height and the product of the second weight value, and the standardized value of the soil organic matter content and the product of the third weight value.

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