Evolution toughness-based ecological restoration evaluation method and device

Abstract

The invention discloses an ecological restoration evaluation method and device based on evolution toughness, and relates to the technical field of ecological environment restoration evaluation.The method comprises the steps that ecological restoration evaluation basic data, including ecological disaster recovery data, ecological environment long-term monitoring data and ecological space pattern data, of a target area are obtained; respectively calculating an ecological toughness index, an ecological environment evolution index and an ecological spatial pattern index; then constructing an evolution toughness evaluation model by adopting a network analysis method; and finally, based on the evolution toughness evaluation model, integrating the mutual influence among the element clusters by adopting a hypermatrix weighting algorithm, and outputting an evolution ecological toughness evaluation result. According to the method, complex and diversified evaluation indexes can be integrated, comprehensive evaluation is carried out on ecological restoration from a longer time scale and a larger space scale, and the accuracy of ecological restoration evaluation is improved.

Description

Technical Field

[0001] This application relates to the field of ecological environment restoration assessment technology, and in particular to an ecological restoration assessment method and apparatus based on evolutionary resilience. Background Technology

[0002] Currently, there are relatively complete evaluation systems for ecosystems, especially those after ecological disasters or during ecological restoration. These include systems for assessing the resilience of regional ecosystems after disasters, assessments based on the overall ecological environment, and assessments of ecosystem patterns on a larger scale. However, current ecological restoration evaluation methods have the following problems.

[0003] (1) The evaluation indicators are complex and diverse, but they still cannot specifically depict the recovery of the ecosystem after it is affected and its impact on the ecological environment on a larger scale, resulting in inaccurate final ecological restoration evaluation results.

[0004] (2) The evaluation indicators are mostly focused on a single spatial dimension, without dynamic evaluation of long-term change processes and impact assessment on a longer time scale, which will also lead to inaccurate final ecological restoration evaluation results.

[0005] In summary, how to integrate complex and diverse evaluation indicators and conduct comprehensive evaluation of ecological restoration from a longer time scale and a larger spatial scale, thereby improving the accuracy of ecological restoration evaluation, has become a technical problem that urgently needs to be solved in this field. Summary of the Invention

[0006] The purpose of this application is to provide an ecological restoration evaluation method and apparatus based on evolutionary resilience, which can integrate complex and diverse evaluation indicators and conduct a comprehensive evaluation of ecological restoration from a longer time scale and a larger spatial scale, thereby improving the accuracy of ecological restoration evaluation.

[0007] To achieve the above objectives, this application provides the following solution: Firstly, this application provides an ecological restoration assessment method based on evolutionary resilience, which includes the following steps: Obtain basic data for ecological restoration assessment of the target area; the basic data for ecological restoration assessment includes ecological disaster recovery data, long-term ecological environment monitoring data, and ecological spatial pattern data.

[0008] Based on the ecological disaster recovery data, the long-term ecological environment monitoring data, and the ecological spatial pattern data, ecological resilience indicators, ecological environment evolution indicators, and ecological spatial pattern indicators are calculated respectively.

[0009] Based on the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index, an evolutionary resilience evaluation model is constructed using network analysis. The evolutionary resilience evaluation model refers to a network analysis model that uses the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index as control layer criteria, and uses the lower-level indicators of the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index as element clusters of the network layer.

[0010] Based on the aforementioned evolutionary resilience evaluation model, a supermatrix weighted algorithm is used to integrate the mutual influences between element clusters and output the evolutionary ecological resilience evaluation results.

[0011] Secondly, this application proposes an ecological restoration evaluation system based on evolutionary resilience, which includes: The data acquisition module is used to acquire basic data for ecological restoration evaluation of the target area; the basic data for ecological restoration evaluation includes ecological disaster recovery data, long-term ecological environment monitoring data, and ecological spatial pattern data.

[0012] The indicator calculation module is used to calculate the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index based on the ecological disaster recovery data, the long-term ecological environment monitoring data, and the ecological spatial pattern data, respectively.

[0013] The network analysis module is used to construct an evolutionary resilience evaluation model based on the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index using network analysis. The evolutionary resilience evaluation model refers to a network analysis model that uses the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index as control layer criteria, and uses the lower-level indicators of the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index as element clusters of the network layer.

[0014] The output module is used to integrate the mutual influences between element clusters based on the evolutionary resilience evaluation model and to output the evolutionary ecological resilience evaluation results.

[0015] Thirdly, this application provides a computer device, including: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the evolutionary resilience-based ecological restoration assessment method described in any one of the above.

[0016] Fourthly, this application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the evolutionary resilience-based ecological restoration assessment method described above.

[0017] Fifthly, this application provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the evolutionary resilience-based ecological restoration assessment method described above.

[0018] According to the specific embodiments provided in this application, this application has the following technical effects.

[0019] This application provides an ecological restoration evaluation method and apparatus based on evolutionary resilience. It acquires three types of data: ecological disaster recovery data, long-term ecological environment monitoring data, and ecological spatial pattern data. It calculates three-dimensional indicators: ecological resilience index, ecological environment evolution index, and ecological spatial pattern index. It constructs an evolutionary resilience evaluation model using network analysis. Finally, based on this evolutionary resilience evaluation model, it integrates the mutual influence between element clusters using a supermatrix weighted algorithm to output the evolutionary ecological resilience evaluation result. As can be seen, this application establishes a multi-dimensional indicator evaluation method that integrates different time scales (short-term time scale for assessing ecological resilience after disasters and long-term time scale for assessing ecological and environmental evolution) and spatial scales (ecological spatial pattern assessment). It comprehensively evaluates ecological resilience, ecological and environmental evolution, and ecological spatial pattern from multiple perspectives. By combining network analysis and hypermatrix weighted algorithms to integrate the mutual influence between element clusters, it not only integrates complex and diverse evaluation indicators but also conducts a comprehensive evaluation from a longer time scale and a larger spatial scale. It quantitatively describes the process of ecosystem evolution and resilience, thereby improving the accuracy of ecological restoration evaluation. It can provide a precise and comprehensive assessment of the overall state after ecological disasters or changes in ecological and environmental conditions, and solve the problem that current ecological restoration evaluation methods are inaccurate due to the complexity and diversity of evaluation indicators, which are mostly concentrated in a single spatial dimension and cannot dynamically assess long-term changes or assess the impact on longer time scales. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0021] Figure 1 This is an application environment diagram of an ecological restoration evaluation method based on evolutionary resilience provided in an embodiment of this application.

[0022] Figure 2 This is a flowchart illustrating an ecological restoration evaluation method based on evolutionary resilience, provided as an embodiment of this application.

[0023] Figure 3 An ecological resilience assessment curve provided for an embodiment of this application.

[0024] Figure 4 A schematic diagram of reference ecological environment damage quantification and resilience assessment indicators provided for an embodiment of this application.

[0025] Figure 5 This is a schematic diagram of a primary indicator for assessing the ecological environment status, provided in an embodiment of this application.

[0026] Figure 6 A schematic diagram of the primary indicators for evaluating the ecological spatial pattern provided in an embodiment of this application.

[0027] Figure 7 This is a schematic diagram of evolution resilience evaluation provided in an embodiment of this application.

[0028] Figure 8 This is a schematic diagram of a toughness pattern evaluation provided in an embodiment of this application.

[0029] Figure 9 This is a schematic diagram of an evolution pattern evaluation provided in an embodiment of this application.

[0030] Figure 10 An evolutionary ecological resilience evaluation diagram provided in one embodiment of this application.

[0031] Figure 11 This is a schematic diagram of the evaluation dimensions of the Evolutionary Ecological Resilience (ERV) assessment provided in an embodiment of this application.

[0032] Figure 12 This is a schematic diagram of the evaluation dimensions of the Evolutionary Ecological Resilience (EER) assessment provided in an embodiment of this application.

[0033] Figure 13 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0034] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0035] This embodiment aims to provide an ecological restoration evaluation method and apparatus based on evolutionary resilience. Besides considering ecological restoration in conjunction with changes in the ecological environment and its patterns, it also fully considers the mutual influence of multiple dimensions of different evaluation factors among ecological disasters, ecological environment systems, and pattern planning and design. It integrates existing ecological and disaster evaluation methods, as well as evolutionary changes over longer time scales, and ecological spatial pattern evaluation systems, and feeds back these into an operational evaluation method to guide ecological restoration, providing guidance for the gradual improvement and refinement of the system during disasters. Based on a three-dimensional evaluation system of ecological resilience, ecological restoration, and ecological pattern (i.e., short-term ecological disaster response, long-term ecological restoration, and spatial pattern), it comprehensively examines the ecosystem's response to disasters and the connection between disaster restoration and long-term restoration in spatial pattern planning and evolution. It integrates various ecological evaluation methods, such as ecological evaluation and ecological disaster evaluation, and simultaneously includes three types of evaluation: ecological resilience evaluation (short-term evaluation of ecosystem response to emergencies), ecological environment evolution evaluation (evaluation of long-term ecological environment changes), and ecological spatial pattern evaluation (evaluation of ecosystem space), which is the evolutionary ecological resilience evaluation.

[0036] To make the above-mentioned objectives, features and advantages of this application more apparent and understandable, the application will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0037] The evolutionary resilience-based ecological restoration evaluation method provided in this application can be applied to, for example... Figure 1In the application environment shown, terminal 102 communicates with server 104 via a network. A data storage system can store the data that server 104 needs to process. The data storage system can be set up independently, integrated into server 104, or placed in the cloud or on other servers. Terminal 102 can send basic ecological restoration evaluation data for the target area to server 104. After receiving the basic ecological restoration evaluation data for the target area, server 104 calculates ecological resilience indicators, ecological environment evolution indicators, and ecological spatial pattern indicators based on ecological disaster recovery data, long-term ecological environment monitoring data, and ecological spatial pattern data, respectively. Then, it uses Analytic Network Process (ANP) to construct an evolutionary resilience evaluation model. Finally, based on the evolutionary resilience evaluation model, it uses a hypermatrix weighted algorithm to integrate the mutual influences between element clusters and outputs the evolutionary ecological resilience evaluation results. Server 104 can feed back the obtained evolutionary ecological resilience evaluation results to terminal 102. In addition, in some embodiments, the ecological restoration evaluation method based on evolutionary resilience can also be implemented by the server 104 or the terminal 102 alone. For example, the terminal 102 can directly perform ecological restoration evaluation processing on the basic ecological restoration evaluation data of the target area, or the server 104 can obtain the basic ecological restoration evaluation data of the target area from the data storage system and perform ecological restoration evaluation processing on the basic ecological restoration evaluation data of the target area.

[0038] The terminal 102 can be, but is not limited to, various desktop computers, laptops, smartphones, tablets, and IoT devices. The server 104 can be implemented using a standalone server or a server cluster consisting of multiple servers, or it can be a cloud server.

[0039] In one exemplary embodiment, such as Figure 2 As shown, an ecological restoration evaluation method based on evolutionary resilience is provided. This method is executed by computer equipment, specifically by a terminal or server alone, or by both a terminal and a server. In this embodiment, the method is applied to... Figure 1 Taking server 104 as an example, the explanation includes the following steps S1 to S4.

[0040] S1: Obtain basic data for ecological restoration assessment of the target area.

[0041] In this embodiment, the basic data for ecological restoration evaluation includes ecological disaster recovery data, long-term ecological environment monitoring data, and ecological spatial pattern data.

[0042] S2: Calculate the ecological resilience index, ecological environment evolution index, and ecological spatial pattern index based on the ecological disaster recovery data, the long-term ecological environment monitoring data, and the ecological spatial pattern data, respectively.

[0043] S3: Based on the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index, a network analysis method is used to construct an evolutionary resilience evaluation model.

[0044] In this embodiment, the evolutionary resilience evaluation model refers to a network analysis model that uses the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index as control layer criteria, and the lower-level indices of the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index as element clusters of the network layer. Therefore, the evolutionary resilience evaluation model is actually a network analysis model, namely the ANP model, which represents the network analysis process of obtaining the evolutionary ecological resilience evaluation results through network analysis.

[0045] In this embodiment, the lower-level indicators refer to all the lower-level indicators included in the ecological resilience indicators, ecological environment evolution indicators, and ecological spatial pattern indicators.

[0046] S4: Based on the evolutionary resilience evaluation model, the supermatrix weighted algorithm is used to integrate the mutual influence between element clusters and output the evolutionary ecological resilience evaluation results.

[0047] In this embodiment, step S4, based on the evolutionary resilience evaluation model, uses a supermatrix weighted algorithm to integrate the mutual influences between element clusters and outputs the evolutionary ecological resilience evaluation result. Specifically, it includes the following steps: S41: Construct a supermatrix based on the evolution resilience evaluation model.

[0048] S42: Weight the supermatrix to obtain a weighted supermatrix.

[0049] S43: Based on the weighted supermatrix, construct the judgment matrix using the 1-9 scaling method.

[0050] S44: Using the sum-product method, calculate the largest eigenvalue of the judgment matrix and its corresponding eigenvector.

[0051] S45: Calculate the weight vector based on the largest eigenvalue of the judgment matrix and its corresponding eigenvector.

[0052] S46: Determine the evaluation results of the evolutionary ecological resilience based on the weight vector.

[0053] In this embodiment, after calculating the weight vector based on the largest eigenvalue of the judgment matrix and its corresponding eigenvector in step S45, the ecological restoration evaluation method based on evolutionary resilience further includes the following steps: performing a consistency check on the judgment matrix to determine whether the judgment matrix meets the consistency check conditions, and obtaining a consistency check result. This consistency check result includes the following two cases.

[0054] (1) When the consistency test result is yes, then the operation of step S46 "determine the evolutionary ecological resilience evaluation result according to the weight vector" is executed.

[0055] (2) When the consistency test result is negative, return to step S43 "construct a judgment matrix based on the weighted supermatrix using the 1-9 scale method" and reconstruct the judgment matrix.

[0056] To make the technical solution of this embodiment clearer, the specific implementation process of the technical solution of this embodiment will be described in detail below by way of example, including the following implementation steps.

[0057] Step 1: Collect basic data for ecological restoration assessment of the target area, including the results and indicators of assessments in various dimensions. These mainly include assessments of post-disaster ecological environment restoration (taking the periodic damage to ecological environment service functions as an example), long-term assessment indicators of the ecosystem (taking the ecological environment quality assessment status index as an example), and assessment indicators of ecological patterns (taking ecological spatial patterns and changes as an example).

[0058] In this embodiment, step 1 is to collect basic data on previous evaluations of a target area, mainly including evaluations of local ecological disasters and disaster restoration, evaluations of ecological environment quality, and evaluations of ecological spatial patterns and changes. This embodiment uses the "National Ecological Status Survey and Assessment Technical Specification—Ecological Problem Assessment" (HJ1174—2021) and the "General Principles and Key Links of the Technical Guidelines for Ecological Environment Damage Identification and Assessment" (GB / T39791.1-2020, GB / T39791.2-2020, GB / T39791.3-2024) as references for ecological disaster and disaster restoration assessment (corresponding to ecological resilience assessment) and indicator selection; the "Ecological Environment Status Assessment Technical Specification" (HJ192-2015) and the "National Ecological Status Survey and Assessment Technical Specification—Ecosystem Quality Assessment" (HJ1172—2021) as references for ecosystem assessment (corresponding to ecological environment evolution assessment) and indicator selection; and the "National Ecological Status Survey and Assessment Technical Specification—Ecological Spatial Pattern Assessment" (HJ1171—2021) as references for ecological spatial pattern assessment (corresponding to ecological spatial pattern assessment) and indicator selection.

[0059] Step 2: Organize the evaluation indicators for each dimension, establish the evaluation indicators for evolutionary resilience, and carry out ecological restoration evaluation based on evolutionary resilience.

[0060] As the evaluation methods for the various types of ecological environment and problems mentioned above already exist, it is necessary to conduct a comprehensive assessment of the ecological restoration of the target area according to three dimensions: disaster recovery, long-term monitoring of ecological environment quality, and ecological pattern.

[0061] This embodiment involves the following three different evaluation methods and evaluation contents.

[0062] (1) Ecological resilience assessment.

[0063] Figure 3 The ecological resilience assessment curve is shown, including three scenarios: good ecological restoration, poor ecological restoration, and no restoration. It can be seen that the ecological environment function changes with the time from the occurrence of damage to the start of restoration and then to the completion of restoration.

[0064] The assessment of ecological and environmental functions caused by disasters mainly includes baseline determination methods and key contents of ecological and environmental damage investigation and assessment, as detailed in the "General Guidelines and Key Aspects of Technical Guidelines for Ecological and Environmental Damage Identification and Assessment" (GB / T39791.1-2020). Damage assessment can be performed based on the amount of damage over a given period. H The evaluation is expressed as follows.

[0065] (1) in, H Indicates the amount of damage during the period; t This refers to any year from the occurrence of ecological and environmental damage to its recovery to baseline. t 0- t n between); t 0 represents the starting year, that is, the year in which the ecological damage occurred; t n This indicates the termination year, which is the year in which the ecological and environmental damage recovers to the baseline. T The base year is generally selected as the year in which the assessment of ecological and environmental damage is carried out. R t For the first t The number of ecological environment service functions in the damaged area each year. d t For the first t The percentage of ecological environment service functions lost relative to baseline in the damaged area in a given year. r In this embodiment, the discount factor is used. r The value ranges from 2% to 5%.

[0066] Figure 4This document presents reference indicators for the quantification of ecological and environmental damage and resilience assessment. Primary indicators include: quantification of damage to environmental media, quantification of damage to biological elements, quantification of damage to ecosystem service functions, quantification of periodic damage, assessment of restoration feasibility, and formulation of restoration plans. Specifically, the quantification of damage to environmental media includes ambient air, surface water, sediments, soil, groundwater, and seawater, with indicators such as soil pollution index, water degradation rate, and air pollutant concentration. The quantification of damage to biological elements includes damage to individual organisms, damage to biological population characteristics, damage to biological community characteristics, and damage to ecosystem characteristics, with indicators such as species diversity loss rate, key population recovery rate, and habitat fragmentation index. The quantification of damage to ecosystem service functions includes the type of ecosystem service function, quantification indicators of ecosystem service functions, and the extent and degree of damage to ecosystem service functions, with indicators such as water conservation capacity loss and carbon sink function decline rate. The quantification of periodic damage includes the definition of periodic damage and methods for quantifying it, with indicators such as the amount of periodic damage. The assessment of restoration feasibility includes economic feasibility, technical feasibility, and operational feasibility, with indicators such as natural restoration potential, human intervention costs, and technical feasibility. The recovery plan includes recovery objectives, strategies, technologies, scale, and alternatives, such as recovery timeframe, funding, and priority strategies.

[0067] This embodiment mainly considers the mutual influence of primary indicators in resilience assessment on ecological environment evolution and ecological spatial pattern evaluation.

[0068] In the process of ecological resilience assessment, a single ecological resilience index represents the ecosystem's ability to recover after being subjected to disasters. By definition, ecological resilience... R It is expressed as the following formula.

[0069] (2) in, R It is an ecological resilience indicator, representing the resilience of an ecosystem. t Any year from the occurrence of ecological and environmental damage to its restoration to baseline ( t 0- t n between). t 0 represents the starting year, that is, the year in which the ecological damage occurred; t n This indicates the termination year, which is the year in which the ecological and environmental damage recovers to the baseline. d t For the first t The percentage of ecological environment service functions lost relative to baseline in the damaged area in a given year. R 0 represents the quality of the assessed ecological and environmental functional system, through the evaluation of... RThe overall system resilience is obtained from a zero-integral score. This definition is very similar to the periodic damage measurement in ecosystem damage assessment. In practical applications, a single ecological resilience index can be used... H = R Operation, then R 0= R t × d t ×(1+ r )^( T - t This refers to the quality of the ecological environment functional system and the quantity of ecological environment service functions in the damaged area at any given moment. R t , No. t The proportion of ecological environment service function loss relative to baseline in the damaged area in the year d t With discount factor r Related functions. Strictly speaking, ecological resilience requires... R The evaluation is performed using 0, rather than through parametric functions or other similar methods. However, it is used to integrate with existing evaluation systems, especially with already collected indicator data. H = R This is also why ecosystem resilience needs to be defined separately.

[0070] (2) Evaluation of the evolution of the ecological environment.

[0071] This embodiment of the ecological environment evolution assessment is mainly based on the regional ecological environment status assessment, with the addition of an overall assessment of changes over time. The assessment of the ecological environment status can refer to the ecological environment status assessment indicators proposed in the "Technical Specification for Ecological Environment Status Assessment" (HJ192-2015), such as... Figure 5 As shown, the assessment of ecological and environmental status mainly involves ecological and environmental indices, including biodiversity index, vegetation cover index, water network density index, land stress index, pollution load index, and environmental limitation index.

[0072] In this embodiment, the ecological environment index EI Defined as follows.

[0073] (3) in, wi For weighted index, Ei As evaluation indicators. This embodiment follows... Figure 5 As shown in the primary indicators and standards, the ecological environment index EI=0.35×Biodiversity Index + 0.25×Vegetation Cover Index + 0.15×Water Network Density Index + 0.15×(100-Land Stress Index) + 0.10×(100-Pollution Load Index) + Environmental Restriction Index.

[0074] This embodiment proposes a new evaluation index, namely the ecological environment evolution index. Ev This uses changes in ecological and environmental indices over a period of time as another indicator to measure ecosystem change. Ecological and environmental evolution indicators. Ev It is expressed as the following formula.

[0075] (4) in, Ev As an indicator of ecological and environmental evolution; EI For ecological environment index; d t Indicates the first t The proportion of ecological environment service functions lost relative to baseline in the damaged area in a given year; T 1. To assess the starting date, T 2. To assess the end date, in relation to ecological resilience T The definitions are different, t 0- t n Ecological environment restoration is usually assessed on an annual basis, while T 1- T 2. Ecosystem environmental changes are typically assessed over a broader timeframe using decadal units. In this embodiment, decadal data is generated by aggregating annual averages. Therefore, in specific assessments, the following formula can be used to calculate the ecological environment evolution index.

[0076] (5) This allows for the evaluation of a single indicator of ecological and environmental evolution. Among them... Ti Indicates the year that needs to be evaluated; EI i These are ecological environment indices obtained from evaluations in different eras.

[0077] (3) Evaluation of ecological spatial pattern.

[0078] Currently, remote sensing interpretation results are typically used to assess long-term ecosystem monitoring, including ecosystem composition, ecological spatial patterns, and overall ecosystem change characteristics. The ecological spatial pattern provided by the reference standard "Technical Specification for National Ecological Status Survey and Assessment—Ecological Spatial Pattern Assessment" (HJ1171—2021) includes three primary indicators and eight secondary indicators, such as... Figure 6As shown, the primary indicators include ecosystem composition and its changes (such as area changes of forest, grassland, and wetland types), ecosystem spatial patterns and their changes (such as patch morphology and distribution characteristics), and overall ecosystem change characteristics (comprehensive trend analysis). The secondary indicators corresponding to ecosystem composition and its changes include the proportion of ecosystem types and the rate of change in ecosystem type area. The secondary indicators corresponding to ecosystem spatial patterns and their changes include average patch area, aggregation index, boundary density, and number of patches. The secondary indicators corresponding to overall ecosystem change characteristics include the direction of change for various ecosystem types and the overall ecosystem dynamics.

[0079] In this embodiment, the ecological spatial pattern index is defined as follows.

[0080] (6) in, EP As an indicator of ecological spatial pattern, it represents the ecological pattern; W epi The weighting coefficients for primary indicators; EP i The evaluation results are for the corresponding indicators.

[0081] By combining the three evaluation contents mentioned above (1), (2), and (3), ecological resilience, namely the ecosystem's ability to recover from disasters, the ecosystem's environmental index, and the ecological spatial pattern, can be evaluated respectively. However, the definition of evolving ecological resilience in this embodiment aims to assess the impact of ecosystem disasters on the system and its longer-term and spatial evolution, and to evaluate the impact of adjustments to certain specific ecological disaster assessment indicators on ecological resilience, as well as the impact of ecological restoration strategies on the overall ecological environment and its pattern. The overall evaluation strategy is an adaptive cyclical system, and the system represents the evaluation strategy for complex ecological evolution.

[0082] (1) Evolutionary Ecological Resilience Assessment (ERV).

[0083] Evolutionary ecological resilience assessment needs to consider both the evolution of the ecological environment and ecological environment evaluation. Typically, ecological resilience assessments span several years, while ecological environment evaluations require a comprehensive assessment of environmental conditions over decades. However, while resilience assessments consider a year-based timescale, ecological environment evaluations require a longer timeframe, or even a more appropriate assessment based on decades.

[0084] When it is necessary to evaluate ecological resilience and ecological environment evolution simultaneously, the method in this embodiment can be used for evaluation.

[0085] like Figure 7As shown, the control layer includes primary and secondary indicators, while the network layer includes tertiary indicators. The primary indicators include evolutionary resilience assessment, and the secondary indicators include ecological resilience assessment (short-term disaster response) and ecological environment status assessment (long-term environmental quality). Their corresponding lower-level indicators are the tertiary indicators of evolutionary resilience assessment. The tertiary indicators corresponding to ecological resilience assessment include clusters of elements quantifying environmental media damage, biological element damage, ecosystem service function damage, periodic damage, restoration feasibility assessment, and restoration plan development. The tertiary indicators corresponding to ecological environment status assessment include clusters of biodiversity indices, vegetation cover indices, water network density indices, land stress indices, pollution load indices, and environmental limitation indices.

[0086] It is easy to understand that in practical applications, quaternary indicators can be further subdivided based on tertiary indicators. Evaluation indicators (equivalent to a new evaluation) can be established for each element in the tertiary indicators, with more detailed element indicators serving as quaternary indicators to facilitate a more refined evaluation. To comprehensively consider the impact of ecosystem damage on ecological evolution, as well as the impact of ecological disasters on ecological evolution, this embodiment uses network analysis. This method can also consider the impact of all quaternary indicators on tertiary indicators, and the impact of tertiary indicators on secondary indicators.

[0087] To simplify the assessment of evolutionary resilience, primary and secondary indicators serve as the control layer, while tertiary indicators form the network layer. For more complex assessments (i.e., a more detailed consideration of the interactions between different tertiary indicators), tertiary indicators can be used as the control layer, with each tertiary indicator designing connections between element clusters in all tertiary networks. However, as a methodological introduction, using tertiary indicators as the control layer allows for a preliminary evaluation of the interaction between ecological resilience and ecological evolution.

[0088] 1) Network analysis method is used to conduct network analysis on ecological evolution resilience.

[0089] If we treat the three-level indicators as network layers, each indicator corresponds to a cluster of elements. C h , h =1, 2, ... N , C h have n k There are elements, represented as follows: e h1 , e h2 …, e hnkThe priority vectors obtained through pairwise comparisons represent the influence of a given set of elements in a certain element cluster on other elements in the system. The priority vectors obtained from the pairwise comparison matrices (obtained by sequentially combining the priority vectors) are part of the hypermatrix columns. The hypermatrix reflects the degree of influence of the elements on the left side of the matrix on the elements at the top of the matrix. Formulas (7) and (8) give the hypermatrix and its submatrices. W ij Element clusters C h The right side lists all the priority vectors calculated based on their parent criterion nodes.

[0090] (7) (8) in, ( =1, 2, ..., ) is the normalized weight vector.

[0091] According to the criteria in the control layer N There are m hypermatrices, all of which are non-negative, forming submatrices. It is column-normalized, but the supermatrix is... W It is not normalization. Therefore... N i As a standard, for N i Criteria for each element cluster C j ( j =1, 2, ..., N The importance of each is compared. C j The normalized eigenvectors obtained after pairwise comparisons can be combined to obtain a matrix. A= , i =1, 2, ... N ; j =1, 2, ... N For hypermatrix W The weighted result is a weighted hypermatrix. , i =1, 2, ... N , j =1, 2, ... N . W The sum of the columns is 1, which is a column random matrix.

[0092] Assuming the control layer N i , i =1, 2… m The weight vector for the target is The weight vector of each element cluster in the network layer to the criterion layer is: Then, for the objective, the weight vector of each scheme is obtained through... The resulting weight vector from the scheme layer (network layer) to the target layer (control layer) is: (9) Weights can be calculated using this process for problems at more complex levels.

[0093] 2) Hierarchical single sorting and consistency check. A judgment matrix can be constructed using the 1-9 scaling method given in Table 1, and the sum-product method can be used to calculate the maximum eigenvalue of each judgment matrix. and its corresponding eigenvectors After normalization, this feature vector becomes the weight value of each factor for the previous layer.

[0094] Table 1. Matrix Scale and Its Meaning

[0095] In this embodiment, the sum-product method is used to calculate the maximum eigenvalue and eigenvector. The main process is as follows: First, normalize the constructed judgment matrix X column-wise to obtain the matrix. ; to matrix Adding rows together yields a matrix. For the matrix Normalization is performed to obtain the feature vector. Finally, calculate the largest eigenvalue. The eigenvector corresponding to the largest eigenvalue is the corresponding weight value. Where: (10) (11) (12) (13) in, To determine the elements of a matrix after column normalization. The elements of the normalized eigenvector matrix are obtained by applying intermediate transformations. w i . For the first The combined value of the row elements, which is the result of summing the normalized matrix by row, reflects the combined influence of the elements in that row. This represents the sum of the combined values ​​of all row elements. This represents the original judgment matrix. Given the complexity of decision-making problems and the inherent limitations of our understanding of things, after calculating the weights indicating the importance ranking, it is necessary to test the consistency of each judgment matrix. This is mainly done using consistency indices, random consistency indices, and consistency ratios, as shown in the following formulas: (14) (15) in, CR Indicates the proportion of random consistency; CI As a consistency indicator; RI The random consistency index has values ​​shown in Table 2, and is related to the matrix order. n Related; To determine the largest eigenvalue of a matrix. When CR If the value is less than 0.1, the constructed judgment matrix can be considered to have passed the consistency test; otherwise, the judgment matrix needs to be reconstructed.

[0096] Table 2. Average Random Consistency Index of the Judgment Matrix

[0097] In the pairwise judgment process during the supermatrix construction, one of the features of the technical solution in this embodiment is that the 1-9 scaling method is used to replace the subjective importance evaluation by quantitatively accounting for the important data in step 2). This yields the evaluation result vector V of evolutionary resilience.

[0098] This embodiment is the first to apply network analysis to a three-dimensional coupled ecological restoration evaluation scenario of "ecological resilience-ecological environment evolution-ecological spatial pattern". By quantifying the influence of cross-dimensional indicators through hypermatrix, the accuracy of ecological restoration evaluation can be effectively improved.

[0099] (2) Resilience pattern assessment (ERS).

[0100] This embodiment primarily considers the impact of ecological damage on the assessment of ecological spatial patterns, specifically evaluating the interaction between ecological damage and the overall ecological environment within a given area. The primary to tertiary indicators for resilience pattern assessment are as follows: Figure 8As shown, the control layer includes primary and secondary indicators, and the network layer includes tertiary indicators. The primary indicators include resilience pattern evaluation, and the secondary indicators include ecological resilience evaluation (short-term disaster response) and ecological pattern evaluation (ecological spatial pattern). The corresponding lower-level indicators are the tertiary indicators of resilience pattern evaluation. The tertiary indicators corresponding to ecological resilience evaluation include the element clusters for quantifying environmental media damage, the element clusters for quantifying biological element damage, the element clusters for quantifying damage to ecosystem service functions, the element clusters for quantifying period damage, the element clusters for evaluating restoration feasibility, and the element clusters for formulating restoration plans. The tertiary indicators corresponding to ecological pattern evaluation include ecosystem composition and changes, ecosystem spatial pattern and changes, and ecosystem overall change characteristics. The resilience pattern evaluation results can be obtained by calculating using equations (4) to (15).

[0101] (3) Evolutionary pattern evaluation (EVS).

[0102] This embodiment considers evaluating the relationship between the evolution of the ecological environment and ecological patterns, examining the interaction between long-term ecological changes and ecological patterns on a larger scale. The primary to tertiary indicators for evaluating the evolutionary pattern are as follows: Figure 9 As shown. The control layer includes primary and secondary indicators, and the network layer includes tertiary indicators. The primary indicators include evolution pattern evaluation, and the secondary indicators include ecological environment status evaluation (long-term environmental quality) and ecological pattern evaluation (ecological spatial pattern). The corresponding lower-level indicators are the tertiary indicators of evolution pattern evaluation. The tertiary indicators corresponding to ecological environment status evaluation include biodiversity index cluster, vegetation cover index cluster, water network density index cluster, land stress index cluster, pollution load index cluster, and environmental limitation index cluster. The tertiary indicators corresponding to ecological pattern evaluation include ecosystem composition and change, ecosystem spatial pattern and change, and ecosystem overall change characteristics. The evolution pattern evaluation results can be obtained by calculating using equations (4) to (15).

[0103] Through the above evaluation, three evaluation indicators can be obtained: evolutionary resilience evaluation, resilience pattern evaluation, and evolutionary pattern evaluation. These three indicators are comprehensive and mutually influential evaluations of the next-level indicators in their respective evaluation methods (mainly referring to the resilience of the ecological environment to disaster impacts, the overall evolution and change of the ecological environment, and changes in ecological pattern). If the comprehensive impact of ecological disasters on ecological evolution and ecological pattern needs to be considered, a comprehensive evaluation of the indicators in all three dimensions is required to form the comprehensive evolutionary ecological resilience evaluation (EER) required in this embodiment. The comprehensive evaluation indicators of this comprehensive evolutionary ecological resilience evaluation are as follows: Figure 10As shown, the control layer includes primary and secondary indicators, and the network layer includes tertiary indicators. Among them, the primary indicators include an evolutionary ecological resilience assessment that integrates three dimensions, and the secondary indicators include ecological resilience assessment (short-term disaster response), ecological environment status assessment (long-term environmental quality), and ecological pattern assessment (ecological spatial pattern). Among them, the tertiary indicators corresponding to the ecological resilience assessment include the element clusters for quantifying environmental media damage, the element clusters for quantifying biological element damage, the element clusters for quantifying damage to ecosystem service functions, the element clusters for quantifying period damage, the element clusters for assessing restoration feasibility, and the element clusters for formulating restoration plans. The tertiary indicators corresponding to the ecological environment status assessment include the element clusters for biological abundance index, vegetation cover index, water network density index, land stress index, pollution load index, and environmental limitation index. The tertiary indicators corresponding to the ecological pattern assessment include the ecosystem composition and changes, the ecosystem spatial pattern and changes, and the overall changes in the ecosystem. The comprehensive evolutionary ecological resilience assessment results can be obtained through the evaluation of equations (4) to (15).

[0104] This embodiment combines three dimensions of indicators—ecological resilience, ecological environment evolution, and ecological spatial pattern—to construct an evolutionary resilience evaluation model. This model uses these three dimensions as control layer criteria and their subordinate indicators as element clusters in the network layer. The evaluation architecture of this evolutionary resilience evaluation model is similar to... Figure 10 Consistent. Therefore, the evolutionary ecological resilience evaluation result output by the evolutionary resilience evaluation model in this embodiment is a comprehensive evolutionary ecological resilience evaluation result that integrates the three dimensions.

[0105] This embodiment considers that the comprehensive evolutionary ecological resilience assessment is a comprehensive, multi-dimensional evaluation index designed to comprehensively examine the interaction between ecological disasters and ecological environment evolution and changes in ecological patterns. It can describe the complex interactions of disasters on the entire ecosystem and their interactions within the ecosystem's evolution. Current single-dimensional assessments only consider damage to the ecosystem during its duration, or use their definitions to replace the assessment of ecological resilience; or they only consider the overall state of the ecosystem without considering ecological environment evolution; or they only consider ecological spatial patterns without considering changes within the ecosystem or changes caused by external influences. Part of the reason for this is the different time scales of the various assessments. Resilience assessments mainly focus on the ecological environment's recovery over several years, while evolutionary assessments typically require long-term ecosystem evaluations on a decadal basis. Pattern changes mainly refer to spatial changes in the ecosystem. Single-dimensional ecological assessments are relatively simple and have specific significance within particular research topics, but comprehensively considering the overall evolution of human interaction with nature requires a combination of multiple dimensions.

[0106] Figure 11 A schematic diagram of the evaluation dimensions for the Evolutionary Ecological Resilience (ERV) assessment. Figure 12 This diagram illustrates the evaluation dimensions of the Evolutionary Ecological Resilience (EER) assessment. Among the three dimensions, ecological evolution assessment and ecological resilience assessment are time-scale indicators, while ecological spatial pattern assessment is a spatial-scale indicator. Integrating these three dimensions for a comprehensive evaluation of the evolution of the ecological environment offers the following advantages: 1) It considers the comprehensive impact of ecological disasters on ecological environment evolution and changes in ecological patterns; 2) It overcomes the limitations of single-dimensional assessments, allowing for consideration of ecological disaster restoration on longer time and larger spatial scales; 3) The pairwise combination of the three dimensions provides different evaluation methods, offering a mathematical basis for a comprehensive overall assessment. In further ecological planning and design, the comprehensive consideration of indicators from multiple dimensions, such as spatial patterns, ecological disasters, and ecological evolution, can enhance the overall holistic nature of ecological restoration strategies.

[0107] Based on the same inventive concept, this application also provides an evolutionary resilience-based ecological restoration assessment system for implementing the above-mentioned evolutionary resilience-based ecological restoration assessment method. The solution provided by this system is similar to the implementation scheme described in the above method. Therefore, the specific limitations of one or more embodiments of the evolutionary resilience-based ecological restoration assessment system provided below can be found in the limitations of the evolutionary resilience-based ecological restoration assessment method described above, and will not be repeated here.

[0108] In one exemplary embodiment, an ecological restoration assessment system based on evolutionary resilience is provided, comprising the following functional modules: The data acquisition module is used to acquire basic data for ecological restoration evaluation of the target area; the basic data for ecological restoration evaluation includes ecological disaster recovery data, long-term ecological environment monitoring data, and ecological spatial pattern data.

[0109] The indicator calculation module is used to calculate the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index based on the ecological disaster recovery data, the long-term ecological environment monitoring data, and the ecological spatial pattern data, respectively.

[0110] The network analysis module is used to construct an evolutionary resilience evaluation model based on the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index using network analysis. The evolutionary resilience evaluation model refers to a network analysis model that uses the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index as control layer criteria, and uses the lower-level indicators of the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index as element clusters of the network layer.

[0111] The output module is used to integrate the mutual influences between element clusters based on the evolutionary resilience evaluation model and to output the evolutionary ecological resilience evaluation results.

[0112] In one exemplary embodiment, a computer device is provided, which may be a server or a terminal, and its internal structure diagram may be as follows. Figure 13 As shown, this computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computational and control capabilities. The memory includes non-volatile storage media and internal memory. The non-volatile storage media stores the operating system, computer programs, and a database. The internal memory provides the environment for the operating system and computer programs in the non-volatile storage media to run. The database stores basic data for ecological restoration assessment of the target area. The I / O interfaces are used for information exchange between the processor and external devices. The communication interface is used for communication with external terminals via a network connection. When the computer program is executed by the processor, it implements an ecological restoration assessment method based on evolutionary resilience.

[0113] Those skilled in the art will understand that Figure 13 The structure shown is merely a block diagram of a portion of the structure related to the present application and does not constitute a limitation on the computer device to which the present application is applied. Specific computer devices may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0114] In one exemplary embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and the processor executes the computer program to implement the steps in the above-described method embodiments.

[0115] In one exemplary embodiment, a computer-readable storage medium is provided storing a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0116] In one exemplary embodiment, a computer program product is provided, including a computer program that, when executed by a processor, implements the steps in the above-described method embodiments.

[0117] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of the relevant data must comply with relevant regulations.

[0118] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM).

[0119] The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchain. The processors involved in the embodiments provided in this application may be, but are not limited to, general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc.

[0120] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0121] This document uses specific examples to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. An ecological restoration evaluation method based on evolutionary resilience, characterized in that, The ecological restoration evaluation method based on evolutionary resilience includes: Acquire basic data for ecological restoration assessment of the target area; the basic data for ecological restoration assessment includes ecological disaster recovery data, long-term ecological environment monitoring data, and ecological spatial pattern data. Based on the ecological disaster recovery data, the long-term ecological environment monitoring data, and the ecological spatial pattern data, ecological resilience indicators, ecological environment evolution indicators, and ecological spatial pattern indicators are calculated respectively. Based on the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index, an evolutionary resilience evaluation model is constructed using network analysis. The evolutionary resilience evaluation model refers to a network analysis model that uses the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index as control layer criteria, and uses the lower-level indicators of the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index as element clusters of the network layer. Based on the aforementioned evolutionary resilience evaluation model, a supermatrix weighted algorithm is used to integrate the mutual influences between element clusters and output the evolutionary ecological resilience evaluation results.

2. The ecological restoration evaluation method based on evolutionary resilience according to claim 1, characterized in that, The ecological resilience index is calculated using the following formula: ； in, R As an indicator of ecological resilience; t Any year from the occurrence of ecological and environmental damage to its restoration to baseline; t 0 represents the starting year, that is, the year in which the ecological damage occurred; t n This indicates the termination year, that is, the year in which the ecological and environmental damage recovers to the baseline. R 0 indicates the quality of the assessed ecological and environmental functional system. d t Indicates the first t The percentage of ecological environment service functions lost relative to baseline in the damaged area in a given year.

3. The ecological restoration evaluation method based on evolutionary resilience according to claim 1, characterized in that, The ecological environment evolution index is calculated using the following formula: ； ； ； in, EI For ecological environment index; wi For weighted index; Ei As evaluation indicators; Ev As an indicator of ecological and environmental evolution; T 1. To assess the starting date, T 2. To assess the end date; d t Indicates the first t The proportion of ecological environment service functions lost relative to baseline in the damaged area in a given year; Ti Indicates the year that needs to be evaluated; EI i These are ecological environment indices obtained from evaluations in different eras.

4. The ecological restoration evaluation method based on evolutionary resilience according to claim 1, characterized in that, The ecological spatial pattern index is calculated using the following formula: ； in, EP Indicators of ecological spatial pattern; W epi The weighting coefficients for primary indicators; EP i The evaluation results are for the corresponding indicators.

5. The ecological restoration evaluation method based on evolutionary resilience according to claim 1, characterized in that, Based on the aforementioned evolutionary resilience evaluation model, a supermatrix weighted algorithm is used to integrate the mutual influences between element clusters, outputting the evolutionary ecological resilience evaluation results, specifically including: Based on the aforementioned evolution resilience evaluation model, a supermatrix is ​​constructed; The supermatrix is ​​weighted to obtain a weighted supermatrix; Based on the weighted hypermatrix, a judgment matrix is ​​constructed using the 1-9 scaling method; The sum-product method is used to calculate the largest eigenvalue of the judgment matrix and its corresponding eigenvector; Calculate the weight vector based on the largest eigenvalue of the judgment matrix and its corresponding eigenvector; The evaluation results of the evolutionary ecological resilience are determined based on the weight vector.

6. The ecological restoration evaluation method based on evolutionary resilience according to claim 5, characterized in that, After the step of calculating the weight vector based on the largest eigenvalue of the judgment matrix and its corresponding eigenvector, the ecological restoration evaluation method based on evolutionary resilience further includes: Perform a consistency check on the judgment matrix to determine whether the judgment matrix satisfies the consistency check condition, and obtain the consistency check result. When the consistency test result is yes, the step of "determining the evolutionary ecological resilience evaluation result based on the weight vector" is executed. If the consistency check result is negative, then return to the step of "constructing a judgment matrix using the 1-9 scaling method based on the weighted supermatrix".

7. An ecological restoration evaluation system based on evolutionary resilience, characterized in that, The evolutionary resilience-based ecological restoration evaluation system includes: The data acquisition module is used to acquire basic data for ecological restoration assessment of the target area; the basic data for ecological restoration assessment includes ecological disaster recovery data, long-term ecological environment monitoring data, and ecological spatial pattern data. The indicator calculation module is used to calculate the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index based on the ecological disaster recovery data, the long-term ecological environment monitoring data, and the ecological spatial pattern data, respectively. The network analysis module is used to construct an evolutionary resilience evaluation model based on the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index using network analysis. The evolutionary resilience evaluation model refers to a network analysis model that uses the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index as control layer criteria, and uses the lower-level indicators of the ecological resilience index, the ecological environment evolution index, and the ecological spatial pattern index as element clusters of the network layer. The output module is used to integrate the mutual influences between element clusters based on the evolutionary resilience evaluation model and to output the evolutionary ecological resilience evaluation results.

8. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the evolutionary resilience-based ecological restoration assessment method according to any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the ecological restoration evaluation method based on evolutionary resilience as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the ecological restoration evaluation method based on evolutionary resilience as described in any one of claims 1-6.

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