Regional habitat ecological network structure and stability evaluation method thereof

Abstract

The invention discloses a regional habitat ecological network structure and a stability evaluation method thereof, and relates to a habitat ecological network structure and a stability evaluation method thereof. The technical problem that dynamic and comprehensive evaluation on a habitat ecological network structure and stability thereof is lacked in the prior art is solved. The method comprises the following steps: 1, constructing a regional habitat ecological network; 2, evaluating structural features of the regional habitat ecological network; 3, evaluating the connectivity of the regional habitat ecological network; 4, constructing various scenes for evaluating the stability of the regional habitat ecological network; 5, evaluating the resistance stability of the regional habitat ecological network based on natural interference and man-made interference scenes; and 6, based on natural recovery and artificial recovery scenes, evaluating the recovery stability of the regional habitat ecological network. According to the invention, comprehensive dynamic evaluation of the structure and the stability of the habitat ecological network is realized, a scientific basis is provided for ecological protection decision, and the adaptability of the habitat ecological network under natural and man-made interference is improved.

Description

Technical Field

[0001] The invention relates to a habitat ecological network structure and a stability evaluation method thereof. Background Art

[0002] As an effective tool for protecting biodiversity, habitat ecological network has been widely used in the management and restoration of ecosystems. Its core is to enhance the connectivity of habitats, maintain the structure and function of ecosystems, and reduce the adverse effects of landscape fragmentation on biodiversity. The structure and stability of habitat ecological network directly affect the survival ability of biological communities and the resilience of ecosystems, and play an irreplaceable role in maintaining global biodiversity.

[0003] The existing ecological network assessment methods have the following shortcomings: First, ecological network assessment is limited to network topological characteristics, often focusing on a single network topological indicator, assessing the density of ecological sources and ecological corridors and their spatial layout, and failing to conduct a comprehensive assessment of the structure and function of the ecological network. Second, ecological network assessment usually uses landscape indices (landscape area, number of patches, etc.) and ecosystem service indicators to assess structure and function, but ignores the interaction between the elements of the ecological network and their impact on connectivity, and ignores the dynamics of material and energy flow in the ecological network. Third, the stability assessment of the ecological network often uses the elasticity or resilience of the network as a single indicator, failing to systematically distinguish between resistance and resilience, thereby reducing the scientificity and accuracy of the ecological network stability assessment. Summary of the invention

[0004] In order to solve the technical problem that the prior art lacks dynamic and comprehensive evaluation of habitat ecological network structure and its stability, the present invention provides a method for evaluating regional habitat ecological network structure and its stability, which is a method that can dynamically and comprehensively evaluate regional habitat ecological network structure and its stability.

[0005] The method for evaluating the regional habitat ecological network structure and its stability of the present invention is carried out according to the following steps:

[0006] Step 1: Construct a regional habitat ecological network. The structural elements of the ecological network include ecological sources and ecological corridors.

[0007] Step 2: Evaluate the structural characteristics of the regional habitat ecological network, calculate the comprehensive centrality of habitat patches, the importance priority of ecological corridors, and the compactness of network structural elements;

[0008] Step 3: Evaluate the connectivity of the regional habitat ecological network, calculate the connectivity index of habitat patches, the patency index of ecological corridors and the connectivity of the network structure;

[0009] Step 4: Construct a regional habitat ecological network stability assessment scenario, set disturbance and restoration scenario models, construct natural and human intervention strategies, and simulate the stability status of the habitat ecological network under different scenarios;

[0010] Step 5: Based on natural disturbance scenarios and human disturbance scenarios, evaluate the resistance stability of the regional habitat ecological network and quantify the ability of the habitat ecological network to maintain its structure and function when it is destroyed;

[0011] Step 6. Based on natural recovery scenarios and artificial recovery scenarios, evaluate the recovery stability of the regional habitat ecological network and quantify the potential ability of the habitat ecological network to restore its structure and function after being destroyed.

[0012] In a single scenario, by setting the parameters of the intervention strategy, the changing process of the stability of the habitat ecological network can be evaluated from multiple angles, such as the number, proportion, and importance of habitat patches or ecological corridors. This not only takes into account the dynamic scenarios of the habitat ecological network caused by changes in external environmental conditions, but also deeply analyzes the internal ecological process of the stability change of the habitat ecological network under a single scenario. The present invention makes up for the shortcomings of existing habitat ecological network assessment technologies, provides a multi-level stability assessment framework that is refined to individual patches and corridors, and more comprehensively reveals the ecological dynamics within the network.

[0013] The present invention proposes a dynamic and comprehensive method for assessing the regional habitat ecological network structure and its stability, innovatively combining multi-scenario simulation to achieve quantitative analysis of network structure, connectivity and stability, and provide decision support for biodiversity conservation and restoration and sustainable management of ecosystems. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 is a schematic flow diagram of Example 1;

[0015] Figure 2 This is the result diagram of regional habitat ecological network construction in Example 1;

[0016] Figure 3 is a graph showing the evaluation results of the regional habitat ecological network structure characteristics of Example 1;

[0017] Figure 4 is the regional habitat ecological network connectivity result diagram of Example 1;

[0018] Figure 5 is a scenario diagram of regional habitat ecological network stability assessment in Example 1;

[0019] Figure 6 This is a graph showing the resistance stability and recovery stability results of the regional habitat ecological network in Example 1. DETAILED DESCRIPTION

[0020] The following will be combined with the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0021] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments may be combined with each other.

[0022] Specific implementation method 1: The regional habitat ecological network structure and its stability assessment method described in this implementation method are carried out according to the following steps:

[0023] Step 1: Construct a regional habitat ecological network. The structural elements of the ecological network include ecological sources and ecological corridors.

[0024] Step 2: Evaluate the structural characteristics of the regional habitat ecological network, calculate the comprehensive centrality of habitat patches, the importance priority of ecological corridors, and the compactness of network structural elements;

[0025] Step 3: Evaluate the connectivity of the regional habitat ecological network, calculate the connectivity index of habitat patches, the patency index of ecological corridors and the connectivity of the network structure;

[0026] Step 4: Construct a regional habitat ecological network stability assessment scenario, set disturbance and restoration scenario models, construct natural and human intervention strategies, and simulate the stability status of the habitat ecological network under different scenarios;

[0027] Step 5: Based on natural disturbance scenarios and human disturbance scenarios, evaluate the resistance stability of the regional habitat ecological network and quantify the ability of the habitat ecological network to maintain its structure and function when it is destroyed;

[0028] Step 6. Based on natural recovery scenarios and artificial recovery scenarios, evaluate the recovery stability of the regional habitat ecological network and quantify the potential ability of the habitat ecological network to restore its structure and function after being destroyed.

[0029] In step 1 of this implementation method, a regional habitat ecological network is constructed, and its structural elements include ecological sources and ecological corridors. The ecological source is extracted based on habitat area, habitat structure, habitat quality, habitat sensitivity and habitat protection planning; taking into account the impact of natural environmental changes and human interference, a comprehensive resistance surface for species migration is constructed, and then the minimum cost corridor method, circuit theory and moving window analysis method are coupled to construct a habitat ecological network.

[0030] In step 2 of this implementation method, the habitat ecological network is extracted into the elements of the network structure: nodes and edges, the structural characteristics of the habitat ecological network are analyzed, the comprehensive centrality of habitat patches, the important priority of ecological corridors and the compactness of network structural elements are calculated, and the structural characteristics and complexity of the habitat ecological network are clarified.

[0031] The connectivity of the habitat ecological network in step three of this implementation method directly affects the reproduction, survival of species and the sustainability of ecosystem service functions; based on the habitat ecological network structure, the connectivity index of habitat patches and the patency index of ecological corridors are calculated, and according to the structural relationship of the habitat ecological network, the overall connectivity of the habitat ecological network is measured, and then the possibility of species migration and gene exchange in the ecological network is analyzed, and the efficiency of species migration and gene exchange in the habitat ecological network is quantified from a macro perspective.

[0032] In step 4 of this implementation method, a regional habitat ecological network stability assessment scenario is constructed. In order to characterize the impact of natural changes and human factors on the habitat ecological network, a two-factor simulation experiment is used to construct four assessment scenario elements: natural disturbance, human disturbance, natural recovery, and human recovery. The stability of the regional habitat ecological network under different disturbance and recovery scenarios is quantified, and the resistance of the habitat ecological network to habitat loss and the ability of the habitat ecological network to restore its structure and function after disturbance are measured.

[0033] In step five of this implementation method, the resistance stability of the regional habitat ecological network is evaluated based on natural disturbance scenarios and human disturbance scenarios, where resistance stability refers to the ability of the habitat ecological network to maintain its normal structure and function when it is destroyed; the ability of the habitat ecological network to maintain connectivity is quantified and the resistance stability is calculated by randomly or artificially removing habitat patches in the ecological network; and the artificial removal rules can be set according to the number, proportion, and importance ranking of habitat patches or ecological corridors.

[0034] In step six of this implementation method, the recovery stability of the regional habitat ecological network is evaluated based on the natural recovery scenario and the artificial recovery scenario. The recovery stability refers to the potential recovery capacity of the ecological network itself after the habitat ecological network is destroyed naturally or artificially. By gradually restoring the habitat patches that once existed but have been lost, the recovery capacity of the largest connected subgraph of the ecological network is quantified and the recovery stability is calculated.

[0035] Specific implementation method 2: This implementation method is different from specific implementation method 1 in that: in step 1, a regional habitat ecological network is constructed: its structural elements include ecological source areas and ecological corridors, and the ecological source areas are extracted based on habitat area, habitat structure, habitat quality, habitat sensitivity and habitat protection planning; based on land use, elevation, slope, nitrogen and phosphorus pollution, distance from roads and distance from water bodies, species migration resistance is quantified; based on the spatial layout of ecological source areas, movement thresholds are set according to the migration capabilities of different species, ecological corridors are generated, ecological pinch points and ecological barrier points on the corridors are identified, and a regional habitat ecological network is constructed. Other steps and parameters are the same as those in specific implementation method 1.

[0036] Specific implementation method three: This implementation method is different from specific implementation method one in that: in step 2, the comprehensive centrality evaluation of habitat patches is as follows: by calculating the degree centrality, closeness centrality, eigenvector centrality and betweenness centrality of habitat patches, normalizing them, eliminating the influence of dimension, and calculating the comprehensive centrality by equal weight addition, so as to comprehensively evaluate the importance of habitat patches;

[0037] in,

[0038] 1) Degree centrality calculation formula: C D (v) = deg(v) (1)

[0039] In the formula, C D (v) is the degree centrality of habitat patch v, deg(v) is the number of connections of habitat patch v;

[0040] 2) Closeness centrality calculation formula:

[0041] In the formula, C C (v) is the closeness centrality of habitat patch v; d(v, t) is the shortest path length from habitat patch v to habitat patch t.

[0042] 3) Eigenvector centrality calculation formula:

[0043] Where N(v) is all the habitat patches connected to habitat patch v; λ is the maximum eigenvalue of the eigenvector;

[0044] 4) Betweenness centrality calculation formula;

[0045] In the formula, C B (v) is the betweenness centrality of habitat patch v; σ st is the number of shortest paths from habitat patch s to habitat patch t; σ st (v) is the number of shortest paths through habitat patch v;

[0046] Important priority assessment of ecological corridors in step 2:

[0047] The smaller the resistance index value of the ecological corridor, the smaller the resistance to species migration, the higher the corridor quality, and the higher the importance and protection priority of the corridor; the calculation formula is as follows:

[0048]

[0049] Where R(l) is the resistance index of ecological corridor l; Cwd is the cost-weighted distance value of the ecological corridor; Lcp is the minimum cost path length.

[0050] Evaluation of the compactness of the network structure in step 2:

[0051] The average clustering coefficient of the habitat ecological network is calculated to measure the local connectivity between the structural elements in the network and reflect the overall structural characteristics of the network. The calculation formula is as follows:

[0052]

[0053] Where: C Cluster (w) is the average clustering coefficient of the habitat ecological network w; N is the total number of habitat patches in the network; C v is the clustering coefficient of habitat patch v, which represents the ratio of the number of actually connected edges to the number of possible connected edges between the neighbors of habitat patch v.

[0054] Specific implementation method 4: The difference between this implementation method and specific implementation method 1 is that: in step 3, the connectivity index of the habitat patch is evaluated: the connectivity integral index and the connectivity probability are equally weighted to calculate the connectivity index of the habitat patch;

[0055] Among them, the calculation formula of connectivity integral index is:

[0056] Where: C IIC (v) is the connectivity score of habitat patch v; N is the total number of habitat patches in the network; P ij is the strength of connectivity between habitat patch i and habitat patch j, usually based on habitat quality or similarity; d ij is the distance between habitat patch i and habitat patch j; k is the attenuation parameter, which determines the influence of distance on the connection strength;

[0057] Connectivity probability calculation formula:

[0058] Where: C PC (v) is the connectivity probability of habitat patch v; N is the total number of habitat patches in the network; P ij is the connection probability between habitat patch i and habitat patch j;

[0059] Evaluation of the patency index of the ecological corridor in step 3: by grading the ecological obstacle points and pinch points, calculating the corridor flow and corridor substitutability, and adding the two with equal weights to calculate the patency index of the ecological corridor;

[0060] The corridor flow calculation formula is: T = 1-barrier density (9)

[0061]

[0062] In the formula, the higher the barrier density, the more obstacles there are in the corridor, the more difficult it is for species to migrate, and the lower the corridor's mobility. The closer the corridor mobility is to 1, the stronger the corridor's mobility is, and the closer it is to 0, the more serious the corridor's obstruction is.

[0063] Corridor alternative calculation formula: R = 1-pinch point density (11)

[0064]

[0065] In the formula, the higher the pinch density, the lower the corridor's substitutability, and the more easily the function is restricted by a single corridor; the substitutability value approaches 0, indicating that the corridor's functional redundancy is low; and the substitutability approaches 1, indicating that the network has high redundancy;

[0066] Ecological pinch points and obstacle points are classified as follows:

[0067] Level 1 (minimum impact area): almost no ecological pinch points or almost no migration barriers;

[0068] Level 2 (minor impact area): pinch point impact is minor, or species migration is affected by some local factors;

[0069] Level 3 (moderate impact area): The pinch point is more obvious, or the migration path is affected by obstacles but still passes;

[0070] Level 4 (severely affected areas): pinch points are obvious, or most migration paths are blocked by barriers;

[0071] Level 5 (extremely severe impact area): The pinch point is obvious and has a large impact, or the species migration path is completely blocked or even the network function is seriously affected;

[0072] Connectivity evaluation of the network structure in step 3: Calculate the α index, β index, γ index, C r Index and CC r Comprehensive connectivity index;

[0073] The calculation formula of α index is:

[0074] Where L represents the number of ecological corridors between habitat patches in the network; V represents the number of habitat patches in the network;

[0075] The beta index calculation formula is:

[0076] Where L represents the number of ecological corridors between habitat patches in the network; V represents the number of habitat patches in the network;

[0077] The formula for calculating the γ index is:

[0078] In the formula, the denominator represents the maximum number of ecological corridors possible in a fully connected network. The closer this value is to 1, the closer the connection in the network is to complete connectivity, and the lower the migration resistance of species.

[0079] C r The index calculation formula is:

[0080] In the formula, C represents the length of the ecological corridor, and L represents the number of ecological corridors.

[0081] CC r The calculation formula of comprehensive connectivity index is:

[0082] The other steps and parameters are the same as those in the first specific implementation.

[0083] Specific implementation method five: This implementation method is different from specific implementation method one in that: the habitat ecological network stability assessment scenario in step four, based on two intervention strategies, random and targeted, characterizes the impact of natural changes and human factors on the habitat ecological network, sets two intervention modes, interference and recovery, and uses two-factor simulation experiments to construct four assessment scenario elements of natural interference, human interference, natural recovery, and human recovery, as well as multiple stability assessment scenarios, to quantify the stability of the regional habitat ecological network under different interference and recovery scenarios, and to measure the resistance of the habitat ecological network to habitat loss and the ability of the habitat ecological network to restore its original structure and function after disturbance;

[0084] The intervention strategies are as follows: random intervention uses the rule of randomly removing or adding habitat patches to simulate the state of the habitat ecological network under natural conditions that is damaged or restored; targeted intervention removes or adds habitat patches according to the set rules to simulate the state of the habitat ecological network after human intervention; the set rules are: removing or adding habitat patches according to the order of importance, quantity, and proportion;

[0085] Evaluate scenario elements:

[0086] The natural disturbance scenario adopts a random intervention strategy to randomly remove habitat patches; the human disturbance scenario adopts a targeted intervention strategy to artificially set removal rules to simulate human disturbance and remove habitat patches; the natural recovery scenario adopts a random intervention strategy to randomly increase habitat patches that once existed but have been lost; the artificial recovery scenario adopts a targeted intervention strategy to artificially set increase rules to increase habitat patches that once existed but have been lost according to ecological restoration management requirements or other standards. Other steps and parameters are the same as those in the first specific implementation method.

[0087] The target intervention setting rules of this implementation method are: remove or increase habitat patches according to importance, quantity, and proportion; specifically, n patches are selected and numbered according to natural numbers. The patches can be removed or increased according to importance, quantity, or proportion. The setting rules of this implementation method can also be used to remove or increase certain specific numbered patches.

[0088] Specific implementation method 6: This implementation method is different from specific implementation method 1 in that: in step 5, the habitat ecological network resistance stability assessment: by randomly or artificially removing habitat patches in the ecological network, the ability of the habitat ecological network to maintain connectivity is quantified, and the resistance stability is calculated;

[0089] The calculation formula is:

[0090] Where: N represents the total number of habitat patches in the habitat ecological network; S0 represents the size of the largest connected subgraph in the initial habitat ecological network; S i Represents the size of the largest connected subgraph in the remaining habitat ecological network after removing the i-th habitat patch; Represents the relative size of the largest connected subgraph in the habitat ecological network after removing the i-th habitat patch; represents the average of the connectivity proportions across all habitat patch removal steps.

[0091] In the natural disturbance scenario in step 5: a random intervention strategy is used to simulate the scenario where the habitat ecological network is disturbed by nature. A random seed is set in each iteration to ensure that the results of each random selection are different. To avoid the contingency of random removal, the average resistance stability value of 100 iterations is used as the final result, reflecting the stability of the entire network when the habitat ecological network faces the random loss of habitat patches.

[0092] In the human disturbance scenario in step 5: the target intervention strategy is used to simulate the scenario where important habitat patches in the habitat ecological network are lost due to human disturbance; the habitat patches are sorted by the comprehensive centrality obtained by the normalized weighted sum of degree centrality, eigenvector centrality, betweenness centrality and proximity centrality, and the habitat patches are removed from high to low according to the comprehensive centrality score, and the resistance stability of the habitat ecological network under the human disturbance scenario is calculated. The other steps and parameters are the same as those in the specific implementation method 1.

[0093] Specific implementation method 7: This implementation method is different from specific implementation method 1 in that: in step 6, the habitat ecological network recovery stability assessment: recovery stability refers to the potential recovery capacity of the ecological network itself after the habitat ecological network is destroyed by nature or man-made damage; by gradually restoring the habitat patches that once existed but have been lost, the recovery capacity of the largest connected subgraph of the ecological network is quantified, and the recovery stability is calculated;

[0094] The calculation formula is:

[0095] Where: N represents the total number of damaged habitat patches in the habitat ecological network; S0 represents the size of the largest connected subgraph in the complete habitat ecological network; S i Represents the size of the largest connected subgraph in the habitat ecological network after the i-th habitat patch is restored; represents the sum of the maximum connected subgraph sizes in all habitat patch restoration steps;

[0096] Natural recovery scenario in step 6:

[0097] A random intervention strategy was used to simulate the natural recovery of the habitat ecological network. A random seed was set in each iteration to ensure that the results of each random selection were different. To avoid the contingency of random increase, the average recovery stability value of 100 iterations was used as the final result, reflecting the stability of the entire network when the habitat ecological network was naturally restored.

[0098] Human recovery scenario in step 6:

[0099] The target intervention strategy is used to simulate the scenario of artificially restoring important habitat patches in the habitat ecological network. The habitat patches are sorted according to the comprehensive centrality obtained by the weighted sum of the normalized degree centrality, eigenvector centrality, betweenness centrality and closeness centrality, and the habitat patches are restored from high to low according to the comprehensive centrality score, and the restoration stability of the habitat ecological network under the artificial restoration scenario is calculated. The other steps and parameters are the same as those in the first specific implementation method.

[0100] The following examples are used to verify the effects of the present invention:

[0101] Example 1 Taking the habitat ecological network structure and its stability assessment scheme of Songnen Plain as an example, the habitat ecological network structure characteristics, connectivity and stability of the region are comprehensively assessed, and its resistance and resilience to natural environmental changes and human interference are dynamically quantified. A method for assessing the regional habitat ecological network structure and its stability is as follows:

[0102] S1. Construct a regional habitat ecological network. The structural elements of the ecological network include ecological sources and ecological corridors;

[0103] S2. Evaluate the structural characteristics of the regional habitat ecological network, quantify the comprehensive centrality of habitat patches, the importance priority of ecological corridors and the compactness of network structural elements;

[0104] S3. Evaluate the connectivity of the regional habitat ecological network, calculate the connectivity index of habitat patches, the patency index of ecological corridors and the connectivity of network structure;

[0105] S4. Construct regional habitat ecological network stability assessment scenarios, set disturbance and recovery scenario models, construct natural and human intervention strategies, and simulate the stability status of the habitat ecological network under different scenarios.

[0106] S5. Based on natural disturbance scenarios and human disturbance scenarios, evaluate the resistance stability of the regional habitat ecological network and quantify its ability to maintain its structure and function when the habitat ecological network is destroyed.

[0107] S6. Evaluate the recovery stability of the regional habitat ecological network based on natural recovery scenarios and anthropogenic recovery scenarios, and quantify the potential ability of the habitat ecological network to restore its structure and function after being destroyed.

[0108] The flow chart of this embodiment is as follows Figure 1 shown.

[0109] Step S1 constructs a regional habitat ecological network, whose structural elements include ecological sources and ecological corridors. The ecological sources are extracted based on habitat area, habitat structure, habitat quality, habitat sensitivity and habitat protection planning; and the impact of natural environmental changes and human interference are comprehensively considered to construct a comprehensive resistance surface for species migration, and then the minimum cost corridor method, circuit theory and moving window analysis method are coupled to construct a habitat ecological network.

[0110] Based on vegetation coverage, temperature, precipitation, growing season drought index, land use and protected area planning data, key habitat areas are extracted as ecological sources; based on land use, elevation, slope, nitrogen and phosphorus pollution, distance from roads and distance from water bodies, species migration resistance is quantified; based on the spatial layout of ecological sources, movement thresholds are set according to the migration capabilities of different species, ecological corridors are generated, ecological pinch points and ecological barrier points on the corridors are identified, and a regional habitat ecological network is constructed.

[0111] Figure 2 This is the result of building the regional habitat ecological network in this embodiment. By evaluating the habitat characteristics in the region, we selected the ecological patches with the highest habitat quality, important and sensitive to climate change, contiguous landscape core areas, and areas where ecological protection policies have been implemented as ecological sources, which can accurately identify the most suitable habitats for species and the departure and destination areas of their migration behaviors, such as Figure 2 As shown in Figure a, there are 36 ecological source areas in the Songnen Plain, accounting for 19.02% of the total area of ​​the region. They are mainly distributed in the eastern woodlands and along the Nenjiang River. These forests, water bodies and wetlands provide important habitats for the survival and reproduction of aquatic, amphibious, mammals and birds in the Songnen Plain. Based on the environmental conditions that affect species migration (topographic changes, land use types, road injury risks and pollution emission risks), the comprehensive resistance surface for species migration in the Songnen Plain is constructed, which can scientifically quantify the difficulty of migration of different species in the region, such as Figure 2 As shown in Figure b, urban expansion (such as Changchun and Harbin) and road construction (such as the Beijing-Harbin Expressway and railway) have the most significant impact on species migration. Farmland expansion and soil pollution are also factors that hinder species migration. According to the length of the migration corridors of amphibians (0.5-5km), small and medium-sized mammals (5-20km) and birds (100-1000km) and the area of ​​regional habitats, ecological corridors are identified, and then the crowded areas (ecological pinch points) and obstruction areas (ecological barrier points) on the ecological corridors are identified. The migration characteristics of different species can be considered in a hierarchical manner, and a regional habitat ecological network that is more in line with the actual situation can be constructed, such as Figure 2 As shown in Figure c, there are 80 ecological corridors in the Songnen Plain, covering most of the Songnen Plain, which means that the organisms in this area can flow through most of the habitat patches in the area through the ecological corridors, obtain more survival resources, and form good information and gene exchanges. There are 78 ecological pinch points on the ecological corridors, which are mainly distributed at the end points of the ecological corridors, the narrow positions of large habitat patches, and the fragmented habitat patches on the ecological corridors. They are especially densely distributed around the Zhalong Nature Reserve and Chagan Lake Nature Reserve, indicating that nature reserves and good habitat patches are places where species frequently migrate. There are 96 ecological barrier points on the ecological corridors, which are mainly distributed in cultivated land, construction land, unused land and around towns between habitat patches, indicating that these areas hinder the migration of species. By considering the combined impact of natural changes and human disturbance, integrating multiple habitat characteristics to extract ecological source areas, combining the behavior patterns of multiple species to construct migration resistance surfaces, setting thresholds based on the migration capabilities of multiple species and identifying ecological corridors, ecological pinch points and ecological barrier points, we can accurately and scientifically construct a regional habitat ecological network from the perspective of habitat characteristics and species behavior, making up for the defect that existing construction technologies do not consider the interaction between natural and human factors from the perspective of habitat characteristics and species behavior.

[0112] Step S2 extracts the ecological sources and ecological corridors of the habitat ecological network as elements of the network structure: nodes and edges, analyzes the structural characteristics of the habitat ecological network, calculates the comprehensive centrality of habitat patches, the important priority of ecological corridors and the compactness of network structural elements, so as to understand the structural complexity of the habitat ecological network.

[0113] (1) Comprehensive centrality assessment of habitat patches

[0114] Taking multiple centrality indicators into comprehensive consideration, the degree centrality, closeness centrality, eigenvector centrality and betweenness centrality of habitat patches are calculated, normalized to eliminate the influence of dimension, and the comprehensive centrality is calculated by equal weighted addition to comprehensively evaluate the importance of habitat patches and more accurately identify key habitat patches that have a greater impact on network structure and function.

[0115] 1) Degree centrality: Degree centrality reflects the number of connections of each habitat patch in the habitat ecological network, that is, the number of direct connections between a habitat patch and other habitat patches. Habitat patches with high degree centrality are directly connected to many other habitat patches and are generally considered to be key habitat patches in the habitat ecological network. The calculation formula is as follows:

[0116] C D (v) = deg(v) (1)

[0117] In the formula, C D (v) is the degree centrality of habitat patch v, and deg(v) is the number of connections of habitat patch v.

[0118] 2) Closeness centrality: Closeness centrality evaluates the average distance between a habitat patch and all other habitat patches in the network, and measures the convenience of a habitat patch to reach other habitat patches. The higher the closeness centrality, the faster the material and energy flow of the habitat patch with other habitat patches in the network. The calculation formula is as follows:

[0119]

[0120] In the formula, C C (v) is the closeness centrality of habitat patch v; d(v, t) is the shortest path length from habitat patch v to habitat patch t.

[0121] 3) Eigenvector centrality: Eigenvector centrality not only considers the number of direct connections of a habitat patch, but also the importance of the habitat patches connected to it, reflecting the comprehensive influence of the habitat patches. The calculation formula is as follows:

[0122]

[0123] Where N(v) is all habitat patches connected to habitat patch v; λ is the maximum eigenvalue of the eigenvector.

[0124] 4) Betweenness centrality: Betweenness measures the bridge role of a habitat patch in the network, indicating the number of shortest paths through the habitat patch, and measures the number of times a species in a path must pass through the habitat patch to reach another habitat patch. Habitat patches with high betweenness control the flow of information or resources between many habitat patches and are "bridge" patches in the network. The calculation formula is as follows:

[0125]

[0126] In the formula, C B (v) is the betweenness centrality of habitat patch v; σ st is the number of shortest paths from habitat patch s to habitat patch t; σ st (v) is the number of shortest paths through habitat patch v.

[0127] (2) Priority assessment of ecological corridors

[0128] The ratio of the cost-weighted distance of ecological corridors to the minimum cost path length can effectively indicate their contribution to the overall network species mobility. The smaller the resistance index value of the ecological corridor, the smaller the resistance to migration, the higher the corridor quality, and the higher the importance and protection priority of the corridor. The calculation formula is as follows:

[0129]

[0130] Where R(l) is the resistance index of ecological corridor l; Cwd is the cost-weighted distance value of the ecological corridor; Lcp is the minimum cost path length.

[0131] (3) Network structure compactness evaluation

[0132] Calculate the average clustering coefficient of the habitat ecological network, measure the local connectivity between the structural elements in the network, reflect the overall structural characteristics of the network, and better interpret the overall structure of the habitat ecological network. The calculation formula is as follows:

[0133]

[0134] Where: C Cluster (w) is the average clustering coefficient of the habitat ecological network w; N is the total number of habitat patches in the network; C v is the clustering coefficient of habitat patch v, which represents the ratio of the number of actually connected edges to the number of possible connected edges between the neighbors of habitat patch v.

[0135] Figure 3This is the result of the evaluation of the regional habitat ecological network structure characteristics in this embodiment. From the perspective of node importance, the comprehensive centrality evaluation results of habitat patches show that habitat patches No. 20 and No. 30 in Songnen Plain have the highest comprehensive centrality (>0.8), which are in the most important position among all habitat patches, and the comprehensive centrality distribution of the other 34 habitat patches is relatively balanced (about 0.3). From the perspective of edge importance, the priority results of ecological corridors show that the importance priority of 80 ecological corridors in Songnen Plain fluctuates within a certain range. Except for corridor No. 71, which has a significant priority, the distribution of the importance priority of each corridor is not as extreme as the importance result of habitat patches. From the perspective of the structural relationship between nodes and edges, the results of the compactness of the habitat ecological network structure show that the habitat patches and ecological corridors in the Songnen Plain are compactly distributed, and their average clustering coefficient is close to 0.7, indicating that the habitat patches and ecological corridors in the network form relatively close groups, realizing a comprehensive assessment of the structural characteristics of the regional habitat ecological network from the perspective of structural elements and the overall structure, clarifying the differences in the importance distribution of habitat patches and ecological corridors and the structural relationship between the two, and revealing the complexity of the habitat ecological network structure.

[0136] Step S3: The connectivity of the habitat ecological network directly affects the reproduction, survival, and sustainability of species and ecological service functions. Based on the results of the habitat ecological network, the connectivity index of the habitat patches and the patency index of the ecological corridor are calculated. According to the structural relationship of the habitat ecological network, the overall connectivity of the habitat ecological network is measured, the possibility of species migration and gene exchange in the ecological network is analyzed, and the efficiency of species migration and gene exchange in the habitat ecological network is quantified from a macro perspective.

[0137] (1) Habitat patch connectivity index assessment

[0138] The connectivity integral index and connectivity probability based on graph theory can indicate the degree of connectivity of each habitat patch and its importance to landscape connectivity. By combining the effects of these two indices and adding them equally, the connectivity index of the habitat patches is obtained, which can assess the migration potential of species between habitat patches, promote gene flow, and reduce the risk of isolated populations.

[0139] 1) Connectivity integral index: The connectivity integral index comprehensively considers the connection between all habitat patches in the network. It is an important indicator for quantifying the connectivity of habitat patches in the ecological network. The value range is 0-1. The larger the value, the better the connectivity. The calculation formula is as follows:

[0140]

[0141] Where: C IIC (v) is the connectivity score of habitat patch v; N is the total number of habitat patches in the network; P ijis the strength of connectivity between habitat patch i and habitat patch j, usually based on habitat quality or similarity; d ij is the distance between habitat patch i and habitat patch j; k is the attenuation parameter, which determines the influence of distance on connection strength.

[0142] 2) Connectivity probability: Connectivity probability reflects the connection probability between any two habitat patches in the network, which can evaluate the accessibility of habitats and the possibility of biological migration. Connectivity probability takes into account a richer connection model and is not affected by neighboring habitat patches when analyzing data. It ranges from 0 to 1 and increases with the improvement of connectivity. The calculation formula is as follows:

[0143]

[0144] Where: C PC (v) is the connectivity probability of habitat patch v; N is the total number of habitat patches in the network; P ij is the connection probability between habitat patch i and habitat patch j.

[0145] (2) Evaluation of ecological corridor accessibility index

[0146] The smoothness of ecological corridors has an important impact on the structure and function of ecological networks. Smooth ecological corridors promote the migration of species between habitats, enhance gene flow, reduce the risk of isolated populations, and maintain and improve biodiversity. When the habitat ecological network is disturbed or damaged, smooth ecological corridors can accelerate the recovery process and promote the recovery of network structure and function. The smoothness of ecological corridors is evaluated from the state of biological flow (crowded state and blocked state) of ecological corridors, and the smoothness index of ecological corridors is obtained by equally weighted summing of corridor circulation and corridor substitutability.

[0147] 1) Corridor mobility: Corridor mobility reflects the efficiency and smoothness of species migration through ecological corridors. Corridors with higher mobility can effectively connect habitat patches and allow species to migrate freely, while corridors with lower mobility will be affected by obstacles and restrict species migration. Focus on corridors with higher barrier density, and reduce their impact on species migration by ecological restoration or pathway optimization. The calculation formula is as follows:

[0148] T = 1-barrier density (9)

[0149]

[0150] In the formula, the higher the barrier density, the more obstacles there are in the corridor, the more difficult it is for species to migrate, and the lower the corridor's mobility. The closer the corridor mobility is to 1, the stronger the corridor's mobility is, and the closer it is to 0, the more serious the corridor's obstruction is.

[0151] 2) Corridor substitutability: Corridor substitutability refers to whether other corridors can provide equivalent functions and maintain species migration and gene flow when a corridor fails. Analyzing corridor substitutability can maintain connectivity through alternative corridors when key corridors fail, thus reducing the vulnerability of the ecosystem.

[0152] R = 1-pinch point density (11)

[0153]

[0154] In the formula, the higher the pinch density, the lower the corridor substitutability, and the more easily the function is restricted by a single corridor; the substitutability value approaches 0, indicating that the corridor has low functional redundancy; and the substitutability approaches 1, indicating that the network has high redundancy.

[0155] 3) Classification of ecological pinch points and obstacles: In order to conduct a more detailed assessment of circulation and substitutability, the ecological pinch points and obstacles are divided into five levels according to their impact, with the levels representing different degrees of impact from low to high. The area of ​​ecological pinch points and obstacles at each level is counted, and the ratio of the area of ​​the fifth level area to the total area is calculated to quantify the impact of its density on the overall corridor connectivity.

[0156] Level 1 (minimum impact area): almost no ecological pinch points or almost no migration barriers;

[0157] Level 2 (minor impact area): pinch point impact is minor, or species migration is affected by some local factors;

[0158] Level 3 (moderate impact area): The pinch point is more obvious, or the migration path is affected by obstacles but still passes;

[0159] Level 4 (severely affected areas): pinch points are obvious, or most migration paths are blocked by barriers;

[0160] Level 5 (extremely severely affected area): The pinch points are obvious and have a large impact, or the species migration paths are completely blocked or even the network functions are seriously affected.

[0161] (3) Network structure connectivity assessment

[0162] Taking into account the number, distribution, aggregation degree and connectivity of habitat patches and ecological corridors in the ecological network structure, three indicators, namely α index, β index and γ index, were used to quantitatively describe the overall connectivity of the habitat ecological network from three aspects: the circular relationship, spatial position and connection efficiency of the habitat ecological network structure.

[0163] 1) α index: The α index is used to describe the number of independent cycles in the habitat ecological network, indicating the complexity of the internal loops of the habitat ecological network. The more loops in the habitat ecological network, the more redundant paths there are in the habitat ecological network, which is of great significance for improving the migration capacity of species. The calculation formula is:

[0164]

[0165] Where L represents the number of ecological corridors between habitat patches in the network; V represents the number of habitat patches in the network.

[0166] 2) β index: β index reflects the density of the network and is used to measure the density of connections between habitats and to determine whether some habitats are too isolated or lack connectivity. The formula is:

[0167]

[0168] Where L represents the number of ecological corridors between habitat patches in the network; V represents the number of habitat patches in the network.

[0169] 3) γ index: The γ index measures the ratio of the number of ecological corridors that actually exist in the network to the maximum number of ecological corridors that may exist in the network, and evaluates whether the connectivity of the entire ecological network is close to the ideal state. The higher the γ index, the closer the connection between habitat patches, and the smoother the migration and material flow in the ecosystem. The calculation formula is:

[0170]

[0171] In the formula, the denominator represents the maximum number of ecological corridors possible in a fully connected network. The closer this value is to 1, the closer the connection in the network is to complete connectivity, and the lower the migration resistance of species.

[0172] 4) C r Index: C r The index measures the cost ratio of constructing corridors, ranging from 0 to 1. The higher the value, the greater the cost of passing through the corridor. Ecological networks with low cost ratios are more likely to form migration corridors. The calculation formula is:

[0173]

[0174] In the formula, C represents the length of the ecological corridor, and L represents the number of ecological corridors.

[0175] 5) CC r Comprehensive Connectivity Index: CC r It is a comprehensive measure of network connectivity, combining α, β, γ and C rFour indices are used to reflect the overall performance of network connectivity. The index combines the contributions of multiple parameters and provides a comprehensive assessment of the overall connectivity and redundancy of the network. The higher the index value, the better the connectivity of the network, the stronger the feasibility of species migration, and the higher the priority of the network. The calculation formula is:

[0176]

[0177] Figure 4 The connectivity results of the regional habitat ecological network in this example are shown. From the perspective of patch connectivity, the connectivity index results of the habitat patches show that the No. 30 habitat patch in the Songnen Plain has the highest connectivity index (close to 1), the No. 20 and No. 35 habitat patches have higher connectivity indexes (about 0.6), and the connectivity indexes of other habitat patches are mostly <0.4, which achieves a quantitative assessment of the connectivity of habitat patches. At the same time, the most important No. 20 habitat patch has a higher connectivity index, while the No. 30 habitat patch with a higher comprehensive centrality has the highest connectivity index, which shows that the comprehensive centrality of the habitat patch is correlated with the connectivity index, but not completely consistent, revealing the role of habitat patches in the network structure from many aspects. From the perspective of corridor connectivity, the substitutability of ecological corridors in Songnen Plain is high, indicating that there are sufficient corridors for biological flow and it is not easily affected by a single corridor. However, the circulation of ecological corridors in Songnen Plain is low, indicating that although there are many corridors, there are more blocked areas, which leads to the limited smoothness of ecological corridors, and the quantitative evaluation of the smoothness of corridors (crowded state and blocked state) is realized. From the perspective of the structural relationship between patches and corridors, the results of the structural connectivity of habitat ecological network show that the complexity of the internal loop of the habitat network in Songnen Plain is moderate (α index = 0.67), the network structure is relatively complete (β index = 2.22), and the network connection is close to the ideal state (γ index = 0.78), but the cost of corridor construction is high (Cr index = 0.97); in general, the overall connectivity of the habitat ecological network in Songnen Plain is good, and the priority is high (CCr index = 1.2), which realizes the comprehensive evaluation of the connectivity of regional habitat ecological network from the perspective of structural elements and overall structure.

[0178] Step S4 constructs a regional habitat ecological network stability assessment scenario, based on two intervention strategies, random and target, characterizes the impact of natural changes and human factors on the habitat ecological network, sets two intervention modes, interference and recovery, and uses a two-factor simulation experiment to construct four assessment scenario elements, natural interference, human interference, natural recovery, and human recovery, as well as multiple stability assessment scenarios, to quantify the stability of the regional habitat ecological network under different interference and recovery scenarios, and to measure the resistance of the habitat ecological network in the face of habitat loss and the ability of the habitat ecological network to restore its original structure and function after experiencing disturbance. In this embodiment, four representative scenarios, natural interference, human interference, natural recovery after interference, and human recovery, are selected to evaluate the resistance stability and recovery stability of the habitat ecological network in the Songnen Plain.

[0179] (1) Intervention strategies

[0180] Random intervention uses the rule of randomly removing or adding habitat patches to simulate the state of the habitat ecological network that is damaged or restored under natural conditions. Targeted intervention removes or adds habitat patches according to certain rules (such as habitat importance ranking, quantity and proportion, etc.) to simulate the state of the habitat ecological network after human intervention.

[0181] (2) Evaluation scenario elements

[0182] The natural disturbance scenario adopts a random intervention strategy to randomly remove habitat patches; the human disturbance scenario adopts a targeted intervention strategy, artificially sets removal rules, and simulates human disturbance to remove habitat patches; the natural recovery scenario adopts a random intervention strategy to randomly increase habitat patches that once existed but have been lost; the human recovery scenario adopts a targeted intervention strategy, artificially sets increase rules, and increases habitat patches that once existed but have been lost according to ecological restoration management requirements or other standards.

[0183] Figure 5 The regional habitat ecological network stability assessment scenario diagram in this embodiment is displayed. According to the steady-state characteristics of the ecosystem and its changing laws, the habitat ecological network's ability to resist interference and self-recovery is evaluated. Considering the four elements of natural, human, interference, and recovery, a total of 14 stability assessment scenarios are generated, which comprehensively characterize the dynamic changes in the stability of the habitat ecological network under different environmental conditions. Through the four typical assessment scenarios of natural interference, human interference, natural recovery, and human recovery, the feedback of the stability of the habitat ecological network to the changes in environmental conditions can be intuitively displayed, which makes up for the shortcomings of the existing technology that only considers a single aspect of the stability of the ecological network (elasticity or resilience) or confuses the two.

[0184] Step S5 evaluates the resistance stability of the regional habitat ecological network based on natural disturbance scenarios and human disturbance scenarios. Resistance stability refers to the ability of the habitat ecological network to maintain its normal structure and function when it is destroyed. By randomly or artificially removing habitat patches in the ecological network, the ability of the habitat ecological network to maintain connectivity is quantified and the resistance stability is calculated.

[0185] Initialize the original habitat ecological network, calculate the size of its largest connected subgraph, and gradually remove habitat patches in random order or according to human intervention rules. After each habitat patch is removed, recalculate the size of the largest connected subgraph in the remaining habitat ecological network until all habitat patches are removed. In this process, the size of the largest connected subgraph in the ecological network is gradually calculated after each habitat patch is removed, and it is divided by the total number of habitat patches in the initial ecological network to obtain the proportion of the size of the connected subgraph removed at each step to the size of the initial ecological network. The sum is accumulated and the accumulated value is divided by the total number of habitat patches to obtain the resistance stability of a single simulation, which reflects the "average performance" of the connectivity of the ecological network during the entire removal process. The range of resistance stability is 0-1. The higher the value, the more likely it is that the habitat ecological network can still maintain a larger connected subgraph during the habitat removal process, showing a stronger anti-interference ability. The calculation formula is as follows:

[0186]

[0187] Where: N represents the total number of habitat patches in the habitat ecological network; S0 represents the size of the largest connected subgraph in the initial habitat ecological network; S i Represents the size of the largest connected subgraph in the remaining habitat ecological network after removing the i-th habitat patch; Represents the relative size of the largest connected subgraph in the habitat ecological network after removing the i-th habitat patch; represents the average of the connectivity proportions across all habitat patch removal steps.

[0188] (1) Natural disturbance scenarios

[0189] A random intervention strategy was used to simulate the scenario of natural disturbance of the habitat ecological network. A random seed was set in each iteration to ensure that the results of each random selection were different. To avoid the contingency of random removal, the average resistance stability value of 100 iterations was used as the final result, reflecting the stability of the entire network when the habitat ecological network faced the random loss of habitat patches.

[0190] (2) Human interference scenario

[0191] The target intervention strategy was adopted to simulate the scenario where important habitat patches in the habitat ecological network were lost due to human disturbance. The habitat patches were sorted according to the comprehensive centrality obtained by the normalized weighted sum of degree centrality, eigenvector centrality, betweenness centrality and closeness centrality, and the habitat patches were removed from high to low according to the comprehensive centrality score, and the resistance stability of the habitat ecological network under the human disturbance scenario was calculated.

[0192] Step S6 evaluates the recovery stability of the regional habitat ecological network based on the natural recovery scenario and the artificial recovery scenario. Recovery stability refers to the potential recovery capacity of the ecological network itself after the habitat ecological network is destroyed by nature or man. By gradually restoring the habitat patches that once existed but have been lost, the recovery capacity of the largest connected subgraph of the ecological network is quantified and the recovery stability is calculated.

[0193] Record the size of the largest connected subgraph after the habitat ecological network is naturally destroyed, add the habitat patches that need to be restored back to the ecological network one by one, and record the size of the largest connected subgraph after each restoration. Each time a habitat patch is restored, the migration corridor will be reconnected with its original adjacent habitat to reflect a more realistic restoration scenario. Then, the restored habitat patches and migration corridor records will be erased from the list to be restored to prevent repeated selection and restoration of the same habitat patches and migration corridors in subsequent cycles, so as to avoid meaningless restoration and result errors. Accumulate the connectivity size of all restoration steps, and normalize it with the initial total number of habitat patches and the size of the largest connected subgraph after the habitat ecological network is destroyed, and calculate the recovery stability of the habitat ecological network after disturbance. The range of recovery stability is 0-1. The higher the value, the greater the ability to maintain a larger connected subgraph during habitat restoration after the habitat ecological network is destroyed. The calculation formula is as follows:

[0194]

[0195] Where: N represents the total number of damaged habitat patches in the habitat ecological network; S0 represents the size of the largest connected subgraph in the complete habitat ecological network; S i Represents the size of the largest connected subgraph in the habitat ecological network after the i-th habitat patch is restored; Represents the sum of the maximum connected subgraph sizes in all habitat patch restoration steps.

[0196] (1) Natural recovery scenario

[0197] A random intervention strategy was used to simulate the natural recovery of the habitat ecological network. A random seed was set in each iteration to ensure that the results of each random selection were different. To avoid the contingency of random increase, the average recovery stability value of 100 iterations was used as the final result, reflecting the stability of the entire network when the habitat ecological network was naturally restored.

[0198] (2) Artificial restoration scenario

[0199] The targeted intervention strategy was used to simulate the scenario of artificially restoring important habitat patches in the habitat ecological network. The habitat patches were sorted according to the comprehensive centrality obtained by the weighted sum of normalized degree centrality, eigenvector centrality, betweenness centrality and closeness centrality, and the habitat patches were restored from high to low according to the comprehensive centrality score, and the restoration stability of the habitat ecological network under the artificial restoration scenario was calculated.

[0200] Figure 6 The results of resistance stability and recovery stability of the regional habitat ecological network are shown. Under the natural disturbance scenario, the resistance stability of the Songnen Plain habitat ecological network is 0.65, and under the human disturbance scenario, it is 0.27, indicating that high-intensity human activities have reduced the resistance stability of the habitat ecological network in the region; while under the natural recovery scenario, the recovery stability of the Songnen Plain habitat ecological network is 0.64, and under the human recovery scenario, it is 0.83, indicating that human recovery measures have significantly increased the recovery capacity of the ecosystem and improved the recovery stability of the regional habitat ecological network. These evaluation results show that under different scenarios, the results of this evaluation method are consistent with ecological principles and practical logic, and realize the dynamic and reliable evaluation of the resistance and resilience of the stability of the habitat ecological network. Through the parameter setting of the intervention strategy, this method can evaluate the changing process of the stability of the habitat ecological network from multiple angles such as the number, proportion, and importance of habitat patches or ecological corridors. This method not only considers the various scenario combinations caused by changes in external environmental conditions of the habitat ecological network, but also deeply analyzes the internal ecological process of the change of the stability of the habitat ecological network under a single scenario, making up for the shortcomings of the existing habitat ecological network evaluation technology.

Claims

1. A method for evaluating the regional habitat ecological network structure and its stability, characterized in that The regional habitat ecological network structure and its stability assessment method are carried out according to the following steps: Step 1: Construct a regional habitat ecological network. The structural elements of the ecological network include ecological sources and ecological corridors. Step 2: Evaluate the structural characteristics of the regional habitat ecological network, calculate the comprehensive centrality of habitat patches, the priority of ecological corridors, and the compactness of network structural elements; Step 3: Evaluate the connectivity of the regional habitat ecological network, calculate the connectivity index of habitat patches, the patency index of ecological corridors and the connectivity of the network structure; Step 4: Construct a regional habitat ecological network stability assessment scenario, set disturbance and restoration scenario models, construct natural and human intervention strategies, and simulate the stability status of the habitat ecological network under different scenarios; Step 5: Based on natural disturbance scenarios and human disturbance scenarios, evaluate the resistance stability of the regional habitat ecological network and quantify the ability of the habitat ecological network to maintain its structure and function when it is destroyed; Step 6. Based on natural recovery scenarios and artificial recovery scenarios, evaluate the recovery stability of the regional habitat ecological network and quantify the potential ability of the habitat ecological network to restore its structure and function after being destroyed.

2. A method for evaluating the regional habitat ecological network structure and its stability according to claim 1, characterized in that In step one, a regional habitat ecological network is constructed: its structural elements include ecological sources and ecological corridors, wherein the ecological sources are extracted based on habitat area, habitat structure, habitat quality, habitat sensitivity and habitat protection planning; based on land use, elevation, slope, nitrogen and phosphorus pollution, distance from roads and distance from water bodies, species migration resistance is quantified; based on the spatial layout of ecological sources, movement thresholds are set according to the migration capabilities of different species, ecological corridors are generated, ecological pinch points and ecological barrier points on the corridors are identified, and a regional habitat ecological network is constructed.

3. A method for evaluating the regional habitat ecological network structure and its stability according to claim 1, characterized in that Comprehensive centrality evaluation of habitat patches in step 2: Calculate the degree centrality, closeness centrality, eigenvector centrality and betweenness centrality of habitat patches, normalize them, eliminate the influence of dimension, calculate the comprehensive centrality by equal weight addition, and comprehensively evaluate the importance of habitat patches; in, 1) Degree centrality calculation formula: C D (v) = deg(v) (1) In the formula, C D (v) is the degree centrality of habitat patch v, deg(v) is the number of connections of habitat patch v; 2) Closeness centrality calculation formula: In the formula, C C (v) is the closeness centrality of habitat patch v; d(v,t) is the shortest path length from habitat patch v to habitat patch t. 3) Eigenvector centrality calculation formula: Where N(v) is all the habitat patches connected to habitat patch v; λ is the maximum eigenvalue of the eigenvector; 4) Betweenness centrality calculation formula: In the formula, C B (v) is the betweenness centrality of habitat patch v; σ st is the number of shortest paths from habitat patch s to habitat patch t; σ st (v) is the number of shortest paths through habitat patch v; Important priority assessment of ecological corridors in step 2: The smaller the resistance index value of the ecological corridor, the smaller the resistance to species migration, the higher the corridor quality, and the higher the importance and protection priority of the corridor; the calculation formula is as follows: Where R(l) is the resistance index of ecological corridor l; Cwd is the cost-weighted distance value of the ecological corridor; Lcp is the minimum cost path length. Evaluation of the compactness of the network structure in step 2: The average clustering coefficient of the habitat ecological network is calculated to measure the local connectivity between the structural elements in the network and reflect the overall structural characteristics of the network. The calculation formula is as follows: Where: C Cluster (w) is the average clustering coefficient of the habitat ecological network w; N is the total number of habitat patches in the network; C v is the clustering coefficient of habitat patch v, which represents the ratio of the number of actually connected edges to the number of possible connected edges between the neighbors of habitat patch v.

4. A method for evaluating a regional habitat ecological network structure and its stability according to claim 1, characterized in that Evaluation of the connectivity index of habitat patches in step 3: The connectivity index of habitat patches is calculated by adding the connectivity integral index and the connectivity probability with equal weights; Among them, the calculation formula of connectivity integral index is: Where: C HC (v) is the connectivity score of habitat patch v; N is the total number of habitat patches in the network; P ij is the strength of connectivity between habitat patch i and habitat patch j, usually based on habitat quality or similarity; d ij is the distance between habitat patch i and habitat patch j; k is the attenuation parameter, which determines the influence of distance on the connection strength; Connectivity probability calculation formula: Where: C PC (v) is the connectivity probability of habitat patch v; N is the total number of habitat patches in the network; P ij is the connection probability between habitat patch i and habitat patch j; Evaluation of the patency index of the ecological corridor in step 3: by grading the ecological obstacle points and pinch points, calculating the corridor flow and corridor substitutability, and adding the two with equal weights to calculate the patency index of the ecological corridor; The corridor flow calculation formula is: T = 1-barrier density (9) In the formula, the higher the barrier density, the more obstacles there are in the corridor, the more difficult it is for species to migrate, and the lower the corridor's mobility. The closer the corridor mobility is to 1, the stronger the corridor's mobility is, and the closer it is to 0, the more serious the corridor's obstruction is. Corridor alternative calculation formula: R = 1-pinch point density (11) In the formula, the higher the pinch density, the lower the corridor substitutability, and the more easily the function is restricted by a single corridor; the substitutability value approaches 0, indicating that the corridor has low functional redundancy; and the substitutability approaches 1, indicating that the network has high redundancy; Ecological pinch points and obstacle points are classified as follows: Level 1 Minimum Impact Area: Almost no ecological pinch points or almost no migration barriers; Level 2 slightly affected area: pinch point impact is small, or species migration is affected by some local factors; Level 3 moderate impact area: the pinch point is obvious, or the migration path is affected by obstacles but still passes; Level 4 Severely affected areas: pinch points are obvious, or most migration paths are blocked by barriers; Level 5: Extremely severely affected areas: The pinch points are obvious and have a large impact, or the species migration paths are completely blocked or even the network functions are seriously affected; Connectivity evaluation of the network structure in step 3: Calculate the α index, β index, γ index, C r Index and CC r Comprehensive connectivity index; The calculation formula of α index is: Where L represents the number of ecological corridors between habitat patches in the network; V represents the number of habitat patches in the network; The beta index calculation formula is: Where L represents the number of ecological corridors between habitat patches in the network; V represents the number of habitat patches in the network; The formula for calculating the γ index is: In the formula, the denominator represents the maximum number of ecological corridors possible in a fully connected network. The closer this value is to 1, the closer the connection in the network is to complete connectivity, and the lower the migration resistance of species; C r The index calculation formula is: In the formula, C represents the length of the ecological corridor, and L represents the number of ecological corridors; CC r The calculation formula of comprehensive connectivity index is:

5. A method for evaluating the regional habitat ecological network structure and its stability according to claim 1, characterized in that In step 4, the habitat ecological network stability assessment scenario is based on two intervention strategies, random and targeted, to characterize the impact of natural changes and human factors on the habitat ecological network. Two intervention modes, disturbance and recovery, are set. Two-factor simulation experiments are used to construct four assessment scenario elements, namely natural disturbance, human disturbance, natural recovery, and human recovery, as well as multiple stability assessment scenarios. The stability of the regional habitat ecological network under different disturbance and recovery scenarios is quantified, and the resistance of the habitat ecological network to habitat loss and the ability of the habitat ecological network to restore its original structure and function after disturbance are measured. The intervention strategies are as follows: random intervention uses the rule of randomly removing or adding habitat patches to simulate the state of the habitat ecological network under natural conditions that is damaged or restored; targeted intervention removes or adds habitat patches according to the set rules to simulate the state of the habitat ecological network after human intervention; the set rules are: removing or adding habitat patches according to the order of importance, quantity, and proportion; Evaluate scenario elements: The natural disturbance scenario adopts a random intervention strategy to randomly remove habitat patches; the human disturbance scenario adopts a targeted intervention strategy, artificially sets removal rules, and simulates human disturbance to remove habitat patches; the natural recovery scenario adopts a random intervention strategy to randomly increase habitat patches that once existed but have been lost; the human recovery scenario adopts a targeted intervention strategy, artificially sets increase rules, and increases habitat patches that once existed but have been lost according to ecological restoration management requirements or other standards.

6. A method for evaluating the regional habitat ecological network structure and its stability according to claim 1, characterized in that Step 5: Assessment of resistance stability of habitat ecological network: by randomly or artificially removing habitat patches in the ecological network, quantify the ability of the habitat ecological network to maintain connectivity and calculate resistance stability; The calculation formula is: Where: N represents the total number of habitat patches in the habitat ecological network; S0 represents the size of the largest connected subgraph in the initial habitat ecological network; S i Represents the size of the largest connected subgraph in the remaining habitat ecological network after removing the i-th habitat patch; Represents the relative size of the largest connected subgraph in the habitat ecological network after removing the i-th habitat patch; represents the average of the connectivity proportions across all habitat patch removal steps. In the natural disturbance scenario in step 5: a random intervention strategy is used to simulate the scenario where the habitat ecological network is disturbed by nature. A random seed is set in each iteration to ensure that the results of each random selection are different. To avoid the contingency of random removal, the average resistance stability value of 100 iterations is used as the final result, reflecting the stability of the entire network when the habitat ecological network faces the random loss of habitat patches. Human disturbance scenario in step five: Use a targeted intervention strategy to simulate the scenario in which important habitat patches in the habitat ecological network are lost due to human disturbance; sort the habitat patches according to the comprehensive centrality obtained by the weighted sum of normalized degree centrality, eigenvector centrality, betweenness centrality and closeness centrality, remove the habitat patches from high to low according to the comprehensive centrality score, and calculate the resistance stability of the habitat ecological network under the human disturbance scenario.

7. A method for evaluating the regional habitat ecological network structure and its stability according to claim 1, characterized in that Evaluation of the restoration stability of the habitat ecological network in step 6: Restoration stability refers to the potential recovery capacity of the ecological network itself after the habitat ecological network is destroyed by nature or man-made damage; by gradually restoring the habitat patches that once existed but have been lost, quantifying the recovery capacity of the largest connected subgraph of the ecological network, and calculating the restoration stability; The calculation formula is: Where: N represents the total number of damaged habitat patches in the habitat ecological network; S0 represents the size of the largest connected subgraph in the complete habitat ecological network; S i Represents the size of the largest connected subgraph in the habitat ecological network after the i-th habitat patch is restored; represents the sum of the maximum connected subgraph sizes in all habitat patch restoration steps; Natural recovery scenario in step 6: A random intervention strategy was used to simulate the natural recovery of the habitat ecological network. A random seed was set in each iteration to ensure that the results of each random selection were different. To avoid the contingency of random increase, the average recovery stability value of 100 iterations was used as the final result, reflecting the stability of the entire network when the habitat ecological network was naturally restored. Human recovery scenario in step 6: The targeted intervention strategy was used to simulate the scenario of artificially restoring important habitat patches in the habitat ecological network. The habitat patches were sorted according to the comprehensive centrality obtained by the weighted sum of normalized degree centrality, eigenvector centrality, betweenness centrality and closeness centrality, and the habitat patches were restored from high to low according to the comprehensive centrality score, and the restoration stability of the habitat ecological network under the artificial restoration scenario was calculated.

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