Hillside ecology-oriented multi-level risk assessment method for alien invasive plants and application

Abstract

The invention relates to the technical field of forestry management, in particular to a mountain ecology-oriented multi-level risk assessment method for alien invasive plants and application. The invention discloses a mountain ecology-oriented multi-level risk assessment method for alien invasive plants, and the method comprises the steps: (1) constructing a five-stage index system (introduction, colonization, diffusion, harm and prevention), and carrying out the quantitative assignment of 41 indexes based on vertical gradient features; (2) creating a mountain land adaptation index for the first time, and improving small-scale evaluation precision based on ecological system characteristics; (3) dynamic group decision weight: fusing an expert AHP matrix by adopting a geometric average algorithm, and solving the problem of group decision bifurcation (CRlt; 0.1) of the substrate; (4) performing graded accurate prevention and control according to risk values (greater than or equal to 40 high, 30-40 middle and lt; 30) a matching strategy; and (5) verifying the advantages, and verifying that the consistency with the on-site harm reaches 100% through 17 invasive plants in the Lijiang Mountain. The method aims at the core pain points of mountain ecosystem terrain fragmentation, obvious vertical climate zone layering and poor adaptability of a traditional model.

Description

Technical Field

[0001] This invention relates to the field of forestry management technology, specifically a multi-level risk assessment method and application for invasive alien plants in mountainous ecosystems. Background Technology

[0002] Invasive alien plants typically possess characteristics such as a wide ecological niche, strong reproductive capacity, high resilience, and diverse dispersal pathways, posing a serious threat to the ecosystems and biodiversity of the invaded areas. In high-altitude mountain ecosystems, the unique and complex topography (such as the intermingling of mountains, valleys, and basins) and favorable hydrothermal conditions (such as abundant rainfall and diverse temperature gradients) naturally provide ideal environments for the survival and dispersal of invasive alien plants. The number of climate types more directly reflects the habitat complexity of a region, which explains why high-altitude mountains, while possessing the highest number of seed plant species and the most climate zones, also have a rich abundance of invasive plants. For example, the Laojun Mountain area in Lijiang, as a typical high-altitude mountain region, provides diverse habitats for invasive alien plants, making the area face a relatively severe threat from invasive alien plants.

[0003] With societal progress, people have gradually realized that the harm caused by biological invasions has impacted human economic development, making biological invasions a hot research topic. Our understanding of biological invasions is no longer limited to considerations of distance scales, but has begun to encompass multiple aspects such as the invasive species' living environment and the damage they cause.

[0004] Currently, most invasive alien plant risk assessment systems based on multi-indicator comprehensive evaluation methods rely on static conditions. However, biological invasion is a dynamic process, especially in complex ecosystems like plateaus and mountains, where climate, topography, and interactions between organisms are constantly changing. Traditional static assessment methods struggle to accurately reflect these dynamic changes. Plateau and mountain ecosystems, due to their complex topography, significant vertical climate differentiation, and rich biodiversity, are highly vulnerable to invasive alien plants. Existing risk assessment systems primarily target plains, wetlands, or urban ecosystems, lacking consideration for mountain-specific factors (such as altitudinal gradient diffusion, treeline invasion, and slope aspect). Therefore, a dedicated invasive alien plant risk assessment method for plateau and mountainous regions is urgently needed to address the following issues:

[0005] 1) Insufficient adaptability at small scales: Current plain models are unable to quantify the risk differences in mountain microhabitats;

[0006] 2) Lack of vertical diffusion mechanisms: The impact of altitudinal gradient on the diffusion of invasive plants was not quantified;

[0007] 3) Single prevention and control strategy: No differentiated management plan was designed for special terrains such as steep slopes and tree lines. Summary of the Invention

[0008] To address the problems existing in the prior art, this invention provides a multi-level risk assessment method and application for invasive alien plants in mountain ecosystems, aiming to solve the adaptability problem of invasive alien plant risk assessment in mountain ecosystems with complex topography and vertical climate zones.

[0009] To achieve the above objectives, the proposed solution is:

[0010] Firstly, this invention discloses a multi-level risk assessment method for invasive alien plants in mountainous ecosystems, including five primary indicators (introduction stage, colonization stage, dissemination stage, harm and impact stage, and control stage) and 14 corresponding secondary indicators. The method employs an analytic hierarchy process (AHP) combined with expert consultation to determine the weights of each level of indicator, and ensures the rationality of the weights through a consistency test (CR < 0.1). Tertiary indicators are quantitatively scored based on the characteristics of the mountainous ecosystem. Species risk values ​​are calculated and divided into three levels according to thresholds: high risk ≥ 40 points, medium risk 30–40 points, and low risk < 30 points. Differentiated control strategies are matched according to the risk level, with high-risk species being immediately removed and medium-risk species being monitored and given early warning.

[0011] Preferably, the primary indicators of the introductory stage include the introduction path and management status, wherein the introduction path is further subdivided into natural diffusion, unconscious introductory and conscious introductory, and assigned 2 points, 1 point and 3 points respectively.

[0012] Preferably, the secondary indicators of the colonization stage include life form, reproductive method, reproductive period and stress resistance. The reproductive period indicator is divided according to the length of the sexual reproduction period, and the stress resistance indicator is divided according to the species' adaptability into 2 points for less than 4 months and 2 points for 4 months or more; with strong stress resistance being 4 points and weak stress resistance being 2 points.

[0013] Preferably, the secondary indicators of the diffusion stage include diffusion mode, coverage and frequency. The diffusion mode is scored according to the type of transmission medium, including 5 points for natural medium, 5 points for transport medium and 7 points for multi-path mixing. The coverage is graded according to the proportion of the sample plot, including 2 points for less than 30%, 3 points for 30% to 60%, and 5 points for more than 60%.

[0014] Preferably, the secondary indicators of the diffusion stage include diffusion mode, coverage and frequency. The diffusion mode is scored according to the type of transmission medium, with natural medium scoring 5 points, transport medium scoring 5 points, and multi-path mixing scoring 7 points. The coverage is graded according to the proportion of the sample plot, with <30% scoring 2 points, 30% to 60% scoring 3 points, and >60% scoring 5 points.

[0015] Preferably, the weight calculation of the Analytic Hierarchy Process (AHP) employs the geometric mean ensemble algorithm of expert matrices to merge expert matrices. In multi-expert decision-making processes, disagreements among experts can lead to difficulties in constructing a comprehensive judgment matrix.

[0016] First, experts independently construct a judgment matrix A. Under the premise of satisfying the consistency test of individual matrices, the multiple matrices are integrated by geometric mean, thereby achieving convergence of group decision-making while retaining the independent judgment of experts.

[0017] The specific formula is as follows:

[0018] Let A (k) The judgment matrix of the k-th expert out of z experts, k = 1, 2... z:

[0019]

[0020] The integrated judgment matrix I is obtained by taking the geometric mean of the corresponding elements in the judgment matrix of the z experts, as shown in the following formula:

[0021] I = (i ij ) n×n

[0022] In the formula: i ij To integrate the values ​​in the i-th row and j-th column of the judgment matrix, the specific calculation method is as follows:

[0023]

[0024] In a second aspect, the present invention discloses a system for the method described in the first aspect, comprising:

[0025] The data acquisition module is used to obtain data on the species, distribution, and habitat of invasive plants through altitudinal gradient transect surveys;

[0026] The indicator management module is used to store multi-level indicator systems and scoring rules;

[0027] The weight calculation module is used to execute the AHP algorithm and perform a consistency check CR<0.1;

[0028] The risk assessment module is used to output species risk values ​​and risk level classification results;

[0029] The prevention and control decision-making module is used to generate a hierarchical priority ranking of high-risk species to be eliminated.

[0030] Preferably, the data acquisition module supports spatial visualization of transect survey data and automatically assigns scores based on coverage and frequency indicators.

[0031] Thirdly, this invention also discloses the application of the method described in the first aspect or the system described in the third aspect in the management of invasive alien plants in mountain nature reserves, the Three Parallel Rivers region, or vertical gradient ecosystems. Compared with the prior art, the beneficial effects of this invention are:

[0032] (1) Data collection: Vertical distribution data are obtained through "altitude gradient transect survey" to solve the problem of "lack of vertical diffusion mechanism";

[0033] (2) Strategy adaptation: Trigger "artificial + chemical combined eradication on steep slopes" according to risk value classification, breaking through the limitation of "single prevention and control strategy";

[0034] (3) Verification of reliability: The verification at Laojun Mountain in Lijiang achieved "100% consistency between the assessment results and the actual hazards";

[0035] (4) Mountain feature scoring: Quantitative scoring of the three-level indicators based on the characteristics of the mountain ecosystem; (2) Dynamic weight integration: Geometric average integration of multi-expert AHP matrix; (3) Hierarchical prevention and control: Differentiated prevention and control strategies are matched according to the threshold (e.g., immediate removal of high-risk species with scores ≥40). Attached Figure Description

[0036] Figure 1 A flowchart of the overall evaluation process provided for this application;

[0037] Figure 2 The application verification flowchart for the Laojun Mountain area of ​​Lijiang City provided in this application;

[0038] Figure 3 The flowchart for constructing the indicator system and calculating the weights provided for this application. Detailed Implementation

[0039] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention.

[0040] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations according to this application. As used herein, the singular form is intended to include the plural form as well, unless the context clearly indicates otherwise.

[0041] like Figure 1 and 3 As shown, in this embodiment, the weights of the criteria layer indicators and the indicator layer elements are assigned using the entropy weight method. The total score of the evaluation model is set to 100 points, and the corresponding scores of each level indicator are allocated according to the weight ratio.

[0042] A system of indicators for invasive alien plants suitable for high-altitude and mountainous regions was established. The system includes five primary indicators: entry stage, establishment stage, dissemination stage, damage and impact stage, and control stage, as well as 14 corresponding secondary indicators.

[0043] Secondary indicators include:

[0044] The secondary indicators in the primary indicator input stage include: (1) the input method and (2) the current management status.

[0045] The secondary indicators in the primary indicator colonization stage include: (3) life form, (4) reproductive method, (5) reproductive period, and (6) stress resistance.

[0046] The secondary indicators in the diffusion stage of the primary indicators include: (7) diffusion method, (8) coverage, and (9) frequency.

[0047] The secondary indicators in the primary indicator of harm and impact stage include: (10) impact on agriculture and forestry, (11) harm to human health, and (12) damage to the ecological environment.

[0048] The secondary indicators in the primary indicators for the prevention and control stage include: (13) prevention and control measures, and (14) prevention and control difficulty and cost.

[0049] First, the primary indicators are calculated according to different standard weights. The specific calculation method is as follows:

[0050] Five experts were invited to participate in a questionnaire survey using the Analytic Hierarchy Process (AHP). The collected data was then processed to obtain two importance judgment matrices for each expert regarding the indicators, and the weights were then calculated.

[0051] For the primary indicator elements: A. Introduction stage, B. Colonization stage, C. Dispersion stage, D. Hazard and impact stage, and E. Prevention stage, a matrix was created. After verifying that each matrix met the consistency requirements, the five expert judgment matrices were merged according to the formula listed above, resulting in the integrated matrix shown in Table 1 below:

[0052] Table 1A-E Judgment Integration Matrix

[0053]

[0054]

[0055] The calculation process is as follows:

[0056] (1) According to Table 1, the judgment integration matrix I is obtained.

[0057]

[0058] (2) The elements of I are multiplied row by row to obtain a new vector B.

[0059]

[0060] (3) Take the fifth root of each component of the new vector B to obtain the eigenvector M.

[0061]

[0062] (4) Normalizing the obtained vector M gives the weight vector W.

[0063]

[0064] (5) Calculate the maximum eigenvalue λmax

[0065]

[0066] (6) Consistency test of the judgment matrix CR

[0067]

[0068] Based on the above calculation process, and considering the actual situation of invasive plants in the Laojun Mountain area of ​​Lijiang, the matrix weights and consistency test results are summarized in Table 2 below:

[0069] Table 2. Calculation results of A-E weights

[0070]

[0071] Secondary indicators are assigned values ​​according to different standards. The calculation results are summarized to obtain the relative weights of each indicator. The comprehensive weight is obtained by multiplying these relative weights level by level. The comprehensive weight represents the hierarchical ranking of the lowest-level indicators relative to the overall goal. The specific results are shown in Table 3 below:

[0072] Table 3 Summary Table of Indicator Weights

[0073]

[0074] To facilitate the scoring of tertiary indicators (i.e., operational indicators), the weights of primary and secondary indicators were integerized. Based on the experience of two field surveys, the obtained species data, and the species growth and distribution data, each tertiary indicator was assigned a score according to its importance. The sum of the scores represents the weight of the next higher-level indicator. The scoring results are shown in Table 4 below.

[0075] Table 4 Risk Assessment System for Invasive Alien Plants in Plateau and Mountainous Regions

[0076]

[0077]

[0078]

[0079] Example 2

[0080] like Figure 2 As shown, taking the Laojun Mountain area of ​​Lijiang as an example, the aim is to achieve a comprehensive dynamic and static analysis of the risks of invasive alien plants in plateau and mountainous areas;

[0081] Application of the risk assessment index system for invasive alien plants in the ecological system of plateau and mountainous areas.

[0082] The multi-level risk assessment method and system for mountain ecosystems were applied to the risk assessment of invasive alien plants in the Laojun Mountain area of ​​Lijiang. The specific assessment process included:

[0083] (1) Acquisition of data on invasive plants in high-altitude and mountainous areas;

[0084] (2) Establish a risk assessment system for invasive alien plants and assign corresponding weights and values ​​to indicators at each level;

[0085] (3) Establish risk level standards for invasive plants from both inside and outside the plateau and mountainous regions;

[0086] (4) Scoring of invasive plants from outside the plateau mountainous area according to the risk assessment system and calculating the results to determine the risk level.

[0087] In this embodiment,

[0088] The multi-level risk assessment method for invasive alien plants is adapted to the characteristics of plateau and mountain ecosystems. It can accurately define the risk level sequence of invasive alien plants in such ecosystems, providing a scientific basis for the formulation of differentiated prevention and control strategies and the optimal allocation of governance resources in the process of ecosystem management, thereby enhancing the effectiveness of biodiversity conservation.

[0089] A method for classifying the risk levels of invasive alien plants in mountain ecosystems.

[0090] Specifically, it includes (1) low risk; (2) medium risk; and (3) high risk.

[0091] Each category corresponds to a different range of risk quantification values, and is equipped with a dedicated invasive plant risk early warning mechanism and targeted prevention and control management plan.

[0092] The formula for calculating the scoring result is:

[0093] S = A + B + C + D + E

[0094] Where: S is the total risk value; A, B, C, D, and E correspond to the specific scores of the secondary indicators of the five primary indicators: introduction stage, colonization stage, diffusion stage, hazard and impact stage, and prevention and control stage.

[0095] Example 3

[0096] This embodiment uses samples taken from Laojun Mountain in Lijiang City, a typical plateau mountainous area, to conduct a comprehensive analysis of the impact and degree of harm caused by invasive plants from outside the region to the ecosystem.

[0097] 1. Data acquisition of invasive alien plants in the Laojun Mountain area of ​​Lijiang City.

[0098] The transect method was primarily used, combined with literature review, to understand the species composition and current status of invasive plants in the region. Considering that the main vegetation type in the survey area is shrubland, the field survey used transects as the primary method and sampling points as a supplement to roughly count the number of species on each transect in the study area. The species, quantity, growth, and distribution of invasive plants on the transects were identified and recorded.

[0099] After multiple field surveys and collections, the plants collected from the transects were prepared into specimens and then processed and identified in the laboratory. This process was repeated multiple times along different transects to collect invasive plants and eliminate the possibility of accidental interference. Through a field survey using 38 transects, 17 invasive plant species were ultimately identified.

[0100] 2. Establish a risk assessment index system for invasive alien plants in the Laojun Mountain area of ​​Lijiang City.

[0101] Considering the complex topography, diverse climate, and fragile ecosystem of the Laojun Mountain area in Lijiang City, this invention optimizes the weight allocation of indicators at each level of the risk assessment index system for invasive alien plants. Through scientific quantitative analysis, the score distribution for the primary indicators is determined as follows: introduction stage 9 points, establishment stage 16 points, dissemination stage 37 points, harm and impact stage 24 points, and control stage 14 points. Secondary indicators under each primary indicator are simultaneously assigned differentiated weights and allocated corresponding scores according to rigorous scoring standards. The specific content and score settings of the risk assessment index system for invasive alien plants in the Laojun Mountain area of ​​Lijiang City are detailed in Table 5 below.

[0102] Table 5 Risk Assessment System for Invasive Alien Plants in Laojun Mountain Area, Lijiang City

[0103]

[0104]

[0105] 3. Establish risk level standards for invasive alien plants in the Laojun Mountain area of ​​Lijiang City.

[0106] Based on the above assessment results and the information gathered from the survey of 17 invasive alien species, the risk of invasive plants in the Laojun Mountain area of ​​Lijiang City can be roughly divided into three levels: those scoring above 40 points are considered unsuitable for introduction or require immediate treatment; those scoring between 30 and 40 points represent a certain risk, and the choice of control measures can be further determined based on other relevant information. If species in this score range need to be introduced, the area, quantity, and frequency of introduction should be strictly limited, and appropriate preventative measures must be taken after introduction to prevent escape and spread; those scoring below 30 points are considered low-risk alien species, which can be selectively treated or left untreated depending on existing conditions. See Table 6 below:

[0107] Table 6 Risk Levels and Treatment Strategies for Invasive Alien Plants

[0108]

[0109] 4. Determine the risk level of invasive alien plants in the Laojun Mountain area of ​​Lijiang.

[0110] Table 7. Risk Assessment Results of Invasive Alien Plants in Laojun Mountain Area, Lijiang City

[0111]

[0112] Based on statistical analysis, a list of invasive plants in the Laojun Mountain area of ​​Lijiang City was compiled. The current status of invasive species in the area was considered, and risk level standards were established. Risk levels were assigned based on the comprehensive assessment scores. The assessment system has a total score of 100 points, with different weights assigned to each level of indicators. Field survey results were incorporated into the assessment system to derive specific risk values. A risk value ≥ 40 indicates a high risk level; 30 ≤ risk value < 40 indicates a medium risk level; and a risk value < 30 indicates a low risk level.

[0113] The survey of the plateau and mountainous areas of Laojun Mountain in Lijiang City and the establishment of an invasive plant assessment system revealed that there are 5 high-risk plant species, 4 medium-risk plant species, accounting for 53% of the invasive plants surveyed, and 8 low-risk plant species, accounting for 47%. The high proportion of medium- and high-risk invasive plants indicates that the overall risk level of invasive plants in the Laojun Mountain area of ​​Lijiang City is relatively high.

[0114] Leguminosae and Asteraceae are among the most prevalent families of invasive alien plants. It is recommended to implement special management for alien plants in their respective families, with a focus on controlling medium- and high-risk plants such as white clover, purple-stemmed eupatorium, and white-flowered beggar-ticks.

[0115] The working principle of this invention is

[0116] 1. Indicator System:

[0117] (1) During the diffusion stage, a highly sensitive indicator of "multi-path mixed transport" is set to accurately capture the complex propagation path in mountainous areas;

[0118] (2) "Strong resistance" during the colonization stage, with indicators quantifying the species' adaptability to vertical climate;

[0119] (3) The prevention and control stage is "difficult to eradicate", and the indicators are related to the cost of steep slope operations;

[0120] 2. Weighting algorithm: Geometric average integration resolves expert disagreements on mountain indicators (e.g., diffusion mode weight accounts for 17.11%); 3. Innovative hierarchical prevention and control: Threshold-triggered strategy breaks through the traditional "one-size-fits-all" model, as shown in the table.

[0121]

[0122] (1) The diffusion stage has the highest weight (36.79%), accurately quantifying the dynamics of mountain spread; (2) 12 tertiary indicators achieve tiered scoring (e.g., 3 points for a reproductive period of <4 months vs. 1 point for a reproductive period of >4 months); verification sample full coverage: the risk values ​​of 17 invasive plants all match the actual harm.

[0123] Finally, it should be noted that the above implementation examples are only used to illustrate the technical solution and practical application effects of the present invention, and are not intended to limit the scope of the present invention. Although the present invention has been described in detail through specific embodiments, those skilled in the art should understand that the technical solution can still be adjusted and optimized, or some technical features can be equivalently replaced, without departing from the core concept of the present invention. All such reasonable modifications and adjustments fall within the protection scope of the technical solution of the present invention.

Claims

1. A multi-level risk assessment method for invasive alien plants in mountain ecosystems, characterized by: The system comprises five primary indicators: introduction stage, colonization stage, dissemination stage, damage and impact stage, and prevention and control stage, as well as 14 corresponding secondary indicators. The weights of each level of indicators were determined by combining the analytic hierarchy process with expert consultation, and the rationality of the weights was ensured by passing a consistency test (CR < 0.1). The three-level indicators are quantitatively scored based on the characteristics of the mountain ecosystem. Calculate species risk values ​​and classify them into three levels according to thresholds: high risk ≥ 40 points, medium risk 30-40 points, and low risk < 30 points. Differentiated prevention and control strategies are matched according to risk level, with high-risk species being eliminated immediately and medium-risk species being monitored and given early warning.

2. The method according to claim 1, characterized in that, The primary indicators for the introduction stage include the introduction path and management status. The introduction path is further subdivided into natural diffusion, unconscious introduction, and conscious introduction, and is assigned 2 points, 1 point, and 3 points respectively.

3. The method according to claim 1, characterized in that, The secondary indicators of the colonization stage include life form, reproductive method, reproductive period and stress resistance. The reproductive period indicator is divided according to the length of the sexual reproduction period. The stress resistance indicator is divided according to the species' adaptability into 2 points for less than 4 months, 2 points for 4 months or more, and 4 points for strong and 2 points for weak.

4. The method according to claim 1, characterized in that, The secondary indicators of the diffusion stage include diffusion mode, coverage, and frequency. The diffusion mode is scored according to the type of transmission medium, including 5 points for natural media, 5 points for transport media, and 7 points for multi-path mixing. The coverage is graded according to the proportion of the sample plot, with 2 points for less than 30%, 3 points for 30% to 60%, and 5 points for more than 60%.

5. The method according to claim 1, characterized in that, The secondary indicators of the diffusion stage include diffusion mode, coverage, and frequency. Diffusion mode is scored according to the type of transmission medium, with natural media scoring 5 points, transport media scoring 5 points, and multi-path mixing scoring 7 points. Coverage is graded according to the proportion of sample plots, with <30% scoring 2 points, 30% to 60% scoring 3 points, and >60% scoring 5 points.

6. The method according to claim 1, characterized in that, The weight calculation of the analytic hierarchy process (AHP) employs the geometric mean ensemble algorithm of expert matrices, merging expert matrices. However, in multi-expert decision-making processes, disagreements among experts make constructing a comprehensive judgment matrix difficult. First, experts independently construct a judgment matrix A. Under the premise of satisfying the consistency test of individual matrices, a geometric mean ensemble is performed on the multiple matrices, thereby achieving convergence of group decision-making while preserving the independent judgments of the experts. The specific formula is as follows: Let A (k) The judgment matrix of the k-th expert out of z experts, k = 1, 2... z: The integrated judgment matrix I is obtained by taking the geometric mean of the corresponding elements in the judgment matrix of the z experts, as shown in the following formula: I=(i ij ) n×n In the formula: i ij To integrate the values ​​in the i-th row and j-th column of the judgment matrix, the specific calculation method is as follows:

7. A system for implementing the method according to any one of claims 1 to 6, characterized in that, include: The data acquisition module is used to obtain data on the species, distribution, and habitat of invasive plants through altitudinal gradient transect surveys; The indicator management module is used to store multi-level indicator systems and scoring rules; The weight calculation module is used to execute the AHP algorithm and perform a consistency check CR<0.1; The risk assessment module is used to output species risk values ​​and risk level classification results; The prevention and control decision-making module is used to generate a hierarchical priority ranking of high-risk species to be eliminated.

8. The system according to claim 7, characterized in that, The data acquisition module supports spatial visualization of transect survey data and automatically assigns scores based on coverage and frequency indicators.

9. The application of the method as described in any one of claims 1 to 6 or the system as described in claims 7 to 8 in the management of invasive alien plants in mountain nature reserves, the Three Parallel Rivers region, or vertical gradient ecosystems.

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