Method for evaluating influence of extradesert sources on biodiversity

Abstract

The invention belongs to the technical field of biological diversity investigation, and provides a method for evaluating the influence of extradesert sources on biological diversity. The method comprises the following steps: (1) determining an exogenous substance discharge point, arranging a quadrat, and sampling; (2) detecting physicochemical properties of the sample; (3) constructing an external source influence area and a background area; and (4) comparing and evaluating the species distribution, dominant species status and inter-species individual distribution uniformity of the external source influence area and the background area to obtain the overall influence condition of the external source on the desert biodiversity. A desert region biodiversity database is established, and the current situation that desert region biodiversity data is lacked is made up; a biological diversity investigation thought is provided, and the evaluation method is simple, convenient, easy to implement and high in operability.

Description

Technical Field

[0001] The invention belongs to the technical field of biodiversity investigation and provides an evaluation method for the impact of sources outside the desert on biodiversity. Background Art

[0002] Biodiversity surveys use knowledge of ecology and statistics to systematically identify species distribution characteristics, population and community characteristics within an ecosystem based on field research. Therefore, the main task of biodiversity surveys is to determine the types, quantity, growth and other conditions of biological species in a specific environment, and to deduce structural characteristics within and between communities based on species distribution data combined with statistical calculation methods, thereby gaining a clear understanding of the biodiversity of the entire ecosystem.

[0003] At present, common statistical indicators, namely diversity assessment indicators, include: species importance value, Marfalef richness index, Simpson diversity index, Shannon-Weiner diversity index, Pielou evenness index, QB-T index, BPI biological index, etc. Different indicators can reflect the characteristics of community structure from different angles. The purpose of biodiversity survey is to provide reference for the assessment of ecological environment changes around the region through scientific investigation and analysis of species in the region.

[0004] Chinese invention patent application CN114912837A discloses a comprehensive evaluation method for lake and reservoir ecological succession and water quality biology; based on the biological information of dominant species of indicator organisms in the target lake or reservoir, water quality biology evaluation is performed using Shannon-wiener diversity index, Margalef richness index, Pielou evenness index, QB-T index, BPI biological index, etc. Chinese invention patent application CN111582753A discloses an evaluation system for the impact of river network connectivity patterns on aquatic biodiversity; based on the aquatic biological data at each river survey point, the Chao difference index is used to determine the aquatic biodiversity matrix; based on the aquatic biodiversity matrix and the river network distance matrix corresponding to each river network connectivity pattern, the response relationship of aquatic biodiversity to different river network connectivity patterns is determined to evaluate the impact of river network connectivity patterns on aquatic biodiversity.

[0005] As for terrestrial organisms, Chinese invention patent application CN11594453A discloses a green space plant diversity evaluation method and species selection method; through high-resolution remote sensing images, the plant species in the study area are counted, and the plant diversity index, richness index and uniformity index are calculated, and the corresponding distribution map is drawn for analysis. This method can reflect the real situation of urban greening in many aspects and improve the function of the urban green space system.

[0006] However, desert organisms, as an important component of global biodiversity, are rarely reported. Desert organisms have significant regional characteristics and play an important role in maintaining the stability of desert ecosystems. Unlike other terrestrial organisms, desert organisms are widely distributed, with extremely poor species and a very harsh living environment. They are drought-scarce and have a large temperature difference between day and night. Therefore, the survey of desert biodiversity is relatively backward, resulting in a lack of basic research data on many desert species, such as population size, population distribution, population dominance and community diversity. This seriously hinders the development of feasibility studies on ecological utilization in desert areas, desert ecological improvement and the formulation of pollutant control standards. At the same time, changes in external conditions can easily lead to irreversible changes in desert ecosystems, such as pollutant emissions and changes in climate and environment. Conducting biodiversity surveys around areas affected by external sources can intuitively monitor the changes in the ecosystem with the environment from the perspective of quantitative indicators, and then specifically estimate the impact of changes in certain environmental conditions on the ecosystem. Summary of the invention

[0007] In order to solve the practical problems in the prior art of lack of information on biodiversity in desert systems, poor species, and unknown impact of external sources on desert biodiversity, the present invention proposes a method for evaluating the impact of external sources on biodiversity in the desert, which provides a feasible basis for the ecological feasibility utilization of desert areas and the formulation of pollutant emission standards.

[0008] The present invention provides a method for assessing the impact of sources outside the desert on biodiversity, comprising the following steps:

[0009] (1) Determine the external source emission point, arrange sample plots around the emission point, conduct sample plot surveys, count the individual quantity indicators of plants in the sample plots, and collect soil and plant samples in the sample plots;

[0010] (2) Detect the physical and chemical indicators of soil samples in different samples, collect the species information of plant samples, and build a regional soil physical and chemical property database and a plant species information database;

[0011] (3) Based on the regional soil physical and chemical property database and plant species information database constructed in step (2), the external source impact area and the background area are divided, and the soil physical and chemical properties and plant species information of the background area are selected as the reference benchmark;

[0012] (4) Based on the external source impact area and background area divided in step (3), combined with the sample plot survey results in step (1), a comparative assessment is conducted on the species distribution, dominant species status and individual distribution uniformity of the external source impact area and the background area to obtain the overall impact of external sources on desert biodiversity.

[0013] Furthermore, in step (1), the basis for arranging the sample plots is: for the drainage area with a slope of <3 degrees, a plum blossom-shaped distribution method is adopted; for the drainage area with a slope of ≥3 degrees, a snake-shaped distribution method is adopted.

[0014] Furthermore, the individual quantity indicators include: density, coverage, frequency, total number of individuals and number of individuals in each population.

[0015] Furthermore, the coverage is calculated based on two indicators: crown width and plant height.

[0016] Furthermore, in step (1), soil samples and plant samples in the sample plot are collected by quartering; the soil sample collection method is: for the sample plot with a height difference greater than 10m from the external discharge source and no high terrain in the middle, the sampling depth is 20-30cm; the collection depth of the remaining sample plots is 10-20cm.

[0017] Furthermore, in step (2), the physical and chemical indicators of the soil sample include total organic carbon TOC, total sulfur TS, C / N ratio, pH, total salt content, water content, organic matter and total nitrogen TN.

[0018] Furthermore, in step (2), the species information of the plant sample includes species population category, total number of individuals and number of individuals in each population.

[0019] Furthermore, in step (3), the external source impact area and the background area are divided according to the following steps:

[0020] S1: Conduct sensitivity screening on the detected soil physical and chemical properties, use soil physical and chemical property indicators as detection factors to differentiate the distribution of species around external sources, and conduct factor detection and interaction detection to obtain the spatial differentiation of the number of species around external sources;

[0021] S2: Based on the detection results, determine the soil physical and chemical property indicators that are sensitive to species distribution;

[0022] S3: performing a systematic cluster analysis on the soil physical and chemical property indicators determined in step S2;

[0023] S4: Based on the cluster analysis results, the region is divided into the external source impact area and the background area.

[0024] Furthermore, in step S1, the spatial distribution of species numbers around the exogenous sources is obtained through geographic detector software.

[0025] Furthermore, in step S2, the index with an explanatory power value greater than 0.900 in the detection results is used as the soil physical and chemical property index sensitive to species distribution.

[0026] Furthermore, in step S3, the cluster analysis is performed using SPSS25 software.

[0027] Furthermore, in step S3, the parameters used in the cluster analysis include: the distance between the sample plot and the external source, and the soil physical and chemical property index sensitive to species distribution in step S2; the distance is the Euclidean distance.

[0028] Furthermore, in step (4), the species distribution is calculated by calculating the species importance values ​​in each sample plot in different areas, and comparing the importance values ​​of the area affected by external sources with the background area. When the species importance values ​​of the two areas are not ranked consistently and the difference in species importance values ​​is greater than 1, the species distribution is affected by external sources. The degree of impact needs to be determined in combination with other indicators and actual environmental conditions.

[0029] Importance value = relative density + relative frequency + relative coverage

[0030] In the formula, relative density refers to the percentage of individuals of a certain species in the sample plot to the total number of individuals of the species;

[0031] Relative frequency refers to the percentage of a certain plant's frequency to the sum of all plant's frequencies;

[0032] Relative cover refers to the percentage of a species's cover to the sum of all species' covers;

[0033] Among them, density, frequency and coverage are all obtained through the sample survey data in step (1).

[0034] The importance value index reflects the status and role of a species in a community. The larger the index, the more obvious the status. Based on the calculation results of the importance value, the dominant species and common species in the region are identified, the area affected by external sources is compared with the background area, and the impact of external sources on the distribution of species in the community is evaluated.

[0035] Furthermore, in step (4), the dominant species status is evaluated by calculating the Simpson diversity index in each sample plot in different regions; comparing the Simpson diversity index of the area affected by external sources with that of the background area; when the difference in the Simpson diversity index of the two areas is greater than 0.3, the dominant species status is affected by external sources; the degree of influence needs to be determined in combination with other indicators and actual environmental conditions.

[0036] The Simpson diversity index is calculated as follows:

[0037]

[0038] Where D is the Simpson diversity index, N is the total number of individuals, and Ni is the number of individuals of the i-th species.

[0039] Simpson indicates the status and role of dominant species in a community. The larger the index, the more obvious the status of dominant species. By comparing the reference benchmark with the calculation results of the impact area, the status change of dominant species in the community can be obtained.

[0040] Furthermore, in step (4), the individual distribution uniformity is evaluated by calculating the Shannon-Weiner diversity index in each sample plot in different areas; the Shannon-Weiner diversity index of the area affected by external sources is compared with that of the background area. When the difference in the Shannon-Weiner diversity index of the two areas is greater than 0.5, the individual distribution uniformity is affected by external sources; the degree of influence needs to be determined in combination with other indicators and actual environmental conditions.

[0041] The Shannon-Weiner diversity index is calculated as follows:

[0042]

[0043] Where H is the Shannon-Weiner diversity index, N is the total number of individuals, and Ni is the number of individuals of the i-th species.

[0044] The Shannon-Weiner diversity index indicates the uniformity of individual distribution between species. The lower the index, the lower the uniformity of individual distribution between species, and the greater the dominance of the constructive species. The area affected by external sources is compared with the background area to obtain the uniformity of individual distribution between species.

[0045] If any of the species distribution, dominant species status and individual distribution uniformity is affected by external sources, it is considered that the external sources have an impact on the desert biodiversity; that is, when the species importance values ​​of the two regions are inconsistent and the difference in species importance values ​​is greater than 1, or the difference in the Simpson diversity index of the two regions is greater than 0.3, or the difference in the Shannon-Weiner diversity index of the two regions is greater than 0.5, then the external sources have an impact on the desert biodiversity.

[0046] Compared with the prior art, the present invention has the following beneficial effects:

[0047] 1. A database of biodiversity in desert areas has been established to make up for the lack of biodiversity data in desert areas; by optimizing the sample layout method, soil sampling method and soil indicators, the assessment of biodiversity in desert areas has been made more accurate and more in line with the actual situation;

[0048] 2. Establish statistical data of background areas as a reference benchmark, and rely on this reference benchmark to provide a theoretical basis for the assessment of the impact of alien objects on biodiversity in desert areas;

[0049] 3. Starting from the three aspects of species distribution, dominant species status and uniformity of individual distribution among species, with the help of three indicators, namely species importance value, Simpson diversity index and Shannon-Weiner diversity index, the overall impact of external sources on the biodiversity of deserts with poor species (species <15) can be more comprehensively reflected, and the evaluation results are more reliable;

[0050] 4. It provides a biodiversity survey idea, including regional division method and species and community structure analysis method. The survey method is simple, easy to implement and highly operational. BRIEF DESCRIPTION OF THE DRAWINGS

[0051] Figure 1 The figure is a full flow chart of the method for assessing the impact of sources outside the desert on biodiversity of the present invention. DETAILED DESCRIPTION

[0052] The following non-limiting examples can enable those skilled in the art to more fully understand the present invention, but do not limit the present invention in any way. The following content is merely an exemplary description of the scope of the present invention, and those skilled in the art can make various changes and modifications to the present invention based on the disclosed content, which should also fall within the scope of the present invention.

[0053] Example

[0054] The following is combined with Figure 1 The process shown is based on a wastewater discharge area in Xinjiang Karamay Oilfield as the research area, with a 5-kilometer range around the external source of discharge as the research area, to conduct a biodiversity impact survey and specifically illustrate the assessment method of the present invention.

[0055] (1) Determine the external source emission point, arrange the sample plot, and take samples:

[0056] (1-1) Determine the location of the artificial wetland that will accommodate the discharged oilfield wastewater (external source);

[0057] (1-2) According to the plum blossom point distribution method, combined with the topography, a total of 21 sample plots were arranged around the artificial wetland, with a sample size of 10m×10m; a sample plot survey was conducted to count the plant species, number, plant height and crown width in the sample plot, where the crown width and plant height were measured with a tape measure; and then used to calculate the density, coverage and frequency of various plants. The results are shown in Table 1; the density, coverage and frequency were statistically analyzed based on the survey results in the sample plot;

[0058] Table 1 Density, frequency and coverage of each plant in the sample plot

[0059]

[0060] (1-3) Five soil sampling points were randomly arranged in each sample plot. Among them, soil samples of 20-30 cm on the surface were collected from low-lying areas (sample plots with a height difference of more than 10 m from the external drainage source and no obvious protrusions in the middle, and the main flow area of ​​the external source), and soil samples of 0-20 cm on the surface were collected from the remaining sample plots. After the soil samples were mixed, two samples were selected using the quartering method. The soil samples were taken once every ten samples in parallel, and plant samples from different parts of the branches and trunks with relatively mature growth were randomly cut; after the soil and plant samples were collected, they were quickly placed in self-sealing bags and placed in the car refrigerator to ensure the representativeness of the soil and plant samples.

[0061] (2) Sample physical and chemical properties testing:

[0062] All soil samples collected were tested, with test indicators including total organic carbon (TOC), total sulfur (TS), C / N ratio, pH, total salt content, moisture content, organic matter and total nitrogen (TN), to establish a database of soil and plant physical and chemical properties in desert areas;

[0063] The detection method is as follows:

[0064] The soil samples were acid-washed and then tested using an element analyzer to determine the total organic carbon TOC, total nitrogen TN, total sulfur TS and carbon-nitrogen ratio C / N in the soil;

[0065] Soil pH was determined according to the method in “Potential Method for Determination of Soil pH” (HJ962-2018);

[0066] The total salt content of soil was determined by mass method;

[0067] The soil moisture content is determined using the internationally accepted drying method;

[0068] Organic matter is measured by the incineration method. The organic matter is detected by an automatic carbon-nitrogen analyzer combined with pre-treatment equipment such as a high-temperature electric furnace. The organic carbon is oxidized into CO2 at high temperature. The organic matter content is estimated by the mass difference before and after incineration or by the amount of CO2 released.

[0069] (3) Determine the external source impact area and background area:

[0070] (3-1) The soil index test results in different samples and the distance between the sample and the external source were input into the GeoDetector software (GeoDetector_2018) to perform differentiation, factor detection and interaction detection on the spatial distribution of species numbers in the region. The detection results are shown in Table 2. The values ​​in the table are the explanatory power values ​​between the indicators. The explanatory power indicates the interaction between different indicators. The larger the number, the stronger the impact on the number of species in the sample, that is, the greater the explanatory power of species diversity when the two factors interact.

[0071] According to the results, the explanatory power of the four indicators of total salt content, total organic carbon (TOC), distance, and water content for the spatial distribution of species numbers in the region is greater than 0.900, which has a large explanatory power and is used as the parameters for the next step of cluster analysis.

[0072] Table 2 Screening results of geographic detectors

[0073] TOC TN TS C / N pH Total salt Moisture content distance TOC 0.487 TN <![CDATA[0.679 BE ]]> 0.083 TS <![CDATA[0.732 NE ]]> <![CDATA[0.307 NE ]]> 0.065 C / N <![CDATA[0.548 BE ]]> <![CDATA[0.600 NE ]]> <![CDATA[0.190 BE ]]> 0.042 pH <![CDATA[0.696 BE ]]> <![CDATA[0.405 NE ]]> <![CDATA[0.505 NE ]]> <![CDATA[0.405 NE ]]> 0.136 Total salt <![CDATA[0.786 BE ]]> <![CDATA[0.905 NE ]]> <![CDATA[0.643 NE ]]> <![CDATA[0.714 BE ]]> <![CDATA[0.714 BE ]]> 0.610 Moisture content <![CDATA[0.982 NE ]]> <![CDATA[0.310 NE ]]> <![CDATA[0.382 NE ]]> <![CDATA[0.405 NE ]]> <![CDATA[0.530 NE ]]> <![CDATA[0.714 BE ]]> 0.164 distance <![CDATA[0.643 BE ]]> <![CDATA[0.333 BE ]]> <![CDATA[0.440 NE ]]> <![CDATA[0.405 NE ]]> <![CDATA[0.315 BE ]]> <![CDATA[0.643 BE ]]> <![CDATA[0.446 BE ]]> 0.211

[0074] *BE: Bi-factor enhancement, NE: Nonlinear enhancement.

[0075] (3-2) SPSS25 software was used to perform cluster analysis on the four indicators of soil total salt content, TOC, moisture content, and available potassium in 21 sample plots, as well as the distance between the sample plot and the external source. The distance measurement was Euclidean distance. The clustering results were divided into two categories at a specific distance. The area affected by oilfield wastewater was regarded as the external source affected area; the area not affected by oilfield wastewater was regarded as the background area. The sample plot attributes of the background area belonged to the reference benchmark. The approximate value matrix results are shown in Table 3.

[0076] Table 3 Cluster analysis approximation matrix

[0077] Sample plot L9 L6 L10 L2 L1 L7 L8 L3 L4 L11 L12 L5 L9 0.000 L6 1.686 0.000 L10 3.546 2.394 0.000 L2 1.654 2.089 2.946 0.000 L1 1.922 2.993 4.050 1.132 0.000 L7 3.176 2.397 2.366 2.476 3.363 0.000 L8 4.712 3.403 3.054 3.997 4.943 2.179 0.000 L3 2.206 0.993 2.678 2.269 3.143 1.751 3.210 0.000 L4 3.923 2.358 3.182 4.023 4.966 3.454 2.790 1.882 0.000 L11 2.342 1.621 1.579 1.963 2.972 1.508 3.195 2.301 3.374 0.000 L12 3.528 2.412 0.946 2.681 3.776 1.592 2.230 2.611 3.149 1.446 0.000 L5 2.735 1.722 1.523 2.802 3.792 2.190 3.491 2.508 3.189 0.999 1.820 0.000

[0078] (4) Comparative evaluation of species distribution:

[0079] (4-1) Species distribution assessment:

[0080] Combined with the regional division and field sample survey results, it was found that the common species in the external source impact area and the background area were Haloxylon ammodendron, Nitraria tangutorum, Phragmites australis, Willow of Many Branches, Ephedra equisetum, Artemisia frigida and Lycium nigra; Capparis spinulosa and Camel thorn were endemic species in the background area; Synthetium chinense was endemic species in the external source impact area. The species importance values ​​were further calculated, and the results are shown in Table 4. The top three species in the external source impact area, namely the dominant species, were Haloxylon ammodendron, Phragmites australis and Willow of Many Branches, while the dominant species in the background area were Haloxylon ammodendron, Nitraria tangutorum and Willow of Many Branches. Combined with the species distribution and the calculation results of the importance values, it was shown that the discharge of oil production wastewater had no obvious effect on the distribution of high bud plants, but had a greater impact on ground bud plants, and the humid environment generated by the discharge of wastewater was beneficial to the growth of reeds.

[0081] Table 4 Species importance values ​​in different regions

[0082]

[0083] (4-2) Comparative evaluation of dominant species status:

[0084] The Simpson diversity index of different areas was calculated. The average Simpson diversity index of the background area, i.e. the reference benchmark, was 0.35, and the average Simpson diversity index of the area affected by external sources was 0.36. The results showed that the Simpson diversity index did not change much, that is, the status of the dominant species did not change significantly, indicating that the discharge of oil production wastewater had no obvious impact on the diversity of the surrounding communities.

[0085] (4-3) Comparative evaluation of individual distribution uniformity among species:

[0086] The Shannon-Weiner diversity index of different regions was calculated. The average Shannon-Weiner diversity index of the background region, i.e. the reference benchmark, was 0.70, and the average Shannon-Weiner diversity index of the region affected by external sources was 0.61. The overall change of the Shannon-Weiner diversity index was not obvious, but the Shannon-Weiner diversity index of three regions in the background region exceeded 1.0, and the average Shannon-Weiner diversity index of only one region in the affected region exceeded 1.0, indicating that the discharge of oil production wastewater slightly reduced the uniformity of individual distribution among species and enhanced the dominance of the species that established the community.

[0087] Comprehensive analysis of three diversity assessment indicators and physical and chemical property detection indicators shows that the discharge of oilfield wastewater has little impact on the dominant species in the region's biodiversity, but has a certain impact on plant growth, that is, species distribution and the establishment of dominant populations. The survey results can provide a scientific basis for the feasibility study and technical specifications of ecological utilization of oilfield wastewater in desert areas and the formulation of pollutant control standards.

[0088] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, rather than to limit the scope of protection of the present invention. Simple modifications or equivalent substitutions of the technical solution of the present invention by ordinary technicians in this field do not deviate from the essence and scope of the technical solution of the present invention.

Claims

1. A method for assessing the impact of non-desert sources on biodiversity, characterized in that: The following steps are involved: (1) Determine the external source emission point, set up sample plots around the emission point, conduct sample plot surveys, count the individual number indicators of plants in the sample plots, and collect soil and plant samples in the sample plots; (2) Detect the physical and chemical indicators of soil samples in different samples, and collect the species information of plant samples to build a regional soil physical and chemical property database and a plant species information database; (3) Based on the regional soil physical and chemical property database and plant species information database constructed in step (2), the external source impact area and the background area are divided, and the soil physical and chemical properties and plant species information of the background area are selected as the reference benchmark; (4) Based on the external source impact area and background area divided in step (3), combined with the sample plot survey results in step (1), a comparative assessment is conducted on the species distribution, dominant species status and individual distribution uniformity of the external source impact area and the background area to determine whether the external source has an impact on desert biodiversity.

2. The method according to claim 1, characterized in that In step (1), the basis for arranging the sample plots is: for the drainage area with a slope of less than 3 degrees, a plum blossom-shaped distribution method is adopted; for the drainage area with a slope of ≥3 degrees, a snake-shaped distribution method is adopted.

3. The method according to claim 1, characterized in that: In step (1), the individual quantity index includes: density, coverage, frequency, total number of individuals and number of individuals in each population, and the coverage is calculated by the two indicators of crown width and plant height.

4. The method according to claim 1, characterized in that In step (1), soil samples and plant samples in the sample plot are collected by quartering method; the soil sample collection method is: for the sample plot with a height difference greater than 10m from the external source and no obvious protrusion in the middle, the sampling depth is 20-30cm; the sampling depth of the remaining sample plots is 10-20cm.

5. The method according to claim 1, characterized in that In step (2), the physical and chemical indicators of the soil sample include total organic carbon TOC, total sulfur TS, C / N ratio, pH, total salt content, water content, organic matter and total nitrogen TN.

6. The method according to claim 1, characterized in that In step (2), the species information of the plant sample includes species population category, total number of individuals and number of individuals in each population.

7. The method according to claim 1, characterized in that In step (3), the external source impact area and the background area are divided as follows: S1: Conduct sensitivity screening on the detected soil physical and chemical properties, use soil physical and chemical property indicators as detection factors to differentiate the distribution of species around external sources, and conduct factor detection and interaction detection to obtain the spatial differentiation of the number of species around external sources; S2: Based on the detection results, determine the soil physical and chemical property indicators that are sensitive to species distribution; S3: performing a systematic cluster analysis on the soil physical and chemical property indicators determined in step S2; S4: Based on the cluster analysis results, the region is divided into the external source impact area and the background area.

8. The method according to claim 7, characterized in that In step S1, the spatial distribution of species numbers around exogenous sources is obtained through geographic detector software.

9. The method according to claim 7, characterized in that: In step S2, the indicators with explanatory power values ​​greater than 0.900 in the detection results are used as soil physical and chemical property indicators that are sensitive to species distribution.

10. The method according to claim 7, characterized in that In step S3, the cluster analysis is performed using SPSS25 software.

11. The method according to claim 7, characterized in that In step S3, the parameters used in the cluster analysis include: the distance between the sample plot and the external source, and the soil physical and chemical property index sensitive to species distribution in step S2; the distance is the Euclidean distance.

12. The method according to claim 1, characterized in that In step (4), the species distribution is calculated by calculating the species importance values ​​in each sample plot in different areas, and comparing the importance values ​​of the area affected by external sources with those of the background area. When the order of the species importance values ​​of the two areas is inconsistent and the difference in the species importance values ​​is greater than 1, the species distribution is affected by external sources.

13. The method according to claim 1, characterized in that In step (4), the dominant species status is determined by calculating the Simpson diversity index in each sample plot in different regions, and comparing the Simpson diversity index in the area affected by external sources with that in the background area. When the difference in the Simpson diversity index between the two regions is greater than 0.3, the dominant species status is affected by external sources.

14. The method according to claim 1, characterized in that In step (4), the individual distribution uniformity is calculated by calculating the Shannon-Weiner diversity index in each sample plot in different regions, and comparing the Shannon-Weiner diversity index of the area affected by external sources with that of the background area. When the difference in the Shannon-Weiner diversity index of the two regions is greater than 0.5, the individual distribution uniformity is affected by external sources.

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