Solenopsis invicta prevention and control method

Abstract

The invention provides a solenopsis invicta prevention and control method. The method comprises the following steps: S1, establishing an initial environment climate variable database of a prevention and control area; s2, investigating the red imported fire ant epidemic situation before dosing in the prevention and treatment area; the MaxEnt model is used for calculating the potential suitable-to-life distribution probability of the solenopsis invicta before dosing in the prevention and control area; s3, making a first prevention and control plan, and taking the first prevention and control plan as a current prevention and control plan to carry out pesticide prevention and control; s4, analyzing a medicament intervention degree variable of the current prevention and treatment plan; s5, the MaxEnt model is used for calculating the potential suitable-to-life distribution probability of the solenopsis invicta after chemical dosing in the prevention and control area; s6, judging whether the potential suitable-for-life distribution probability of the solenopsis invicta reaches a non-suitable-for-life threshold value or not after the pesticide is added into the prevention and control area in the step S5, if not, making a new prevention and control plan as a current prevention and control plan to carry out pesticide prevention and control, and then turning to the step S4 to execute; and if so, ending the program. And a plurality of factors are combined to evaluate the red imported fire ant potential suitable growth area, and dynamic and accurate control of red imported fire ants is realized.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of red imported fire ant prevention and control, in particular to a red imported fire ant prevention and control method. BACKGROUND

[0002] Current red imported fire ant prevention and control mainly adopts traditional methods such as chemical agent nest irrigation, toxic bait killing and physical removal, highly depends on artificial patrol to determine the target area of pesticide application, and determines the frequency and dosage of pesticide application based on experience. Due to the failure to determine the spatial correlation between pesticide application records (such as frequency and dosage) and environmental variables (such as precipitation, soil humidity and temperature), it is difficult to analyze the actual inhibitory effect of the drug on the red imported fire ant, and it is impossible to quantitatively evaluate the prevention and control efficiency. Prevention and control personnel usually have difficulty in accurately identifying the target area of pesticide application, often resulting in mismatch of prevention and control resources, leading to overuse of pesticides in low-risk areas and insufficient investment in high-adaptation areas. At the same time, the evaluation of the prevention and control effect usually depends on the later field survey, which has a long cycle and slow feedback, and is not conducive to timely adjustment of prevention and control strategies. These deficiencies make the existing prevention and control system have the risks of resource waste, response delay and resistance out of control.

[0003] Therefore, it is of great significance to develop a comprehensive method that can respond to environmental changes in real time, dynamically intervene in drug intervention, and effectively evaluate its prevention and control effect, in order to improve the precision, efficiency and sustainability of red imported fire ant prevention and control. SUMMARY

[0004] The technical problem to be solved by the present application is to provide a red imported fire ant prevention and control method, which integrates pesticide prevention and control, climate environment of prevention and control area and red imported fire ant epidemic data, and uses MaxEnt model to predict potential adaptation area, quantitatively evaluates the influence of pesticide application measures on red imported fire ant, and aims to realize the precision of dynamic prevention and control of red imported fire ant.

[0005] In order to solve the above technical problems, the technical scheme adopted by the present application is:

[0006] A red imported fire ant prevention and control method, the method comprises the following steps:

[0007] S1, establishing an initial environmental climate variable database of the prevention and control area: obtaining initial climate environmental variables of the prevention and control area, and storing the standardized initial climate environmental variables in the initial environmental climate variable database;

[0008] S2, investigating the red imported fire ant epidemic before pesticide application in the prevention and control area;

[0009] Importing the red imported fire ant epidemic before pesticide application and the initial environmental climate variable database in step S1 into the MaxEnt model to calculate the potential adaptation distribution probability of the red imported fire ant before pesticide application in the prevention and control area;

[0010] S3, according to the potential suitable distribution probability of the Solenopsis invicta in the prevention and treatment area before the drug is put in the prevention and treatment area in step S2, a first prevention and treatment plan is formulated, and the first prevention and treatment plan is taken as a current prevention and treatment plan to carry out the pesticide prevention and treatment, and the prevention and treatment plan comprises a drug putting area division, a corresponding drug amount allocation of each drug putting area and a drug putting time planning;

[0011] S4, after the pesticide prevention and treatment according to the current prevention and treatment plan is carried out, a pesticide intervention degree variable of the current prevention and treatment plan is analyzed;

[0012] S5, a prevention and treatment period climate environment variable during the pesticide prevention and treatment according to the current prevention and treatment plan is collected, and after the standardization treatment, the prevention and treatment period climate environment variable is stored in a prevention and treatment period climate variable database;

[0013] The post-drug Solenopsis invicta epidemic situation after the prevention and treatment according to the current prevention and treatment plan is investigated;

[0014] The pesticide intervention degree variable of the current prevention and treatment plan, the post-drug Solenopsis invicta epidemic situation and the prevention and treatment period climate variable database are imported into a MaxEnt model, and the potential suitable distribution probability of the Solenopsis invicta in the prevention and treatment area after the drug is put in the prevention and treatment area is calculated;

[0015] S6, whether the potential suitable distribution probability of the Solenopsis invicta in the prevention and treatment area after the drug is put in the prevention and treatment area in step S5 reaches a non-suitable threshold value is judged: if the potential suitable distribution probability of the Solenopsis invicta in the prevention and treatment area after the drug is put in the prevention and treatment area does not reach the non-suitable threshold value, a new prevention and treatment plan is formulated according to the potential suitable distribution probability of the Solenopsis invicta in the prevention and treatment area after the drug is put in the prevention and treatment area, and the new prevention and treatment plan is taken as the current prevention and treatment plan to carry out the pesticide prevention and treatment, and then step S4 is executed; if the potential suitable distribution probability of the Solenopsis invicta in the prevention and treatment area after the drug is put in the prevention and treatment area reaches the non-suitable threshold value, the program is ended.

[0016] The beneficial effects of the present application are that:

[0017] 1, by fusing meteorological, environmental, human pesticide intervention and other multi-source dynamic change data, the inhibition and killing effect of the pesticide on the Solenopsis invicta population can be more accurately predicted, and the limitation of the traditional static model is overcome;

[0018] 2, the drug amount, frequency and range can be dynamically adjusted according to the regional environmental difference and the population suitability difference, the precise prevention and treatment can be realized, the drawbacks of the “one-size-fits-all” are avoided, the prevention and treatment efficiency is improved, and the pesticide waste and environmental pollution are reduced;

[0019] 3, the prevention and treatment effect can be quickly fed back, and is used for guiding the subsequent prevention and treatment strategy iteration optimization. BRIEF DESCRIPTION OF DRAWINGS

[0020] Figure 1 The flow chart of the Solenopsis invicta prevention and treatment efficiency evaluation method of the embodiment of the present application;

[0021] Figure 2 The potential suitable area distribution map of the embodiment of the present application. DETAILED DESCRIPTION

[0022] To explain the technical content of the present application, the purposes achieved and the effects, the following describes the embodiments in conjunction with the accompanying drawings.

[0023] Please refer to Figure 1 The present application provides the following embodiments:

[0024] A red imported fire ant prevention and control efficiency evaluation method, the method comprising:

[0025] S1, establishing an initial environmental climate variable database of the prevention and control area: obtaining initial climate environment variables of the prevention and control area, and storing the standardized initial climate environment variables in the initial environmental climate variable database;

[0026] S2, investigating the red imported fire ant epidemic before drug administration in the prevention and control area;

[0027] Importing the red imported fire ant epidemic before drug administration and the initial environmental climate variable database in step S1 into the MaxEnt model to calculate the potential distribution probability of the red imported fire ant in the prevention and control area before drug administration;

[0028] S3, formulating a first prevention and control plan according to the potential distribution probability of the red imported fire ant in the prevention and control area before drug administration in step S2, and carrying out drug prevention and control with the first prevention and control plan as the current prevention and control plan, wherein the prevention and control plan comprises drug administration area division, corresponding drug dosage allocation of each drug administration area, and drug administration time planning;

[0029] S4, analyzing the drug intervention degree variable of the current prevention and control plan after carrying out drug prevention and control according to the current prevention and control plan;

[0030] S5, collecting the climate environment variables during the prevention and control period according to the drug prevention and control carried out according to the current prevention and control plan, and storing the standardized climate environment variables in the prevention and control period climate variable database;

[0031] Investigating the red imported fire ant epidemic after drug administration after the prevention and control according to the current prevention and control plan;

[0032] Importing the drug intervention degree variable of the current prevention and control plan, the red imported fire ant epidemic after drug administration, and the prevention and control period climate variable database into the MaxEnt model to calculate the potential distribution probability of the red imported fire ant in the prevention and control area after drug administration;

[0033] S6, judging whether the potential distribution probability of the red imported fire ant in the prevention and control area after drug administration in step S5 reaches a non-suitable threshold: if the potential distribution probability of the red imported fire ant after drug administration does not reach the non-suitable threshold, formulating a new prevention and control plan according to the potential distribution probability of the red imported fire ant after drug administration, and carrying out drug prevention and control with the new prevention and control plan as the current prevention and control plan, and then going to step S4 for execution; if the potential distribution probability of the red imported fire ant after drug administration reaches the non-suitable threshold, the program ends.

[0034] The climate environment variables include monthly maximum temperature, monthly minimum temperature, average relative humidity, monthly total sunshine hours, maximum daily precipitation, soil moisture, slope, normalized vegetation index, monthly average sunshine hours, monthly total solar radiation, and monthly evaporation.

[0035] The climate environment variable standardization processing refers to clipping each climate environment variable to the control area, unifying the spatial resolution and coordinate system, and converting each climate environment variable data into ASCII format and storing in the climate environment variable database.

[0036] The common problems in the prevention and control of the red imported fire ant include the tendency to carry out large-area and indiscriminate pesticide application in the whole area, and the failure to differentiate according to the nest density, environmental suitability and diffusion risk. The climate environment variables and the red imported fire ant epidemic in the control area are introduced into the MaxEnt model as parameters to predict the potential suitable distribution probability of the red imported fire ant, and on this basis, the first prevention and control plan is made. The first prevention and control plan is taken as the current prevention and control plan to carry out prevention and control. After the current prevention and control plan ends, the MaxEnt model is introduced again to predict the potential suitable distribution probability of the red imported fire ant in combination with the climate environment variables during the prevention and control period, the red imported fire ant epidemic after pesticide application, and the pesticide intervention degree variable of the current prevention and control plan. The predicted potential suitable distribution probability of the red imported fire ant is used as the basis to make the next prevention and control plan, and prevention and control is carried out again. In this way, the potential suitable distribution probability of the red imported fire ant is dynamically updated, the prevention and control plan is dynamically specified, and finally the potential suitable distribution probability of the red imported fire ant in the control area reaches the non-suitable threshold. The present application not only introduces multi-source data that has an impact on the survival and prevention and control of the red imported fire ant, but also realizes relatively accurate prevention and control of the red imported fire ant, and through dynamic prevention and control, the control effect in the suitable area reaches the expected effect, thereby providing a relatively dynamic and long-term effective prevention and control idea for the prevention and control of the red imported fire ant.

[0037] Further, the step S2 of "investigating the red imported fire ant epidemic before pesticide application in the control area" has the following specific method:

[0038] S21 carries out the red imported fire ant epidemic investigation before pesticide application by combining nest foot inspection with trapping monitoring, records the longitude and latitude of the nest and the trapping occurrence point, and realizes the investigation of the red imported fire ant epidemic before pesticide application by screening, converting and spatially refining the investigation data to obtain effective red imported fire ant distribution sample points before pesticide application.

[0039] Further, the step S2 of "introducing the red imported fire ant epidemic before pesticide application and the initial environmental climate variable database in step S1 into the MaxEnt model to calculate the potential suitable distribution probability of the red imported fire ant in the control area before pesticide application" has the following specific method:

[0040] S22, screening the initial environmental and climatic variables in the initial environmental and climatic variable database in S1 based on the collinearity detection and the importance of replacement, and retaining the factors that have greater influence on the suitable distribution of Solenopsis invicta;

[0041] S23, evaluating the original suitable distribution probability of Solenopsis invicta based on the Maxent model: introducing the distribution sample points of Solenopsis invicta before the drug administration in S21 and the screened environmental and climatic variables in S22 into the MaxEnt model, calculating the potential suitable distribution probability of Solenopsis invicta in the prevention and control area before the drug administration, representing the potential distribution probability of Solenopsis invicta without the intervention of drug administration. Combining the Solenopsis invicta epidemic before the drug administration with the initial environmental and climatic variable database before the drug administration, the potential distribution probability of Solenopsis invicta at the initial stage is predicted by the Maxent model.

[0042] Further, the "calculating the potential suitable distribution probability of Solenopsis invicta" in S23 is specifically: dividing the potential suitable distribution of Solenopsis invicta according to different threshold values, and generating a potential suitable area distribution map, as shown in FIG. 6. Figure 2 The formula for grading the suitable area is:

[0043]

[0044] In the above formula (1), P is the probability value, and Zone(P) is the probability of the occurrence of Solenopsis invicta in the Zone area.

[0045] Zone(P): the probability of the occurrence of Solenopsis invicta in the Zone area;

[0046] P: probability value;

[0047] High suitable area: high suitable area;

[0048] Moderable suitable area: medium suitable area;

[0049] Low suitable area: low suitable area;

[0050] Unsuitable area: unsuitable area.

[0051] The Solenopsis invicta epidemic in the prevention and control area is divided into four grades, which facilitates the adoption of different drug dosages and drug administration times for the prevention and control of different grades of areas.

[0052] Further, the "developing the first prevention and control plan according to the potential suitable distribution probability of Solenopsis invicta before the drug administration in the prevention and control area in S2" in S3 is specifically:

[0053] S31 divides the drug administration area, specifically: according to the biological characteristics of the red imported fire ant, the maximum foraging range is set to 30 meters, and each maximum boundary point rectangle (the maximum boundary point rectangle edge line can contain all the ranges of its corresponding suitable area, and the upper, lower, left and right boundary points of the corresponding suitable area are on the maximum boundary point rectangle edge line) is cut into four equal parts with a cross line, if the small rectangle area after four equal parts has a side length greater than 30 meters, then the small rectangle area is cut into four equal parts again, until the side length of each small rectangle area after cutting is less than or equal to 30 meters, each small rectangle area with a side length less than or equal to 30 meters is determined as a drug administration unit area; during each drug administration, a pesticide is placed at the center point of the drug administration unit area, which can ensure that each drug administration can cover the entire drug administration unit area, so as to ensure that each drug administration covers the entire drug administration area, of course, during actual drug administration, manual drug administration or unmanned aerial vehicle drug administration can be used;

[0054] S32 assigns a drug dosage to each drug administration unit area, specifically: if the drug administration unit area is in a high suitable area, use 1.2 times the normal drug dosage; if the drug administration unit area is in a medium suitable area, use the normal drug dosage; if the drug administration unit area is in a low suitable area, use 0.8 times the normal drug dosage; if the drug administration unit area is in a non-suitable area, no drug needs to be used; if the drug administration unit area has a suitable area level conflict, the higher level is selected for drug dosage allocation; the drug dosage is allocated according to the suitable level, which is more in line with the actual demand, avoiding waste and excessive use of drugs;

[0055] S33 plans the drug administration time for each drug administration unit area, specifically: during the entire prevention and control process, each drug administration unit area is planned to be administered m times, one point at a time, and each drug administration point is administered a drug dosage of A i *B, where B is the normal drug dosage of each drug administration point each time, A i is the drug dosage coefficient for each i administration, i = 1, 2,..., m, and the drug efficacy interval time for each administration is n days, and the prevention and control ends after the last administration and n days. For the same drug, the drug efficacy interval time n for each administration is the same, and the number of administrations each time is also the same, but the drug dosage used by each suitable area is different, to ensure that each prevention and control plan is synchronized and ends, and to ensure the prevention and control effect.

[0056] Further, in step S4, "analyze the drug intervention degree variable of the current prevention and control plan after the current prevention and control plan is carried out", specifically:

[0057] S41 calculates the pesticide concentration used by each pixel (x, y) of each drug administration unit area during drug administration, the formula is:

[0058] C 0,i(x, y) = A i *B*c Formula (2)

[0059] In the above formula (2): C 0,i (x, y): the pesticide concentration used by the pixel (x, y) in the i-th pesticide application process;

[0060] A i : the i-th pesticide application amount coefficient, i = 1, 2,..., m; A i Take one of 0, 0.8, 1, 1.2;

[0061] B: the normal pesticide dose per application point per time;

[0062] c: the active ingredient content of the pesticide;

[0063] S42 After the control is completed, the effective concentration of the pesticide after application of each pixel (x, y) is calculated, and the calculation formula is:

[0064] C i (x, y) = C 0，i (x, y) * e -k*n*(m-i+1) Formula (3)

[0065]

[0066] Wherein:

[0067] C 0,i (x, y): the pesticide concentration used by the pixel (x, y) in the i-th pesticide application process;

[0068] C i (x, y): the effective concentration of the pesticide after the pixel (x, y) from the i-th pesticide application to the end of the i-th pesticide application;

[0069] C(x, y): the effective concentration of the pesticide after the pixel (x, y) from the 1st pesticide application to the end of the i-th pesticide application, that is, the effective concentration of the pesticide after the pixel (x, y) is applied;

[0070] k: decay rate constant;

[0071] m: the number of pesticide applications per pesticide unit area;

[0072] n: the pesticide efficacy interval time (unit: days) per application, which is the fixed number of days between two consecutive pesticide applications;

[0073] i: pesticide event, i = 1, 2,..., m, wherein i = 1 represents the first pesticide application, and i = m represents the last pesticide application;

[0074] S43 converts the data of the effective concentration of the pesticide after each pixel (x, y) is dosed into ASCII format for storage, i.e. the pesticide intervention degree factor variable. The pesticide intervention degree factor variable takes into account the use amount of the pesticide, the content of the active ingredient of the pesticide, the concentration of the pesticide, the decay rate of the pesticide, the dosing frequency and other factors, and has high accuracy.

[0075] Further, the step S5 "collecting the control period climate environment variables during the pesticide control according to the current control plan, and storing them in the control period climate variable database after standardization" has the following specific method:

[0076] S51 collects and analyzes the control period climate environment variables during the pesticide control according to the current control plan, collects daily data first, and then performs statistical analysis, including: maximum temperature, minimum temperature, average relative humidity, total sunshine hours, maximum daily precipitation, soil moisture, slope, normalized vegetation index, average sunshine hours, total solar radiation, and evaporation. Each control period climate environment variable is cropped to the control area, the spatial resolution and coordinate system are unified, and each control period climate environment variable data is converted into ASCII format and stored in the control period climate variable database. The control period climate variable database during the current control plan is used as one of the parameters for the next suitable area prediction, improving the accuracy of the suitable area prediction.

[0077] Further, the step S5 "investigating the Solenopsis invicta epidemic after dosing according to the current control plan" has the following specific method:

[0078] S52 investigates the Solenopsis invicta epidemic after the current control plan by combining nest inspection and trapping monitoring, records the latitude and longitude of the nests and trapping points, and obtains effective Solenopsis invicta distribution sample points after dosing by screening, converting and spatial refining the investigation data.

[0079] Further, the step S5 "importing the pesticide intervention degree variable of the current control plan, the Solenopsis invicta epidemic after dosing, and the control period climate variable database into the MaxEnt model, and calculating the potential suitable distribution probability of Solenopsis invicta after dosing in the control area" has the following specific method:

[0080] S53 screens the control period climate environment variables in the control period climate variable database in step S51 based on collinearity detection and permutation importance, and retains the factors that have a greater impact on the suitable distribution of Solenopsis invicta;

[0081] S54: Estimate the potential suitable distribution probability of the current control plan after the red imported fire ant: The pesticide intervention degree variable of the current control plan obtained in S4, the distribution sample points of the red imported fire ant after the pesticide is applied in S52, and the screened climate variable factors in the control period in S53 are introduced into the MaxEnt model to calculate the potential suitable distribution probability of the red imported fire ant in the control area after the pesticide is applied. The grading formula of the suitable area is shown in formula (1). The pesticide intervention degree variable of the current control plan obtained in S4, the distribution sample points of the red imported fire ant after the pesticide is applied in S52, and the screened climate variable factors in the control period in S53 are introduced into the MaxEnt model to predict the potential suitable distribution probability of the red imported fire ant after the pesticide is applied, which serves as the basis for the next pesticide control, realizes the dynamic change of the dynamic control basis data, and makes the red imported fire ant control more accurate.

[0082] Further, the step S6 "formulate a new control plan according to the potential suitable distribution probability of the red imported fire ant after the pesticide is applied" is the same as steps S31 to S33.

[0083] In summary, the red imported fire ant control method provided by the application has the following advantages:

[0084] 1. By fusing meteorological, environmental, and artificial pesticide intervention multi-source dynamic change data, the inhibition and killing effect of the pesticide on the red imported fire ant population can be more accurately predicted, and the limitations of the traditional static model are overcome.

[0085] 2. The amount, frequency, and range of the pesticide can be dynamically adjusted according to the regional environmental differences and population suitability differences, and the real epidemic situation of the red imported fire ant can be realized to achieve accurate suitable area prediction and control, avoid the drawbacks of "one size fits all", improve the control efficiency, and reduce the waste of pesticides and environmental pollution.

[0086] 3. The control effect can be quickly fed back to guide the subsequent iteration and optimization of the control strategy, and finally the suitable area control effect reaches the expected effect.

[0087] The above description is only an embodiment of the application, and does not limit the patent range of the application. Any equivalent transformation or direct or indirect application in related technical fields based on the content of the specification and drawings is also included in the patent protection range of the application.

Claims

1. A method for controlling red imported fire ants, characterized in that, The method is as follows: S1 Establish a database of initial environmental climate variables for the prevention and control area: Obtain the initial climate and environmental variables of the prevention and control area, standardize each initial climate and environmental variable, and store it in the database of initial environmental climate variables. S2 conducted an investigation into the red imported fire ant epidemic situation in the control area before the application of pesticides; Import the database of red imported fire ant epidemic before pesticide application and the initial environmental climate variables in step S1 into the MaxEnt model to calculate the potential suitable distribution probability of red imported fire ants in the control area before pesticide application. S3 Based on the potential suitable distribution probability of red imported fire ants in the control area before drug application in step S2, formulate the first control plan and use the first control plan as the current control plan to carry out drug control. The control plan includes the division of the drug application area, the allocation of drug dosage for each drug application area and the drug application time plan. S4 After implementing chemical control according to the current control plan, analyze the variable of the degree of chemical intervention in the current control plan; S5 collects climate and environmental variables during the control period of chemical control based on the current control plan, and stores them in the control period climate variable database after standardization. An investigation was conducted into the red imported fire ant outbreak following pesticide application in accordance with the current control plan. The databases of the current control plan's chemical intervention level, the red imported fire ant epidemic after application, and the climate variables during the control period were imported into the MaxEnt model to calculate the potential suitable distribution probability of red imported fire ants in the control area after application. S6 determines whether the potential suitable distribution probability of red imported fire ants in the control area after the application of pesticide in step S5 has reached the unsuitable threshold: if it has not reached the unsuitable threshold, then a new control plan is formulated based on the potential suitable distribution probability of red imported fire ants after the application of pesticide, and the new control plan is used as the current control plan for pesticide control. Then, the process proceeds to step S4. If the infertility threshold is reached, the program terminates.

2. The method for controlling red imported fire ants according to claim 1, characterized in that, The specific method for "conducting an investigation into the red imported fire ant epidemic situation in the control area before applying pesticides" in step S2 is as follows: S21 conducted a pre-treatment survey of red imported fire ants by combining nest inspection with trapping monitoring. The latitude and longitude of nests and trapping sites were recorded, and the survey data were screened, transformed, and spatially refined to obtain effective pre-treatment red imported fire ant distribution sample points.

3. The method for controlling red imported fire ants according to claim 2, characterized in that, In step S2, "importing the database of red imported fire ant epidemic before pesticide application and the initial environmental climate variables from step S1 into the MaxEnt model to calculate the potential suitable distribution probability of red imported fire ants in the control area before pesticide application" specifically means: S22 uses collinearity detection and permutation importance to screen the initial environmental climate variables in the initial environmental climate variable database in step S1, retaining factors that have a greater impact on the suitable distribution of red imported fire ants. S23. Evaluate the original suitable distribution probability of red imported fire ants based on the Maxent model: Import the red imported fire ant distribution sample points before pesticide application in step S21 and the screened environmental climate variables in step S22 into the MaxEnt model to calculate the potential suitable distribution probability of red imported fire ants in the control area before pesticide application.

4. The method for controlling red imported fire ants according to claim 3, characterized in that, Step S23, "calculating the potential suitable distribution probability of red imported fire ants," specifically involves classifying the potential suitability of red imported fire ants according to different thresholds and generating a distribution map of potential suitable areas. The formula for classifying suitable areas is: In the above formula (1): P: Probability of occurrence; High suitable area; Moderable suitable area: moderately suitable living area; Low suitable area: low-suitability area; Unsuitable area: an area unsuitable for human habitation.

5. The method for controlling red imported fire ants according to claim 1, characterized in that, In step S3, "based on the potential suitable distribution probability of red imported fire ants in the control area before pesticide application in step S2, formulate the first control plan" is specifically implemented as follows: S31 divides the application area as follows: Based on the biological characteristics of red imported fire ants, their maximum feeding range is set to 30 meters. The maximum boundary rectangle of each suitable habitat (the edge of the maximum boundary rectangle can contain the entire range of its corresponding suitable habitat, and the upper, lower, left, and right boundary points of the corresponding suitable habitat are on the edge of the maximum boundary rectangle) is divided into four equal parts by cross lines. If any of the smaller rectangular areas after the division into four equal parts has a side length greater than 30 meters, these smaller rectangular areas are divided into four equal parts again until the side length of each smaller rectangular area after the division is less than or equal to 30 meters. Each smaller rectangular area with a side length less than or equal to 30 meters is determined as the application unit area. S32 assigns a drug dosage to each drug delivery unit area as follows: if the drug delivery unit area is in a high-suitability zone, use 1.2 times the normal drug dosage; if the drug delivery unit area is in a medium-suitability zone, use the normal drug dosage; if the drug delivery unit area is in a low-suitability zone, use 0.8 times the normal drug dosage; if the drug delivery unit area is in an unsuitable zone, no drug is needed; if there is a conflict between the suitability zone levels of the drug delivery unit area, the higher level is selected for drug dosage allocation. S33 plans the application time for each application unit area, specifically: throughout the entire control process, each application unit area will be applied m times, with one application point per application point, and the dosage of pesticide applied at each application point per application point is A. i *B, where B is the normal dosage at each dosing point, and A i Let i be the dosage coefficient for each application of pesticide, i = 1, 2, ..., m. The interval between each application is n days. The control ends after the last application and n days later.

6. The method for controlling red imported fire ants according to claim 5, characterized in that, Step S4, "After implementing chemical control according to the current control plan, analyze the chemical intervention level variables of the current control plan," specifically refers to: S41 calculates the pesticide concentration used during the application process for each pixel (x, y) in each application unit area using the following formula: C 0,i (x,y)=A i Formula (2) In formula (2) above: C 0,i (x,y): The pesticide concentration used in the i-th application of the pixel (x,y) in the application unit region; A i : The dosage coefficient for each i-th dose, i = 1, 2, ..., m; A i The value can be one of 0, 0.8, 1, or 1.2; B: Normal dosage of medication at each administration point each time; c: Content of the effective ingredient in the applied drug; After the S42 control measures are completed, the effective pesticide concentration after application is calculated for each pixel (x, y). The calculation formula is as follows: C j (x, y) = C 0,i (x, y) * e -k*n*(m-i+1) Formula (3) in: C 0,i (x,y): The pesticide concentration used in the i-th application of the pixel (x,y); C i (x,y): The effective pesticide concentration of pixel (x,y) from the i-th application to the end of the i-th application; C(x,y): The effective pesticide concentration of pixel (x,y) from the first application to the end of the i-th application, i.e. the effective pesticide concentration after application of pixel (x,y); k: decay rate constant; m: Number of times each drug delivery unit area is used; n: The interval between each dose of medication (unit: days); i: Drug administration event, i = 1, 2, ..., m; S43 converts the effective pesticide concentration data after pesticide application in each pixel (x,y) into ASCII format for storage, which is the pesticide intervention degree factor variable.

7. The method for controlling red imported fire ants according to claim 1, characterized in that, The specific method for "collecting climate and environmental variables during the pesticide application period according to the current prevention and control plan, and storing them in the prevention and control period climate variable database after standardization processing" in step S5 is as follows: S51 collects and analyzes the climate environmental variables during the current control plan's chemical control period. First, daily data is collected, and then statistical analysis is performed, including: maximum temperature, minimum temperature, average relative humidity, total sunshine hours, maximum daily precipitation, soil moisture, slope, normalized difference vegetation index, average sunshine hours, total solar radiation, and evaporation. The climate environmental variables of each control period are clipped to the control area, and the spatial resolution and coordinate system are unified. The climate environmental variable data of each control period are converted into ASCII format and stored in the control period climate variable database.

8. The method for controlling red imported fire ants according to claim 7, characterized in that, Step S5, "Investigate the red imported fire ant epidemic after pesticide application according to the current control plan," specifically includes: S52 conducted a survey of red imported fire ant epidemics after the current control plan by combining ant nest inspections with trapping monitoring. The latitude and longitude of ant nests and trapping sites were recorded, and the survey data were screened, transformed, and spatially refined to obtain effective sample points of red imported fire ant distribution after pesticide application.

9. The method for controlling red imported fire ants according to claim 8, characterized in that, Step S5, "Importing the current control plan's pesticide intervention level variables, post-application red imported fire ant epidemic data, and climate variables during the control period into the MaxEnt model to calculate the potential suitable distribution probability of red imported fire ants in the control area after pesticide application," specifically involves: S53 Based on collinearity detection and permutation importance, the environmental climate variables of the prevention and control period in the climate variable database of the prevention and control period in step S51 are screened, and the factors that have a greater impact on the suitable distribution of red imported fire ants are retained. S54 assesses the potential suitable distribution probability of red imported fire ants after the current control plan based on the MaxEnt model: the chemical intervention level variable of the current control plan obtained in S4, the red imported fire ant distribution sample points after the application of pesticides in S52, and the climatic variable factors of the control period after screening in S53 are imported into the MaxEnt model to calculate the potential suitable distribution probability of red imported fire ants after the application of pesticides in the control area.

Images