Method for investigating and monitoring esculent swift population

Abstract

The invention provides a esculent swift population investigation and monitoring method, and relates to the field of poultry population investigation and monitoring. The method comprises the following steps: acquiring a potential distribution region pre-confirmed for a esculent swift population, and determining the altitude of the potential distribution region; if it is determined that the altitude is smaller than a preset esculent swift activity altitude threshold value, determining the potential distribution region as a candidate distribution region; performing region division on the candidate distribution region, and determining at least one target investigation unit; performing multiple times of chirp attraction in each target investigation unit, and collecting attraction monitoring data; and determining the number and distribution of esculent swift populations and the environmental characteristics of the distribution area according to the enrollment monitoring data. According to the technical scheme, the esculent swiftlet population investigation efficiency can be effectively improved, the monitoring accuracy is enhanced, dynamic monitoring and long-term evaluation are supported, and more effective technical support is provided for scientific research and ecological protection of esculent swiftlets.

Description

Technical Field

[0001] The present application relates to the technical field of poultry population investigation and monitoring, and in particular to a method for investigating and monitoring swiftlet populations. Background Art

[0002] The swiftlet belongs to the genus swiftlet of the family Apodidae. It is a small bird. The salivary glands of some species swell during the breeding season and can secrete a large amount of sticky saliva, which condenses into solid in the air. It is the main material for the swiftlet to build its nest. The nest it builds is called a bird's nest, which has high nutritional value and economic value. The Java swiftlet, which can produce bird's nests, was officially listed as a national second-level key protected wild animal by my country in 2021.

[0003] Under natural conditions, swiftlets live in rock caves. They usually go out to hunt insects during the day and return to their nests to rest in the evening. Since the four toes of swiftlets are all facing forward, they are small climbing birds and cannot grasp branches or stand on the ground, so they will not stay on branches or the ground. Therefore, swiftlets are always in flight after going out to live in caves, and their flying speed is very fast. In addition, due to their small size, it is usually difficult to observe swiftlets directly at close range. Conventional bird survey and monitoring methods are difficult to effectively implement the survey and monitoring of swiftlet populations and habitats. At the same time, swiftlets have singing behavior. The singing of swiftlets of different species is specific, and swiftlets have a phenomenon of gathering the singing of individuals of the same species. Therefore, the use of singing attraction technology to investigate and monitor swiftlet populations is an effective method.

[0004] It should be noted that the information disclosed in the above background technology section is only used to enhance the understanding of the background of the present application, and therefore may include information that does not constitute the prior art known to ordinary technicians in the field. Summary of the invention

[0005] The purpose of the embodiments of the present application is to provide a method for investigating and monitoring the swiftlet population, which can guide the behavior of the swiftlet by attracting it with singing sounds, thereby facilitating the investigation and monitoring of the swiftlet population.

[0006] Other features and advantages of the present application will become apparent from the following detailed description, or may be learned in part by the practice of the present application.

[0007] According to a first aspect of an embodiment of the present application, a method for investigating and monitoring a swiftlet population is provided, comprising:

[0008] Obtain the potential distribution areas confirmed in advance for the swiftlet population and determine the altitude of the potential distribution areas;

[0009] If it is determined that the altitude is lower than the preset swiftlet activity altitude threshold, the potential distribution area is determined as a candidate distribution area;

[0010] Divide the candidate distribution area into regions to determine at least one target survey unit;

[0011] Perform multiple calls to attract swiftlets in each target survey unit, and collect attracting monitoring data, wherein the attracting monitoring data at least includes quantity information, environmental information, and directional information of swiftlets flying away;

[0012] The number, distribution pattern and environmental characteristics of the swiftlet population are determined based on the attraction monitoring data.

[0013] In some example embodiments of the present application, based on the aforementioned scheme, multiple calls to attract are performed in each of the target survey units to collect attraction monitoring data, including: constructing a target swiftlet attraction call based on a pre-corrected swiftlet test call; playing the target swiftlet attraction call multiple times in a loop with a preset first single playback duration, so as to collect the swiftlet attraction situation within the attraction range and obtain attraction monitoring data.

[0014] In some example embodiments of the present application, based on the aforementioned scheme, the target swiftlet attracting sound is constructed according to the pre-corrected swiftlet test sound, comprising: obtaining the pre-corrected swiftlet test sound, the swiftlet test sound including the sound of swiftlet group activities, the sound of chasing and courting, the sound of nesting, the sound of predation and the sound of feeding young birds; according to the sound of the swiftlet group activities, the sound of chasing and courting, the sound of nesting, the sound of predation and the sound of feeding young birds, a plurality of sound combinations are constructed in the form of simultaneously playing or looping the plurality of sound combinations to obtain the target swiftlet attracting sound.

[0015] In some example embodiments of the present application, based on the aforementioned scheme, the target swiftlet attracting sound is constructed according to the pre-corrected swiftlet test sound, comprising: obtaining the pre-corrected swiftlet test sound, the swiftlet test sound including the sound of swiftlet group activities, the sound of chasing and courting, the sound of nesting, the sound of predation and the sound of feeding young birds; according to any one of the sounds of the swiftlet group activities, the sound of chasing and courting, the sound of nesting, the sound of predation and the sound of feeding young birds, and constructing the target swiftlet attracting sound in the form of looping and playing any one of the selected sounds.

[0016] In some example embodiments of the present application, based on the aforementioned scheme, the attraction monitoring data also includes behavioral data information. After the attraction is completed, the multiple sound attraction is performed in each of the target investigation units, and also includes: playing a preset swiftlet test sound once with a preset second single playback duration, and recording the single behavioral data information; wherein the swiftlet test sound includes one of the pre-collected sounds of swiftlet group activities, sounds during chasing and courting, sounds during nesting, sounds during predation, or sounds when feeding young birds.

[0017] In some example embodiments of the present application, based on the aforementioned solution, the behavioral data information includes at least the action reaction, flight position and call response of the swiftlet.

[0018] In some example embodiments of the present application, based on the aforementioned scheme, the method of determining the number, distribution patterns and environmental characteristics of the distribution area of ​​the swiftlet population according to the attraction monitoring data also includes: analyzing the action response and the flight position of the swiftlet according to the preset swiftlet test call to determine the influence of the swiftlet test call on the behavior of the swiftlet and the influence on the attraction effect; and correcting the swiftlet test call in combination with the influence on the behavior of the swiftlet and the influence on the attraction effect to obtain a pre-corrected swiftlet test call.

[0019] In some example embodiments of the present application, based on the aforementioned scheme, determining the number, distribution pattern and environmental characteristics of the distribution area of ​​the swiftlet population according to the attraction monitoring data also includes: correcting the swiftlet test sound according to the call response and the corresponding swiftlet test sound to obtain a pre-corrected swiftlet test sound.

[0020] In some example embodiments of the present application, based on the aforementioned scheme, the environmental information includes time information, weather information, temperature information, wind information, humidity information, location information, vegetation information, topography information, etc.

[0021] In some example embodiments of the present application, based on the aforementioned scheme, performing multiple sound-calling to attract the target survey units further includes: performing multiple sound-calling to attract the target swiftlets during their hunting and homing time period.

[0022] The technical solution provided by the embodiments of the present application may have the following beneficial effects:

[0023] The swiftlet population survey and monitoring method in the example embodiment of the present application can effectively narrow the geographical scope of the survey by identifying and analyzing the potential distribution areas of the swiftlet, reduce the waste of resources and low survey efficiency caused by the excessively large monitoring scope in traditional survey and monitoring methods, and at the same time improve the initial positioning capability of the swiftlet population distribution, providing more concentrated and scientific basic data for swiftlet population research.

[0024] By further dividing the candidate distribution area into multiple target survey units, we can more accurately calibrate the specific areas where swiftlets may be active. By statistically comparing and analyzing the survey data obtained from different units, we can avoid the randomness and uncertainty in traditional methods, significantly improve our ability to grasp the activity patterns of swiftlet groups, and improve monitoring accuracy, thereby ensuring the efficiency of swiftlet surveys and monitoring.

[0025] By conducting multiple sound-calling attraction operations in each target survey unit, the number, distribution patterns and environmental characteristics of the swiftlet population can be determined. This will enable us to understand the population status and distribution patterns of the swiftlet in a more systematic and comprehensive manner, effectively improve the comprehensiveness and reliability of attraction monitoring data collection, support the dynamic assessment and long-term monitoring of the swiftlet population, and further ensure the accuracy and effectiveness of monitoring the number, distribution patterns and environmental characteristics of the swiftlet population.

[0026] It should be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The drawings herein are incorporated into the specification and constitute a part of the specification, illustrate embodiments consistent with the present application, and together with the specification are used to explain the principles of the present application. Obviously, the drawings described below are only some embodiments of the present application, and for ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0028] Figure 1 The flowchart of the swiftlet population survey and monitoring method according to some embodiments of the present application is schematically shown.

[0029] Figure 2 The following schematically shows a flow chart of collecting attraction monitoring data according to some embodiments of the present application. DETAILED DESCRIPTION

[0030] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The implementations described in the following exemplary embodiments do not represent all implementations consistent with this specification. Instead, they are merely examples of devices and methods consistent with some aspects of this specification as detailed in the appended claims.

[0031] Furthermore, the drawings are only schematic illustrations and are not necessarily drawn to scale. The block diagrams shown in the drawings are only functional entities and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in software form, or in one or more hardware modules or integrated circuits, or in different networks and / or processor devices and / or microcontroller devices.

[0032] In this exemplary embodiment, a method for investigating and monitoring swiftlet populations is first provided, which can be applied to terminal devices, such as mobile phones, computers and other electronic devices. The terminal device includes a sound acquisition unit, such as a microphone device, and an image acquisition unit, such as a camera. Figure 1 The following is a schematic diagram of the process of the swiftlet population survey and monitoring method according to some embodiments of the present application. Figure 1 As shown, the swiftlet population survey and monitoring method may include the following steps:

[0033] Step S110, obtaining a pre-confirmed potential distribution area for the swiftlet population, and determining the altitude of the potential distribution area;

[0034] Step S120, if it is determined that the altitude is less than the preset swiftlet activity altitude threshold, then determining the potential distribution area as a candidate distribution area;

[0035] Step S130, dividing the candidate distribution area into regions to determine at least one target survey unit;

[0036] Step S140, performing multiple calls to attract swiftlets in each of the target survey units, and collecting attracting monitoring data, wherein the attracting monitoring data at least includes quantity information, environmental information, and directional information of the swiftlets flying away;

[0037] Step S150, determining the number, distribution pattern and environmental characteristics of the swiftlet population according to the attraction monitoring data.

[0038] According to the swiftlet population survey and monitoring method in this example embodiment, by identifying and analyzing the potential distribution areas of the swiftlet, the geographical scope of the survey can be effectively narrowed, reducing the waste of resources and low survey efficiency caused by the excessive monitoring scope in traditional survey and monitoring methods, while improving the initial positioning capability of the swiftlet population distribution, providing more concentrated and scientific basic data for swiftlet population research.

[0039] By further dividing the potential distribution area into multiple target survey units, we can more accurately calibrate the specific areas where swiftlets may be active. By statistically comparing and analyzing the survey data obtained from different survey units, we can avoid the randomness and uncertainty in traditional methods, significantly improve our ability to grasp the activity patterns of swiftlet groups, and improve monitoring accuracy, thereby ensuring the efficiency of swiftlet surveys and monitoring.

[0040] By conducting multiple sound-calling attraction operations in each target survey unit, the number, distribution patterns and environmental characteristics of the swiftlet population can be determined. This will enable us to understand the behavioral characteristics and distribution patterns of swiftlets in a more systematic and comprehensive manner, effectively improve the comprehensiveness and reliability of attraction monitoring data collection, support the dynamic assessment and long-term monitoring of swiftlet populations, and further ensure the accuracy and effectiveness of monitoring the number, distribution patterns and environmental characteristics of swiftlet populations.

[0041] Next, the swiftlet population survey and monitoring method in this exemplary embodiment will be further described.

[0042] In step S110, a potential distribution area pre-confirmed for the swiftlet population is obtained, and the altitude of the potential distribution area is determined.

[0043] In an exemplary embodiment of the present application, the potential distribution area refers to a geographical area where swiftlets may be active or inhabited, which is preliminarily screened out based on the known habitat characteristics and biological laws of swiftlets.

[0044] The potential distribution area can be confirmed by referring to relevant literature, historical distribution records and ecological research results, and analyzing in combination with the ecological and environmental characteristics of the region. For example, according to relevant literature, geographical areas such as forests, wetlands or farmlands in tropical and subtropical coastal areas can be determined as potential distribution areas for swiftlet populations. Of course, this is only a schematic example. Specifically, the potential distribution area can be determined based on the local activities or habitat characteristics of the swiftlet population under study, and this embodiment is not limited to this.

[0045] The confirmation of potential distribution areas can also be done through preliminary surveys, such as driving in a specific time period, such as the time period when swiftlets are out foraging, or at sunrise, and conducting visual observation or investigation along a certain route, and recording the areas where swiftlets are found, marking the areas as potential distribution areas, directly recording the potential distribution areas where swiftlets exist, and then supplementing the potential distribution areas with literature records.

[0046] In an exemplary embodiment of the present application, the number of target survey units is at least 5, such as 6, 10 or 15, and can be adaptively adjusted based on actual circumstances.

[0047] The determination of the altitude may be based on a statistical analysis of the terrain height difference in the region. For example, a Geographic Information System (GIS) may be used to process the altitude data of the potential distribution area, and the altitude value within the potential distribution area may be calculated through point sampling and interpolation, or a boundary line of altitude values, i.e., a terrain boundary line, may be formed. This embodiment does not impose any special limitation on the method for determining the altitude.

[0048] In other words, the above altitude is an absolute altitude value, not the concept of average altitude. Using this as a distinction can reduce the interference caused by terrain factors, exclude areas with too high altitudes, and reduce the workload of manual surveys.

[0049] In some optional implementations, the potential distribution areas can also be screened using remote sensing data, satellite images or high-resolution geographic images taken by drones for auxiliary identification. In this embodiment, a rule-based approach can also be used. For example, ecological conditions and altitude thresholds can be set, or a machine learning-based model can be combined to predict multiple environmental factors to screen out potential distribution areas suitable for swiftlets.

[0050] In step S120, if it is determined that the altitude is lower than the preset swiftlet activity altitude threshold, the potential distribution area is determined as a candidate distribution area.

[0051] In an example embodiment of the present application, the swiftlet activity altitude threshold refers to the height range set based on the activity range of the swiftlet in ecological research. For example, the swiftlet activity altitude threshold can be set to 200 meters, and the potential distribution area with an altitude of less than 200 meters is determined as the candidate distribution area. Of course, the swiftlet activity altitude threshold can be adjusted according to research needs. For example, for certain swiftlet populations that move and live in high-altitude areas, the swiftlet activity altitude threshold can be set to 300 meters; similarly, for certain swiftlet populations that move and live in low-altitude areas, the swiftlet activity altitude threshold can be set to 150 meters, and this example embodiment is not limited to this.

[0052] In an exemplary embodiment of the present application, taking the entire island of Hainan as an example, the activity altitude threshold of the swiftlet is set within 200 meters. Hainan Island is low and flat on all sides and high in the middle. There are no or very few swiftlet populations in the central mountainous area with an altitude of more than 200 meters. Therefore, setting the activity altitude threshold of the swiftlet within 200 meters can improve the efficiency of investigation and monitoring, while reducing the difficulty of manual operations.

[0053] In an optional embodiment of the present application, taking the coastal areas of Southeast Asia as an example, the activity altitude threshold of swiftlets can be set within 1500 meters.

[0054] In an optional embodiment of the present application, the activity altitude threshold of the swiftlet may be set within 2,800 meters.

[0055] Candidate distribution areas refer to areas that are more consistent with the activities and habitat habits of swiftlets after further screening. The confirmation of candidate distribution areas can greatly narrow the scope of the survey, improve monitoring efficiency, and reduce waste of resources.

[0056] In addition, the selection of candidate distribution areas can also be adjusted according to the season. For example, in spring, summer and autumn, the candidate distribution areas can be distributed more evenly, while in autumn and winter, the potential distribution areas close to the equator are investigated. Seasons are often accompanied by changes in temperature and food abundance, and the distribution of swiftlet populations will change to a certain extent with the change of seasons.

[0057] By identifying and analyzing the potential and candidate distribution areas of the swiftlet, the geographical scope of the survey can be effectively narrowed, reducing the waste of resources and low survey efficiency caused by the large monitoring scope in traditional survey and monitoring methods. At the same time, the initial positioning capability of the swiftlet population distribution can be improved, providing more concentrated and scientific basic data for swiftlet population research.

[0058] In step S130, the candidate distribution area is divided into regions to determine at least one target survey unit.

[0059] In an example embodiment of the present application, regional division refers to dividing the candidate distribution area into several target survey units, so as to more accurately monitor the environmental information and swiftlet activities in the area, and facilitate data analysis of the weights of different parameters. For example, the method of survey unit division can be to set survey points or fixed monitoring points, can be based on survey grids per kilometer, can be based on survey grids per unit longitude and latitude, or can be combined with geographical features such as rivers, mountains, etc. to divide natural areas. In the division process, regional connectivity, geographical diversity and monitoring feasibility can be considered to improve the accuracy and reliability of the target survey units obtained by division.

[0060] In an exemplary embodiment of the present application, the candidate distribution area is divided into regular grids, and the size of each grid is set to an 8 square kilometer grid, or a 0°10′0″ longitude and latitude grid. For example, on Hainan Island, such a setting can divide more than 100 sample plots. On the one hand, such a setting is convenient for investigation and the investigation workload will not be too large. On the other hand, the sample size of the investigation is sufficient and the data statistics are accurate.

[0061] In some optional implementations, each survey unit can be prioritized using an artificial intelligence-based target survey unit analysis model, and the most likely survey unit can be selected based on a priority threshold. Of course, the most likely survey unit can also be selected based on expert experience. This example embodiment does not place any special limitation on the method of determining the survey unit.

[0062] In step S140, multiple calls are performed to attract swiftlets in each target survey unit to collect attraction monitoring data, which at least includes quantity information, environmental information, and directional information of the swiftlets flying away.

[0063] In an example embodiment of the present application, sound attraction refers to a technical means of attracting swiftlets by playing specific swiftlet sounds. Multiple sound attraction refers to repeatedly playing specific swiftlet sounds at multiple time points or environmental conditions to obtain monitoring data on swiftlet activities and flight trajectories to the greatest extent. The sound attraction device can be a portable speaker, and the volume and frequency of the playback need to be adjusted to cover a reasonable range. For example, the playback range of the sound attraction device can be set to a circular area with a radius of 100 to 1000 meters.

[0064] It is understandable that this propagation range refers to the maximum range of sound information that the swiftlet can obtain, not the range of sound that humans can hear.

[0065] In an exemplary embodiment of the present application, the playback range of the device for attracting different environmental sounds can be set to a circular area with a radius of 500 to 1000 meters, such as areas with environmental noise such as the seaside and islands.

[0066] In an exemplary embodiment of the present application, the playback range of the device for attracting different environmental sounds can be set to a circular area with a radius of 100 to 300 meters, such as a wetland park near a residential area, and the impact on the surrounding residents needs to be considered.

[0067] Attraction monitoring data may include quantity information (referring to the number of swiftlets appearing within the attraction range), environmental information (referring to weather, temperature, humidity, wind speed and other data related to the attraction environment), and directional information of swiftlets flying away (referring to the flight direction and trajectory of swiftlets leaving after attraction). Attraction monitoring data can be collected by taking photos, video recording, infrared sensor capture or manual recording, and stored in a database for subsequent analysis.

[0068] The attraction monitoring data also includes the changes in the number of swiftlets in different time periods after the call, such as the number of swiftlets within one minute after the call, the number of swiftlets within 1 minute to 1.5 minutes after the call, and the number of swiftlets within 3 minutes to 5 minutes after the call. This setting can determine the time and distance of the swiftlets after hearing the call, that is, the size of the effective attraction range. In addition, it can more accurately determine the effect of attraction and the impact of the continuous playback of the attraction sound on the swiftlet's stay.

[0069] In an exemplary embodiment of the present application, the duration of the sound attraction is at least 15 minutes.

[0070] In step S150, the number, distribution pattern and environmental characteristics of the swiftlet population are determined based on the attraction monitoring data.

[0071] In an exemplary embodiment of the present application, population size refers to the number of swiftlets directly observed, or at least the number of populations obtained by summing up, or the estimated number of the total population obtained by further statistical analysis; the distribution pattern of swiftlet populations refers to the spatial distribution characteristics of swiftlet populations in candidate distribution areas; and the environmental characteristics of the distribution area refer to the comprehensive environmental characteristics of the swiftlet distribution area, including vegetation characteristics, topographical characteristics, human interference conditions, climate and meteorological parameters, etc.

[0072] By conducting multiple sound-calling attraction operations in each target survey unit, the number, distribution patterns and environmental characteristics of the swiftlet population can be determined. This will enable us to understand the population status and distribution patterns of the swiftlet in a more systematic and comprehensive manner, effectively improve the comprehensiveness and reliability of attraction monitoring data collection, support the dynamic assessment and long-term monitoring of the swiftlet population, and further ensure the accuracy and effectiveness of monitoring the number, distribution patterns and environmental characteristics of the swiftlet population.

[0073] It should be noted that the survey purpose of the above embodiments is based on the research and protection of the swiftlet population. First, data on the number of swiftlets is collected, and variable parameters affecting the number of swiftlets and population density are obtained based on data analysis. Secondly, the distribution of swiftlets is understood, including the number information and distribution patterns of distribution, and the factors affecting its distribution patterns are comprehensively considered. Finally, a comprehensive analysis is conducted on the habitat suitable for swiftlets, including topographic and geomorphic characteristics, vegetation characteristics, climate characteristics, human interference, etc.

[0074] Next, the contents of step S110 to step S150 are described in detail.

[0075] In an exemplary embodiment of the present application, the Figure 2 The steps in step S140 are implemented in which multiple calls are made to attract the target survey units and the contents of the attracting monitoring data are collected. Figure 2 As shown, it may specifically include:

[0076] Step S210, constructing a target swiftlet attracting call according to the pre-corrected swiftlet test call;

[0077] Step S220, the target swiftlet attracting sound is played repeatedly in a loop for a preset first single playing time, so as to collect the swiftlet attracting situation within the attracting range and obtain the attracting monitoring data.

[0078] The pre-corrected swiftlet test sound refers to an audio signal obtained by collecting the original sound emitted by swiftlets at different physiological and behavioral stages and processing them to optimize the sound quality and signal characteristics. The source of the swiftlet test sound may include the sound of swiftlets during group activities, the sound of chasing and courting, the sound of nesting, the sound of predation, and the sound of feeding young birds. Of course, it can also be the sound of swiftlets in other behavioral activities. This exemplary embodiment does not specifically limit the type of swiftlet test sound.

[0079] The target swiftlet attracting sound refers to an induced audio signal generated based on the pre-corrected swiftlet test sound according to the set playback mode and sound combination. For example, the target swiftlet attracting sound can be an induced audio signal obtained by looping any one of the sounds of swiftlets during group activities, chasing and courting, nesting, predation, and feeding chicks. It can also be an induced audio signal obtained by simultaneously playing or looping at least two combinations of the sounds of swiftlets during group activities, chasing and courting, nesting, predation, and feeding chicks. The present embodiment is not limited to this.

[0080] The method of constructing the target swiftlet attracting call can be through audio processing software, for example, the pre-corrected swiftlet test call can be edited, the frequency can be adjusted, and the signal can be enhanced through Audacity or professional audio editing tools; of course, the target swiftlet attracting call can also be constructed by machine learning models, for example, a large number of swiftlet call samples can be analyzed to automatically generate attracting audio that meets specific goals. In addition, the construction process may also require dynamic adjustment of the type and intensity of the target swiftlet attracting call according to the monitoring environment, for example, the call of chasing and courting can be given priority during the breeding season, and the call of group activities can be selected during the period of frequent swiftlet activities. In an optional embodiment, mixed audio technology can also be used to superimpose multiple calls and adjust the volume ratio to optimize the attraction effect.

[0081] The first single playback duration refers to the duration of each target swiftlet's call in a playback cycle during the attraction process. The first single playback duration can be determined based on the swiftlet's auditory sensitivity and reaction time. For example, the preset first single playback duration can usually be set within the range of 10 to 15 minutes to ensure that the swiftlet can perceive and respond to the call. Multiple loops refer to the loop playback of the target swiftlet's call. Here, there is no limit on the stop time of the target swiftlet's call, and it only needs to be played continuously.

[0082] Loop playback means repeatedly playing the target swiftlet attracting call during the entire monitoring process to ensure the continuity and stability of the attracting signal during the monitoring period. The playback device can be a portable outdoor speaker or a fixed acoustic device. The appropriate playback power and frequency range can be selected according to the monitoring range to cover an effective area of ​​100 to 150 meters to ensure effective guidance and monitoring of swiftlets.

[0083] During the monitoring process, the playback of the target swiftlet attraction call can be dynamically adjusted in combination with the ambient noise level. For example, under high wind speed or heavy rainfall conditions, the playback volume can be increased to improve the clarity of signal transmission. In order to verify the attraction effect, data collection can be performed synchronously during the playback to record the number of swiftlets appearing in the attraction range, their behavioral responses, and their activity trajectories. These data can be obtained through manual observation, photographic equipment, or automatic recording equipment, and stored in the data processing system for subsequent analysis.

[0084] In an optional embodiment, the playback process can also be combined with sound wave directional technology to enhance the directionality of the signal and improve the attraction effect in a specific area. During the monitoring period, in order to avoid interference with other birds, the audio signal can be adjusted to retain only the unique sound characteristics of the swiftlet or amplify the unique sound frequency of the swiftlet.

[0085] By constructing the target swiftlet attracting call based on the pre-corrected swiftlet test call, the problems of single attracting sound and insensitive response to swiftlet behavior in traditional technology are solved. The pre-corrected call can optimize the frequency range, volume and playback mode to make the played target attracting call more in line with the physiological characteristics and behavioral habits of swiftlets, which can significantly improve the propagation effect of sound signals and enhance the ability to attract target swiftlets in complex environments. By adopting the method of multiple loop playback of the target swiftlet attracting call, combined with the preset single playback time, the problems of insufficient sound coverage and poor playback continuity in traditional monitoring are further solved. The loop playback mode ensures the stability and consistency of the audio signal during long-term monitoring, avoids the defect of inaccurate monitoring results caused by behavioral deviations of swiftlets in different time periods, and can capture the behavioral data of swiftlets more comprehensively under diverse time nodes and environmental conditions.

[0086] Optionally, when collecting the information on attracting swiftlets within the attraction range and obtaining the attraction monitoring data, the number of house martins, lesser white-rumped swifts and passing swiftlets can be distinguished and excluded. The distinction can be made by including the body shape, flight posture, tail spread status and abdominal feather color of the swiftlet or house martins.

[0087] Among them, the flight state refers to the dynamic performance of the target bird when it is moving in the air. The flight of the swiftlet is mainly fast straight or curved flight, usually accompanied by a small tail swing, while the flight state of the house martin is more flexible, with obvious turning and emergency stops. By analyzing the flight trajectory, the species of the target bird can be inferred. For example, the flight trajectory curve model in the video can be used to identify whether it conforms to the typical flight pattern of the swiftlet. When shooting, it can be combined with the continuous shooting mode to record multiple key nodes during the flight process for trajectory reproduction and comparative analysis.

[0088] Tail spread is a method of classification by observing the shape and spread angle of the tail feathers of the target bird. During flight, the tail of the swiftlet is narrow and long, forming an arc when spread and with a sharp tail end, while the tail of the house martin is wider, deeply forked when spread and with a relatively blunt tail end. In order to obtain a clear tail shape, the bird can be photographed at a specific angle during flight. For example, a wide-angle lens can be used to capture flight images from the dorsal side, or slow video playback technology can be used to observe the dynamic changes of the tail.

[0089] The color of the abdominal feathers is an important means of distinguishing the target birds based on their appearance. The abdominal feathers of the swiftlet are usually dark gray or gray, showing a single tone, while the abdominal feathers of the house martin are usually white or light yellow markings. The difference in color distribution can significantly distinguish the two. During the collection process, the lighting conditions of the target area can be enhanced by combining sunlight or artificial light to obtain higher quality image data. In the video recording, the aperture size and exposure time are adjusted to ensure that the abdominal details of the swiftlet and the house martin are still clearly visible in motion.

[0090] By comprehensively capturing the characteristic data of house martins and golden swiftlets and excluding the number of house martins and passing golden swiftlets, the accuracy and reliability of the monitoring data can be further improved.

[0091] The Little White-waisted Bird is larger than the Golden-winged Swiftlet, has a wider wingspan, and is a little stronger. The adult bird has very obvious bright white spots on its waist. It flaps its wings more vigorously and at a higher frequency when flying. The chirping sounds it makes are obviously different from those of the Golden-winged Swiftlet. The Little White-waisted Bird tends to fly at a higher altitude, and will not fly low when playing the chirping sounds of the Golden-winged Swiftlet, let alone approach or hover around the player.

[0092] Optionally, the following steps may be used to implement the construction of the target swiftlet attracting sound according to the pre-corrected swiftlet test sound in step S210, which may specifically include:

[0093] Pre-corrected swiftlet test calls can be obtained, and the swiftlet test calls can include the calls of swiftlets during group activities, the calls of chasing and courting, the calls of nesting, the calls during predation, and the calls when feeding young birds; and then, based on the calls of swiftlets during group activities, the calls of chasing and courting, the calls of nesting, the calls during predation, and the calls when feeding young birds, a target swiftlet attracting call can be constructed in the form of simultaneous or looped playback of multiple call combinations.

[0094] The swiftlet test calls refer to the sound signals obtained by collecting and preliminarily processing the original calls of swiftlets in different behavioral states. The source of the swiftlet test calls can be natural sounds recorded by on-site recording equipment or swiftlet audio data obtained from existing audio databases. Highly sensitive directional microphones or professional wildlife recording equipment can be used during the recording process to reduce environmental noise interference and improve the clarity of the audio signal.

[0095] The collected swiftlet test calls may include, but are not limited to, calls during group activities of swiftlets (such as interactive calls during roosting), calls during pursuit and courtship (such as high-frequency short calls in courtship rituals), calls during nesting (such as calls used to consolidate the nest position), calls during the process of predation (such as low-frequency calls during circling flight), and calls during feeding of young birds (such as short calls during feeding).

[0096] After obtaining the swiftlet test calls, the original audio can be preprocessed, and the processing content may include noise removal, signal enhancement, and audio editing, etc. Of course, other types of audio preprocessing methods can also be used, and this embodiment is not limited to this. Noise removal can be achieved through spectrum analysis technology to separate background noise from the target call; signal enhancement can increase the volume of the target signal through gain adjustment; audio editing can be time-cut and organized according to behavior-specific segments. Of course, artificial intelligence algorithms can also be used to automatically separate mixed audio in a natural environment and extract representative swiftlet call segments. This example embodiment does not specifically limit the preprocessing method of the collected swiftlet test calls.

[0097] The target swiftlet attracting call refers to the induced audio signal generated by processing the pre-corrected test call according to certain combination rules. The combination rules are formulated based on the sensitivity and response intensity of swiftlets to different types of calls. For example, swiftlets may respond more strongly to the calls of chasing and courting and the calls during nesting during the breeding season, while they are more sensitive to the calls of group activities and the calls during the predation process during foraging activities. Therefore, the target swiftlet attracting calls in different situations can be dynamically adjusted according to monitoring needs.

[0098] For example, the target swiftlet attracting call can be at least two combinations of the calls of swiftlets during group activities, the calls of chasing and courting, the calls of nesting, the calls during the predation process, and the calls of feeding young birds. For example, the target swiftlet attracting call is an audio combination of the calls of swiftlets during group activities and the calls of chasing and courting, or it can be an audio combination of the calls of nesting and the calls of feeding young birds that are played simultaneously or in a loop; the target swiftlet attracting call can be the calls of swiftlets during group activities, the calls of chasing and courting, the calls of nesting, the calls during the predation process, and the calls of feeding young birds. At least three combinations of the calls, such as the target swiftlet attracting call can be an audio that simultaneously plays or loops the combined calls of swiftlets’ group activities, calls when chasing and courting, and calls when building nests; it can also be an audio that simultaneously plays or loops the combined calls of nesting, calls during the predation process, and calls when feeding young birds; the target swiftlet attracting call can also be an audio that simultaneously plays or loops the calls of swiftlets’ group activities, calls when chasing and courting, calls when building nests, calls during the predation process, and calls when feeding young birds, at least four combinations, or at least five combinations, and examples are not given here one by one.

[0099] The realization of the combination of sounds can be operated through audio editing software, including the synthesis and mixing of multi-track audio. Multiple sounds can be played simultaneously in parallel, for example, the sounds of group activities and the sounds of nesting can be superimposed; they can also be played in a loop in a time series, for example, the sounds of predation can be played first, and then the sounds of feeding young birds can be played. The playback mode can be optimized according to the activity patterns of swiftlets. For example, the playback interval and the number of repetitions can be set to improve the attraction effect. The above settings can be customized according to the actual scenario, and this embodiment is not limited to the description here.

[0100] In some optional implementations, a specific combination of attracting calls can be generated by training models based on machine learning audio generation technology, and complex audio structures can be achieved without manual editing. In addition, a method of real-time collection and processing of on-site audio can be used to dynamically integrate the actual calls of swiftlets in the environment into target swiftlet attracting calls, thereby better fitting the natural habits and environmental characteristics of swiftlets.

[0101] Optionally, the following steps may be used to implement the construction of the target swiftlet attracting call according to the pre-corrected swiftlet test call in step S210, which may specifically include:

[0102] Pre-corrected swiftlet test calls can be obtained, and the swiftlet test calls include the calls of swiftlets during group activities, the calls of chasing and courting, the calls of nesting, the calls during predation, and the calls when feeding young birds. According to any one of the calls of swiftlets during group activities, the calls of chasing and courting, the calls of nesting, the calls during predation, and the calls when feeding young birds, a target swiftlet attracting call is constructed in the form of looping any one of the selected calls.

[0103] For example, the target swiftlet attracting sound can be the sound of swiftlets' group activities played in a loop, or the sound of swiftlets chasing and courting played in a loop, or the sound of swiftlets building nests played in a loop, or the sound of swiftlets feeding their young played in a loop. The specific type of sound to be used can be determined based on the actual scene requirements.

[0104] By using any one or a combination of the sounds of swiftlets during group activities, chasing and courting, building nests, preying, and feeding their young, the problem of insufficient behavioral stimulation and low response rate of single sound signals in traditional technologies is solved. By playing a combination of one or more sounds, especially in simultaneous or looped playback modes, a sound scene that is closer to the natural environment of the swiftlet can be simulated, thereby attracting more swiftlets to approach the target area, effectively improving the pertinence of attraction signals during the breeding season, foraging time, and roosting period, and improving the accuracy and reliability of swiftlet behavior research in various environments.

[0105] In an exemplary embodiment of the present application, the recruitment monitoring data may also include behavior data information. After the recruitment is completed, the collection of behavior data information may be achieved through the following steps, which may specifically include:

[0106] The preset second single playback duration is used to play the preset swiftlet test sound once, and the single behavioral data information is recorded; wherein the swiftlet test sound includes one of the pre-collected sounds of swiftlets during group activities, chasing and courting, nesting, predation, or feeding young birds.

[0107] The second single play duration refers to the duration of the audio during the single audio play process of the sound test. The second single play duration can be set in combination with the swiftlet's reaction time to the sound signal and its behavioral characteristics. For example, the second single play duration can be set to 5 to 8 minutes to ensure that the swiftlet's behavioral response to a specific sound can be fully recorded. Of course, it can also be 4 to 10 minutes, and this embodiment is not limited to this.

[0108] The pre-collected swiftlet test calls refer to the audio signals of swiftlets in different behavioral scenarios obtained from the natural environment, which have been screened and modified to optimize their attraction ability. Each call has specific acoustic characteristics. For example, the calls during group activities usually have a lower frequency and a long rhythm, which is suitable for attracting swiftlets at a distance; the calls during chasing and courting are high-frequency and short signals, which are usually used to attract breeding individuals; the calls during nesting have continuous rhythmic changes, which can have a strong attraction to individuals in the nesting stage; the calls during the predation process are intermittent low-frequency signals, which are more suitable for reflecting the foraging activities of swiftlets; the calls when feeding young birds have a higher frequency and a soft rhythm, which are used to monitor nesting activities during the breeding season.

[0109] The collection of swiftlet test calls can be completed by a high-sensitivity recording device, such as a directional microphone, a wireless acoustic collection device, or a portable recorder with noise reduction function. The collected audio signal can be filtered, denoised, and frequency adjusted by professional audio processing software to improve the clarity and recognizability of the audio. Optionally, an audio signal with similar characteristics to the actual test call can be generated by analog synthesis to replace the naturally collected call to meet specific experimental conditions.

[0110] Behavioral data information refers to the record of the swiftlet's action response, flight position and other behavioral characteristics during the broadcast. Specific collection methods may include manual observation, image capture, video recording, infrared detection or automated equipment recording. Manual observation can use telescopes or high-magnification photography equipment to observe and manually record the swiftlet's activity trajectory and behavioral characteristics; image capture, video recording or infrared detection can use high-resolution cameras or infrared cameras to capture in poor light conditions; automated equipment such as intelligent monitoring systems can combine image recognition algorithms to automatically generate behavioral data information records.

[0111] By setting the second single playback duration, the problem of playback time not matching the behavioral response characteristics of swiftlets is avoided, and the preset single playback duration is optimized according to the swiftlet's reaction time to the sound signal and its behavioral patterns, so that the playback process can fully attract the swiftlet to approach the sound source within a reasonable time, thereby avoiding the situation where the swiftlet fails to respond completely due to too short playback time, and also avoiding the waste of resources due to too long playback time, thereby improving the efficiency and pertinence of attraction and monitoring data collection within a specific time window; the single playback mode combined with the recording of behavioral data information can realize the efficient identification of individual responses of swiftlets, especially capturing key behavioral characteristics in a short time, and can quickly obtain high-quality monitoring data with limited resources; by recording single behavioral data information, it lays the foundation for the comprehensive evaluation of swiftlet behavior patterns, effectively improving the accuracy and comprehensiveness of attraction and monitoring data.

[0112] Optionally, the recorded behavioral data information includes at least the swiftlet's action response, flight position, and call response.

[0113] Action response refers to the dynamic behavior characteristics of swiftlets in response to the target sound played, which may include approaching the sound source, moving away from the sound source, hovering at a close distance, or changing the flight direction. The method of collecting action response can be achieved through manual observation or video recording. Manual observation can use high-magnification telescopes or telephoto lenses to clearly capture the behavior of swiftlets; video recording can use high-definition video equipment or thermal imaging cameras. Especially in poor light environments, thermal imaging technology can effectively capture the movement trajectory of swiftlets.

[0114] The flight position refers to the flight altitude, flight path, flight radius distance and its distribution in space when the swiftlet plays its call. The flight altitude can be calibrated through multiple ranges, such as 1 to 15 meters, 15 to 30 meters, etc. The flight radius distance can also be calibrated through multiple ranges, such as within 15 meters, within 25 meters, within 35 meters, etc. The specific flight position can be determined by combining a laser rangefinder or a three-dimensional imaging device to accurately obtain flight trajectory data. The flight path and distribution range can be collected through GPS locators or drone-assisted observations, and a spatial distribution map can be generated for subsequent analysis. As an alternative implementation method, an acoustic monitoring system can also be used to indirectly infer the flight position and path by analyzing the sound intensity and propagation direction of the swiftlet's call.

[0115] Call response refers to the characteristic information of the call signal emitted by the swiftlet when it receives the target call. The collection of call response can be combined with a directional microphone or acoustic sensor to capture the call of the swiftlet within the target range and perform signal analysis. The specific analysis content may include characteristic parameters such as the frequency, amplitude and rhythm of the call. The processing of audio data can be completed through spectrum analysis software to separate the response signal of the swiftlet from the environmental noise and further optimize the signal characteristics. As an alternative implementation method, multi-channel acoustic monitoring equipment can also be used to realize the collection of calls from different directions in the space, thereby improving the efficiency of capturing call responses.

[0116] By recording and analyzing the action reaction, flight position and call response, the behavioral characteristics of the swiftlet to the target call can be fully reflected. These behavioral data not only provide a reliable basis for subsequent monitoring and research, but also provide a scientific basis for optimizing the call attraction effect. To ensure the accuracy and consistency of data collection, multiple recording devices can be combined to collect information synchronously, and integrated and analyzed through data fusion technology to maximize the monitoring accuracy.

[0117] In an exemplary embodiment of the present application, the correction of the swiftlet test call can be achieved by the following steps:

[0118] The action response and flight position of the swiftlet can be analyzed based on the preset swiftlet test call to determine the impact of the swiftlet test call on the swiftlet's behavior and the impact on the attraction effect; based on the impact on the swiftlet's behavior and the impact on the attraction effect, the swiftlet test call is corrected to obtain a pre-corrected swiftlet test call.

[0119] Among them, the preset swiftlet test calls refer to typical call signals of swiftlets at different behavioral stages, such as sound samples of scenes such as group activities, courtship, nesting, predation or feeding young birds. The calls are collected by high-sensitivity recording equipment and filtered and frequency optimized to ensure the authenticity and clarity of the audio. The analysis of the swiftlet's action response and flight position is to extract the swiftlet's dynamic performance of the target call through multi-dimensional processing of the monitoring data, which can include the speed of approaching the sound source, trajectory changes, flight altitude adjustment and its repeated response pattern to specific sounds. Data analysis can be completed in combination with manual observation records, video image analysis or computer vision algorithms.

[0120] Through the aggregate analysis of action response and flight position data, the behavioral characteristics of swiftlets can be quantified. For example, the average response time, response intensity and repetition rate can be calculated. Combined with these analysis results, the impact on the attraction effect is evaluated to determine the applicability of the current call in a specific scenario and its shortcomings. The correction process of the call can use professional audio processing software to adjust the volume, frequency range, rhythm and signal duration. The corrected audio can be repeatedly verified through simulation experiments to further optimize the attraction performance.

[0121] Optionally, the swiftlet test call may be corrected according to the call response and the corresponding swiftlet test call to obtain a pre-corrected swiftlet test call.

[0122] Among them, the call response is the acoustic response of the swiftlet after receiving the target call signal. The collected calls are recorded by directional microphones or multi-channel acoustic monitoring equipment and stored as audio data files. The spectral characteristics, amplitude, frequency and time characteristics of the call response can be extracted and annotated by acoustic analysis software. According to the correspondence between the call response and the swiftlet's test call, the intensity and characteristics of the swiftlet's call response to different types of test calls can be determined. For example, the most effective call segment can be screened out by comparing the number of responses and response strength induced by various test calls.

[0123] The correction process can be based on the analysis results, by adjusting the spectral characteristics of the test calls or mixing different types of calls to generate pre-corrected audio signals. For example, the low-frequency component of the predation call can be increased to enhance the attraction to foraging swiftlets, or the interval time of the courtship call can be appropriately shortened to improve the response efficiency. The corrected test call needs to be verified in combination with actual attraction experiments and further adjusted according to feedback data to ensure its effectiveness.

[0124] In an example embodiment of the present application, the collection of attraction monitoring data may include environmental information, and the specific environmental information may include time information, weather information, temperature information, wind information, humidity information, location information, vegetation information, topography information, etc. Among them, environmental information is an important external factor affecting the activities of swiftlets, and its collection and recording are the key to ensuring the integrity and accuracy of monitoring data. Time information is usually recorded by synchronizing device timestamps to ensure the timing consistency of the data. Weather information, temperature, wind speed and humidity can be collected in real time through portable weather stations or environmental sensors, and the data accuracy is required to be within an acceptable error range, such as temperature ±0.5°C and wind speed ±0.2m / s.

[0125] Location information can be obtained through the GPS module, including the latitude, longitude and altitude of the monitoring location. The collected environmental data needs to be stored synchronously with the behavioral data for subsequent analysis. Of course, the location information can also be obtained by shooting with a watermark camera with a location information tag. Environmental information can also be used to filter and exclude abnormal data. For example, attraction monitoring data under extreme weather conditions may not have reference value. In order to improve recording efficiency, the environmental data collection module can be integrated into the monitoring equipment to achieve automatic recording and uploading.

[0126] In an exemplary embodiment of the present application, the location information includes the coordinates of the swiftlet population and the topographic information at the coordinates. The possible nesting areas at the coordinates can be distinguished based on the topographic information to facilitate monitoring.

[0127] Time information, weather information, temperature information, wind information, humidity information, vegetation information, etc. can be obtained in real time using on-site equipment, and can also be obtained simultaneously through nearby meteorological stations, satellite data, etc., to facilitate accurate acquisition of environmental parameters.

[0128] In a specific embodiment, for example, in the coastal area of ​​Hainan Island, the terrain of a certain area can be recorded through the map plate, and effective environmental parameters can be recorded through real-time weather information, etc. For another example, on an island, it is not convenient to collect environmental parameters or an uninhabited island without facilities such as a weather station, so it is necessary to carry a portable device to collect environmental data on the island where swiftlets are distributed.

[0129] In an exemplary embodiment of the present application, the content of performing multiple calls to attract the target survey units in step S140 can also be implemented by the following steps, which can specifically include:

[0130] You can make multiple calls to attract swiftlets during the period when they return to their nests after hunting.

[0131] Among them, the predation and homing time period refers to the specific time interval when the swiftlet ends its daytime foraging activities and returns to its habitat. Since the habit of the swiftlet is to hunt during the day, the location of the nest cannot be tracked. After attracting it in the evening, the location of the swiftlet's nest can be tracked and found, which is convenient for monitoring the habitat. Therefore, multiple calls to attract during the predation and homing time period can improve the monitoring success rate of the population size, distribution pattern and environmental characteristics of the distribution area. According to observation and research data, the predation and homing time period of the swiftlet usually occurs in the evening. For example, the predation and homing time period can be selected between 5:30 and 7:30 pm, or between 6:00 and 7:00 pm, or between 6:15 and 6:45 pm. The selection of this time period can be combined with the seasonal changes in the region and the living habits of the swiftlet, and verified and determined through long-term monitoring data, and this embodiment is not limited to this. When the light is insufficient in the evening, image information can be collected by means of an infrared camera.

[0132] The implementation of sound attraction can include multiple loops of optimized target sound signals, and the playback duration and interval must match the frequency and rhythm of homing activities. The playback device can choose an outdoor speaker with a timing function to ensure that the playback signal covers the entire potential habitat area during the peak period of swiftlet activity. In order to improve the efficiency of observation under low light conditions, an infrared camera can be used to record behavioral data during the attraction period to capture more detailed information. By attracting during the predation and homing period, the success rate of monitoring can be effectively improved and the potential habitat area of ​​swiftlets can be accurately located. As an alternative, the ambient light intensity sensor can be used to dynamically adjust the attraction time to adapt to changes in different natural environments.

[0133] By selecting the time period when swiftlets are returning to their nests for hunting and roosting, the problem of low success rate of attraction caused by improper time selection can be effectively solved. The time period when swiftlets are returning to their nests for hunting and roosting is a period when the activity intensity of swiftlets is high and their behaviors are concentrated. The selection of the time period when swiftlets are returning to their nests is based on the biological learning of swiftlets, and is verified and optimized in combination with regional long-term observation data, so that the sound attraction can cover the high-frequency time window when swiftlets return to their nests. By performing multiple sound attraction in this time period, swiftlets can be attracted to the target area more efficiently, effectively improving the efficiency of attraction monitoring and data collection; by combining the technical design of dynamically adjusted time period selection and multiple attraction, the problem of unreliable data caused by the randomness of individual responses of swiftlets can be avoided. The selection of the time period when swiftlets are returning to their nests is based on the biological behavior of swiftlets, and multiple playbacks can repeatedly strengthen the attraction signal, making the activities of swiftlets in the target area more concentrated and significant, which can effectively reduce the interference of random behavior on the monitoring results, thereby effectively improving the stability and repeatability of the collected attraction monitoring data.

[0134] In an example embodiment of the present application, the process of attracting and investigating swiftlets is a long process, which requires data collection and scientific monitoring of the population size, distribution, and dynamic changes of swiftlets throughout the year. For example, multiple surveys are conducted in different seasons of winter and summer, and the key survey scope is gradually narrowed to accurately collect the population data and data changes of swiftlets, comprehensively analyze the dynamics of the population, and achieve more scientific investigation and monitoring.

[0135] It should be noted that, although the steps of the method in the present application are described in a specific order in the drawings, this does not require or imply that the steps must be performed in the specific order, or that all the steps shown must be performed to achieve the desired results. Additionally or alternatively, some steps may be omitted, multiple steps may be combined into one step, and / or one step may be decomposed into multiple steps, etc.

[0136] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any variations, uses or adaptations of the present application, which follow the general principles of the present application and include common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and embodiments are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the claims.

[0137] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A method for investigating and monitoring swiftlet populations, characterized in that: include: Obtain the potential distribution areas confirmed in advance for the swiftlet population and determine the altitude of the potential distribution areas; If it is determined that the altitude is lower than the preset swiftlet activity altitude threshold, the potential distribution area is determined as a candidate distribution area; Divide the candidate distribution area into regions to determine at least one target survey unit; Perform multiple calls to attract swiftlets in each target survey unit, and collect attracting monitoring data, wherein the attracting monitoring data at least includes quantity information, environmental information, and directional information of swiftlets flying away; The number, distribution pattern and environmental characteristics of the swiftlet population are determined based on the attraction monitoring data.

2. The method for investigating and monitoring swiftlet populations according to claim 1, characterized in that: The method of performing multiple calls to attract the target survey units and collecting the attracting monitoring data includes: Construct the target swiftlet attracting call based on the pre-corrected swiftlet test call; The target swiftlet attracting sound is played repeatedly in a loop with a preset first single playing time, so as to collect the swiftlet attracting situation within the attracting range and obtain the attracting monitoring data.

3. The method for investigating and monitoring swiftlet populations according to claim 2, characterized in that: The method of constructing a target swiftlet attracting call based on the pre-corrected swiftlet test call comprises: Acquire pre-corrected swiftlet test calls, wherein the swiftlet test calls include calls of swiftlets during group activities, calls during pursuit and courtship, calls during nesting, calls during predation, and calls during feeding of young birds; The target swiftlet attracting sound is constructed based on a combination of sounds from the group activities of the swiftlet, the chasing and courting sounds, the nesting sounds, the predation sounds and the feeding sounds of the young birds, and by playing the multiple sound combinations simultaneously or in a loop.

4. The method for investigating and monitoring swiftlet populations according to claim 3, characterized in that: The method of constructing a target swiftlet attracting call based on the pre-corrected swiftlet test call comprises: Acquire pre-corrected swiftlet test calls, wherein the swiftlet test calls include calls of swiftlets during group activities, calls during pursuit and courtship, calls during nesting, calls during predation, and calls during feeding of young birds; The target swiftlet attracting sound is constructed by playing any one of the selected sounds during group activities, the sounds during chasing and courting, the sounds during nesting, the sounds during predation, and the sounds during feeding young birds in a loop.

5. The method for investigating and monitoring swiftlet populations according to claim 2, characterized in that: The attraction monitoring data also includes behavioral data information. After the attraction is completed, the sound attraction is performed multiple times in each target investigation unit, and also includes: Playing the preset swiftlet test call once for a preset second single play time, and recording the single behavior data information; The swiftlet test sound includes one of the pre-collected sounds of swiftlets during group activities, sounds during chasing and courting, sounds during nesting, sounds during predation, or sounds during feeding of young birds.

6. The method for investigating and monitoring swiftlet populations according to claim 5, characterized in that: The behavior data information at least includes the action response, flight position and call response of the swiftlet.

7. The method for investigating and monitoring swiftlet populations according to claim 6, characterized in that: The method of determining the number, distribution pattern and environmental characteristics of the swiftlet population according to the attraction monitoring data also includes: According to the preset swiftlet test call, the action response and the flight position of the swiftlet are analyzed to determine the influence of the swiftlet test call on the behavior of the swiftlet and the influence on the attraction effect; The swiftlet test call is modified in combination with the influence on the behavior of the swiftlet and the influence on the attraction effect to obtain a pre-corrected swiftlet test call.

8. The method for investigating and monitoring swiftlet populations according to claim 6, characterized in that: The method of determining the population size, distribution pattern and environmental characteristics of the swiftlet distribution area according to the attraction monitoring data also includes: According to the call response and the corresponding swiftlet test call, the swiftlet test call is corrected to obtain a pre-corrected swiftlet test call.

9. The method for investigating and monitoring swiftlet populations according to claim 1, characterized in that: The environmental information includes time information, weather information, temperature information, wind information, humidity information, location information, vegetation information, topography information, etc.

10. The method for investigating and monitoring swiftlet populations according to any one of claims 1 to 9, characterized in that: The method of performing multiple calls to attract the target survey units also includes: The method uses multiple calls to attract the swiftlets during the period when the swiftlets return to their nests after hunting.

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