Information processing device, information processing method, and program

Abstract

The present technique relates to an information processing device, an information processing method, and a program that make it possible to improve the accuracy of diversity index values related to biodiversity. A calculation unit of the present technique calculates, in a target area for which a diversity index value related to biodiversity is to be calculated, a diversity index value related to biodiversity in a case where at least one specific biological species is observed, on the basis of habitability indicating the possibility of an interactive species, which is a biological species causing interaction with the specific biological species, living in the target area. The present technique can be applied, for example, to a case of evaluating an ecosystem of a farm or the like.

Description

Information processing device, information processing method, and program

[0001] The present technology relates to an information processing device, an information processing method, and a program, and in particular to an information processing device, an information processing method, and a program that enable, for example, improving the accuracy of diversity index values ​​related to biodiversity.

[0002] In recent years, Synecoculture (registered trademark) or Synecoculture (registered trademark) has attracted attention. This method involves thinning out densely mixed plants and harvesting them under the constraints of no tillage, no fertilizer, no pesticides, and no introduction of anything other than seeds and seedlings. It achieves species diversity exceeding that of natural conditions through vegetation arrangement, while producing useful plants in an ecologically optimized state. Synecoculture (registered trademark) or Synecoculture (registered trademark) allows the introduction of a wide variety of plant species, creating an expanded ecosystem with enhanced biodiversity and ecosystem function.

[0003] One method for evaluating the ecosystem of various locations, including those where traditional farming methods (conventional farming, organic farming, natural farming, etc.) are practiced, including not only Synecoculture (registered trademark) or Synecoculture (registered trademark), is to calculate some kind of index value related to the biodiversity of the location (hereinafter also referred to as diversity index value).

[0004] For example, a method has been proposed in which a diversity index value is calculated by adding up the number of (inter-organism) interactions that each species in a list of described species has with other species (see, for example, non-patent document 1).

[0005] Funabashi, Masatoshi, and Tomoyuki Minami. "Dynamic assessment of aboveground and underground biodiversity with supportive AI." Measurement: Sensors 18 (2021): 100167.

[0006] The calculation of the diversity index value in Non-Patent Document 1 is performed using a global database in which interaction information is registered based on reported cases of interactions, but does not take into account the observation site where the interaction was observed or the habitats of other biological species that may interact.

[0007] Therefore, the biodiversity index value of a certain location is calculated without taking into consideration whether the interactions occur with other biological species that do not inhabit that location (or are highly unlikely to inhabit that location) or with other biological species that do inhabit that location (are highly likely to inhabit that location). Therefore, for example, if a biological species that interacts with African elephants (another biological species) inhabits (grows) in a farm field in Tokyo, the biodiversity index value of that field can be calculated by taking into consideration the interactions contributed by African elephants that do not inhabit the vicinity of the field equally with other interactions.

[0008] However, if the diversity index value of a field is calculated by taking into account interactions contributed by other biological species that do not live near the field equally with other interactions, the accuracy of the diversity index value may decrease.

[0009] The present technology has been made in view of such circumstances, and makes it possible to improve the accuracy of diversity index values.

[0010] The information processing device or program of the present technology is an information processing device that has a calculation unit that calculates a diversity index value related to biodiversity when one or more specified biological species are observed in a target area for which a diversity index value related to biodiversity is to be calculated, based on a habitat probability that represents the possibility that an interacting species, which is a biological species that interacts with the specified biological species, is likely to inhabit the target area, or a program that causes a computer to function as such an information processing device.

[0011] The information processing method of the present technology is an information processing method that includes calculating a diversity index value related to biodiversity when one or more specified biological species are observed in a target area for which a diversity index value related to biodiversity is to be calculated, based on a habitat probability that represents the possibility that an interacting species, which is a biological species that interacts with the specified biological species, is inhabiting the target area.

[0012] In this technology, when one or more specified biological species are observed in a target area for which a diversity index value related to biodiversity is calculated, the diversity index value related to biodiversity is calculated based on habitat probability, which represents the possibility that an interacting species, which is a biological species that interacts with the specified biological species, will inhabit the target area.

[0013] The information processing device may be an independent device or an internal block constituting a single device.

[0014] The program can be provided by transmitting it via a transmission medium or by recording it on a recording medium.

[0015] 1 is a diagram illustrating an example configuration of an embodiment of an information processing system to which the present technology is applied. FIG. 1 is a diagram illustrating an example hardware configuration of a terminal 11. FIG. 1 is a diagram illustrating an example hardware configuration of a server 12. FIG. 2 is a diagram illustrating an overview of the present technology. FIG. 3 is a diagram illustrating an example use case of the present technology. FIG. 4 is a block diagram illustrating a first example functional configuration of the server 12. FIG. 5 is a block diagram illustrating a first example configuration of the calculation unit 42. FIG. 6 is a diagram illustrating an example of target site information. FIG. 7 is a diagram illustrating an example of a biological species list. FIG. 8 is a diagram illustrating an example of interaction information stored in an interaction DB that the interacting species identification unit 51 refers to in identifying interacting species. FIG. 9 is a diagram illustrating an example of observation point information stored in an observation point DB that the observation point identification unit 52 refers to in identifying observation points of interacting species. FIG. 10 is a flowchart illustrating an example of processing by the server 12. FIG. 11 is a block diagram illustrating a first example configuration of the habitability calculation unit 53. FIG. 12 is a diagram illustrating an example probability distribution of the presence probability of a predetermined biological species. FIG. 13 is a block diagram illustrating a second example configuration of the habitability calculation unit 53. FIG. 14 is a flowchart illustrating an example of processing for setting habitability by the habitability setting unit 72. FIG. 15 is a block diagram illustrating a second example configuration of the calculation unit 42. FIG. 16 is a block diagram illustrating an example configuration of the habitability correction unit 81. FIG. 17 is a block diagram illustrating a third example configuration of the calculation unit 42. 10A and 10B are diagrams illustrating examples of second index values ​​acquired by an index value acquisition unit 111.

[0016] <One embodiment of an information processing system to which the present technology is applied>

[0017] FIG. 1 is a diagram showing an example of the configuration of an embodiment of an information processing system to which the present technology is applied.

[0018] The information processing system 10 calculates a diversity index value related to biodiversity when one or more specified biological species are observed in a target area for which a diversity index value related to biodiversity is to be calculated, based on the habitat probability, which represents the possibility that an interacting species, which is a biological species that interacts with the specified biological species, is living in the target area, and provides the calculated value to the user.

[0019] The target site may be, for example, a farm (or a field within a farm) where various farming methods such as Synecoculture (registered trademark) or Synecoculture (registered trademark) are practiced, a farm where various farming methods are planned to be practiced, or any other location.

[0020] The information processing system 10 includes one or more terminals 11-i, one or more servers 12, and a database (DB) 13. The terminals 11-i, the servers 12, and the DB 13 can communicate with each other via a network 14, which may include a wired local area network (LAN), a wireless LAN, the Internet, a mobile communication network such as 5G, or the like.

[0021] 1, four terminals 11-1, 11-2, 11-3, and 11-4 are provided as terminals 11-i. However, the number of terminals 11-i may be one to three, or five or more. Hereinafter, unless there is a particular need to distinguish between terminals 11-1, 11-2, 11-3, and 11-4, they will be referred to as terminals 11.

[0022] 1, one server 12 is provided as the server 12, but multiple servers 12 can be provided. When multiple servers 12 are provided, the processes described below can be distributed among the multiple servers 12. Furthermore, for the multiple servers 12, a terminal 11 can be assigned to each server 12, and each server 12 can perform processes only for the terminal 11 that it is responsible for.

[0023] Furthermore, in the information processing system 10, some or all of the processing performed by the server 12 can be performed by the terminal 11. When all of the processing performed by the server 12 is performed by the terminal 11, the information processing system 10 can be configured without the server 12.

[0024] The terminal 11 is configured, for example, as a personal computer (PC) or the like, and is operated by a user. Alternatively, the terminal 11 may be configured as a mobile terminal (device) such as a smartphone or smart glasses.

[0025] A user can input necessary information by operating the terminal 11. For example, the user can operate the terminal 11 to input target site information indicating the location of the target site. The user can also operate the terminal 11 to input biological species (such as names (species names)) such as plant species, animal species, and microbial species that inhabit (grow) in the target site or that are (planned to be) introduced into the target site. The user can also operate the terminal 11 to input the habitability threshold and adjustment coefficient (described below) and other information necessary for processing by the terminal 11 and the server 12. Note that input of a biological species into the terminal 11 can be performed by inputting the name, etc., of the biological species, or by photographing the biological species with the terminal 11. When input of a biological species into the terminal 11 is performed by photographing the biological species with the terminal 11, image recognition of the image obtained by the photograph is performed by the terminal 11, the server 12, etc., to recognize the biological species appearing in the image (the biological species is identified).

[0026] The terminal 11 transmits (via the network 14) to the server 12 information such as target area information input by the user and a list of biological species that describes biological species (such as their names).

[0027] The terminal 11 receives, for example, an image as a presentation UI (user interface) that presents a biodiversity index value, etc. of a target area when a biological species in the biological species list (a biological species whose name is described in the biological species list) is observed in the target area, transmitted from the server 12 (via the network 14). The terminal 11 presents the biodiversity index value, etc. to the user by, for example, displaying the presentation UI (or outputting it as audio).

[0028] The server 12 calculates a diversity index value for a target area when a biological species on the biological species list is observed in the target area.

[0029] For example, the server 12 receives target site information, a biological species list, etc. transmitted from the terminal 11 (via the network 14). Using the target site information and the biological species list, etc., the server 12 calculates a biodiversity index value for the target site when a biological species on the biological species list is observed in the target site, based on a habitat probability that indicates the possibility that an interacting species, which is a biological species that interacts with a biological species on the biological species list, will inhabit the target site. The server 12 generates a presentation UI that presents the biodiversity index value, etc. for the target site, and transmits it to the terminal 11 (via the network 14).

[0030] The server 12 refers to the DB 13 (via the network 14) as necessary and performs processing using the information stored in the DB 13.

[0031] The DB 13 stores big data as various types of information. For example, the DB 13 includes an interaction DB, an observation point DB, a geography DB, a meteorological DB, a classification DB, and the like.

[0032] The interaction DB stores interaction information, which is information that associates, for each biological species, (its name, etc.) a biological species with (its name, etc.) an interacting species that interacts with the biological species, and (its name, etc.) the interaction.

[0033] The observation point DB stores observation point information, which is information that associates each biological species with the location information of the location where the biological species (or its habitat) was observed.

[0034] The geographic database stores GIS (Geographic Information System) geographic information. GIS geographic information (geospatial information) is information that associates a location on the Earth, such as latitude and longitude, with information related to that location (such as the elevation, slope, road width, land use subdivision, etc.).

[0035] The weather DB stores weather information, such as annual precipitation and average temperatures for each region.

[0036] The phylogenetic classification DB stores phylogenetic classification information, which is information that associates each biological species with its taxonomic rank (such as genus or family).

[0037] <Example of hardware configuration of terminal 11 and server 12>

[0038] FIG. 2 is a diagram showing an example of the hardware configuration of the terminal 11. As shown in FIG.

[0039] The terminal 11 includes a communication unit 21, a calculation unit 22, an input / output unit 23, a storage 24, a positioning unit 25, and a sensor unit 26. The communication unit 21 to the sensor unit 26 are interconnected via a bus, enabling the exchange of information.

[0040] The communication unit 21 functions as a transmitting unit that transmits information via the network 14 and as a receiving unit that receives information.

[0041] The calculation unit 22 has a processor such as a central processing unit (CPU) or a digital signal processor (DSP), and performs various processes by executing programs recorded in the storage 24 .

[0042] The input / output unit 23 has a keyboard, a touch panel, a microphone, etc., and receives operations and other various inputs from the user. The input / output unit 23 also has a speaker and a display (display unit), and presents information to the user by outputting sound, displaying images, etc.

[0043] The storage 24 is composed of semiconductor memory such as RAM (random access memory) or nonvolatile memory, SSD (solid state drive), HDD (hard disk drive), etc. The storage 24 records (stores) programs executed by the calculation unit 22, data necessary for the processing of the calculation unit 22, etc.

[0044] The program executed by the calculation unit 22 can be installed in the computer serving as the terminal 11 from a removable recording medium such as a DVD (digital versatile disc) or a memory card. Alternatively, the program can be downloaded to the computer serving as the terminal 11 via the network 14 or the like and installed in the storage 24.

[0045] The positioning unit 25 is, for example, a global positioning system (GPS), measures (locates) the position of the terminal 11, and outputs position information representing the position, such as latitude and longitude (and necessary altitude).

[0046] The sensor unit 26 has various sensors, such as a camera, a distance sensor, a temperature sensor, and a humidity sensor, and performs various sensing operations, such as taking images, detecting distance, detecting temperature, and detecting humidity, and outputs images, distance, temperature, humidity, etc. as sensing results.

[0047] FIG. 3 is a diagram showing an example of the hardware configuration of the server 12.

[0048] The server 12 has a communication unit 31, a calculation unit 32, an input / output unit 33, and a storage 34. The communication unit 31 to the storage 34 are configured in the same manner as the communication unit 21 to the storage 24 in Fig. 2, respectively, and therefore a description thereof will be omitted. Note that the communication unit 31 to the storage 34 may be configured to have higher performance than the communication unit 21 to the storage 24 in terms of capacity, processing speed, and other performance.

[0049] <Overview of this technology>

[0050] FIG. 4 is a diagram illustrating an overview of the present technology.

[0051] In Figure 4, biological species (plant species in Figure 4) A1, A2, and A3 inhabit the target area.

[0052] When a user wishes to obtain a diversity index value for a target area, the user operates the terminal 11 to input the biological species A1 to A3 that inhabit the target area.

[0053] Although various other insects, microorganisms, birds, and other organisms may inhabit the target area, it is not realistic to find all of the species that currently inhabit the target area. Therefore, when obtaining a diversity index value for the target area, the species to be input can be limited to species that meet specified conditions, such as only plant species, only insect species, or species that can be observed within a specified time period.

[0054] The terminal 11 generates a species list in which the species A1 to A3 input by the user are described, and transmits the list to the server 12.

[0055] Here, let us assume that there are biological species B1, B2, B3, B4, and B5 that interact with any of biological species A1 to A3. Biological species B1 to B3 live near the target area, while biological species B4 and B5 live far from the target area.

[0056] If a simple value based on interactions with one of the species A1 to A3 on the species list is used as the diversity index value for a target area when a species on the species list is observed in the target area, the accuracy of the diversity index value may be reduced.

[0057] Here, the simple value based on interactions refers to a value calculated based on interactions that does not take into account the possibility that interacting species inhabit the target area. For example, a simple value based on interactions would be the total number of interactions that occur between any of the biological species A1 to A3 on the biological species list and any of the interacting species B1 to B5, or the number of interacting species B1 to B5 that interact with any of the biological species A1 to A3.

[0058] When a simple value based on interactions is adopted as the diversity index value of the target area, the interacting species B1 to B3 (or interactions occurring with interacting species B1 to B3) that live near the target area and the interacting species B4 and B5 (or interactions occurring with interacting species B4 and B5) that do not live near the target area are taken into equal consideration to calculate the diversity index value of the target area.

[0059] As described above, if the diversity index value for the target area is calculated by considering interacting species B4 and B5, which do not live near the target area, equally with interacting species B1 to B3, which live near the target area, the accuracy of the diversity index value may be reduced.

[0060] Therefore, in the server 12, when biological species A1 to A3 on the biological species list are observed in the target area, the diversity index value of the target area is calculated based on the habitat probability, which represents the possibility that each of interacting species B1 to B5, which interact with any of the biological species A1 to A3 on the biological species list, will inhabit the target area.

[0061] As described above, when the biodiversity index value of a target area is calculated based on the habitability of interacting species, the degree of consideration can be increased for interacting species B1 to B3 that inhabit the vicinity of the target area, while the degree of consideration can be decreased for interacting species B4 and B5 that do not inhabit the vicinity of the target area. As a result, the accuracy of the biodiversity index value can be improved. Hereinafter, a biodiversity index value calculated based on the habitability of interacting species is also referred to as a biodiversity index value based on habitability.

[0062] <Examples of use cases for this technology>

[0063] FIG. 5 is a diagram illustrating an example of a use case of the present technology.

[0064] For example, a farmer who practices Synecoculture® or Synecoculture® in a field can use a diversity index value based on habitability to assess the (quality of) ecosystem in the field before and after implementing Synecoculture® or Synecoculture®.

[0065] In Synecoculture® or Synecoculture®, a variety of species are introduced into the field. A diversity index based on habitability can be calculated using the species observed in the field before and after the implementation of Synecoculture® or Synecoculture®.

[0066] By comparing the biodiversity index values ​​before and after the implementation of Synecoculture® or Synecoculture®, if the biodiversity index value increases by more than a predetermined value, or if the biodiversity index value after the implementation is equal to or exceeds a value corresponding to the biodiversity recognized as being in the implementation of Synecoculture® or Synecoculture®, it can be recognized that an augmented ecosystem has been established in the field through the implementation of Synecoculture® or Synecoculture®. Therefore, for example, if a certification system is established to certify that a farm having a field is a farm practicing Synecoculture® or Synecoculture® (a synecoculture farm) or that a crop (harvest) in the field is a crop grown using Synecoculture® or Synecoculture® (a synecoculture crop), the biodiversity index value can be used for that certification. For example, the biodiversity index value can be used in a certification business that certifies whether a farm or crop is a synecoculture farm or a synecoculture crop.

[0067] Furthermore, for example, when a farming practitioner practices Synecoculture (registered trademark) or Synecoculture (registered trademark), a diversity index value based on habitability can be used to evaluate the combination of plant species (hereinafter also referred to as a vegetation plan) to be introduced into a field (evaluating the ecosystem of the field into which the plant species of the vegetation plan have been introduced).

[0068] For example, for two vegetation plans A and B, when a combination of plant species from each of vegetation plans A and B is introduced into a field, a diversity index value based on habitability can be calculated assuming that a combination of plant species from each of vegetation plans A and B is observed in the field.

[0069] By adopting the vegetation plan with the higher diversity index value between vegetation plans A and B, an expanded ecosystem with improved ecosystem function can be constructed. Therefore, the diversity index value can be used to determine the vegetation plan that will create an expanded ecosystem with improved ecosystem function. For example, the diversity index value can be used in consulting businesses that develop vegetation plans (vegetation strategies) and propose them to agricultural practitioners.

[0070] <First Functional Configuration Example of Server 12>

[0071] FIG. 6 is a block diagram showing a first example of the functional configuration of the server 12. As shown in FIG.

[0072] The functional configuration of the server 12 is realized by the calculation unit 32 in FIG. 3 executing a program.

[0073] 6, the server 12 includes an acquisition unit 41, a calculation unit 42, and a generation unit 43.

[0074] The acquisition unit 41 acquires various information such as target location information and a biological species list transmitted from the terminal 11 by receiving them.

[0075] The acquisition unit 41 supplies the acquired information to the necessary blocks. For example, the acquisition unit 41 supplies the target site information and the biological species list to the calculation unit 42.

[0076] The calculation unit 42 uses the target site information and biological species list from the acquisition unit 41, as well as information from DB13, to calculate a diversity index value related to biodiversity when a biological species from the biological species list from the acquisition unit 41 is observed in the target site whose location is represented by the target site information, based on the habitat probability, which represents the possibility that an interacting species that interacts with a biological species from the biological species list will inhabit the target site.

[0077] That is, the calculation unit 42 refers to the information in the DB 13, identifies interacting species that interact with the biological species in the biological species list, calculates the habitability of the interacting species in the target area, and then calculates a diversity index value for the target area based on the habitability of the interacting species.

[0078] The calculation unit 42 supplies the diversity index value of the target area to the generation unit 43 .

[0079] The generation unit 43 generates a presentation UI that presents the diversity index value from the calculation unit 42 and other information about the target location, and transmits the UI to the terminal 11 .

[0080] <First Configuration Example of Calculation Unit 42>

[0081] FIG. 7 is a block diagram showing a first example of the configuration of the calculation unit 42 in FIG.

[0082] In FIG. 7, the calculation unit 42 includes an interacting species identification unit 51, an observation point identification unit 52, a habitat possibility calculation unit 53, and an index value calculation unit 54.

[0083] The interacting species identification unit 51 is supplied with the biological species list from the acquisition unit 41 ( FIG. 6 ). The interacting species identification unit 51 refers to the interaction DB in the DB 13, and for each biological species in the biological species list, identifies the interacting species that interact with that biological species, and supplies the interacting species (such as their names) to the observation point identification unit 52.

[0084] The observation point identification unit 52 refers to the observation point DB in the DB 13, and for each interacting species from the interacting species identification unit 51, identifies (the location information of) the observation point where the interacting species was observed, and supplies this to the habitability calculation unit 53. There is not necessarily only one observation point for a certain interacting species.

[0085] The habitability calculation unit 53 is supplied with the observation points of each interacting species from the observation point identification unit 52, as well as with target site information from the acquisition unit 41. The habitability calculation unit 53 refers to the DB 13 as needed, and calculates the habitability of each interacting species in the target site using the observation points of each interacting species from the observation point identification unit 52 and the target site information from the acquisition unit 41, and supplies the calculated habitability to the index value calculation unit 54. Habitability is information that represents the possibility that a certain biological species will inhabit a certain site. For example, the habitability can be a value that represents the probability (presence probability) that a certain biological species will inhabit (exist) at a certain site, or a value that represents the likelihood (likelihood) that a certain biological species will exist at a certain site.

[0086] The index value calculation unit 54 calculates a diversity index value for the target area based on the habitability of each interacting species from the habitability calculation unit 53, and supplies the calculated value to the generation unit 43 (FIG. 6).

[0087] FIG. 8 is a diagram illustrating an example of target location information.

[0088] The target location information may be the latitude and longitude of a position within an area of ​​the target location, such as a field, farm, etc. Alternatively, the target location information may be the latitude and longitude of each vertex of a rectangle or other polygon that approximates the shape of the area as the target location.

[0089] FIG. 9 is a diagram showing an example of a biological species list.

[0090] The biological species list is a list that describes the names of biological species, such as scientific names, and other information that identifies the biological species.

[0091] FIG. 10 is a diagram showing an example of interaction information stored in the interaction DB that the interaction type specifying unit 51 in FIG. 7 refers to in specifying the interaction type.

[0092] Interaction information is information that associates a biological species (Species A) (its name and other information that identifies the biological species), an interacting species (Species B) (its name and other information that identifies the biological species) that is another biological species that interacts with that biological species, and the interaction type (its name and other information that identifies the interaction).

[0093] FIG. 11 is a diagram showing an example of observation point information stored in the observation point DB that the observation point specifying unit 52 in FIG. 7 refers to in specifying the observation point of the interacting species.

[0094] The observation point information is information that associates a biological species with position information, such as latitude and longitude, of a point where the biological species was observed in the past.

[0095] FIG. 12 is a flowchart illustrating an example of processing by the server 12 of FIG.

[0096] In step S11, the acquisition unit 41 of the server 12 acquires the target location information, the biological species list, etc. transmitted from the terminal 11, and supplies them to the calculation unit 42, and the process proceeds to step S12.

[0097] In step S12, the calculation unit 42 uses the target site information and biological species list from the acquisition unit 41, etc., to calculate a diversity index value for the target site based on the habitat probability, which represents the possibility that interacting species that interact with biological species in the biological species list will inhabit the target site.

[0098] In step S12, first, in step S21, the interacting species identification unit 51 of the calculation unit 42 (Figure 7) identifies the interacting species that interact with each biological species in the biological species list from the acquisition unit 41, and supplies this to the observation point identification unit 52, and the processing proceeds to step S22.

[0099] In step S22, the observation point identification unit 52 identifies the observation point where each interacting species from the interacting species identification unit 51 was observed, supplies this to the habitat possibility calculation unit 53, and processing proceeds to step S23.

[0100] In step S23, the habitability calculation unit 53 calculates the habitability of each interacting species in the target site, using the observation site of each interacting species from the observation site identification unit 52 and the target site information from the acquisition unit 41. The habitability calculation unit 53 supplies the habitability of each interacting species to the index value calculation unit 54, and the process proceeds from step S23 to step S24.

[0101] In step S24, the index value calculation unit 54 calculates a diversity index value of the target area based on the habitability of each interacting species from the habitability calculation unit 53.

[0102] The calculation unit 42 supplies the diversity index value of the target location calculated in step S12 as described above to the generation unit 43, and the process proceeds to step S13.

[0103] In step S13 , the generation unit 43 generates a presentation UI for presenting the diversity index value from the calculation unit 42 and transmits the UI to the terminal 11 .

[0104] <First configuration example of the habitability calculation unit 53>

[0105] FIG. 13 is a block diagram showing a first example of the configuration of the habitability calculation unit 53 of FIG.

[0106] In FIG. 13 , the habitability calculation unit 53 includes a probability distribution calculation unit 61 and a habitability setting unit 62 .

[0107] The probability distribution calculation unit 61 is supplied with the observation points of each interacting species from the observation point identification unit 52 ( FIG. 7 ). The probability distribution calculation unit 61 refers to the geographic DB and meteorological DB, and uses the observation points of the interacting species from the observation point identification unit 52 to calculate a probability distribution of the existence probability of the interacting species at each point, and supplies the calculated probability to the habitability setting unit 62. The existence probability represents the probability that the interacting species exists, for example, as a value ranging from 0 to 1.

[0108] For example, the probability distribution calculation unit 61 can calculate the probability distribution of interacting species (probability distribution of the probability of existence of interacting species at each point) using ecological niche modeling. Ecological niche modeling using Maxent, for example, can be used. Ecological niche modeling using Maxent is described, for example, in Phillips, SJ, RP Anderson, and RE Schapire. 2006. Maximum entropy modeling of species geographic distributions. Ecological Modelling 190: 3-4 pp 231-259 (hereinafter also referred to as Reference 1).

[0109] Ecological niche modeling using Maxent uses mesh data of various environmental information, including observation points for interacting species, to estimate the probability that the interacting species (and their niches) are present at each location. Environmental information used includes altitude, slope, annual precipitation, average temperature, road width, and land use subdivision. Environmental information is obtained from GIS geographic information stored in a geographic database and meteorological information stored in a meteorological database.

[0110] The habitability setting unit 62 is supplied with the probability distribution of each interacting species from the probability distribution calculation unit 61, as well as with the target location information from the acquisition unit 41 (FIG. 6). For each interacting species, the habitability setting unit 62 sets the probability of existence in the target location indicated by the target location information in the probability distribution of the interacting species as the habitability of that interacting species, and supplies this to the index value calculation unit 54 (FIG. 7).

[0111] As described above, the index value calculation unit 54 calculates a diversity index value for the target site based on the habitability of each interacting species supplied from the habitability setting unit 62. For example, the index value calculation unit 54 calculates the total (sum) of the habitability of each interacting species from the habitability setting unit 62 as the diversity index value for the target site. In this case, the diversity index value for the target site depends on the number of interacting species and the habitability of each interacting species in the target site, and represents (a value equivalent to) the expected value of the number of interacting species.

[0112] As described above, when the biodiversity index value of a target site is calculated based on the possibility of interacting species habiting the target site, greater consideration is given to interacting species that inhabit the target site, while less consideration is given to interacting species that do not inhabit the target site. As a result, the biodiversity index value is calculated taking into account the geographical and environmental aspects of the target site and the habitats of interacting species (including places where interacting species actually inhabit as well as places where they are predicted to inhabit), thereby improving the accuracy of the biodiversity index value.

[0113] FIG. 14 is a diagram showing an example of a probability distribution of the existence probability of a predetermined biological species.

[0114] Figure 14 shows the probability distribution obtained as a result of ecological niche modeling using Maxent, as described in Reference 1. Figure 14 shows the probability distribution only for the vicinity of South America. In Figure 14, the darker the area, the higher the probability of existence.

[0115] <Second configuration example of the habitability calculation unit 53>

[0116] FIG. 15 is a block diagram showing a second example of the configuration of the habitability calculation unit 53 of FIG.

[0117] In FIG. 15 , the habitability calculation unit 53 has a relationship specification unit 71 and a habitability setting unit 72 .

[0118] The relationship identifying unit 71 receives the observation points of each interacting species from the observation point identifying unit 52 ( FIG. 7 ) and the target location information from the acquiring unit 41 ( FIG. 6 ). For each interacting species, the relationship identifying unit 71 uses the observation points of the interacting species and the target location information to identify relationship information that indicates the distance and / or environmental relationship (distance proximity (distance) and / or environmental proximity) between the target location and the observation point. For example, the relationship identifying unit 71 identifies whether the target location and the observation point are within a predetermined distance (e.g., 100 km) (or the same region of the same country) as the relationship information. Additionally, the relationship identifying unit 71 identifies, for example, whether the target location and the observation point are in the same country or belong to the same climate zone (e.g., whether they are in the same climate zone according to the Köppen climate classification).

[0119] Here, the observation point of the interacting species is not limited to one point. If there are multiple observation points of the interacting species, the relationship identification unit 71 can use, for example, the observation point closest to the target location or the observation point in the environment closest to the environment of the target location as the observation point of the interacting species when identifying the relationship information.

[0120] The habitability setting unit 72 sets a habitability that indicates the possibility that the interacting species observed at the observation point inhabits the target area, based on the relationship information of the interacting species (environmental information that indicates the distance and / or environmental relationship of the interacting species with the target area) from the relationship identification unit 71. For example, the closer the target area and the observation point are in terms of distance and / or environment, the more likely the habitability that is set indicates that the interacting species observed at the observation point inhabits the target area.

[0121] The habitability setting unit 72 supplies the habitability of the interacting species, which is set based on the relationship information of the interacting species, to the index value calculation unit 54 (FIG. 7).

[0122] As described above, the index value calculation unit 54 calculates a diversity index value for the target site based on the habitability of each interacting species supplied from the habitability setting unit 72. For example, the index value calculation unit 54 calculates the total (sum) of the habitability of each interacting species from the habitability setting unit 72 as the diversity index value for the target site. In this case, the diversity index value for the target site depends on the number of interacting species and the habitability of each interacting species in the target site, and represents the expected value for the number of interacting species.

[0123] As described above, when the biodiversity index value of a target site is calculated depending on the habitat possibility of interacting species, the degree of consideration in calculating the biodiversity index value is increased for interacting species that live near the target site, while the degree of consideration is decreased for interacting species that do not live near the target site. As a result, the biodiversity index value is calculated taking into account the geographical and environmental aspects of the target site and the habitats of interacting species, thereby improving the accuracy of the biodiversity index value.

[0124] FIG. 16 is a flowchart illustrating an example of processing for setting the habitability of each interacting species by the habitability setting unit 72 of FIG.

[0125] In step S31, the habitat possibility setting unit 72 determines, based on the relationship information of the interacting species, whether the distance between the target site and the observation point is within a predetermined distance (e.g., 100 km) or whether the target site and the observation point are in the same region.

[0126] If it is determined in step S31 that the distance between the target site and the observation site is within a predetermined distance, or if it is determined that the target site and the observation site are in the same region, the process proceeds to step S32. In step S32, the habitability setting unit 72 sets the habitability of the interacting species to a relatively large first value (a value indicating a high possibility of habitation), for example, 0.4, and the process ends.

[0127] If it is determined in step S31 that the distance between the target site and the observation site is not within the predetermined distance and that the target site and the observation site are not in the same region, the process proceeds to step S33. In step S33, the habitability setting unit 72 determines whether the target site and the observation site are in the same country based on the relationship information of the interacting species.

[0128] If it is determined in step S33 that the target location and the observation point are in the same country, the process proceeds to step S34, where the habitability setting unit 72 sets the habitability of the interacting species to a second value smaller than the first value, for example, 0.3, and the process ends.

[0129] If it is determined in step S33 that the target area and the observation point are not in the same country, the processing proceeds to step S35, and the habitat possibility setting unit 72 determines whether the target area and the observation point belong to the same climatic zone based on the relationship information of the interacting species.

[0130] If it is determined in step S35 that the target site and the observation point belong to the same climatic zone, the process proceeds to step S36, where the habitability setting unit 72 sets the habitability of the interacting species to a third value smaller than the second value, for example, 0.2, and the process ends.

[0131] If it is determined in step S35 that the target site and the observation point do not belong to the same climatic zone, the process proceeds to step S37, in which the habitability setting unit 72 sets the habitability of the interacting species to a fourth value smaller than the third value, for example, 0.1, and the process ends.

[0132] <Second Configuration Example of Calculation Unit 42>

[0133] FIG. 17 is a block diagram showing a second example of the configuration of the calculation unit 42 in FIG.

[0134] In the figure, parts corresponding to those in FIG. 7 are given the same reference numerals, and the description thereof will be omitted below as appropriate.

[0135] In FIG. 17, the calculation unit 42 includes an interacting species identification unit 51 , an observation point identification unit 52 , a habitability calculation unit 53 , an index value calculation unit 54 , and a habitability correction unit 81 .

[0136] 17 is the same as the case of FIG. 7 in that it has everything from the interacting species identification unit 51 to the index value calculation unit 54. However, the calculation unit 42 of FIG. 17 is different from the case of FIG. 7 in that a habitability correction unit 81 is newly provided between the habitability calculation unit 53 and the index value calculation unit 54.

[0137] The habitability correction unit 81 is supplied with the habitability of each interacting species from the habitability calculation unit 53, as well as with target site information from the acquisition unit 41 (FIG. 6). Furthermore, an adjustment coefficient and a habitability threshold are supplied to the habitability correction unit 81. The adjustment coefficient and the habitability threshold can be set to default values ​​by the server 12, or can be set in response to user operation of the terminal 11, for example.

[0138] The habitability correction unit 81 refers to DB13 and uses the target area information, adjustment coefficient, and threshold value to correct the habitability of the interacting species from the habitability calculation unit 53 based on its habitability, and supplies the corrected habitability to the index value calculation unit 54.

[0139] Therefore, in the calculation unit 42 of FIG. 17, the index value calculation unit 54 calculates the diversity index value of the target area based on the corrected habitability from the habitability correction unit 81.

[0140] FIG. 18 is a block diagram showing an example of the configuration of the habitability correction unit 81 shown in FIG.

[0141] Although interacting species with low habitability are unlikely to inhabit the vicinity of the target site, there is a high possibility that closely related species of such interacting species may inhabit the vicinity of the target site. Furthermore, although closely related species of interacting species have not yet been observed, they are expected to interact with species on the biological species list. Therefore, when calculating the biodiversity index value of the target site, if the closely related species of an interacting species with low habitability have a relatively high possibility of inhabiting, it is expected that the accuracy of the biodiversity index value will be improved by taking into account the closely related species of that interacting species rather than the interacting species with low habitability.

[0142] Therefore, in the case where the habitability of a closely related species of an interacting species with low habitability is relatively high, the habitability correction unit 81 corrects the habitability of the interacting species based on the habitability of the closely related species of the interacting species. In this way, by correcting the habitability of an interacting species with low habitability based on the habitability of a closely related species with relatively high habitability, the accuracy of the diversity index value can be improved.

[0143] In FIG. 18 , the habitat possibility correction unit 81 has a low habitat species identification unit 91 , a closely related species identification unit 92 , an observation point identification unit 93 , a habitat possibility calculation unit 94 , a habitat possibility adjustment unit 95 , and a habitat possibility selection unit 96 .

[0144] The habitability of each interacting species is supplied to the low inhabitant species identification unit 91 from the habitability calculation unit 53 ( FIG. 17 ). Furthermore, a habitability threshold is supplied to the low inhabitant species identification unit 91. The habitability threshold is set to a value within the range that the habitability can take. For example, if the habitability can take a value within the range from 0 to 1, the habitability threshold is set to any value within the range from 0 to 1 (e.g., 0.2).

[0145] The low inhabitation species identification unit 91 identifies interacting species whose inhabitability is equal to or less than a threshold value as biological species that are unlikely to inhabit the target area (hereinafter also referred to as low inhabitation species), and supplies the low inhabitation species (the name, etc.) to the related species identification unit 92. For example, if an interacting species is a cabbage white butterfly and the inhabitability of the interacting species is 0.15, when the threshold is 0.2, the interacting species will be identified as a low inhabitation species. Therefore, the inhabitability threshold can be said to be a threshold for identifying low inhabitation species.

[0146] Hereinafter, the habitability correction unit 81 may correct the habitability of low-inhabitability species, that is, interacting species whose habitability is below a threshold.

[0147] The closely related species identifying unit 92 refers to the phylogenetic classification DB and, for each low inhabitant species from the low inhabitant species identifying unit 91, identifies a closely related species of that low inhabitant species and supplies the closely related species (such as its name) to the observation point identifying unit 93. For example, the closely related species identifying unit 92 identifies, in the phylogenetic classification information stored in the phylogenetic classification DB, a biological species that is the same as a low inhabitant species up to a predetermined taxonomic level as that low inhabitant species as a closely related species of that low inhabitant species. For example, when a biological species that is the same as a low inhabitant species up to the taxonomic level "genus" (i.e., a biological species that is the same as a low inhabitant species in the kingdom, phylum, class, order, family, genus, or species) is identified as a closely related species of that low inhabitant species, if the low inhabitant species is cabbage, then kale or the like that is the same as cabbage up to the taxonomic level "genus" is identified as a closely related species of cabbage. The closely related species identification unit 92 can identify biological species that share the same taxonomic class "genus" as the low inhabitant species, as well as biological species that share other taxonomic classes, for example, "family," as closely related species of the low inhabitant species. The taxonomic class up to which biological species share the same taxonomic class can be set according to, for example, the user's operation of the terminal 11.

[0148] 7 , the observation point identification unit 93 refers to the observation point DB in the DB 13, and for each closely related species from the closely related species identification unit 92, identifies the observation point at which the closely related species was observed, and supplies this to the habitat possibility calculation unit 94. There is not necessarily only one observation point for a certain closely related species.

[0149] The habitability calculation unit 94 is supplied with the observation points of each related species from the observation point identification unit 93, as well as target site information from the acquisition unit 41 ( FIG. 6 ). Similar to the habitability calculation unit 53 in FIG. 7 , the habitability calculation unit 94 refers to DB 13 as needed and calculates the habitability of each related species in the target site using the observation points of each related species from the observation point identification unit 93 and the target site information from the acquisition unit 41. The habitability calculation unit 94 supplies the habitability of each related species to the habitability adjustment unit 95.

[0150] The habitability adjustment unit 95 is supplied with the habitability of each closely related species from the habitability calculation unit 94, as well as an adjustment coefficient. The adjustment coefficient is a coefficient for adjusting the habitability of closely related species, and is set to any value in the range from 0 to 1, for example.

[0151] Here, when calculating the diversity index value of a target site, interacting species and their related species can be equally considered. However, since interactions between related species and species on the biological species list have not actually been observed, it may be appropriate to give less consideration to related species than to interacting species. Therefore, the habitability adjustment unit 95 can adjust the degree of consideration of related species using an adjustment coefficient. The adjustment coefficient can also be considered as a penalty imposed on the habitability of related species when interactions between related species and species on the biological species list have not actually been observed. Note that when the adjustment coefficient is set to 0, related species are not considered. When the adjustment coefficient is set to 1, related species are considered equally to interacting species.

[0152] The habitability adjustment unit 95 adjusts the habitability of each related species by multiplying the habitability of each related species from the habitability calculation unit 94 by an adjustment coefficient as a penalty. For example, if the habitability of a certain related species is 0.6 and the adjustment coefficient is set to 0.5, the habitability of the related species is adjusted to 0.6 x 0.5 = 0.3. For each low inhabitability species (each interacting species identified as a low inhabitability species), the habitability adjustment unit 95 adjusts the habitability of each related species of that low inhabitability species and supplies the adjusted habitability to the habitability selection unit 96.

[0153] The habitability selection unit 96 is supplied with the adjusted habitability of the related species from the habitability adjustment unit 95, as well as the habitability of each interacting species from the habitability calculation unit 53 (FIG. 17). The habitability selection unit 96 selects the adjusted habitability of the related species from the habitability adjustment unit 95 or the habitability of the interacting species from the habitability calculation unit 53 as the corrected habitability obtained by correcting the habitability of the interacting species, and supplies it to the index value calculation unit 54 (FIG. 17).

[0154] For interacting species for which the adjusted habitability of closely related species is not provided by the habitability adjustment unit 95, i.e., for interacting species that are not low habitability species, the habitability selection unit 96 selects the habitability of the interacting species from the habitability calculation unit 53 as the corrected habitability.

[0155] Furthermore, for an interacting species for which the adjusted habitability of its related species has been provided by the habitability adjustment unit 95, i.e., an interacting species identified as a low inhabitability species, the habitability selection unit 96 compares the habitability of the interacting species with the adjusted habitability of its related species. In this comparison, the habitability selection unit 96 selects a representative related species from the related species of the interacting species identified as a low inhabitability species. If there is only one related species of the interacting species identified as a low inhabitability species, that one related species is selected as the representative related species. If there are multiple related species of the interacting species identified as a low inhabitability species, a predetermined one of the multiple related species, for example, the related species with the highest habitability, is selected as the representative related species. Then, the habitability selection unit 96 compares the habitability of the interacting species identified as a low inhabitability species with the adjusted habitability of the representative related species of that interacting species.

[0156] If the habitability of an interacting species identified as a low inhabitant species is equal to or greater than the adjusted habitability of a representative relative of that interacting species, the habitability selection unit 96 selects the habitability of the interacting species identified as a low inhabitant species as the adjusted habitability.

[0157] On the other hand, if the habitability of an interacting species identified as a low inhabitant species is less than the adjusted habitability of the representative relative species of that interacting species, the habitability selection unit 96 selects the adjusted habitability of the representative relative species of the interacting species identified as a low inhabitant species as the corrected habitability.

[0158] For example, if the low-inhabitability species is cabbage and the representative relative of cabbage is kale, and the habitability of cabbage is 0.15 and the adjusted habitability of kale is 0.3, then the adjusted habitability of kale, 0.3, is selected as the corrected habitability of cabbage.

[0159] As described above, in the habitability correction unit 81, if the habitability after adjusting the habitability of the representative related species using the adjustment coefficient is not greater than the habitability of the interacting species (low inhabitability species) for that representative related species, the habitability of the interacting species is used as the corrected habitability as is. On the other hand, if the habitability after adjustment of the representative related species is greater than the habitability of the interacting species for that representative related species, the adjusted habitability of the representative related species is used as the corrected habitability.

[0160] <Third Configuration Example of Calculation Unit 42>

[0161] FIG. 19 is a block diagram showing a third example of the configuration of the calculation unit 42 in FIG.

[0162] In the figure, parts corresponding to those in FIG. 7 are given the same reference numerals, and the description thereof will be omitted below as appropriate.

[0163] 19, the calculation unit 42 includes an interacting species identification unit 51 , an observation point identification unit 52 , a habitat possibility calculation unit 53 , an index value calculation unit 54 , an index value acquisition unit 111 , and an index value integration unit 112 .

[0164] 19 is the same as the case of Fig. 7 in that it has components from an interacting species identification unit 51 to an index value calculation unit 54. However, the calculation unit 42 of Fig. 19 is different from the case of Fig. 7 in that it is newly provided with an index value acquisition unit 111 and an index value integrating unit 112.

[0165] The index value acquisition unit 111 acquires a diversity index value of a type different from the diversity index value based on habitability calculated by the index value calculation unit 54 as a diversity index value when a biological species in the biological species list is observed in the target area, and supplies the acquired diversity index value to the index value integration unit 112. The diversity index value based on habitability calculated by the index value calculation unit 54 is also referred to as a first index value. The diversity index value of a type different from the first index value acquired by the index value acquisition unit 111 is also referred to as a second index value.

[0166] The index value integrating unit 112 is supplied with the second index value from the index value acquiring unit 111, as well as the first index value from the index value calculating unit 54. The index value integrating unit 112 calculates an integrated index value by integrating the first index value from the index value calculating unit 54 and the second index value from the index value acquiring unit 111, and supplies this to the generating unit 43 ( FIG. 6 ) as the (final) diversity index value of the target area. The integration of the first index value and the second index value can be achieved, for example, by multiplying the first index value by the second index value.

[0167] The integrated index value, which is a combination of a first index value, which is a diversity index value based on habitability, and a second index value, which is a diversity index value of a different type from the first index value, is influenced by the evaluation result of the biodiversity of the target site from the perspective of habitability (first index value) and the evaluation result of the biodiversity of the target site from a perspective other than habitability (second index value). Therefore, the integrated index value can be obtained by simultaneously evaluating the biodiversity of the target site from different perspectives (perspectives).

[0168] In addition, in addition to the first index value and the second index value, the index value integration unit 112 can further integrate one or more types of diversity index values ​​that are different from the first index value and the second index value.

[0169] FIG. 20 is a diagram illustrating an example of the second index value acquired by the index value acquisition unit 111 in FIG.

[0170] FIG. 20 shows an example of an interaction network for the species in the species list.

[0171] The interaction network for the species in the species list represents interactions that occur between the species in the species list. The interaction network for the species in the species list is a network in which the species in the species list and the interacting species that interact with them are nodes, and the interactions that occur between the species in the species list and the interacting species are links (edges). In Figure 20, the species in the species list (hereinafter also referred to as list species) are represented by black circle nodes, and the interacting species are represented by white circle nodes.

[0172] The index value acquisition unit 111 can calculate a second index value as a diversity index value when the listed species is observed in the target area based on the interaction network for the listed species. The diversity index value calculated based on the interaction network is also called an interaction network-based diversity index value.

[0173] As a diversity index value based on an interaction network, for example, the network density, degree, cluster coefficient, etc. of the interaction network can be adopted.

[0174] The network density of an interaction network is a value corresponding to the total number of links (interactions) in the interaction network, for example, the total number of links in the interaction network, X1, divided by the total number of combinations of two nodes in the interaction network, X2.

[0175] The degree (number of dimensions) of an interaction network is, for example, the average number of links that nodes in the interaction network have.

[0176] The clustering coefficient of an interaction network is, for example, the average value of the clustering coefficients of the nodes. The clustering coefficient of a node N is calculated by dividing the total number of triangles, n(n-1) / 2, whose vertices are the node N and any two other nodes connected to the node N by the total number of triangles whose vertices are the node N and any two other nodes, where n is the number of links the node N has.

[0177] It should be noted that the second index value is not limited to the diversity index value based on the interaction network.

[0178] In this specification, the processing performed by a computer according to a program does not necessarily have to be performed in chronological order according to the order described in the flowchart. In other words, the processing performed by a computer according to a program also includes processing that is executed in parallel or individually (for example, parallel processing or object-based processing).

[0179] The program may be processed by a single computer (processor), or may be distributed among multiple computers. Furthermore, the program may be transferred to and executed on a remote computer.

[0180] Furthermore, in this specification, a system refers to a collection of multiple components (devices, modules (components), etc.), regardless of whether all of the components are contained in the same housing. Therefore, multiple devices housed in separate housings and connected via a network, and a single device housed in a single housing with multiple modules, are both systems.

[0181] It should be noted that the embodiments of the present technology are not limited to the above-described embodiments, and various modifications are possible within the scope of the present technology.

[0182] For example, the present technology can be configured as a cloud computing system in which a single function is shared and processed collaboratively by a plurality of devices via a network.

[0183] Furthermore, each step described in the above flowchart can be executed by one device, or can be shared and executed by a plurality of devices.

[0184] Furthermore, when one step includes multiple processes, the multiple processes included in that one step can be executed by one device or can be shared and executed by multiple devices.

[0185] Furthermore, the effects described in this specification are merely examples and are not limiting, and other effects may also be present.

[0186] This technology may be related to at least Goal 1 "No Poverty," Goal 2 "Zero Hunger," Goal 13 "Climate Action," and Goal 15 "Life on Land" of the Sustainable Development Goals (SDGs) adopted at the United Nations Summit in 2015.

[0187] The Synecoculture® or Synecoculture® technology used in this project increases biodiversity and enables the cultivation of plants by controlling ecosystems so that they can withstand climate change caused by natural disasters such as droughts and landslides. Furthermore, by creating densely mixed plant growth, it increases the amount of greenhouse gas (GHG) fixation and contributes to reducing greenhouse gas emissions by eliminating the need for fertilizers and pesticides.

[0188] The present technology can have the following configurations.

[0189] <1> An information processing device including a calculation unit that calculates a biodiversity-related diversity index value, when one or more predetermined biological species are observed in a target area for which a biodiversity-related diversity index value is to be calculated, based on a habitability that represents the possibility that an interacting species, which is a biological species that interacts with the predetermined biological species, is inhabiting the target area. <2> The information processing device described in <1>, wherein the calculation unit: identifies the interacting species for the predetermined biological species; identifies observation points where the interacting species are observed; calculates the habitability of the interacting species using the observation points of the interacting species; and calculates the biodiversity index value based on the habitability. <3> The information processing device described in <2>, wherein the calculation unit: calculates a probability distribution of the presence probability of the interacting species being present at each point using the observation points of the interacting species; and sets the presence probability in the target area from the probability distribution as the habitability of the interacting species. <4> The information processing device described in <3>, wherein the calculation unit calculates the probability distribution using ecological niche modeling. <5> The information processing device according to <2>, wherein the calculation unit sets the habitability of the interacting species based on a distance and / or environmental relationship between the target area and the observation point of the interacting species. <6> The information processing device according to <5>, wherein the calculation unit sets the habitability indicating that the closer the target area and the observation point are in distance and / or environment, the more likely an interacting species observed at the observation point is to inhabit the target area. <7> The information processing device according to <5> or <6>, wherein the calculation unit sets the habitability of the interacting species based on whether the target area and the observation point are within a predetermined distance, are in the same region, the same country, or belong to the same climatic zone. <8> The information processing device according to any of <1> to <7>, wherein the calculation unit corrects the habitability and calculates the diversity index value based on the corrected habitability. <9> The information processing device according to <8>, wherein the calculation unit corrects the habitability below a threshold.<10> The information processing device described in <9>, wherein the calculation unit corrects the habitability that is equal to or less than the threshold value to the habitability of a closely related species of the interacting species relative to the habitability. <11> The information processing device described in <10>, wherein, when the habitability of the closely related species is higher than the habitability of the interacting species, the calculation unit corrects the habitability of the interacting species to the habitability of the closely related species. <12> The information processing device described in <11>, wherein, when the habitability of the closely related species is adjusted by a predetermined adjustment coefficient and the adjusted habitability is higher than the habitability of the interacting species, the calculation unit corrects the habitability of the interacting species to the adjusted habitability. <13> The information processing device described in any of <1> to <12>, wherein the calculation unit calculates an integrated index value that integrates the diversity index value based on the habitability and other diversity index values ​​of a type different from the diversity index value. <14> The information processing device according to <13>, wherein the other diversity index value is a diversity index value based on an interaction network in which the predetermined biological species and the interacting species are nodes and interactions occurring between the predetermined biological species and the interacting species are links. <15> The information processing device according to <14>, wherein the other diversity index value is a network density, degree, or cluster coefficient of the interaction network. <16> The information processing device according to any of <1> to <15>, wherein the predetermined biological species is a plant species. <17> The information processing device according to any of <1> to <16>, further comprising an acquisition unit that acquires a biological species list in which the predetermined biological species is described, transmitted from a terminal. <18> The information processing device according to any of <1> to <17>, further comprising a generation unit that generates a presentation user interface (UI) that presents the diversity index value. <19> An information processing method, comprising: calculating a diversity index value related to biodiversity when one or more specified biological species are observed in a target area for which a diversity index value related to biodiversity is to be calculated, based on a habitat probability that represents the possibility that an interacting species, which is a biological species that interacts with the specified biological species, is present in the target area.<20> A program for causing a computer to function as a calculation unit that calculates a diversity index value related to biodiversity when one or more specified biological species are observed in a target area for which a diversity index value related to biodiversity is to be calculated, based on a habitat probability that represents the possibility that an interacting species, which is a biological species that interacts with the specified biological species, is present in the target area.

[0190] 10 Information processing system, 11-1 to 11-4 Terminal, 12 Server, 13 DB, 14 Network, 21 Communication unit, 22 Calculation unit, 23 Input / output unit, 24 Storage, 25 Positioning unit, 26 Sensor unit, 31 Communication unit, 32 Calculation unit, 33 Input / output unit, 34 Storage, 41 Acquisition unit, 42 Calculation unit, 43 Generation unit, 51 Interacting species identification unit, 52 Observation point identification unit, 53 Habitat possibility calculation unit, 54 Index value calculation unit, 61 Probability distribution calculation unit, 62 Habitat possibility setting unit, 71 Relationship identification unit, 72 Habitat possibility setting unit, 81 Habitat possibility correction unit, 91 Low habitat species identification unit, 92 Closely related species identification unit, 93 Observation point identification unit, 94 Habitat possibility calculation unit 95 Habitability adjustment unit, 96 Habitability selection unit, 111 Index value acquisition unit, 112 Index value integration unit

Claims

1. An information processing device having a calculation unit that calculates a diversity index value related to biodiversity when one or more specified biological species are observed in a target area for which a diversity index value related to biodiversity is to be calculated, based on a habitat probability that represents the possibility that an interacting species, which is a biological species that interacts with the specified biological species, is inhabiting the target area.

2. The information processing device described in claim 1, wherein the calculation unit: identifies the interacting species for the specified biological species; identifies an observation point where the interacting species was observed; calculates the habitability of the interacting species using the observation point of the interacting species; and calculates the diversity index value based on the habitability.

3. The information processing device described in claim 2, wherein the calculation unit uses the observation points of the interacting species to calculate a probability distribution of the probability of the interacting species being present at each point, and sets the probability of the interacting species being present in the target area based on the probability distribution as the habitat possibility of the interacting species.

4. The information processing device according to claim 3, wherein the calculation unit calculates the probability distribution by ecological niche modeling.

5. The information processing device according to claim 2, wherein the calculation unit sets the habitability of the interacting species based on the distance and / or environmental relationship between the target area and the observation point of the interacting species.

6. The information processing device of claim 5, wherein the calculation unit sets the habitat probability to indicate that the closer the target area and the observation point are in terms of distance and / or environment, the more likely it is that the interacting species observed at the observation point will inhabit the target area.

7. The information processing device described in claim 5, wherein the calculation unit sets the habitability of the interacting species based on whether the target area and the observation point are within a predetermined distance, are in the same region, the same country, or belong to the same climatic zone.

8. The information processing device according to claim 1, wherein the calculation unit corrects the habitability and calculates the diversity index value based on the corrected habitability.

9. The information processing device according to claim 8, wherein the calculation unit corrects the habitability below a threshold value.

10. The information processing device according to claim 9, wherein the calculation unit corrects the habitability below the threshold to the habitability of a species closely related to the interacting species relative to the habitability.

11. The information processing device according to claim 10, wherein the calculation unit corrects the habitability of the interacting species to the habitability of the related species when the habitability of the related species is greater than the habitability of the interacting species.

12. The information processing device described in claim 11, wherein the calculation unit corrects the habitability of the interacting species to the adjusted habitability of the related species when the adjusted habitability is greater than the habitability of the interacting species by adjusting the habitability of the related species by a predetermined adjustment coefficient.

13. The information processing device according to claim 1, wherein the calculation unit calculates an integrated index value by integrating the diversity index value based on the habitability and other diversity index values of a different type from the diversity index value.

14. The information processing device described in claim 13, wherein the other diversity index value is a diversity index value based on an interaction network in which the specified biological species and the interacting species are nodes and interactions occurring between the specified biological species and the interacting species are links.

15. The information processing device according to claim 14, wherein the other diversity index value is the network density, degree, or cluster coefficient of the interaction network.

16. The information processing device according to claim 1, wherein the predetermined biological species is a plant species.

17. The information processing device according to claim 1, further comprising an acquisition unit that acquires a biological species list containing the specified biological species, the biological species list being sent from a terminal.

18. The information processing device according to claim 1, further comprising a generation unit that generates a presentation user interface (UI) that presents the diversity index value.

19. An information processing method that includes calculating a diversity index value related to biodiversity when one or more specified biological species are observed in a target area for which a diversity index value related to biodiversity is to be calculated, based on habitat probability, which represents the possibility that an interacting species, which is a biological species that interacts with the specified biological species, is present in the target area.

20. A program for causing a computer to function as a calculation unit that calculates a diversity index value related to biodiversity when one or more specified biological species are observed in a target area for which a diversity index value related to biodiversity is to be calculated, based on habitat probability, which represents the possibility that an interacting species, which is a biological species that interacts with the specified biological species, may inhabit the target area.

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