Information processing device, information processing method, and program

Abstract

The present technology relates to an information processing device, information processing method, and program which make it possible to appropriately evaluate an ecosystem. An integrated index value obtained by integrating a plurality of types of diversity index values is calculated on the basis of a plurality of types of diversity index values related to biodiversity. The present technology can be applied, for example, when evaluating an ecosystem such as 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 appropriate evaluation of an ecosystem, for example.

[0002] For example, Patent Document 1 describes a technology that proposes combinations of plant species that improve species diversity by employing an evaluation method that gives a high rating to improvements in soil microbiome species diversity. Furthermore, for example, Patent Document 2 describes a technology that outputs vegetation environment improvement information and species diversity improvement information for urban greening plans, i.e., a technology that predicts the effects of urban greening plans, such as the effects of improving green networks and the effects of improving the diversity of inhabiting biological species. However, there is no description of a technology for generating urban greening plans.

[0003] International Publication No. 2023 / 002658 Japanese Patent Application Laid-Open No. 2009-136265

[0004] 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.

[0005] One method for evaluating ecosystems in various locations, including those where traditional farming methods (conventional farming, organic farming, natural farming, etc.) are practiced, as well as those where greening projects are implemented, is to calculate some kind of index value related to the biodiversity of the location (hereinafter also referred to as a diversity index value). This is not limited to Synecoculture (registered trademark) or Synecoculture (registered trademark).

[0006] However, there are various types of diversity index values, and even if one type of diversity index value is good, other types of diversity index values ​​may not be good. Therefore, evaluating an ecosystem using one specific type of diversity index value may not be an appropriate evaluation. For example, if an ecosystem has one type of diversity index value that is good but other types of diversity index values ​​that are not good, evaluating the ecosystem using one good type of diversity index value may result in an incorrect evaluation of the ecosystem.

[0007] This technology was developed in light of these circumstances, and makes it possible to appropriately evaluate ecosystems.

[0008] The information processing device or program of the present technology is an information processing device that has a calculation unit that calculates an integrated index value that integrates multiple types of diversity index values ​​related to biodiversity based on the multiple types of diversity index values, or a program for causing a computer to function as such an information processing device.

[0009] The information processing method of the present technology is an information processing method that includes calculating an integrated index value by integrating multiple types of diversity index values ​​related to biodiversity, based on the multiple types of diversity index values.

[0010] In this technology, an integrated index value is calculated by integrating a plurality of types of diversity index values ​​related to biodiversity, based on the plurality of types of diversity index values.

[0011] The information processing device may be an independent device or an internal block constituting a single device.

[0012] The program can be provided by transmitting it via a transmission medium or by recording it on a recording medium.

[0013] 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. 2 is a diagram illustrating an example hardware configuration of a server 12. FIG. 3 is a diagram illustrating a first example use case of the information processing system 10. FIG. 4 is a diagram illustrating a second example use case of the information processing system 10. FIG. 5 is a block diagram illustrating an example functional configuration of the server 12. FIG. 6 is a block diagram illustrating a first example configuration of a calculation unit 42. FIG. 7 is a flowchart illustrating an example of processing by the server 12. FIG. 8 is a block diagram illustrating an example configuration of an individual index value calculation unit 51. FIG. 9 is a diagram illustrating α diversity, β diversity, and γ diversity. FIG. 10 is a block diagram illustrating an example configuration of a β index value calculation unit 62. FIG. 11 is a diagram illustrating an example of a biological species list. FIG. 12 is a diagram illustrating an example of a list pair table. FIG. 13 is a block diagram illustrating an example configuration of an inhabitation index value calculation unit 64. FIG. 14 is a block diagram illustrating a second example configuration of the calculation unit 42. FIG. 15 is a diagram illustrating an example of generation of a set list by the set list generation unit 91. FIG. 16 is a block diagram illustrating a third example configuration of the calculation unit 42. FIG. 17 is a diagram illustrating an example of combining a fixed list with a set list by the combining unit 111. FIG. 18 is a block diagram illustrating a third example configuration of the calculation unit 42. FIG. 19 is a block diagram illustrating an example of a configuration of the calculation unit 42. Fig. 10 is a diagram showing a display example of a presentation UI. Fig. 11 is a diagram showing a display example of a presentation UI that displays the biological species of a set list represented by a set list mark designated by a user. Fig. 12 is a diagram showing a display example of a presentation UI that displays the biological species of a set list represented by a set list mark designated by a user.

[0014] <One embodiment of an information processing system to which the present technology is applied>

[0015] 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.

[0016] The information processing system 10 calculates an integrated index value by integrating multiple types of biodiversity-related diversity index values ​​based on the multiple types of biodiversity index values. For example, the information processing system 10 calculates an integrated index value for a biological species list in which biological species are described and inhabit a target area for which the integrated index value is to be calculated, as the integrated index value for the biological species list. The information processing system 10 provides the integrated index value to a user.

[0017] 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.

[0018] A diversity index value is an index value related to biodiversity, and any value that has some relationship to biodiversity can be used as a diversity index value. Therefore, a diversity index value includes index values ​​that directly represent biodiversity as well as index values ​​related to biodiversity.

[0019] Indicator values ​​that directly represent biodiversity are values ​​that represent the degree of biodiversity, i.e., species diversity, genetic diversity, and ecosystem diversity. Examples of indicator values ​​that directly represent biodiversity include the number of biological species, the number of genes, and the number of ecosystems in a target area.

[0020] Biodiversity-related indicator values ​​are values ​​that have some correlation with biodiversity or that biodiversity may affect. Examples of biodiversity-related indicator values ​​include the number of interacting species, which are other biological species that interact with (biological) species inhabiting the target area, and the number of interactions between interacting species. Other examples of biodiversity-related indicator values ​​include the number of useful plant species in the target area and indicator values ​​representing the functional diversity of the target area (e.g., the diversity of ecological functions, such as pollinating specific plant species, and physiological functions, such as the expression of specific compounds). Furthermore, indicator values ​​representing the crop yield obtained in the target area, the amount of carbon fixed in the target area, and the intensity of each ecosystem service in the target area (e.g., the health of the water cycle) also fall under biodiversity-related indicator values. Ecosystem service intensity refers to the degree of ecosystem service provision (the degree of enjoyment of ecosystem services). Regarding the relationship between productivity such as yield and biodiversity, for example, it is described in Tilman, David, Forest Isbell, and Jane M. Cowles, "Biodiversity and ecosystem functioning," Annual review of ecology, evolution, and systematics 45 (2014): 471-493 (hereinafter also referred to as Document A) that productivity is correlated with biodiversity.The Abstract of Document A states that "Species diversity is a major determinant of ecosystem productivity, stability, invasibility, and nutrient dynamics. Hundreds of studies spanning terrestrial, aquatic, and marine ecosystems show that high-diversity mixtures are approximately twice as productive as monocultures of the same species, and that this difference increases through time."

[0021] 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.

[0022] 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.

[0023] 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.

[0024] 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.

[0025] 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.

[0026] A user can input necessary information by operating the terminal 11. For example, a user can operate the terminal 11 to input (the name (species name) or the like) of a biological species such as a plant species, animal species, or microbial species that inhabits (grows) in a target area or is (planned to be) introduced into the target area. A user can operate the terminal 11 to input other information necessary for processing by the terminal 11 or the server 12. Note that input of a biological species into the terminal 11 can be performed by inputting the name or the like of the biological species, or by photographing the biological species with the terminal 11. When a biological species is input into the terminal 11 by photographing the biological species with the terminal 11, image recognition of the image obtained by photographing the biological species is performed by the terminal 11 or the server 12, etc., and the biological species shown in the image is recognized (the biological species is identified).

[0027] The terminal 11 transmits (via the network 14) to the server 12 a biological species list describing the biological species (names, etc.) input in response to user operation, and other necessary information. For example, the terminal 11 generates one or more biological species lists, etc. for the target area in response to user operation, and transmits them to the server 12.

[0028] The terminal 11 receives, for example, an image as a presentation UI (user interface) that presents the integrated index value, etc., when a biological species in the biological species list (a biological species whose name is described in the biological species list) inhabits the target area, transmitted from the server 12 (via the network 14). The terminal 11 presents the integrated index value, etc., to the user by, for example, displaying the presentation UI (or outputting it as audio).

[0029] The server 12 calculates an integrated index value by integrating the diversity index values ​​of multiple types of species when the species in the species list inhabit the target area, based on the diversity index values ​​of multiple types of species.

[0030] For example, the server 12 receives a biological species list or the like transmitted from the terminal 11 (via the network 14). The server 12 uses the biological species list or the like to calculate multiple types of diversity index values ​​when the biological species in the biological species list inhabit, and calculates an integrated index value based on the multiple types of diversity index values. The server 12 generates a presentation UI that presents the integrated index value or the like, and transmits it to the terminal 11 (via the network 14).

[0031] 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.

[0032] <Example of hardware configuration of terminal 11 and server 12>

[0033] FIG. 2 is a diagram showing an example of the hardware configuration of the terminal 11. As shown in FIG.

[0034] 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.

[0035] The communication unit 21 functions as a transmitting unit that transmits information via the network 14 and as a receiving unit that receives information.

[0036] 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 .

[0037] 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.

[0038] 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.

[0039] 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.

[0040] 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).

[0041] 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.

[0042] FIG. 3 is a diagram showing an example of the hardware configuration of the server 12.

[0043] 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.

[0044] <Use cases of the information processing system 10>

[0045] FIG. 4 is a diagram illustrating a first example of a use case of the information processing system 10. As shown in FIG.

[0046] In the information processing system 10, a user can input biological species such as plant species, animal species, and microbial species that inhabit a target area, or biological species to be introduced into the target area, by operating the terminal 11. The terminal 11 generates a biological species list that describes the biological species input in response to the user's operation, and transmits the list to the server 12.

[0047] Although various insects, microorganisms, birds, and other organisms may inhabit a target area, it is not realistic to find all of the species that currently inhabit the target area. Therefore, when a user inputs the species that inhabit the target area, the input species can be limited to species that meet certain conditions, such as only plant species, only insect species, or species that can be observed within a certain time period.

[0048] The server 12 calculates a plurality of types of biodiversity index values ​​when the biological species in the biological species list from the terminal 11 inhabit the target area. Furthermore, the server 12 calculates an integrated index value based on the plurality of types of biodiversity index values, and generates a presentation UI that presents the integrated index value, etc.

[0049] The server 12 transmits the presentation UI to the terminal 11, and the terminal 11 presents the integrated index value and the like to the user by displaying the presentation UI from the server 12. The user can use the integrated index value to evaluate the ecosystem of the target area from the perspective of biodiversity when the biological species in the biological species list inhabit it.

[0050] The information processing system 10 can be used, for example, to evaluate the current ecosystem of a certain location, to compare multiple ecosystems from the perspective of biodiversity, and to plan combinations of biological species to introduce into an ecosystem to improve biodiversity.

[0051] When comparing multiple ecosystems from the perspective of biodiversity, it is possible to compare ecosystems in different locations, as well as ecosystems in the same location at different times. For example, if a location where conventional farming methods have been practiced is switched to Synecoculture® or Synecoculture®, it is possible to compare the ecosystem when the conventional farming methods were practiced with the ecosystem after Synecoculture® or Synecoculture® is implemented.

[0052] Figure 4 shows an example of the ecosystem assessment of farms A and B as different locations.

[0053] The user selects farms A and B as target areas, observes the biological species, for example, plant species, that inhabit each of farms A and B, and inputs the observed plant species by operating terminal 11.

[0054] In this case, the server 12 calculates multiple types of diversity index values ​​for each of the farms A and B using the plant species observed by the user, and calculates an integrated index value based on the multiple types of diversity index values. Furthermore, the server 12 generates a presentation UI that presents the integrated index value, etc., and transmits it to the terminal 11.

[0055] In Figure 4, farm A has three fields a1, a2, and a3. Each field is treated as a single biological community, and the index values ​​of alpha diversity, beta diversity, and gamma diversity of farm A as the target area are calculated as multiple types of diversity index values. Similarly, the index values ​​of alpha diversity, beta diversity, and gamma diversity of farm B are calculated as multiple types of diversity index values. Alpha diversity, beta diversity, and gamma diversity will be described later.

[0056] The terminal 11 displays a presentation UI from the server 12. The user can view the integrated index values ​​and the like displayed in the presentation UI to evaluate the ecosystems of each of the farms A and B, and compare the ecosystems of the farms A and B.

[0057] In Figure 4, the presentation UI displays the integrated index values ​​XA and XB of farms A and B, respectively. In addition, a radar chart RA of the index values ​​of α diversity, β diversity, and γ diversity of farm A used in calculating the integrated index value XA is also displayed. In addition, a radar chart RB of the index values ​​of α diversity, β diversity, and γ diversity of farm B used in calculating the integrated index value XB is also displayed.

[0058] FIG. 5 is a diagram illustrating a second example of a use case of the information processing system 10. In FIG.

[0059] FIG. 5 shows an example of a plan for a combination of species to be introduced into a target site.

[0060] The user determines multiple species as candidate species for introduction, which are candidates for species to be introduced into the target area. For example, the user can determine plant species, insect species, soil microbial species, etc. that the user wishes to introduce into the target area as candidate species for introduction.

[0061] The user selects a combination of one or more species from the candidate species for introduction and creates an introduction plan for the combination to be introduced into the target area. In Figure 5, introduction plans A and B are planned.

[0062] The user operates the terminal 11 to input (combinations of) biological species as introduction plans for each of introduction plans A and B.

[0063] In this case, the server 12 calculates multiple types of diversity index values ​​for each of introduction plans A and B when the combination of biological species represented by those introduction plans inhabits the target area, and calculates an integrated index value based on the multiple types of diversity index values. Furthermore, the server 12 generates a presentation UI that presents the integrated index value, etc., and transmits it to the terminal 11.

[0064] In Figure 5, the target site has three fields a1, a2, and a3, similar to farm A in Figure 4. Each field is treated as a single biological community, and the index values ​​of alpha diversity, beta diversity, and gamma diversity of the target site are calculated as multiple types of diversity index values. Similarly, for introduction plan B, the index values ​​of alpha diversity, beta diversity, and gamma diversity of the target site are calculated as multiple types of diversity index values.

[0065] The terminal 11 displays a presentation UI from the server 12. The user can view the integrated index values ​​and the like displayed in the presentation UI to evaluate the ecosystem of the target area when the combinations of biological species in introduction plans A and B are introduced into the target area. The user can also compare the ecosystem of the target area when the combinations of biological species in introduction plans A and B are introduced into the target area. Furthermore, this comparison makes it possible to determine an introduction plan that will improve biodiversity (allowing the design of an ecosystem with high biodiversity) from introduction plans A and B.

[0066] 5, the presentation UI displays integrated index values ​​XA and XB for implementation plans A and B, respectively (integrated index values ​​for the target area when implementation plans A and B are implemented in the target area). Furthermore, a radar chart RA of the index values ​​of α-diversity, β-diversity, and γ-diversity for implementation plan A, which were used to calculate integrated index value XA, is also displayed. Furthermore, a radar chart RB of the index values ​​of α-diversity, β-diversity, and γ-diversity for implementation plan B, which were used to calculate integrated index value XB, is also displayed.

[0067] The integrated index value, which integrates multiple types of diversity index values, allows for evaluation of ecosystems from a multidimensional perspective of biodiversity, enabling appropriate evaluation of ecosystems.

[0068] For example, the present inventors have confirmed that there is a tendency for a trade-off between the index values ​​of alpha diversity and the index values ​​of beta diversity. Therefore, even if one of the index values ​​of alpha diversity and beta diversity is good, the other index value may not be good. Therefore, evaluating an ecosystem based on only one of the index values ​​of alpha diversity and beta diversity may lead to an incorrect evaluation.

[0069] On the other hand, when an ecosystem is evaluated using an integrated index value calculated based on multiple types of diversity index values, including index values ​​for alpha diversity and beta diversity, an ecosystem with good index values ​​for both alpha diversity and beta diversity can be appropriately evaluated as an ecosystem with high biodiversity.

[0070] <Example of functional configuration of server 12>

[0071] FIG. 6 is a block diagram showing an example of the functional configuration of the server 12.

[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 (one or more) biological species lists about the target area by receiving them from the terminal 11 .

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

[0076] The calculation unit 42 uses the biological species list etc. from the acquisition unit 41 to calculate an integrated index value that integrates multiple types of diversity index values ​​based on multiple types of diversity index values ​​when biological species in the biological species list inhabit the target area, and supplies the integrated index value to the generation unit 43. The calculation unit 42 can supply to the generation unit 43 information other than the integrated index value, for example, the diversity index value used to calculate the integrated index value, the biological species list from the acquisition unit 41, and other necessary information that can be used for presentation by the presentation UI.

[0077] The calculation unit 42 calculates multiple types of diversity index values ​​when biological species in the biological species list inhabit a target area. Each diversity index value among the multiple types of diversity index values ​​is also referred to as an individual index value. The calculation unit 42 calculates an integrated index value by integrating the multiple types of individual index values ​​as the multiple types of diversity index values. In other words, the calculation unit 42 calculates an integrated index value by integrating the multiple types of individual index values ​​based on the multiple types of individual index values ​​as the multiple types of diversity index values.

[0078] Here, the higher the biodiversity, the larger the individual and integrated index values. However, it is also possible to adopt individual index values ​​that are smaller the higher the biodiversity. The same applies to the integrated index value.

[0079] As an integration method for integrating multiple types of individual index values, a method can be used that combines multiple types of individual index values ​​into a single value, such as a function (calculation) that uses multiple types of individual index values ​​as arguments and outputs a single scalar value. In particular, an integration method can be used that results in a large integrated index value (or a small integrated index value) when there are many large individual index values, and a small integrated index value (or a large integrated index value) when there are many small individual index values. For example, multiplication, addition, etc. can be used as the integration method. That is, the multiplication value or average value of multiple types of individual index values ​​can be used as the integrated index value. When the multiplication value (or a value similar to the multiplication value) of multiple types of individual index values ​​is used as the integrated index value, the integrated index value can be considered as an index value that represents the balance of multiple types of individual index values. That is, the integrated index value, which is the multiplication value of multiple types of individual index values, will be extremely large when all of the multiple types of individual index values ​​are large, but will not be extremely large when even one type of small individual index value is present. Therefore, the integrated index value, which is the product of multiple types of individual index values, can be considered to be an index value that increases when multiple types of individual index values ​​increase in a balanced manner.

[0080] The generation unit 43 generates a presentation UI that presents the integrated index value and the like from the calculation unit 42 and transmits the UI to the terminal 11 .

[0081] <First Configuration Example of Calculation Unit 42>

[0082] FIG. 7 is a block diagram showing a first example of the configuration of the calculation unit 42 in FIG.

[0083] In FIG. 7, the calculation unit 42 includes an individual index value calculation unit 51 and an integrated index value calculation unit 52 .

[0084] The individual index value calculation unit 51 is supplied with (one or more) biological species lists for the target area from the acquisition unit 41 ( FIG. 6 ). The individual index value calculation unit 51 uses the biological species list from the acquisition unit 41 to calculate multiple types of individual index values ​​as multiple types of diversity index values ​​when biological species in the biological species list inhabit the target area, and supplies these to the integrated index value calculation unit 52.

[0085] The integrated index value calculation unit 52 calculates an integrated index value based on the multiple types of individual index values ​​from the individual index value calculation unit 51, and supplies the calculated integrated index value to the generation unit 43 (FIG. 6).

[0086] FIG. 8 is a flowchart illustrating an example of processing by the server 12 of FIG.

[0087] In step S11, the acquisition unit 41 of the server 12 acquires the biological species list and the like transmitted from the terminal 11, and supplies it to the calculation unit 42, and the process proceeds to step S12.

[0088] In step S12, the calculation unit 42 uses the biological species list etc. from the acquisition unit 41 to calculate an integrated index value when a biological species in the biological species list inhabits the target area.

[0089] In step S12, first, in step S21, the individual index value calculation unit 51 of the calculation unit 42 (FIG. 7) calculates multiple types of individual index values ​​as multiple types of diversity index values ​​when biological species in the biological species list from the acquisition unit 41 inhabit the target site. The individual index value calculation unit 51 supplies the multiple types of individual index values ​​to the integrated index value calculation unit 52, and the process proceeds from step S21 to step S22.

[0090] In step S22, the integrated index value calculation unit 52 calculates an integrated index value by integrating the multiple types of individual index values ​​from the individual index value calculation unit 51, based on the multiple types of individual index values.

[0091] The calculation unit 42 supplies the integrated index value calculated in step S12 as described above to the generation unit 43, and the process proceeds to step S13.

[0092] In step S13 , the generation unit 43 generates a presentation UI that presents the integrated index value and the like from the calculation unit 42 , and transmits the UI to the terminal 11 .

[0093] <Configuration example of individual index value calculation unit 51>

[0094] FIG. 9 is a block diagram showing an example of the configuration of the individual index value calculation unit 51 shown in FIG.

[0095] The individual index value calculation unit 51 has a plurality of calculation units that calculate various types of individual index values. For example, the individual index value calculation unit 51 has an α index value calculation unit 61, a β index value calculation unit 62, a γ index value calculation unit 63, and a habitat index value calculation unit 64.

[0096] Each calculation unit that constitutes the individual index value calculation unit 51, for example, the α index value calculation unit 61 to the habitat index value calculation unit 64, is supplied with a list of (one or more) biological species for the target area from the acquisition unit 41 (Figure 6).

[0097] The α index value calculation unit 61 calculates an α index value that represents α diversity, which is one type of diversity index value when a biological species in the biological species list from the acquisition unit 41 is observed in the target area, and supplies it to the integrated index value calculation unit 52 (Figure 7) as one type of individual index value.

[0098] The β index value calculation unit 62 calculates a β index value that represents β diversity, which is one type of diversity index value when a biological species from the biological species list from the acquisition unit 41 is observed in the target area, and supplies it to the integrated index value calculation unit 52 as one type of individual index value.

[0099] The gamma index value calculation unit 63 calculates a gamma index value that represents gamma diversity, which is one type of diversity index value when a biological species from the biological species list from the acquisition unit 41 is observed in the target area, and supplies it to the integrated index value calculation unit 52 as one type of individual index value.

[0100] The habitat index calculation unit 64 calculates a diversity index based on habitat possibility (hereinafter also referred to as habitat index), which is one type of diversity index when a biological species in the biological species list from the acquisition unit 41 is observed in the target area. The habitat index calculation unit 64 supplies the habitat index to the integrated index calculation unit 52 as one type of individual index. Habitat possibility and habitat index will be described later.

[0101] The individual index values ​​calculated by the individual index value calculation unit 51 are not limited to the α index value, β index value, γ index value, and habitat index value. The individual index value calculation unit 51 can calculate any number of types of individual index values.

[0102] That is, for example, the individual index value calculation unit 51 can calculate only two or three types of individual index values ​​instead of all four types of individual index values, i.e., the α index value, the β index value, the γ index value, and the habitat index value. Also, for example, the individual index value calculation unit 51 can calculate types of individual index values ​​other than the α index value, the β index value, the γ index value, and the habitat index value.

[0103] Other types of individual index values ​​include, for example, the number of interacting species, the number of interactions with interacting species, the number of useful plant species (one of the index values ​​representing the diversity of useful plants), functional diversity, crop yield, carbon fixation amount, and the intensity of each ecosystem service, as mentioned above.

[0104] The type of individual index value calculated by the individual index value calculation unit 51, i.e., the type of individual index value used to calculate the integrated index value, can be set, for example, by the server 12 or by the user operating the terminal 11.

[0105] Note that individual index values ​​may be diversity index values, i.e., index values ​​related to biodiversity, and may also be index values ​​related to ecosystem properties other than biodiversity. For example, with regard to biological functions, closely related species may have different functions, and distantly related species may have the same or similar functions, so an index value representing functional diversity is also an index value showing the functional properties of a biological community.

[0106] Furthermore, the multiple types of individual index values ​​calculated by the individual index value calculation unit 51 can include individual index values ​​that tend to have a trade-off relationship, such as an α index value and a β index value.

[0107] <Alpha diversity, beta diversity, gamma diversity>

[0108] FIG. 10 is a diagram illustrating α diversity, β diversity, and γ diversity.

[0109] 10, farm A as a target site has two fields a1 and a2. The field a1 is inhabited by biological species s1, s2, and s3, and the field a2 is inhabited by biological species s2, s4, s5, and s6.

[0110] Alpha diversity corresponds to the number of biological species in a field as a biological community of the target area. The alpha index value representing such alpha diversity can be, for example, the number of species in the field. Furthermore, if the number of individuals of each species in the field is known, the alpha index value can be the Shannon-Wiener diversity index, which counts the number of species in the field based on weights corresponding to the number of individuals of each species.

[0111] For example, if the number of species of biological species is used as the α index value, in Figure 10, the α index value for field a1 will be 3, which is the number of species of biological species s1, s2, and s3, and the α index value for field a2 will be 4, which is the number of species of biological species s2, s4, s5, and s6. As the α index value for farm A as the target area, for example, a value obtained by combining the α index values ​​of fields a1 and a2 owned by farm A, such as an average value, can be used.

[0112] Beta diversity corresponds to the number of unique species that inhabit only one of two fields (hereinafter referred to as a field pair) that make up the biological community of the target area. Examples of beta index values ​​that represent such beta diversity include the number of species that are not common to the two fields in the field pair, and the Jaccard coefficient, which indicates the degree of similarity between the combinations of species that inhabit each of the two fields in the field pair.

[0113] For example, if the number of biological species that are not common to the two fields in a field pair is used as the β index value, the β index value for the combination of fields a1 and a2 as a field pair in Figure 10 will be 5, which is the number of species s1 and s2 that inhabit only field a1 and the number of species s4, s5, and s6 that inhabit only field a2. As the β index value for farm A as the target area, for example, a value obtained by combining the β index values ​​of all possible field pairs that can be constituted by the fields owned by farm A, such as the average value, can be used.

[0114] The gamma diversity corresponds to the number of biological species in the entire target area. As the gamma index value representing such gamma diversity, for example, a value similar to the alpha diversity can be adopted.

[0115] For example, if the number of species of biological species is used as the gamma diversity, in FIG. 10, the gamma index value of farm A as the target site will be 6, which is the number of species of biological species s1, s2, s3, s4, s5, and s6.

[0116] Here, in the individual index value calculation unit 51 of Figure 9, the calculation units for each individual index value, for example, the α index value calculation unit 61 to the habitat index value calculation unit 64, can calculate the α index value, β index value, γ index value, and habitat index value, respectively, by considering the biological species in one biological species list transmitted from the terminal 11 for the target area to be biological species that inhabit one field as one biological community in the target area.

[0117] In this case, of the α index value, β index value, γ index value, and habitat index value, the α index value, γ index value, and habitat index value can be calculated whether there is one or multiple biological species lists for the target area transmitted from the terminal 11. The β index value requires a field pair for its calculation, and therefore can be calculated when there are multiple biological species lists for the target area transmitted from the terminal 11. Therefore, the β index value is not calculated when there is only one biological species list for the target area transmitted from the terminal 11.

[0118] Alpha diversity, beta diversity, and gamma diversity are described, for example, in Monleon-Getino, Toni, Clara I. Rodriguez-Casado, and Pablo Emilio Verde. "Shannon entropy ratio, a Bayesian biodiversity index used in the uncertainty mixtures of metagenomic populations." J Adv Stat 4.4 (2019): 23-49.

[0119] <Configuration example of β index value calculation unit 62>

[0120] FIG. 11 is a block diagram showing an example of the configuration of the β index value calculation unit 62 shown in FIG.

[0121] In FIG. 11 , the β index value calculation unit 62 includes a list pair generation unit 71 and an index value calculation unit 72 .

[0122] The list pair generation unit 71 is supplied with (one or more) biological species lists for the target location from the acquisition unit 41 (FIG. 6). If there is only one biological species list for the target location supplied to the list pair generation unit 71, the β index value calculation unit 62 does not perform any further processing and does not calculate a β index value.

[0123] When multiple biological species lists for a target location are supplied to the list pair generation unit 71, the list pair generation unit 71 generates all possible combinations of two biological species lists (hereinafter also referred to as list pairs) from the multiple biological species lists. The list pair generation unit 71 supplies (information about) the list pairs to the index value calculation unit 72.

[0124] The index value calculation unit 72 calculates the β index value for each list pair (field pair), assuming that the biological species in the two biological species lists as each list pair from the list pair generation unit 71 are biological species that inhabit the two fields as the field pair, respectively.

[0125] FIG. 12 is a diagram showing an example of a biological species list.

[0126] The biological species list contains the name of the biological species, for example, its scientific name. A list ID (identification information) that identifies the biological species list can be assigned to the biological species list.

[0127] FIG. 13 is a diagram illustrating an example of a list pair table.

[0128] The list pair generation unit 71 generates all possible combinations of list IDs of two biological species lists from the list IDs of the multiple biological species lists from the acquisition unit 41, and generates a list pair table that lists these combinations. The list pair generation unit 71 supplies the list pair table to the index value calculation unit 72 ( FIG. 11 ) as list pair information.

[0129] The index value calculation unit 72 identifies two species lists as a list pair from the combination of list IDs in the list pair table from the list pair generation unit 71, and calculates the β index value of the list pair.

[0130] 13 shows a list pair table when there are three biological species lists from the acquisition unit 41 (terminal 11). In the list pair table, list ID 1 is the list ID of one of the two biological species lists forming the list pair, and list ID 2 is the list ID of the other.

[0131] <Configuration example of habitat index value calculation unit 64>

[0132] FIG. 14 is a block diagram showing an example of the configuration of the habitat index value calculation unit 64 shown in FIG.

[0133] The habitat index calculation unit 64 calculates a diversity index value when a biological species in the biological species list from the acquisition unit 41 (FIG. 6) is observed in the target area, based on habitat probability, which represents the possibility that an interacting species that interacts with a biological species in the biological species list will inhabit the target area. The diversity index value calculated based on habitat probability in this way is the habitat index value.

[0134] In FIG. 14, the habitat index calculation unit 64 has an interacting species identification unit 81 , an observation point identification unit 82 , a habitat possibility calculation unit 83 , and an index calculation unit 84 .

[0135] The interacting species identification unit 81 is supplied with the biological species list from the acquisition unit 41 ( FIG. 6 ). The interacting species identification unit 81 refers to 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 names) to the observation point identification unit 82. Here, the DB 13 stores, for each biological species, interaction information that associates the biological species (such as names), interacting species (such as names) that are other biological species that interact with that biological species, and the interaction (such as names).

[0136] The observation point identification unit 82 refers to the DB 13, and for each interacting species from the interacting species identification unit 81, identifies (location information of) the observation point where that interacting species was observed, and supplies this to the habitability calculation unit 83. Here, the DB 13 stores, for each biological species, observation point information that associates the biological species with (location information of) the observation point where that biological species (inhabitation) was observed. There is not necessarily only one observation point for a certain biological species.

[0137] The habitability calculation unit 83 is supplied with the observation points of each interacting species from the observation point identification unit 82, as well as with target site information. The target site information is location information of the target site, and is transmitted from the terminal 11 to the server 12 in response to a user operation. The target site information from the terminal 11 is acquired by the acquisition unit 41 and supplied to the habitability calculation unit 83.

[0138] The habitability calculation unit 83 refers to the DB 13 as needed, and calculates the habitability of each interacting species in the target location using the observation location of each interacting species from the observation location identification unit 82 and the target location information from the acquisition unit 41, and supplies the calculated habitability to the index value calculation unit 84. Habitability is information that represents the possibility that a certain biological species will inhabit a certain location. For example, values ​​that represent the probability (presence probability) that a certain biological species will inhabit (exist) at a certain location, or the likelihood (likelihood) that a certain biological species will exist at a certain location can be used as the habitability.

[0139] The index value calculation unit 84 calculates a habitat index value for the target area based on the habitat possibility of each interacting species from the habitat possibility calculation unit 83, and supplies the calculated value to the generation unit 43 (FIG. 6).

[0140] The habitability calculation unit 83 can calculate a probability distribution of the probability of the existence of interacting species at each point (probability distribution of interacting species) using, for example, the observation points of interacting species from the observation point identification unit 82. The probability distribution of interacting species can be calculated, for example, by ecological niche modeling. For example, a modeling method called Maxent can be used as ecological niche modeling.

[0141] For example, the habitability calculation unit 83 can set, for each interacting species, 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.

[0142] In this case, the index value calculation unit 84 can calculate, for example, the total (sum) value of the habitability of each interacting species as the habitat index value for the target area. This habitat index value for the target area depends on the number of interacting species and the habitability of each interacting species in the target area, and represents (a value equivalent to) the expected value of the number of interacting species. Note that the number of interacting species depends in part on the number of species in the biological species list, so the habitat index value that depends on the number of interacting species can also be said to depend on the number of species in the biological species list.

[0143] Additionally, the habitability calculation unit 83 can, for example, use the observation point of each interacting species and the target site information to identify relationship information that indicates the distance and / or environmental relationship (distance proximity (distance) or / and environmental proximity) between the target site and the observation point. For example, it can identify as relationship information whether the target site and the observation point are within a predetermined distance (e.g., 100 km) (or the same region of the same country). It can also identify as relationship information whether the target site and the observation point are in the same country or whether they belong to the same climate zone (e.g., whether they are in the same climate zone according to the Köppen climate classification).

[0144] Here, the observation point of the interacting species is not limited to one point. If there are multiple observation points of the interacting species, when identifying the relationship information, for example, the observation point of the interacting species that is closest to the target location or the observation point in the environment closest to the environment of the target location can be used.

[0145] The habitability calculation unit 83 can set a habitability that indicates the possibility that an interacting species observed at an observation point will inhabit a 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). For example, the closer the target area and the observation point are to each other in terms of distance and / or environment, the more likely it is that an interacting species observed at the observation point will inhabit the target area.

[0146] In this case, the index value calculation unit 84 can calculate the total (sum) of the habitability of each interacting species as the habitat index value of the target area. This habitat index value of the target area also depends on the number of interacting species and the habitability of each interacting species in the target area, and represents the expected number of interacting species.

[0147] As described above, the habitat index value of a target site is calculated depending on the possibility of interacting species occupying the site. Therefore, when calculating the habitat index value, greater consideration is given to interacting species that inhabit the vicinity of the target site, while less consideration is given to interacting species that do not inhabit the vicinity of the target site. As a result, the habitat 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 expected to inhabit), and therefore accurately represents biodiversity from the perspective of interactions.

[0148] The integrated index value calculation unit 52 in Figure 7 can calculate an integrated index value by integrating two, three, or four of the four types of individual index values, for example, the α index value, β index value, γ index value, and habitat index value described above, based on those two, three, or four individual index values.

[0149] The integration of a plurality of individual index values ​​is performed after normalizing the individual index values ​​as necessary.

[0150] For example, when the Jaccard coefficient is used as the β index value, normalization is not required because the Jaccard coefficient is a normalized value.

[0151] Furthermore, for example, when a genus is adopted as the α index value, the β index value, and the γ index value, the α index value, the β index value, and the γ index value are normalized by dividing them by the γ index value, for example.

[0152] The habitat index value is normalized, for example, by dividing it by the total number of interacting species.

[0153] For example, when an integrated index value integrating the α index value and the β index value is calculated by multiplication, the integrated index value integrating the α index value and the β index value is calculated as the average value of the normalized α index value of each biological species list for the target area (the α index value of the fields in which the biological species in the biological species list live) multiplied by the average value of the normalized β index value of each list pair of the biological species list for the target area (the β index value of the two fields (field pairs) in which the biological species in the two biological species lists live as a list pair). For example, if the average value of the normalized α index value of each biological species list for the target area is 0.4 and the average value of the normalized β index value of each list pair of the biological species list for the target area is 0.6, then the integrated index value calculated is 0.024.

[0154] <Second Configuration Example of Calculation Unit 42>

[0155] FIG. 15 is a block diagram showing a second example of the configuration of the calculation unit 42 in FIG.

[0156] 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.

[0157] 15, the calculation unit 42 includes an individual index value calculation unit 51, an integrated index value calculation unit 52, a set list generation unit 91, and a set list selection unit 92.

[0158] Therefore, the calculation unit 42 in Figure 15 is similar to the case in Figure 7 in that it has an individual index value calculation unit 51 and an integrated index value calculation unit 52, but differs from the case in Figure 7 in that it has a set list generation unit 91 and a set list selection unit 92 newly provided.

[0159] The calculation unit 42 in FIG. 7 calculates an integrated index value when a biological species in the biological species list inhabits the target area.

[0160] In contrast, the calculation unit 42 in FIG. 15 calculates, for each of a plurality of set lists each describing one or more biological species generated using the biological species list, the integrated index value for the set list when the biological species in the set list inhabits the target area. Furthermore, the calculation unit 42 in FIG. 15 selects a set list based on the integrated index value of the set list. For example, a set list whose integrated index value is equal to or greater than a threshold, or K set lists whose integrated index values ​​are within the top K, are selected. Here, K is an integer equal to or greater than 1, and when K=1, the set list with the best integrated index value is selected. The threshold and K, which are parameters used when selecting a set list, can be set in advance in the server 12, or can be set in response to a user's operation of the terminal 11, for example.

[0161] When multiple biological species lists for a target area are transmitted from the terminal 11 to the server 12, for example, each of the multiple biological species lists can be used as a single set list as is.

[0162] When a single biological species list for a target area is sent from terminal 11 to server 12, for example, by repeatedly selecting one or more biological species from that single biological species list multiple times, multiple set lists can be generated that describe the selected biological species.

[0163] One or more species lists for the target area are supplied from the acquisition unit 41 ( FIG. 6 ) to the set list generation unit 91. For simplicity of explanation, it is assumed here that the set list generation unit 91 is supplied with one species list for the target area, for example, one species list describing multiple species observed in the target area without distinguishing between fields, or multiple species that are desired to be introduced into the target area.

[0164] The set list generation unit 91 uses the biological species list from the acquisition unit 41 to generate N set lists, each describing one or more biological species, and supplies them to the individual index value calculation unit 51 and the set list selection unit 92.

[0165] When the individual index value calculation unit 51 calculates an α index value or a β index value, the number of sublists M is also supplied to the set list generation unit 91. When the number of sublists M is supplied, the set list generation unit 91 generates a set list consisting of as many sublists as the number of sublists M. A sublist is a list in which biological species are described. The number of sublists M is the number of sublists that make up the set list, and is set, for example, in response to the user's operation of the terminal 11. The number of sublists M can be, for example, the number of fields that serve as biological communities in the target area, or the number of fields that are planned to be constructed in the target area.

[0166] 15 , the individual index value calculation unit 51 calculates multiple types of individual index values ​​for each of the N set lists from the set list generation unit 91, and supplies the multiple types of individual index values ​​for each set list to the integrated index value calculation unit 52. The integrated index value calculation unit 52 calculates an integrated index value for each set list by integrating the multiple types of individual index values ​​for each set list from the individual index value calculation unit 51, and supplies the integrated index value to the set list selection unit 92.

[0167] The set list selection unit 92 selects one or more set lists from the N set lists from the set list generation unit 91 as appropriate set lists describing biological species that are appropriate for improving the biodiversity of the target area, based on the integrated index value for each set list from the integrated index value calculation unit 52. For example, the set list selection unit 92 selects, from the N set lists from the set list generation unit 91, the set list with the best (largest) integrated index value from the integrated index value calculation unit 52 as the appropriate set list.

[0168] The set list selection unit 92 supplies the appropriate set list and the integrated index value of the appropriate set list to the generation unit 43 (FIG. 6).

[0169] In this case, the generation unit 43 generates a presentation UI that presents the appropriate set list from the set list selection unit 92, the integrated index value, and the like.

[0170] The set list can be generated in response to user operations, i.e., by describing the species in the set list in response to the user operations. However, generating a large number of set lists places a heavy burden on the user.

[0171] In contrast, when a single biological species list is used to generate set lists in the set list generation unit 91, a large number of set lists can be generated simply by the user inputting the biological species described in the single biological species list. Furthermore, a large-scale search of such a large number of set lists can be performed to obtain an appropriate set list that improves biodiversity.

[0172] <Setlist generation>

[0173] FIG. 16 is a diagram illustrating an example of the set list generated by the set list generating unit 91 of FIG.

[0174] When the individual index value calculation unit 51 calculates an alpha index value or a beta index value, the number of sublists M is supplied to the set list generation unit 91, and the set list generation unit 91 generates a set list consisting of as many sublists as the number M of sublists.

[0175] The set list generation unit 91 randomly selects one or more biological species from the biological species in the biological species list from the acquisition unit 41, and generates a sublist L1 describing the selected one or more biological species s1, s2, .... The set list generation unit 91 repeats the same biological species selection a number of times, M times the number of sublists, to generate M sublists L1, L2, ..., L#M, and generates a set list LS1 consisting of the M sublists L1 to L#M.

[0176] The set list generating unit 91 repeats the above-described set list generation N times, where N is a number, to generate N set lists LS1, LS2, . . . , LS#N.

[0177] In the individual index value calculation unit 51, for a set list LS#n, multiple types of individual index values ​​such as α index value and β index value are calculated, assuming that the biological species of each sublist L#m that makes up the set list LS#n inhabit each field as a biological community in the target area.

[0178] Here, the habitat index value can be calculated by calculating the habitat index value of each sublist L#m that constitutes the set list LS#n, that is, by assuming that the biological species in the sublist L#m inhabit the field, and calculating the habitat index value of the field for each field. Furthermore, the habitat index value can be calculated by assuming that all biological species in the sublists L#1 to L#M that constitute the set list LS#n inhabit the target area (in any of the fields). When calculating the habitat index value of a field, the average value of the (normalized) habitat index values ​​of the field can be used to calculate the integrated index value.

[0179] The presentation UI that presents the appropriate set list and integrated index values, etc., generated by the generation unit 43, can display the appropriate set list (the names of the species in each sublist L#m that constitutes the appropriate set list) in a form that allows the user to recognize that the species in one sublist L#m that constitutes the appropriate set list are species that should inhabit one field. That is, for example, the presentation UI can display the appropriate set list by dividing it into sublists L#m that constitute the appropriate set list.

[0180] In this case, by looking at the presented UI, the user can recognize the biological species that should be introduced (introduced) into each field in the target area in order to improve biodiversity. For example, if α index value and β index value are used as multiple types of individual index values, the user can recognize the biological species that should be introduced into each field in the target area in order to improve biodiversity from the perspectives of both α diversity and β diversity.

[0181] Note that if the individual index values ​​calculated by the individual index value calculation unit 51 do not include individual index values ​​calculated using the concept of biological community, such as α index values, β index values, etc., the set list generation unit 91 can generate a set list that does not have a sublist and describes biological species selected from the biological species list. A set list that does not have a sublist and describes biological species selected from the biological species list can also be considered to be composed of one sublist describing biological species selected from the biological species list.

[0182] <Third Configuration Example of Calculation Unit 42>

[0183] FIG. 17 is a block diagram showing a third example of the configuration of the calculation unit 42 in FIG.

[0184] In the figure, parts corresponding to those in FIG. 15 are given the same reference numerals, and the description thereof will be omitted below as appropriate.

[0185] 15, the calculation unit 42 includes an individual index value calculation unit 51, an integrated index value calculation unit 52, a set list generation unit 91, a set list selection unit 92, and a combination unit 111.

[0186] Therefore, the calculation unit 42 in Figure 17 is similar to the case of Figure 15 in that it has an individual index value calculation unit 51, an integrated index value calculation unit 52, a set list generation unit 91, and a set list selection unit 92, but differs from the case of Figure 15 in that it has a new combination unit 111.

[0187] The combining unit 111 is supplied with N set lists from the set list generating unit 91 and also with a fixed list from the acquiring unit 41 (FIG. 6).

[0188] When constructing an ecosystem in a target area, there may be species of organisms that the user wants to leave intact among the species already living in the target area. For example, there may be cases where the user wants to leave intact all of the species already living in the target area (species that have been observed in the target area). There may also be cases where the user strongly wishes to introduce species into the target area.

[0189] However, when the calculation unit 42 of the second configuration example of Figure 15 is adopted, the appropriate set list displayed in the presentation UI may not necessarily include biological species that the user wants to keep as is or biological species that the user strongly wishes to introduce.

[0190] Therefore, the calculation unit 42 in Figure 17 is capable of obtaining an appropriate set list that includes biological species that the user wants to keep as they are or biological species that the user strongly wishes to introduce, and other biological species that the user wants to have inhabit the target area permanently (hereinafter also referred to as fixed biological species).

[0191] 17 , the terminal 11 generates a fixed list in addition to the biological species list and transmits it to the server 12. That is, the user inputs fixed biological species by operating the terminal 11. The terminal 11 generates a fixed list describing the fixed biological species input in accordance with the user's operation and transmits it to the server 12. In the server 12, the acquisition unit 41 ( FIG. 6 ) acquires the biological species list and fixed list from the terminal 11 and supplies them to the calculation unit 42.

[0192] In the calculation unit 42, the combination unit 111 is supplied with the fixed list from the acquisition unit 41. Furthermore, the combination unit 111 is supplied with N set lists from the set list generation unit 91. The combination unit 111 combines the fixed list from the acquisition unit 41 with each of the N set lists from the set list generation unit 91. That is, the combination unit 111 includes the fixed species in the fixed list in each of the N set lists, and generates N set lists including the fixed species.

[0193] The combining unit 111 combines the fixed lists with the N set lists, respectively, and supplies the resulting N set lists to the individual index value calculation unit 51 and the set list selection unit 92 .

[0194] Thereafter, in the calculation unit 42 of Figure 17, processing similar to that in Figure 15 is performed on the set list obtained after combining N fixed lists, and the appropriate set list and the integrated index value of that appropriate set list are supplied to the generation unit 43 (Figure 6).

[0195] In this case, the appropriate set list displayed in the presentation UI generated by the generation unit 43 includes fixed species. Therefore, the user can recognize species, including fixed species, as species that should be introduced into each field in the target area to improve biodiversity. For example, if species that already inhabit the target area are adopted as fixed species, an appropriate set list is obtained that describes species that should be newly introduced into the target area to improve biodiversity while maintaining the species already inhabiting the target area. Therefore, the user can recognize additional species that should be introduced into the target area to improve biodiversity.

[0196] 17, the set list selection unit 92 selects an appropriate set list from the set list after the fixed lists are combined, which is supplied from the combination unit 111. However, in Fig. 17, the set list selection unit 92 is supplied with the set lists generated by the set list generation unit 91 before the fixed lists are combined, and from the set lists before the fixed lists are combined, the set list with the best integration index value of the set list after the fixed lists are combined can be selected as the appropriate set list.

[0197] FIG. 18 is a diagram illustrating an example of combining a fixed list with a set list by the combining unit 111. In FIG.

[0198] The fixed list is composed of M sublists L1 to L#M, each of which describes a fixed species, similar to the set list LS#n described in Fig. 16. The fixed species of one sublist L#m constituting the fixed list is, for example, a species that the user wants to have inhabit a certain field in the target area.

[0199] When combining a fixed list with a set list, the species in the set list and the (fixed) species in the fixed list are combined to generate a new set list that describes a collection of unique species.

[0200] For example, when combining a fixed list with a set list LS1, one unselected sublist L#m is randomly selected from the set list LS1, and one unselected sublist L#m' is randomly selected from the fixed list. Then, the fixed species of the sublist L#m' of the fixed list are added to the sublist L#m of the set list LS1.

[0201] The above-described selection of sublists from the set list LS1 and the fixed list, and addition of fixed species from the selected sublist of the fixed list to the selected sublist of the set list LS1 are performed M times. As a result, the fixed list is combined with the set list LS1.

[0202] The fixed list is linked to the other set lists LS2 to LS#N in a similar manner.

[0203] Here, the fixed list may be composed of M sublists L1 to L#M, or, for example, may be composed of one or more but less than M' sublists L1 to L#M' depending on the user's operation. When the fixed list is composed of M' sublists L1 to L#M' (less than M), the selection of sublists from the set list LS#n and the fixed list, and the addition of fixed species from selected sublists of the fixed list to selected sublists of the set list LS#n can be performed M' times. In this case, the addition of fixed species to sublists of the fixed list is performed only to M' sublists out of the M sublists that make up the set list LS#n. Therefore, M-M' sublists out of the M sublists that make up the set list LS#n remain unchanged.

[0204] In addition, when the fixed list is composed of M' sublists L1 to L#M', for example, as described above, fixed species from a selected sublist of the fixed list can be added to a selected sublist of the set list LS#n M' times, and then duplicate selection of sublists can be performed M-M' times to select sublists from the fixed list, and the fixed species from the selected sublist can be added to M-M' sublists in the set list LS#n to which no fixed species have been added.

[0205] <Third Configuration Example of Calculation Unit 42>

[0206] FIG. 19 is a block diagram showing a third example of the configuration of the calculation unit 42 in FIG.

[0207] 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.

[0208] 19, the calculation unit 42 includes an integrated index value calculation unit 52 and an individual index value calculation unit 121.

[0209] Therefore, the calculation unit 42 in Figure 19 is similar to the case in Figure 7 in that it has an integrated index value calculation unit 52, but differs from the case in Figure 7 in that it has an individual index value calculation unit 121 instead of the individual index value calculation unit 51.

[0210] 19, the terminal 11 generates a species dominance list in response to user operation in addition to the biological species list, and transmits it to the server 12. In the server 12, the acquisition unit 41 (FIG. 6) acquires the species list and the species dominance list from the terminal 11 and supplies them to the calculation unit 42. The species dominance list is a list that describes species dominance, which indicates the extent of space occupied by the biological species in the species list in the target area.

[0211] For example, the number of individuals of a biological species can be used as the species dominance. Furthermore, if the biological species is a plant species, the coverage rate, which is the percentage of the target land (surface) that the plant species covers, can be used as the species dominance. By operating the terminal 11, the user can input an actually observed value as the species dominance. Furthermore, if the user is planning to build an ecosystem in the target land, the user can input planned values ​​for the number of individuals and coverage rate of the biological species to be introduced.

[0212] The individual index value calculation unit 121 is supplied with the biological species list and species-by-species dominance list from the acquisition unit 41 ( FIG. 6 ). The individual index value calculation unit 121 uses the biological species list and species-by-species dominance list from the acquisition unit 41 to calculate multiple types of individual index values ​​as multiple types of diversity index values ​​when biological species in the biological species list inhabit the target area, and supplies these to the integrated index value calculation unit 52.

[0213] <Configuration example of individual index value calculation unit 121>

[0214] FIG. 20 is a block diagram showing an example of the configuration of the individual index value calculation unit 121 shown in FIG.

[0215] The individual index value calculation unit 121 has a plurality of calculation units that calculate various types of individual index values, similar to the individual index value calculation unit 51 in Fig. 9. For example, the individual index value calculation unit 121 has an α index value calculation unit 131, a β index value calculation unit 132, a γ index value calculation unit 133, and a habitat index value calculation unit 134.

[0216] Each calculation unit that constitutes the individual index value calculation unit 121, for example, the α index value calculation unit 131 to the habitat index value calculation unit 134, is supplied with a biological species list and a species dominance list for the target area from the acquisition unit 41 (Figure 6).

[0217] The α index value calculation unit 131 calculates an α index value when a biological species in the biological species list from the acquisition unit 41 is observed in the target area based on the species dominance in the species dominance list from the acquisition unit 41, and supplies this as one type of individual index value to the integrated index value calculation unit 52 (Figure 7).

[0218] The β index value calculation unit 132 calculates a β index value when a biological species in the biological species list from the acquisition unit 41 is observed in the target area based on the species dominance in the species dominance list from the acquisition unit 41, and supplies this to the integrated index value calculation unit 52 as one type of individual index value.

[0219] The gamma index value calculation unit 133 calculates a gamma index value when a biological species in the biological species list from the acquisition unit 41 is observed in the target area based on the species dominance in the species dominance list from the acquisition unit 41, and supplies this to the integrated index value calculation unit 52 as one type of individual index value.

[0220] The habitat index value calculation unit 134 calculates a habitat index value when a biological species in the biological species list from the acquisition unit 41 is observed in the target area based on the species dominance in the species dominance list from the acquisition unit 41, and supplies this to the integrated index value calculation unit 52 as one type of individual index value.

[0221] The individual index values ​​calculated by the individual index value calculation unit 121 are not limited to the α index value, β index value, γ index value, and habitat index value. The individual index value calculation unit 121 can calculate any number of types of individual index values, similar to the case described for the individual index value calculation unit 51 in FIG. 9 .

[0222] FIG. 21 is a diagram showing an example of a type dominance list.

[0223] The species dominance list describes the species (names) in the species list as well as the species dominance of each species. In the species dominance list of Fig. 21, coverage is used as the species dominance.

[0224] The species dominance can be described in the species list in association with the species (name). When the species dominance is described in the species list, the species dominance list is not necessary.

[0225] The individual index value calculation unit 121 calculates various individual index values ​​such as the α index value, β index value, γ index value, and habitat index value when a biological species in the biological species list is observed in the target area based on the species dominance in the species dominance list.The α index value, β index value, γ index value, and habitat index value serve as indicators of biodiversity that take into account not only the species composition (species composition) of the target area, but also the space occupied by each biological species in the target area (whether the space in the target area is occupied by each biological species without being biased towards a particular biological species), or the number of individuals of each biological species inhabiting the target area.

[0226] As a method for calculating the α index value and the γ index value based on the species dominance of the biological species in the biological species list, for example, a method using a formula based on the entropy formula, such as the formula for calculating the Shannon-Wiener diversity index (Shannon Index), can be adopted.

[0227] The Shannon-Wiener diversity index can be calculated according to the formula −ΣP(i)×logP(i), where P(i) represents the proportion of the number of individuals of the i-th species, n(i), to the total number of individuals, N, (n(i) / N), and Σ represents the summation across the number of species.

[0228] When calculating the α and γ index values, if a method using an equation based on the entropy equation is adopted, the species abundance can be used instead of P(i) in the equation -ΣP(i) × logP(i).

[0229] As a method for calculating the β index value based on the species dominance of the species in the species list, for example, a method using weighted UniFrac can be adopted. In weighted UniFrac, the differences (similarity) between microorganisms (communities) are calculated using phylogenetic evolution information such as a phylogenetic tree and the number (abundance) of each microorganism. Weighted UniFrac is described, for example, in "Statistical Analysis of Microbiome Data with R" by Yinglin Xia, Jun Sun, and Ding-Geng Chen, published by Springer (https: / / link.springer.com / book / 10.1007 / 978-981-13-1534-3).

[0230] When the weighted UniFrac method is used to calculate the β index value, the species abundance can be used instead of the number of microorganisms.

[0231] One method of calculating the habitat index value based on the species dominance of a species in the species list is to use (multiply, etc.) the species dominance of a species in the species list that interacts with the interacting species as a weight on the habitat probability of the interacting species used to calculate the habitat index value.

[0232] <Presentation UI>

[0233] FIG. 22 is a diagram showing a display example of the presentation UI.

[0234] The presentation UI can display the integrated index value, the appropriate set list, as well as information used in the process of calculating the integrated index value, information obtained in the process of calculating the integrated index value, and information that can be generated from that information.

[0235] For example, the presentation UI can display a graph (hereinafter also referred to as a set list plot graph) in which marks representing a set list are plotted with multiple types of diversity index values ​​calculated by the calculation unit 42 as axes.

[0236] FIG. 22 shows an example of a display of a set list plot graph.

[0237] In the set list plot graph of Figure 22, β index values ​​and γ index values ​​are used as multiple types of diversity index values, with the vertical axis representing the β index value and the horizontal axis representing the γ index value. Furthermore, the set list (Observed + Introduced) obtained by the combining unit 111 of the calculation unit 42 of Figure 17 after combining the fixed lists, i.e., a plurality of N = 10,000 set lists including fixed biological species, are represented by circles (hereinafter also referred to as set list marks) plotted at positions representing the β index value and γ index value of the set list. Note that in the set list plot graph of Figure 22, the number of set list marks is less than N = 10,000, but this is because there are set list marks plotted in the same position.

[0238] According to the set list plot graph of FIG. 22, the user can easily recognize the β index value and γ index value of each set list and compare the β index values ​​and γ index values ​​of different set lists.

[0239] In the set list plot graph of Figure 22, in addition to the set list marks of the set list after the fixed lists are combined, the fixed list (Figure 18) combined into the set list is treated as a single set list and the set list mark PL1 of the fixed list (observed) is plotted.

[0240] In the set list plot graph of Figure 22, the set list represented by the set list mark at the top right has both higher β and γ index values, and therefore a higher integrated index value. The user can easily recognize that a plan to inhabit the target area with the biological species in the set list represented by set list marks PL2 and PL3 at the top right of the set list plot graph, for example, is an appropriate plan (better plan(s)) for improving the biodiversity of the target area.

[0241] On the other hand, in the set list plot graph of Figure 22, the set lists represented by the set list marks at the bottom right, top left, and bottom left have lower beta index values ​​and / or gamma index values, and therefore, the integrated index value is also lower. For example, the set list represented by set list mark PL4 at the bottom right of the set list plot graph has a high gamma index value, and a plan to inhabit the target area with the biological species of that set list appears at first glance to be an appropriate plan for improving biodiversity. However, the set list represented by set list mark PL4 has a low beta index value, and therefore, the integrated index value is also low. From the perspective of beta diversity, the plan to inhabit the target area with the set list represented by set list mark PL4 is an inappropriate plan (worse plan) for improving biodiversity.

[0242] For a set list whose set list mark is plotted on the set list plot graph, the user can check the biological species of that set list. For example, when the user specifies a set list mark on the set list plot graph by clicking, tapping, or other operations, the presented UI displays (information about) the biological species of the set list represented by the set list mark specified by the user.

[0243] 23 and 24 are diagrams showing examples of display of a presentation UI that displays the biological species of a set list represented by a set list mark designated by a user.

[0244] Figure 23 shows an example of a display of the biological species in the set list represented by the set list mark PL2 as a plan suitable for improving biodiversity in the target area of ​​Figure 22. Figure 24 shows an example of a display of the biological species in the set list represented by the set list mark PL4 as a plan unsuitable for improving biodiversity in the target area of ​​Figure 22.

[0245] In Figures 23 and 24, the species names of the biological species in the biological species list used to generate the set list are arranged (row-wise). In Figures 23 and 24, Name represents the Japanese name, and Kingdom through Species represent the phylogenetic classification levels of kingdom, phylum, order, family, genus, and species, respectively. Note that Species also represents the scientific name. SpeciesName represents the scientific name plus the variety name, subspecies name, or cultivar name. Note that in Figures 23 and 24, the biological species are arranged so that biological species that are close in phylogenetic terms are placed close to each other.

[0246] 23 and 24, the number of sublists M is 2, i.e., the set list is made up of two sublists, and whether or not a biological species is included in the two sublists is shown as Presence / Absence 1 and Presence / Absence 2. Therefore, the presentation UIs in Fig. 23 and 24 can be said to present the presence or absence of a biological species in the biological species list in the set list.

[0247] In presence / absence 1 and presence / absence 2 in Figures 23 and 24, if a species in the species list is included in the sublist, it is shown as TRUE, and if a species in the species list is not included in the sublist, it is shown as FALSE.

[0248] Depending on whether or not 1 and whether or not 2 of the presentation UI in Figures 23 and 24 are present, the user can recognize various information about the biological species of the corresponding set list (the set list represented by the set list mark specified by the user when displaying the presentation UI in Figures 23 and 24).

[0249] For example, the user can recognize that the corresponding set list contains biological species for which at least one of the combinations of Presence / Absence 1 and Presence / Absence 2 is TRUE, i.e., the breakdown of biological species in the corresponding set list. Furthermore, the user can recognize and compare the breakdown of biological species (species composition) in different set lists.

[0250] For example, the user can recognize that if there are many combinations of presence / absence 1 and presence / absence 2 in which at least one is TRUE, the gamma index value of the corresponding set list is high.

[0251] For example, the user can recognize that if there are many combinations of presence / absence 1 and presence / absence 2 where both are FALSE, the gamma index value of the corresponding set list is low.

[0252] For example, the user can recognize that if there are many combinations of presence / absence 1 and presence / absence 2 where both are TRUE, the β index value of the corresponding set list is low.

[0253] For example, the user can recognize that if there are many combinations of presence / absence 1 and presence / absence 2 in which one is TRUE and the other is FALSE, the β index value of the corresponding set list is high.

[0254] In the presentation UI of Figure 23, there are many combinations of Presence / Absence 1 and Presence / Absence 2 where at least one is TRUE, and many combinations where one is TRUE and the other is FALSE. Therefore, the user can recognize that both the gamma index value and the beta index value are high, and furthermore, that the integrated index value is high. In addition, the user can recognize that biological species in combinations of Presence / Absence 1 and Presence / Absence 2 where one is TRUE and the other is FALSE are contributing to a high beta index value (and thus to an improvement in biodiversity).

[0255] In the presentation UI of FIG. 24 , there are many combinations of Presence / Absence 1 and Presence / Absence 2 in which at least one is TRUE. However, there are few combinations of Presence / Absence 1 and Presence / Absence 2 in which one is TRUE and the other is FALSE, and there are many combinations in which both are TRUE. Therefore, the user can recognize that the gamma index value is high because there are many combinations of Presence / Absence 1 and Presence / Absence 2 in which at least one is TRUE. Furthermore, the user can recognize that the beta index value is low because there are many combinations of Presence / Absence 1 and Presence / Absence 2 in which both are TRUE. Furthermore, the user can recognize that the low beta index value means that the integrated index value is also low. The user can then recognize that the low integrated index value is caused by biological species in which both Presence / Absence 1 and Presence / Absence 2 are TRUE.

[0256] 23 and 24, as described above, the species in the species list are arranged so that species that are close in phylogenetic classification are placed close to each other. Therefore, for example, it is possible to recognize the tendency of the relationship between the number (fewness) of closely related species in the set list and the low (high) β index value.

[0257] In addition, the presentation UI can also display, for example, a frequency distribution showing the frequency of set lists belonging to each class, with the integrated index value being used as a class.

[0258] The integrated index value can also be corrected as appropriate. For example, the integrated index value can be corrected based on the relationships between the species in the biological species list or set list, or the relationships between the species in the biological species list or set list and the environment of the target area. Specifically, for example, if the species in the biological species list or set list have mutualistic or companion plant relationships, the integrated index value can be corrected in a positive direction. Furthermore, for example, if the environment of the target area, such as soil moisture or climate, is suitable for the habitat of the species in the biological species list or set list (if it is within the conditions for the species to live), the integrated index value can be corrected in a positive direction. On the other hand, for example, if the species in the biological species list or set list have antagonistic relationships, or if the environment of the target area is not suitable for the habitat of the species in the biological species list or set list, the integrated index value can be corrected in a negative direction.

[0259] All or part of the above-described configuration examples can be combined to the extent that no contradictions occur. For example, the calculation unit 42 in Fig. 15 or 17 can use the individual index value calculation unit 121 in Fig. 19 instead of the individual index value calculation unit 51.

[0260] 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).

[0261] 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.

[0262] 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.

[0263] 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.

[0264] 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.

[0265] 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.

[0266] 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.

[0267] Furthermore, the effects described in this specification are merely examples and are not limiting, and other effects may also be present.

[0268] 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.

[0269] 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.

[0270] The present technology can have the following configurations.

[0271] <1> An information processing device comprising a calculation unit that calculates an integrated index value by integrating multiple types of biodiversity-related biodiversity index values ​​based on the multiple types of biodiversity index values. <2> The information processing device described in <1>, wherein the calculation unit calculates the multiple types of biodiversity index values. <3> The information processing device described in <1>, wherein the calculation unit calculates the integrated index value when biological species from a biological species list describing biological species inhabit a target area for which the integrated index value is calculated, as the integrated index value of the biological species list. <4> The calculation unit calculates the multiple types of biodiversity index values ​​when biological species from the biological species list inhabit the target area. <5> The information processing device described in <3>, wherein the calculation unit calculates the multiple types of biodiversity index values ​​when biological species from the biological species list inhabit the target area, based on species dominance that indicates the degree of space occupied by the biological species from the biological species list in the target area. <6> The information processing device according to any one of <3> to <5>, wherein the plurality of types of biodiversity index values ​​are two or more of index values ​​representing α-diversity, β-diversity, γ-diversity, functional diversity, diversity of useful plants, yield, carbon fixation, and intensity of ecosystem services, and a habitat index value calculated based on habitat possibility representing the possibility that interacting species, which are biological species that interact with the biological species in the biological species list, will inhabit the target area. <7> The information processing device according to any one of <3> to <6>, wherein the plurality of types of biodiversity index values ​​include two biodiversity index values ​​that tend to have a trade-off relationship. <8> The information processing device according to any one of <3> to <7>, further comprising: a generation unit that generates a presentation user interface (UI) that presents an integrated index value of the biological species list. <9> The information processing device according to any one of <3> to <8>, further comprising: an acquisition unit that acquires the biological species list transmitted from a terminal.<10> The information processing device described in <1>, wherein the calculation unit calculates an integrated index value for a set list in which biological species are described, as the integrated index value of the set list when biological species in the set list inhabit a target location for which the integrated index value is to be calculated, and selects one or more set lists from a plurality of set lists based on the integrated index value of the set list. <11> The information processing device described in <10>, wherein the calculation unit generates the plurality of set lists using a biological species list in which biological species are described. <12> The information processing device described in <11>, wherein the calculation unit generates the set list including biological species in a fixed list in which biological species are described. <13> The information processing device described in <11> or <12>, wherein the calculation unit selects the set list with the best integrated index value. <14> The information processing device described in any of <11> to <13>, further comprising a generation unit that generates a presentation user interface (UI) that presents the set list selected based on the integrated index value of the set list. <15> The information processing device according to <14>, wherein the generation unit generates the presentation UI that presents an integrated index value of the set list selected based on the integrated index value of the set list. <16> The information processing device according to <14> or <15>, wherein the generation unit generates the presentation UI that presents a graph in which marks representing the set list are plotted with the plurality of types of diversity index values ​​as axes. <17> The information processing device according to any of <14> to <16>, wherein the generation unit generates the presentation UI that presents the presence or absence of a biological species in the biological species list in the set list. <18> The information processing device according to any of <11> to <17>, further comprising an acquisition unit that acquires the biological species list transmitted from a terminal. <19> An information processing method, comprising: calculating, based on a plurality of types of diversity index values ​​related to biodiversity, an integrated index value that integrates the plurality of types of diversity index values. <20> A program that causes a computer to function as a calculation unit that calculates, based on a plurality of types of diversity index values ​​related to biodiversity, an integrated index value that integrates the plurality of types of diversity index values.

[0272] 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 Individual index value calculation unit, 52 Integrated index value calculation unit, 61 α index value calculation unit, 62 β index value calculation unit, 63 γ index value calculation unit, 64 Habitat index value calculation unit, 71 List pair generation unit, 72 Index value calculation unit, 81 Interacting species identification unit, 82 Observation point identification unit, 83 Habitat possibility calculation unit, 84 Index value calculation unit, 91 Set list generation unit, 92 set list selection unit, 111 combination unit, 121 individual index value calculation unit, 131 α index value calculation unit, 132 β index value calculation unit, 133 γ index value calculation unit, 134 habitat index value calculation unit

Claims

1. An information processing device comprising a calculation unit that calculates an integrated index value by integrating multiple types of biodiversity-related diversity index values based on the multiple types of biodiversity-related diversity index values.

2. The information processing device according to claim 1, wherein the calculation unit calculates the plurality of types of diversity index values.

3. The information processing device according to claim 1, wherein the calculation unit calculates the integrated index value of the biological species list as the integrated index value when a biological species in a biological species list in which the biological species are described inhabits the target area for which the integrated index value is calculated.

4. The information processing device according to claim 3, wherein the calculation unit calculates the diversity index values of the plurality of species when the biological species in the biological species list inhabit the target area.

5. The information processing device described in claim 3, wherein the calculation unit calculates the diversity index values of the multiple types of biological species in the biological species list when they inhabit the target area based on a species dominance that indicates the degree of space occupied by the biological species in the biological species list in the target area.

6. The information processing device described in claim 3, wherein the multiple types of diversity index values are two or more of index values representing alpha diversity, beta diversity, gamma diversity, functional diversity, diversity of useful plants, yield, amount of carbon fixation, and intensity of ecosystem services, and habitat index values calculated based on habitat possibility representing the possibility that interacting species, which are biological species that interact with biological species in the biological species list, can inhabit the target area.

7. The information processing device according to claim 3, wherein the plurality of types of diversity index values include two diversity index values that tend to have a trade-off relationship.

8. The information processing device according to claim 3, further comprising a generation unit that generates a presentation UI (user interface) that presents the integrated index values of the biological species list.

9. The information processing device according to claim 3, further comprising an acquisition unit that acquires the biological species list transmitted from a terminal.

10. The information processing device according to claim 1, wherein the calculation unit calculates the integrated index value of the set list as the integrated index value of the set list when the biological species described in the set list inhabit the target area for which the integrated index value is calculated, and selects one or more set lists from a plurality of set lists based on the integrated index value of the set list.

11. The information processing device according to claim 10, wherein the calculation unit generates the plurality of set lists using a biological species list in which biological species are described.

12. The information processing device according to claim 11, wherein the calculation unit generates the set list including the biological species of a fixed list in which the biological species are described.

13. The information processing device according to claim 11, wherein the calculation unit selects the set list with the best integrated index value.

14. The information processing device according to claim 11, further comprising a generation unit that generates a presentation user interface (UI) that presents the set list selected based on the integrated index value of the set list.

15. The information processing device according to claim 14, wherein the generation unit generates the presentation UI that presents the integrated index value of the set list selected based on the integrated index value of the set list.

16. The information processing device according to claim 14, wherein the generation unit generates the presentation UI that presents a graph in which marks representing the set list are plotted with the plurality of types of diversity index values as axes.

17. The information processing device according to claim 14, wherein the generation unit generates the presentation UI that presents the presence or absence of a biological species in the biological species list in the set list.

18. The information processing device according to claim 11, further comprising an acquisition unit that acquires the biological species list transmitted from a terminal.

19. An information processing method comprising calculating an integrated index value by integrating multiple types of biodiversity-related diversity index values based on the multiple types of biodiversity-related diversity index values.

20. A program for causing a computer to function as a calculation unit that calculates an integrated index value by integrating multiple types of biodiversity-related diversity index values based on the multiple types of biodiversity-related diversity index values.

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