A dynamic assessment system for biodiversity resource response mechanisms

Abstract

This invention discloses a dynamic assessment system for biodiversity resource response mechanisms, relating to the field of biodiversity technology. Through a biodiversity assessment value analysis module, the target enterprise's resource monitoring area is divided into sub-regions, and the system obtains species diversity fit values, genetic diversity fit values, ecosystem diversity fit values, and inter-organism interaction fit values ​​for each sub-region within a recent historical period. This multi-dimensional analysis method comprehensively and deeply reflects all aspects of biodiversity, avoiding the limitations of single-indicator assessments. The data collection method determination module determines the biodiversity level of each sub-region based on its resource assessment values ​​within a recent historical period, and then formulates the corresponding data collection method for each sub-region in the current period. This personalized data collection strategy can reasonably adjust the collection intensity and method according to the biodiversity status of different sub-regions.

Description

Technical Field

[0001] This invention relates to the field of bioresource technology, and more specifically to a dynamic assessment system for biodiversity resource response mechanisms. Background Technology

[0002] As society's attention to environmental protection continues to grow, corporate environmental responsibility has become an important component of sustainable development. More and more companies are recognizing the impact of their activities on the ecological environment, including biodiversity, and are facing multifaceted pressures to take measures to reduce negative impacts and actively promote ecological protection. Companies need a scientific and dynamic assessment system to manage and improve their impact on biodiversity; therefore, a dynamic assessment system for biodiversity resource response mechanisms is required.

[0003] Current technologies typically do not tailor collection methods to the biodiversity levels of different regions. This can lead to excessive disturbance or damage to sensitive areas and relatively fragile ecosystems with high biodiversity during resource collection, while insufficient collection may occur in areas with low biodiversity, failing to fully utilize resources and making it difficult to achieve a balance between resource utilization and biodiversity conservation. Clearly, this approach has at least the following problems: 1. Current technologies struggle to personalize collection methods based on resource distribution in different regions. Different ecosystems have unique functions. Wetlands purify water and regulate floods, while forests conserve soil and water and regulate climate. Inappropriate collection methods can damage these ecosystem functions. For example, over-collecting reeds and other plants in wetlands may impair their filtration and purification functions, leading to water quality deterioration. Over-harvesting timber in mountainous forests weakens their water conservation function, increases the risk of soil erosion, and consequently affects downstream ecological environments and water resource utilization. In cases of uneven resource distribution, failure to tailor collection methods to actual resource conditions can lead to resource waste. For example, in some areas, there may be over-collection of a certain resource, while this resource may be more abundant or easier to obtain in other areas. Meanwhile, unreasonable harvesting in some low-resource areas may yield very little useful resources while causing significant damage to the local ecosystem. This is an inefficient way of using resources, and the irrationality of resource distribution and harvesting methods can trigger a series of social problems. Local communities may rely on certain natural resources for their livelihoods; over-harvesting or unreasonable harvesting may deprive them of their means of survival, leading to increased social conflict. For example, fishermen losing income due to overfishing leading to the depletion of fishery resources may trigger social instability. Furthermore, the destruction of resources with cultural value due to unreasonable harvesting will also negatively impact the preservation of local culture.

[0004] 2. Existing technologies often focus on a single dimension or a few indicators to assess biodiversity, such as species numbers and habitat area, while lacking comprehensive consideration of multiple dimensions, including species diversity fit, genetic diversity fit, ecosystem diversity fit, and interbiotic interactions fit. This may result in an incomplete assessment of biodiversity, failing to accurately reflect the true state and changing trends of ecosystems, ignoring the intrinsic connections and interactions between the various components of biodiversity, and most existing assessment techniques are phased or one-off, lacking the ability to monitor biodiversity in a long-term and dynamic manner. Unlike dynamic assessment systems, they cannot conduct continuous assessments at different time points, such as adjacent historical cycles and current cycles, and cannot compare and analyze changes in biodiversity resources in different sub-regions. They struggle to capture subtle changes and short-term fluctuations in biodiversity in a timely manner, thus missing the optimal opportunity for early intervention and protection. Summary of the Invention

[0005] To address the aforementioned technical shortcomings, the purpose of this invention is to provide a dynamic assessment system for biodiversity resource response mechanisms.

[0006] To solve the above-mentioned technical problems, the present invention adopts the following technical solution: The present invention provides a dynamic assessment system for the response mechanism of biodiversity resources, comprising:

[0007] Biological resource assessment value analysis module: It is used to divide the resource monitoring area of ​​the target enterprise into several sub-regions, thereby obtaining the species diversity fit value, genetic diversity fit value, ecosystem diversity fit value and inter-organism interaction fit value of each sub-region in the adjacent historical period, and then analyze the resource assessment value corresponding to each sub-region in the adjacent historical period.

[0008] The data collection method determination module is used to assess the biodiversity level of each sub-region in the adjacent historical period based on the resource assessment value of each sub-region in the adjacent historical period, and then determine the data collection method for each sub-region in the current period, and collect data in each sub-region in the current period according to the determined data collection method.

[0009] Multi-data integration and analysis module: After the target enterprise has completed the collection of resource data in each sub-region of the current period according to the determined collection method, it can obtain the resource change data corresponding to each sub-region of the current period. The resource change data includes the change rate of species diversity fit value, the change rate of genetic diversity fit value, the change rate of ecosystem diversity fit value, and the change rate of inter-organism interaction fit value.

[0010] Regional biological resource assessment module: It is used to analyze the resource change data of each sub-region in the current period to obtain the resource improvement assessment value of each sub-region in the current period, and then assess whether the biological resources of each sub-region in the current period have improved. If the biological resources of a certain sub-region in the current period have not improved, an early warning will be issued.

[0011] Preferably, the specific process for obtaining the species diversity fit value, genetic diversity fit value, interbiotic interaction fit value, and ecosystem diversity fit value corresponding to each sub-region in the immediate historical cycle is as follows:

[0012] A1. Obtain the species richness, number of endemic species, and proportion of rare and endangered species for each sub-region in the immediate historical period, and input the species richness, number of endemic species, and proportion of rare and endangered species for each sub-region in the immediate historical period into the species diversity analysis model, and output the species diversity fit value for each sub-region in the immediate historical period.

[0013] A2. Obtain the allele richness, gene diversity index, and genetic differentiation coefficient of each sub-region in the immediate historical cycle, and input the allele richness, gene diversity index, and genetic differentiation coefficient of each sub-region in the immediate historical cycle into the species diversity analysis model, and output the genetic diversity fit value of each sub-region in the immediate historical cycle.

[0014] A3. Obtain the number of ecosystem types and ecosystem productivity corresponding to each sub-region in the immediate historical period, and input the number of ecosystem types and ecosystem productivity corresponding to each sub-region in the immediate historical period into the ecosystem diversity analysis model, and output the ecosystem diversity fit value corresponding to each sub-region in the immediate historical period.

[0015] A4. Obtain the food web connectivity, interspecific competition intensity, and symbiotic relationship frequency of each sub-region in the immediate historical cycle, and input the food web connectivity, interspecific competition intensity, and symbiotic relationship frequency of each sub-region in the immediate historical cycle into the interbiological interaction analysis model, and output the interbiological interaction fit value of each sub-region in the immediate historical cycle.

[0016] Preferably, the analysis yields resource assessment values ​​for each sub-region immediately adjacent to the historical period. The specific analysis process is as follows:

[0017] The species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and interbiotic interaction fit value corresponding to each sub-region in the immediate historical cycle are respectively denoted as: , , and k represents the number corresponding to each sub-region, and k is a positive integer. Substituting into the calculation formula: In this process, resource assessment values ​​corresponding to each sub-region adjacent to the historical cycle are obtained. ,in, , , , These are the standard species diversity fit values, standard genetic diversity fit values, standard ecosystem diversity fit values, and standard inter-organism interaction fit values ​​corresponding to the defined sub-regions. , , , These are the weighting factors corresponding to the set subregion species diversity fit values, genetic diversity fit values, ecosystem diversity fit values, and inter-organism interaction fit values, respectively.

[0018] Preferably, the specific analysis process for assessing the biodiversity levels of sub-regions corresponding to each sub-region immediately adjacent to the historical period is as follows:

[0019] The resource assessment values ​​corresponding to each sub-region adjacent to the historical period are compared with the resource assessment value range corresponding to the biodiversity level of each sub-region. If the resource assessment value corresponding to a certain sub-region adjacent to the historical period is within the resource assessment value range corresponding to the biodiversity level of a certain sub-region, then the biodiversity level of that sub-region is recorded as the biodiversity level of that sub-region adjacent to the historical period. In this way, the biodiversity level of each sub-region adjacent to the historical period is assessed.

[0020] Preferably, the specific analysis process for determining the acquisition method corresponding to each sub-region of the current period is as follows:

[0021] B1. If a sub-region with a low biodiversity level is adjacent to a historical period, a grid-like sampling method will be adopted for that sub-region in the current period, with 3 to 5 sampling and monitoring points set up per square kilometer. For biological populations, the number of individuals, age structure, and reproductive status of species will be monitored. For plants, the number of plants, coverage area, and growth stage will be recorded. For animals, the number of individuals will be counted through tag-recapture and infrared camera monitoring methods. Reproductive behavior and the number of larvae during the reproductive cycle will be observed. Environmental factors, including soil moisture, temperature, nutrient content, and water pH and dissolved oxygen, will be monitored. At the same time, at least four comprehensive surveys will be conducted each year, in four quarters.

[0022] B2. If the biodiversity level of a sub-region adjacent to a historical period is the same as that of a neutron region, then multiple survey methods will be used in combination for that sub-region in the current period. For plants, quadrats will be set up in different habitats: 10m×10m for arbor forests, 5m×5m for shrub forests, and 1m×1m for herbaceous vegetation. The species, quantity, height, and cover of plants within the quadrats will be counted. For animals, the transect method, sampling point method, and trap method will be used. Transects of 1-2km will be set up in mountain forests, with a sampling point set up every 500m. The species and quantity of animals passing through the transects and sampling points will be counted. Traps will be set up in grasslands and wetlands to capture small invertebrates and amphibians. At the same time, at least two comprehensive surveys will be conducted each year, in spring and autumn respectively.

[0023] B3. If a sub-region with a high biodiversity level is adjacent to a historical period, then in the current period, non-destructive collection methods shall be adopted for that sub-region, and only some branches, leaves or fruits shall be collected, with the collection amount being 10%-20% of its biomass. For collectable animals, a marked and limited collection method shall be adopted, with the collection amount being 5% of its biomass. For a certain type of collectable fish, the catch shall not exceed 30% of its annual growth.

[0024] Preferably, the process of obtaining resource change data corresponding to each sub-region in the current period is as follows:

[0025] The study obtains the species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and inter-organism interaction fit value for each sub-region in the current period. Based on the species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and inter-organism interaction fit value for each sub-region in the immediate historical period, the study analyzes the change rate of the species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and inter-organism interaction fit value for each sub-region in the current period.

[0026] Preferably, the assessment process for determining whether the biological resources of each sub-region in the current period have improved is as follows:

[0027] The change rates of species diversity fit values, genetic diversity fit values, ecosystem diversity fit values, and inter-organism interaction fit values ​​for each sub-region in the current period are input into the resource improvement assessment value evaluation model, and the resource improvement assessment value results for each sub-region in the current period are output.

[0028] The resource improvement assessment results include values ​​of 1 and -1. When the resource improvement assessment result for a sub-region in the current period is 1, it is assessed that the biological resources of the sub-region in the current period have improved. Conversely, when the resource improvement assessment result for a sub-region in the current period is -1, it is assessed that the biological resources of the sub-region in the current period have not improved.

[0029] Preferably, the expression for the resource improvement assessment value evaluation model is: In the formula, This represents the resource improvement assessment result corresponding to the k-th sub-region in the current period. This represents the resource improvement assessment value corresponding to the k-th sub-region in the current period. The threshold value for resource improvement assessment is set, where k represents the number corresponding to each sub-region, and k is a positive integer;

[0030] The rates of change in species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and interbiotic interaction fit value for each sub-region in the current period are respectively denoted as: , , and k represents the number corresponding to each sub-region, and k is a positive integer. Substituting into the calculation formula: In this process, the resource improvement assessment values ​​corresponding to each sub-region in the current period are obtained. ,in, , , , These represent the rate of change of standard species diversity fitness values, standard genetic diversity fitness values, standard ecosystem diversity fitness values, and standard inter-organism interaction fitness values ​​for the designated sub-regions, respectively. , , , These are the weighting factors corresponding to the rate of change in fitness values ​​for species diversity, genetic diversity, ecosystem diversity, and inter-organism interactions, respectively. , , , These are the moderating factors corresponding to the rate of change in fitness values ​​for species diversity, genetic diversity, ecosystem diversity, and inter-organism interactions, respectively. Represents the natural constant.

[0031] The beneficial effects of this invention are as follows: 1. In the embodiments of this invention, the biological resource assessment value analysis module divides the target enterprise's resource monitoring area into sub-regions and obtains the species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and inter-organism interaction fit value of each sub-region in the immediate historical cycle. This multi-dimensional analysis method can comprehensively and deeply reflect all aspects of biodiversity, avoiding the limitations of single-indicator assessment. For example, it can not only understand the changes in species numbers, but also grasp the changes in inter-species relationships and genetic levels, thereby accurately analyzing and obtaining the resource assessment values ​​corresponding to each sub-region in the immediate historical cycle. Based on the comparison of resource assessment values ​​in the current cycle and the immediate historical cycle, the trend of biodiversity change can be dynamically monitored. Enterprises can clearly see whether the biological resources in each sub-region are improving, deteriorating, or remaining stable, and promptly detect subtle changes in biodiversity, providing a basis for early intervention.

[0032] 2. In this embodiment of the invention, the data collection method determination module determines the biodiversity level of each sub-region based on the resource assessment values ​​of each sub-region adjacent to the historical period, and then formulates the corresponding data collection method for each sub-region in the current period. This personalized data collection strategy can reasonably adjust the data collection intensity and method according to the biodiversity status of different sub-regions. For example, for sub-regions with low biodiversity, a relatively mild and simple data collection method can be adopted to reduce interference with fragile ecosystems; while for sub-regions with high and stable biodiversity, more efficient data collection can be carried out while ensuring that biodiversity is not damaged, helping enterprises find a balance between resource utilization and biodiversity conservation. Enterprises can meet their own development needs for resources while maximizing the protection of biodiversity through scientific data collection methods, avoiding irreversible damage to biological resources caused by over-collection, and achieving sustainable development.

[0033] 3. In this embodiment of the invention, when the regional biological resource assessment module detects that the biological resources of a certain sub-region have not improved in the current period, the early warning function can quickly issue an alert to relevant departments of the enterprise. This enables enterprises to take corresponding measures before biodiversity issues worsen, such as adjusting business activities, strengthening protection measures, or carrying out ecological restoration work, which helps enterprises fulfill their environmental responsibilities and actively participate in biodiversity conservation. By accurately assessing and effectively managing biodiversity resources, enterprises can demonstrate their commitment to environmental protection to the public, enhance their corporate image, and meet stakeholders' expectations of corporate environmental responsibility. Attached Figure Description

[0034] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0035] Figure 1 This is a schematic diagram of the system module connections of the present invention. Detailed Implementation

[0036] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] Examples of embodiments of the present invention Figure 1 As shown, a dynamic assessment system for biodiversity resource response mechanisms includes: a biological resource assessment value analysis module, a data collection method determination module, a multi-data combination analysis module, and a regional biological resource assessment module.

[0038] The data collection method determination module is connected to the biological resource assessment value analysis module and the multi-data combination analysis module, respectively, and the regional biological resource assessment module and the multi-data combination analysis module are connected.

[0039] Biological resource assessment value analysis module: It is used to divide the resource monitoring area of ​​the target enterprise into several sub-regions, thereby obtaining the species diversity fit value, genetic diversity fit value, ecosystem diversity fit value and inter-organism interaction fit value of each sub-region in the adjacent historical period, and then analyzing the resource assessment value corresponding to each sub-region in the adjacent historical period.

[0040] In a specific embodiment, the process of obtaining the species diversity fit value, genetic diversity fit value, interbiotic interaction fit value, and ecosystem diversity fit value corresponding to each sub-region in the immediate historical period is as follows:

[0041] A1. Obtain the species richness, number of endemic species, and proportion of rare and endangered species for each sub-region in the immediate historical period, and input the species richness, number of endemic species, and proportion of rare and endangered species for each sub-region in the immediate historical period into the species diversity analysis model, and output the species diversity fit value for each sub-region in the immediate historical period.

[0042] It should be noted that field surveys were conducted to record the species within each sub-region. Statistical software (such as R and Python) was used to analyze the species data, calculating species richness (number of species), the number of endemic species (species found only in specific areas), and the proportion of rare and endangered species.

[0043] It should be noted that the analysis process for the species diversity fit values ​​corresponding to each sub-region in adjacent historical cycles is as follows: the species richness, number of endemic species, and proportion of rare and endangered species corresponding to each sub-region in adjacent historical cycles are normalized, and the normalized species richness, number of endemic species, and proportion of rare and endangered species corresponding to each sub-region in adjacent historical cycles are denoted as follows: , and Substitute into the analysis formula The species diversity fit values ​​for each sub-region in the immediate historical cycle were obtained. , , , These are the weighting coefficients corresponding to the species richness of the defined sub-regions, the weighting coefficients corresponding to the number of endemic species, and the weighting coefficients corresponding to the proportion of rare and endangered species, respectively. Here, k represents the number corresponding to each sub-region, and k is a positive integer.

[0044] A2. Obtain the allele richness, gene diversity index, and genetic differentiation coefficient of each sub-region in the immediate historical cycle, and input the allele richness, gene diversity index, and genetic differentiation coefficient of each sub-region in the immediate historical cycle into the species diversity analysis model, and output the genetic diversity fit value of each sub-region in the immediate historical cycle.

[0045] It should be noted that samples were collected from each subregion for gene sequencing. Bioinformatics tools (such as Arlequin, PopGene, etc.) were used to calculate allele richness, gene diversity indices (such as the Shannon-Wiener index), and genetic differentiation coefficients (such as FST).

[0046] It should be noted that the analysis process for the genetic diversity fit values ​​corresponding to each sub-region in the immediate historical cycle is as follows: the allele richness, gene diversity index, and genetic differentiation coefficient corresponding to each sub-region in the immediate historical cycle are normalized, and the normalized allele richness, gene diversity index, and genetic differentiation coefficient corresponding to each sub-region in the immediate historical cycle are denoted as follows: , and Substitute into the analysis formula This yields the genetic diversity fit values ​​for each subregion within the immediate historical cycle. , , , These are the weighting coefficients corresponding to the allele richness of the sub-region, the gene diversity index, and the genetic differentiation coefficient, respectively, where k represents the number of each sub-region and k is a positive integer.

[0047] A3. Obtain the number of ecosystem types and ecosystem productivity corresponding to each sub-region in the immediate historical period, and input the number of ecosystem types and ecosystem productivity corresponding to each sub-region in the immediate historical period into the ecosystem diversity analysis model, and output the ecosystem diversity fit value corresponding to each sub-region in the immediate historical period.

[0048] It should be noted that GIS software (such as ArcGIS and QGIS) is used to analyze ecosystem types and identify the number of different ecosystems. Remote sensing data (such as NDVI) or field measurements (such as biomass) are used to assess ecosystem productivity.

[0049] It should be noted that the analysis process for the ecosystem diversity fit values ​​corresponding to each sub-region in the immediate historical cycle is as follows: the number of ecosystem types and ecosystem productivity corresponding to each sub-region in the immediate historical cycle are normalized, and the normalized number of ecosystem types and ecosystem productivity corresponding to each sub-region in the immediate historical cycle are denoted as follows: and Substitute into the analysis formula The ecosystem diversity fit values ​​for each sub-region in the immediate historical cycle were obtained. , , These are the weighting coefficients corresponding to the number of ecosystem types in the set sub-region and the weighting coefficients corresponding to ecosystem productivity, respectively, where k represents the number corresponding to each sub-region and k is a positive integer.

[0050] A4. Obtain the food web connectivity, interspecific competition intensity, and symbiotic relationship frequency of each sub-region in the immediate historical cycle, and input the food web connectivity, interspecific competition intensity, and symbiotic relationship frequency of each sub-region in the immediate historical cycle into the interbiological interaction analysis model, and output the interbiological interaction fit value of each sub-region in the immediate historical cycle.

[0051] It's important to note that a food network diagram is constructed by recording the food chain relationships for each species. Each node represents a species, and edges represent predator-prey relationships. Network analysis software (such as Gephi and Cytoscape) is used to calculate connectivity. Connectivity can be obtained by calculating the number of connections each species participates in (i.e., the number of food chains it participates in). The calculation formula is: Connectivity = Number of connections for a species / Total number of species. Data such as the density of competing species and resource utilization rates are recorded. Sample surveys can be used to periodically measure the growth rate and quantity of different species within a sample area, and then statistical methods such as correlation analysis and analysis of variance (ANOVA) can be used to assess the intensity of interspecific competition. Competition coefficients (such as α and β) can be used to quantify the degree of influence between species. Ecological surveys can be conducted in the target area to record symbiotic relationships (such as mutualism and parasitism) between different species. Observational and sampling methods can be used to calculate the frequency of symbiotic relationships, usually expressed as the ratio of the number of times a symbiotic relationship occurs to the total number of observations. For example: Symbiotic relationship frequency = Number of occurrences of symbiotic relationship / Total number of observations.

[0052] It should be noted that the analysis process for the interbiological adaptability values ​​corresponding to each sub-region in adjacent historical cycles is as follows: the food web connectivity, interspecific competition intensity, and symbiotic relationship frequency corresponding to each sub-region in adjacent historical cycles are normalized, and the normalized food web connectivity, interspecific competition intensity, and symbiotic relationship frequency corresponding to each sub-region in adjacent historical cycles are denoted as follows: , and Substitute into the analysis formula This yields the interbiological adaptability values ​​for each sub-region within the immediate historical cycle. , , , These are the weight coefficients corresponding to the food web connectivity of the defined sub-regions, the weight coefficients corresponding to the interspecific competition intensity, and the weight coefficients corresponding to the frequency of symbiotic relationships, respectively, where k represents the number corresponding to each sub-region and k is a positive integer.

[0053] In another specific embodiment, the analysis yields resource assessment values ​​for each sub-region immediately adjacent to the historical period. The specific analysis process is as follows:

[0054] The species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and interbiotic interaction fit value corresponding to each sub-region in the immediate historical cycle are respectively denoted as: , , and k represents the number corresponding to each sub-region, and k is a positive integer. Substituting into the calculation formula: In this process, resource assessment values ​​corresponding to each sub-region adjacent to the historical cycle are obtained. ,in, , , , These are the standard species diversity fit values, standard genetic diversity fit values, standard ecosystem diversity fit values, and standard inter-organism interaction fit values ​​corresponding to the defined sub-regions. , , , These are the weighting factors corresponding to the set subregion species diversity fit values, genetic diversity fit values, ecosystem diversity fit values, and inter-organism interaction fit values, respectively.

[0055] It should be noted that, , , , All are greater than 0 and less than 1.

[0056] It should also be noted that this process involved summarizing a large amount of research and experimental data. Standard species diversity, genetic diversity, ecosystem diversity, and interbiotic interactions adaptation values ​​were set for each sub-region by professional and research institutions. Furthermore, these values ​​were based on the expertise and research of field experts, and discussed and confirmed with industry organizations or professional institutions. Experts then set the weighting factors for the sub-regional species diversity adaptation values, genetic diversity adaptation values, ecosystem diversity adaptation values, and interbiotic interactions adaptation values ​​based on their experience and knowledge.

[0057] The data collection method determination module is used to assess the biodiversity level of each sub-region in the adjacent historical period based on the resource assessment values ​​of each sub-region in the adjacent historical period, and then determine the data collection method for each sub-region in the current period, and collect data in each sub-region in the current period according to the determined data collection method.

[0058] In one specific embodiment, the evaluation of the biodiversity levels of sub-regions corresponding to each sub-region immediately adjacent to the historical period is specifically analyzed as follows:

[0059] The resource assessment values ​​corresponding to each sub-region adjacent to the historical period are compared with the resource assessment value range corresponding to the biodiversity level of each sub-region. If the resource assessment value corresponding to a certain sub-region adjacent to the historical period is within the resource assessment value range corresponding to the biodiversity level of a certain sub-region, then the biodiversity level of that sub-region is recorded as the biodiversity level of that sub-region adjacent to the historical period. In this way, the biodiversity level of each sub-region adjacent to the historical period is assessed.

[0060] In another specific embodiment, the specific analysis process for determining the acquisition method corresponding to each sub-region of the current period is as follows:

[0061] B1. If a sub-region with a low biodiversity level is adjacent to a historical period, a grid-like sampling method will be adopted for that sub-region in the current period, with 3 to 5 sampling and monitoring points set up per square kilometer. For biological populations, the number of individuals, age structure, and reproductive status of species will be monitored. For plants, the number of plants, coverage area, and growth stage will be recorded. For animals, the number of individuals will be counted through tag-recapture and infrared camera monitoring methods. Reproductive behavior and the number of larvae during the reproductive cycle will be observed. Environmental factors, including soil moisture, temperature, nutrient content, and water pH and dissolved oxygen, will be monitored. At the same time, at least four comprehensive surveys will be conducted each year, in four quarters.

[0062] B2. If the biodiversity level of a sub-region adjacent to a historical period is the same as that of a neutron region, then multiple survey methods will be used in combination for that sub-region in the current period. For plants, quadrats will be set up in different habitats: 10m×10m for arbor forests, 5m×5m for shrub forests, and 1m×1m for herbaceous vegetation. The species, quantity, height, and cover of plants within the quadrats will be counted. For animals, the transect method, sampling point method, and trap method will be used. Transects of 1-2km will be set up in mountain forests, with a sampling point set up every 500m. The species and quantity of animals passing through the transects and sampling points will be counted. Traps will be set up in grasslands and wetlands to capture small invertebrates and amphibians. At the same time, at least two comprehensive surveys will be conducted each year, in spring and autumn respectively.

[0063] B3. If a sub-region with a high biodiversity level is adjacent to a historical period, then in the current period, non-destructive collection methods shall be adopted for that sub-region, and only some branches, leaves or fruits shall be collected, with the collection amount being 10%-20% of its biomass. For collectable animals, a marked and limited collection method shall be adopted, with the collection amount being 5% of its biomass. For a certain type of collectable fish, the catch shall not exceed 30% of its annual growth.

[0064] In this embodiment of the invention, the data collection method determination module determines the biodiversity level of each sub-region based on the resource assessment values ​​of each sub-region adjacent to the historical period, and then formulates the corresponding data collection method for each sub-region in the current period. This personalized data collection strategy can reasonably adjust the data collection intensity and method according to the biodiversity status of different sub-regions. For example, for sub-regions with low biodiversity, a relatively mild and simple data collection method can be adopted to reduce disturbance to fragile ecosystems; while for sub-regions with high and stable biodiversity, more efficient data collection can be carried out while ensuring that biodiversity is not damaged, helping enterprises find a balance between resource utilization and biodiversity conservation. Enterprises can meet their own development needs for resources while maximizing the protection of biodiversity through scientific data collection methods, avoiding irreversible damage to biological resources caused by over-collection, and achieving sustainable development.

[0065] Multi-data integration and analysis module: After the target enterprise has completed the collection of resource data in each sub-region of the current period according to the determined collection method, it can obtain the resource change data corresponding to each sub-region of the current period. The resource change data includes the change rate of species diversity fit value, the change rate of genetic diversity fit value, the change rate of ecosystem diversity fit value, and the change rate of inter-organism interaction fit value.

[0066] In a specific embodiment, the process of obtaining and analyzing the resource change data corresponding to each sub-region in the current period is as follows:

[0067] The study obtains the species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and inter-organism interaction fit value for each sub-region in the current period. Based on the species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and inter-organism interaction fit value for each sub-region in the immediate historical period, the study analyzes the change rate of the species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and inter-organism interaction fit value for each sub-region in the current period.

[0068] It should be noted that by substituting the current period's fitted value and the fitted value of the immediately adjacent historical period into the rate of change formula, the rate of change for each indicator is calculated as follows: Rate of Change = {Current Period Fitted Value - Immediately Adjacent Historical Period Fitted Value} divided by {Immediately Adjacent Historical Period Fitted Value} 100%.

[0069] Regional biological resource assessment module: It is used to analyze the resource change data of each sub-region in the current period to obtain the resource improvement assessment value of each sub-region in the current period, and then assess whether the biological resources of each sub-region in the current period have improved. If the biological resources of a certain sub-region in the current period have not improved, an early warning will be issued.

[0070] This invention, through a biological resource assessment value analysis module, divides the target enterprise's resource monitoring area into sub-regions and obtains the species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and inter-organism interaction fit value for each sub-region in adjacent historical cycles. This multi-dimensional analysis method can comprehensively and deeply reflect all aspects of biodiversity, avoiding the limitations of single-indicator assessment. For example, it can not only understand changes in species numbers but also grasp changes in inter-species relationships and genetic levels, thereby accurately analyzing the resource assessment values ​​corresponding to each sub-region in adjacent historical cycles. Based on the comparison of resource assessment values ​​in the current cycle and adjacent historical cycles, it can dynamically monitor the trend of biodiversity change. Enterprises can clearly see whether the biological resources in each sub-region are improving, deteriorating, or remaining stable, promptly detecting subtle changes in biodiversity and providing a basis for early intervention.

[0071] In one specific embodiment, the evaluation process for assessing whether the biological resources corresponding to each sub-region in the current period have improved is as follows:

[0072] The change rates of species diversity fit values, genetic diversity fit values, ecosystem diversity fit values, and inter-organism interaction fit values ​​for each sub-region in the current period are input into the resource improvement assessment value evaluation model, and the resource improvement assessment value results for each sub-region in the current period are output.

[0073] The resource improvement assessment results include values ​​of 1 and -1. When the resource improvement assessment result for a sub-region in the current period is 1, it is assessed that the biological resources of the sub-region in the current period have improved. Conversely, when the resource improvement assessment result for a sub-region in the current period is -1, it is assessed that the biological resources of the sub-region in the current period have not improved.

[0074] In another specific embodiment, the expression for the resource improvement assessment value evaluation model is: In the formula, This represents the resource improvement assessment result corresponding to the k-th sub-region in the current period. This represents the resource improvement assessment value corresponding to the k-th sub-region in the current period. The threshold value for resource improvement assessment is set, where k represents the number corresponding to each sub-region, and k is a positive integer;

[0075] The rates of change in species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and interbiotic interaction fit value for each sub-region in the current period are respectively denoted as: , , and k represents the number corresponding to each sub-region, and k is a positive integer. Substituting into the calculation formula: In this process, the resource improvement assessment values ​​corresponding to each sub-region in the current period are obtained. ,in, , , , These represent the rate of change of standard species diversity fitness values, standard genetic diversity fitness values, standard ecosystem diversity fitness values, and standard inter-organism interaction fitness values ​​for the designated sub-regions, respectively. , , , These are the weighting factors corresponding to the rate of change in fitness values ​​for species diversity, genetic diversity, ecosystem diversity, and inter-organism interactions, respectively. , , , These are the moderating factors corresponding to the rate of change in fitness values ​​for species diversity, genetic diversity, ecosystem diversity, and inter-organism interactions, respectively. Represents the natural constant.

[0076] It should be noted that, , , , All are greater than 0 and less than 1.

[0077] It should also be noted that this process involved summarizing a large amount of research and experimental data. Based on the standard species diversity fit rate, standard genetic diversity fit rate, standard ecosystem diversity fit rate, and standard inter-organism interaction fit rate set by professional and research institutions for each sub-region, and considering the professional knowledge and research of experts in the field, as well as discussions and confirmation with industry organizations or professional institutions, experts set weighting factors for the sub-regional species diversity fit rate, genetic diversity fit rate, ecosystem diversity fit rate, and inter-organism interaction fit rate, based on their experience and knowledge. They also set moderating factors for these sub-regional species diversity fit rate, genetic diversity fit rate, ecosystem diversity fit rate, and inter-organism interaction fit rate.

[0078] In this embodiment of the invention, when the regional biological resource assessment module detects that the biological resources of a certain sub-region have not improved in the current period, the early warning function can quickly issue an alert to relevant departments of the enterprise. This enables enterprises to take corresponding measures before biodiversity issues worsen, such as adjusting business activities, strengthening protection measures, or carrying out ecological restoration work, which helps enterprises fulfill their environmental responsibilities and actively participate in biodiversity conservation. By accurately assessing and effectively managing biodiversity resources, enterprises can demonstrate their commitment to environmental protection to the public, enhance their corporate image, and meet stakeholders' expectations of corporate environmental responsibility.

[0079] The above description is merely an example and illustration of the concept of the present invention. Those skilled in the art can make various modifications or additions to the specific embodiments described or use similar methods to replace them, as long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the protection scope of the present invention.

Claims

1. A dynamic assessment system for biodiversity resource response mechanisms, characterized in that, include: Biological resource assessment value analysis module: It is used to divide the resource monitoring area of ​​the target enterprise into several sub-regions, thereby obtaining the species diversity fit value, genetic diversity fit value, ecosystem diversity fit value and inter-organism interaction fit value of each sub-region in the adjacent historical period, and then analyze the resource assessment value corresponding to each sub-region in the adjacent historical period. The specific process for obtaining the species diversity fit value, genetic diversity fit value, interbiotic interaction fit value, and ecosystem diversity fit value for each sub-region in the immediate historical cycle is as follows: A1. Obtain the species richness, number of endemic species, and proportion of rare and endangered species for each sub-region in the immediate historical period, and input the species richness, number of endemic species, and proportion of rare and endangered species for each sub-region in the immediate historical period into the species diversity analysis model, and output the species diversity fit value for each sub-region in the immediate historical period. A2. Obtain the allele richness, gene diversity index, and genetic differentiation coefficient of each sub-region in the immediate historical cycle, and input the allele richness, gene diversity index, and genetic differentiation coefficient of each sub-region in the immediate historical cycle into the species diversity analysis model, and output the genetic diversity fit value of each sub-region in the immediate historical cycle. A3. Obtain the number of ecosystem types and ecosystem productivity corresponding to each sub-region in the immediate historical period, and input the number of ecosystem types and ecosystem productivity corresponding to each sub-region in the immediate historical period into the ecosystem diversity analysis model, and output the ecosystem diversity fit value corresponding to each sub-region in the immediate historical period. A4. Obtain the food web connectivity, interspecific competition intensity, and symbiotic relationship frequency of each sub-region in the immediate historical cycle, and input the food web connectivity, interspecific competition intensity, and symbiotic relationship frequency of each sub-region in the immediate historical cycle into the interbiological interaction analysis model, and output the interbiological interaction fit value of each sub-region in the immediate historical cycle. The analysis yields resource assessment values ​​for each sub-region immediately adjacent to the historical period. The specific analysis process is as follows: The species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and interbiotic interaction fit value corresponding to each sub-region in the immediate historical cycle are respectively denoted as: , , and k represents the number corresponding to each sub-region, and k is a positive integer. Substituting into the calculation formula: In this process, resource assessment values ​​corresponding to each sub-region adjacent to the historical cycle are obtained. ,in, , , , These are the standard species diversity fit values, standard genetic diversity fit values, standard ecosystem diversity fit values, and standard inter-organism interaction fit values ​​corresponding to the defined sub-regions. , , , These are the weighting factors corresponding to the set subregion species diversity fit values, genetic diversity fit values, ecosystem diversity fit values, and inter-organism interaction fit values, respectively. The data collection method determination module is used to assess the biodiversity level of each sub-region in the adjacent historical period based on the resource assessment value of each sub-region in the adjacent historical period, and then determine the data collection method for each sub-region in the current period, and collect data in each sub-region in the current period according to the determined data collection method. Multi-data integration and analysis module: After the target enterprise has completed the collection of resource data in each sub-region of the current period according to the determined collection method, it can obtain the resource change data corresponding to each sub-region of the current period. The resource change data includes the change rate of species diversity fit value, the change rate of genetic diversity fit value, the change rate of ecosystem diversity fit value, and the change rate of inter-organism interaction fit value. Regional biological resource assessment module: It is used to analyze the resource change data of each sub-region in the current period to obtain the resource improvement assessment value of each sub-region in the current period, and then assess whether the biological resources of each sub-region in the current period have improved. If the biological resources of a certain sub-region in the current period have not improved, an early warning will be issued.

2. The dynamic assessment system for biodiversity resource response mechanisms as described in claim 1, characterized in that, The specific analysis process for assessing the biodiversity levels of sub-regions corresponding to each sub-region immediately adjacent to the historical period is as follows: The resource assessment values ​​corresponding to each sub-region adjacent to the historical period are compared with the resource assessment value range corresponding to the biodiversity level of each sub-region. If the resource assessment value corresponding to a certain sub-region adjacent to the historical period is within the resource assessment value range corresponding to the biodiversity level of a certain sub-region, then the biodiversity level of that sub-region is recorded as the biodiversity level of that sub-region adjacent to the historical period. In this way, the biodiversity level of each sub-region adjacent to the historical period is assessed.

3. The dynamic assessment system for biodiversity resource response mechanisms as described in claim 2, characterized in that, The specific analysis process for determining the data collection method corresponding to each sub-region in the current period is as follows: B1. If a sub-region with a low biodiversity level is adjacent to a historical period, a grid-like sampling method will be adopted for that sub-region in the current period, with 3 to 5 sampling and monitoring points set up per square kilometer. For biological populations, the number of individuals, age structure, and reproductive status of species will be monitored. For plants, the number of plants, coverage area, and growth stage will be recorded. For animals, the number of individuals will be counted through tag-recapture and infrared camera monitoring methods. Reproductive behavior and the number of larvae during the reproductive cycle will be observed. Environmental factors, including soil moisture, temperature, nutrient content, and water pH and dissolved oxygen, will be monitored. At the same time, at least four comprehensive surveys will be conducted each year, in four quarters. B2. If the biodiversity level of a sub-region adjacent to a historical period is the same as that of a neutron region, then multiple survey methods will be used in combination for that sub-region in the current period. For plants, quadrats will be set up in different habitats: 10m×10m for arbor forests, 5m×5m for shrub forests, and 1m×1m for herbaceous vegetation. The species, quantity, height, and cover of plants within the quadrats will be counted. For animals, the transect method, sampling point method, and trap method will be used. Transects of 1-2km will be set up in mountain forests, with a sampling point set up every 500m. The species and quantity of animals passing through the transects and sampling points will be counted. Traps will be set up in grasslands and wetlands to capture small invertebrates and amphibians. At the same time, at least two comprehensive surveys will be conducted each year, in spring and autumn respectively. B3. If a sub-region with a high biodiversity level is adjacent to a historical period, then in the current period, non-destructive collection methods shall be adopted for that sub-region, and only some branches, leaves or fruits shall be collected, with the collection amount being 10%-20% of its biomass. For collectable animals, a marked and limited collection method shall be adopted, with the collection amount being 5% of its biomass. For a certain type of collectable fish, the catch shall not exceed 30% of its annual growth.

4. The dynamic assessment system for biodiversity resource response mechanisms as described in claim 1, characterized in that, The specific process for obtaining and analyzing the resource change data corresponding to each sub-region in the current period is as follows: The study obtains the species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and inter-organism interaction fit value for each sub-region in the current period. Based on the species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and inter-organism interaction fit value for each sub-region in the immediate historical period, the study analyzes the change rate of the species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and inter-organism interaction fit value for each sub-region in the current period.

5. A dynamic assessment system for biodiversity resource response mechanisms as described in claim 4, characterized in that, The assessment process for determining whether the biological resources in each sub-region have improved during the current period is as follows: The change rates of species diversity fit values, genetic diversity fit values, ecosystem diversity fit values, and inter-organism interaction fit values ​​for each sub-region in the current period are input into the resource improvement assessment value evaluation model, and the resource improvement assessment value results for each sub-region in the current period are output. The resource improvement assessment results include values ​​of 1 and -1. When the resource improvement assessment result for a sub-region in the current period is 1, it is assessed that the biological resources of the sub-region in the current period have improved. Conversely, when the resource improvement assessment result for a sub-region in the current period is -1, it is assessed that the biological resources of the sub-region in the current period have not improved.

6. The dynamic assessment system for biodiversity resource response mechanisms as described in claim 5, characterized in that, The expression for the resource improvement assessment value evaluation model is as follows: In the formula, This represents the resource improvement assessment result corresponding to the k-th sub-region in the current period. This represents the resource improvement assessment value corresponding to the k-th sub-region in the current period. The threshold value for resource improvement assessment is set, where k represents the number corresponding to each sub-region, and k is a positive integer; The change rates of species diversity fit value, genetic diversity fit value, ecosystem diversity fit value, and interbiotic interaction fit value for each sub-region in the current period are respectively denoted as: , , and k represents the number corresponding to each sub-region, and k is a positive integer. Substituting into the calculation formula: In this process, the resource improvement assessment values ​​corresponding to each sub-region in the current period are obtained. ,in, , , , These represent the rate of change of standard species diversity fitness values, standard genetic diversity fitness values, standard ecosystem diversity fitness values, and standard inter-organism interaction fitness values ​​for the designated sub-regions, respectively. , , , These are the weighting factors corresponding to the rate of change in fitness values ​​for species diversity, genetic diversity, ecosystem diversity, and inter-organism interactions, respectively. , , , These are the moderating factors corresponding to the rate of change in fitness values ​​for species diversity, genetic diversity, ecosystem diversity, and inter-organism interactions, respectively. Represents the natural constant.

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