A method and device for simulating population dynamics of Chinese white dolphins and evaluating protection measures

Abstract

The application discloses a Chinese white dolphin population dynamic simulation and protection measure evaluation method and device, relies on field measurement and multi-source database integration to build a standardized population life table, automatically builds a projection matrix based on the divided growth stage structure and constructs a quantitative basic model, breaks away from the limitations that traditional monitoring can only statistically analyze population data after the event and cannot predict long-term population evolution trends, acquires sensitivity analysis results through Sobol global sensitivity analysis, locks core main control factors, and solves the defects that traditional methods are difficult to quantize parameter coupling; combined with elastic matrix analysis and Sobol sensitivity analysis results, matched protection measures can be formulated, multiple protection scenarios can be simulated in parallel, and the evaluation link takes the original population trajectory without intervention as the benchmark, combines the parameter sensitivity law, compares the population quantity and extinction probability improvement range under different schemes horizontally, and provides quantitative support for endangered species protection decision-making.

Description

Technical Field

[0001] This invention relates to the field of computer technology, specifically to a method and apparatus for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures. Background Technology

[0002] Global biodiversity is currently experiencing a sharp decline, facing a crisis of biodiversity loss. According to the International Union for Conservation of Nature (IUCN), approximately 28% of known species worldwide are threatened with extinction to varying degrees. Endangered wild animals generally suffer from low population sizes, aging populations, habitat loss and fragmentation, and their population dynamics are influenced by multiple factors, including environmental randomness, population statistics randomness, and human interference. Traditional field monitoring can only complete post-event data collection and cannot predict future population trends or scientifically assess the effectiveness of conservation measures.

[0003] The Indo-Pacific humpback dolphin is a key protected cetacean species in my country's coastal waters. Human activities such as coastal shipping, land reclamation projects, underwater noise, and water pollution are constantly shrinking its living space and causing serious underwater noise and water pollution, which exacerbates its population decline. In addition, the species is difficult to monitor in the wild, which further restricts the development of population dynamics research.

[0004] Population viability analysis (PVA) is the mainstream technique for assessing the extinction risk of endangered species, mainly divided into two categories: deterministic matrix models and stochastic simulation models. Deterministic models are computationally simple but cannot simulate random fluctuations in the natural environment; existing stochastic simulation models suffer from drawbacks such as difficulty in obtaining parameters, strong subjectivity in setting conservation scenarios, and limited assessment dimensions. Furthermore, current assessments of conservation measures often rely on post-hoc comparisons, lacking model-driven forward-looking predictive methods, leading to irrational allocation of conservation resources and difficulty in determining conservation priorities. Summary of the Invention

[0005] To address the aforementioned deficiencies, this invention discloses a method and apparatus for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures. This method integrates multi-source monitoring data and can quantitatively simulate population dynamics.

[0006] The first aspect of this invention discloses a method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures, comprising: The population dynamics parameter set of the Indo-Pacific humpback dolphin was collected by field monitoring and data recording and database, and a standardized population life table was constructed based on the population dynamics parameter set of the Indo-Pacific humpback dolphin; the parameters included in the population dynamics parameter set are at least the initial population size, survival rate, reproductive rate and environmental carrying capacity; The growth stage structure of the Indo-Pacific humpback dolphin is predefined based on the standardized population life table, and the survival rate and reproduction rate of the Indo-Pacific humpback dolphin are obtained. A projection matrix is ​​constructed based on the growth stage structure, survival rate and reproduction rate, a population iteration formula is predefined, the simulation duration and number of iterations are set, and an initial population vector is obtained. A basic model is constructed based on the projection matrix, the population iteration formula, the number of iterations and the initial population vector. Based on the aforementioned population attributes, a quantitative standard for the extinction of the Indo-Pacific humpback dolphin was established. Multiple population dynamic projections were performed based on the aforementioned basic model and simulation duration to obtain the corresponding population trajectories. Each population dynamic projection involved random environmental sampling. Several parameters are selected from the population dynamics parameter set, and a perturbation interval for the uniform distribution of the selected parameters is set to perform a global sensitivity analysis of Sobol to obtain the sensitivity analysis results. The sensitivity analysis results include the key indices and interaction relationships of the selected parameters. Based on the standardized population life table, projection matrix, basic model, population trajectory and sensitivity analysis results, survival threat factors are determined, protection measures conditions matching the survival threat factors are set and quantified as key parameters and input into the basic model to output the new population trajectory under the protection measures conditions. The effectiveness of the protection measures was evaluated based on population trajectory, new population trajectory, and sensitivity analysis results.

[0007] As an optional implementation, in the first aspect of the present invention, the extinction quantification criteria include: functional extinction is defined as the population containing only individuals of a single sex or the population number being consistently below 50 individuals; and absolute extinction is defined as the population number being 0 individuals.

[0008] As an optional implementation, in the first aspect of the present invention, the projection matrix is ​​a Leslie projection matrix; constructing the projection matrix based on the growth stage structure, survival rate, and reproduction rate includes: The row and column dimensions of the Leslie projection matrix are determined based on the growth stage structure. The first row of the Leslie projection matrix is ​​assigned a value according to the reproduction rate of different growth stages included in the growth stage structure. The second diagonal of the Leslie projection matrix is ​​assigned a value according to the survival rate of adjacent growth stages. The remaining positions of the Leslie projection matrix are assigned a value of 0.

[0009] As an optional implementation, in a first aspect of the present invention, the growth stage structure includes a juvenile stage, a adolescent stage, a sub-adult stage, and an adult reproductive stage.

[0010] As an optional implementation, in the first aspect of the present invention, setting the disturbance interval with uniformly distributed selected parameters includes: The selected parameters are survival rate, reproduction rate, and environmental carrying capacity. The perturbation range for the survival rate is set to 0.9-1.1 times the baseline value for the survival rate, the perturbation range for the reproduction rate is set to 0.9-1.1 times the baseline value for the reproduction rate, and the perturbation range for the environmental carrying capacity is set to 0.8-1.2 times the baseline value for the environmental carrying capacity.

[0011] As an optional implementation, in the first aspect of the present invention, the step of performing Sobol global sensitivity analysis to obtain sensitivity analysis results includes: Multiple sets of different parameter combinations are generated using Saltelli sequences. For each set of parameter combinations, the Leslie projection matrix and basic model corresponding to the growth stage structure are run and output. The duration of a single simulation is 100 years. The output result is the population size at the end of 100 years. The variance decomposition of the output results corresponding to multiple sets of different parameter combinations yields the first-order index, the total effect index, and the second-order interaction index; among which, the key indices include the first-order index, the total effect index, and the second-order interaction index. A noise threshold is set, and when the second-order interaction exponent exceeds the noise threshold, it is determined that the selected parameters have a valid interaction relationship.

[0012] As an optional implementation, in a first aspect of the present invention, evaluating the effectiveness of the protection measures based on population trajectory, new population trajectory, and sensitivity analysis results includes: The population trajectory is compared with the new population trajectory to determine whether the difference between the new population trajectory and the population trajectory corresponding to different selected parameters is greater than a set interval. If it is greater than the set interval, the key parameter and the corresponding protection measures are deemed to be effective.

[0013] The second aspect of this invention discloses a device for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures, comprising: Data collection module: used to collect population dynamics parameter sets of Indo-Pacific humpback dolphins through field monitoring and data recording and database, and to construct a standardized population life table based on the population dynamics parameter sets of Indo-Pacific humpback dolphins; the population dynamics parameter sets include at least the initial population size, survival rate, reproductive rate, and environmental carrying capacity; Model building module: used to predefine the growth stage structure of the Chinese white dolphin based on the standardized population life table, obtain the survival rate and reproduction rate of the Chinese white dolphin, construct a projection matrix according to the growth stage structure, survival rate and reproduction rate, predefine the population iteration formula, set the simulation duration and number of iterations, obtain the initial population vector, and construct the basic model based on the projection matrix, population iteration formula, number of iterations and initial population vector; Population projection module: used to establish a quantitative standard for the extinction of the Indo-Pacific humpback dolphin based on the population attributes, and to perform multiple dynamic projections of the population based on the basic model and simulation duration to obtain the population trajectory for each number of projections. Each dynamic projection involves random environmental sampling. Parameter analysis module: used to select several parameters from the population dynamics parameter set and set a perturbation interval for uniform distribution of the selected parameters to perform global sensitivity analysis of Sobol and obtain sensitivity analysis results. The sensitivity analysis results include the key indices and interaction relationships of the selected parameters. Scenario Protection Module: This module is used to determine survival threat factors based on standardized population life tables, projection matrices, basic models, population trajectories, and sensitivity analysis results; set protection measures conditions that match the survival threat factors; quantify these conditions into key parameters; input them into the basic model; and output new population trajectories under the protection measures conditions. Effective evaluation module: used to evaluate the effectiveness of the protection measures based on population trajectory, new population trajectory, and sensitivity analysis results.

[0014] As an optional implementation, in the second aspect of the present invention, the extinction quantification criteria include: functional extinction is defined as the population containing only individuals of a single sex or the population size being consistently below 50 individuals; and absolute extinction is defined as the population size being 0 individuals.

[0015] As an optional implementation, in a second aspect of the present invention, the projection matrix is ​​a Leslie projection matrix; constructing the projection matrix based on the growth stage structure, survival rate, and reproduction rate includes: The row and column dimensions of the Leslie projection matrix are determined based on the growth stage structure. The first row of the Leslie projection matrix is ​​assigned a value according to the reproduction rate of different growth stages included in the growth stage structure. The second diagonal of the Leslie projection matrix is ​​assigned a value according to the survival rate of adjacent growth stages. The remaining positions of the Leslie projection matrix are assigned a value of 0.

[0016] As an optional implementation, in a second aspect of the present invention, the growth stage structure includes a juvenile stage, a adolescent stage, a sub-adult stage, and an adult reproductive stage.

[0017] As an optional implementation, in the first aspect of the present invention, setting the disturbance interval with uniformly distributed selected parameters includes: The selected parameters are survival rate, reproduction rate, and environmental carrying capacity. The perturbation range for the survival rate is set to 0.9-1.1 times the baseline value for the survival rate, the perturbation range for the reproduction rate is set to 0.9-1.1 times the baseline value for the reproduction rate, and the perturbation range for the environmental carrying capacity is set to 0.8-1.2 times the baseline value for the environmental carrying capacity.

[0018] As an optional implementation, in a second aspect of the present invention, the step of performing a global sensitivity analysis of Sobol to obtain the sensitivity analysis results includes: Multiple sets of different parameter combinations were generated using Saltelli sequences. For each set of parameter combinations, the Leslie projection matrix and basic model output corresponding to four different growth stage structures were run. The market was simulated for 100 years at a time. The output results were obtained, which were the population sizes at the end of 100 years. The variance decomposition of the output results corresponding to multiple sets of different parameter combinations yields the first-order index, the total effect index, and the second-order interaction index; among which, the key indices include the first-order index, the total effect index, and the second-order interaction index. A noise threshold is set, and when the second-order interaction exponent exceeds the noise threshold, it is determined that the selected parameters have a valid interaction relationship.

[0019] As an optional implementation, in a second aspect of the present invention, evaluating the effectiveness of the protection measures based on population trajectory, new population trajectory, and sensitivity analysis results includes: The population trajectory is compared with the new population trajectory to determine whether the difference between the new population trajectory corresponding to different selected parameters and the basic model population trajectory is greater than a set interval. If it is greater than the set interval, the key parameter and the corresponding protection measures are deemed to be effective.

[0020] A third aspect of the present invention discloses an electronic device, comprising: a memory storing executable program code; a processor coupled to the memory; the processor calling the executable program code stored in the memory to execute the method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures disclosed in the first aspect of the present invention.

[0021] The fourth aspect of this invention discloses a computer-readable storage medium storing a computer program, wherein the computer program causes a computer to execute the method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures disclosed in the first aspect of this invention.

[0022] Compared with the prior art, the embodiments of the present invention have the following beneficial effects: This invention utilizes field measurements and multi-source databases to construct a standardized population life table. Based on the defined growth stages, a Leslie projection matrix is ​​automatically built. A quantitative model is constructed through matrix iteration, overcoming the limitations of traditional monitoring methods that only provide post-hoc population data and cannot predict long-term population evolution trends. This allows for a complete simulation of the dynamic changes in population age structure and individual numbers across different time periods. The embodiments independently sample environmental randomness, generating multiple differentiated population trajectories in batches, fully reproducing the random disturbances to the population caused by interannual fluctuations in the natural environment. Sensitivity analysis results are obtained through Sobol global sensitivity analysis, identifying core controlling factors and overcoming the traditional difficulty in quantifying parameter coupling effects. Combining elastic matrix analysis and Sobol sensitivity analysis results, matching protection measures can be formulated, enabling parallel simulation of multiple protection scenarios. The evaluation phase uses the uninterrupted original population trajectory as a benchmark, comparing the improvement in population size and extinction probability under different schemes based on parameter sensitivity patterns, providing quantitative support for endangered species protection decisions. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments 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.

[0024] Figure 1 This is a flowchart illustrating a method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures, as disclosed in an embodiment of the present invention. Figure 2 This is a schematic diagram illustrating the population distribution changes of the Indo-Pacific humpback dolphin according to the present invention; Figure 3 This is a schematic diagram illustrating the population trajectory of the Indo-Pacific humpback dolphin according to the present invention; Figure 4 This is a schematic diagram of the sensitivity index comparison analysis of the present invention; Figure 5 This is a schematic diagram of the variance decomposition of the model output of the present invention; Figure 6 This is a schematic diagram of the second-order interaction effect between parameters in this invention; Figure 7 This is a schematic diagram of the structure of a device for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures, provided in an embodiment of the present invention. Figure 8 This is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed Implementation

[0025] 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.

[0026] It should be noted that the terms "first," "second," "third," "fourth," etc., in the specification and claims of this invention are used to distinguish different objects, not to describe a specific order. The terms "comprising" and "having," and any variations thereof, in the embodiments of this invention are intended to cover non-exclusive inclusion. Exemplarily, a process, method, system, product, or device that includes a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to these processes, methods, products, or devices.

[0027] This invention discloses a method, device, electronic equipment, and storage medium for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures. It constructs a standardized population life table based on field measurements and multi-source database integration, automatically builds a Leslie projection matrix based on the defined growth stages, and iteratively constructs a quantitative basic model. This overcomes the limitations of traditional monitoring methods, which can only statistically analyze population data after the fact and cannot predict long-term population evolution trends. It can fully simulate the dynamic changes in population age structure and individual numbers at different time periods. The embodiment independently samples environmental randomness, generating multiple differentiated population trajectories in batches, fully restoring the random disturbances to the population caused by interannual fluctuations in the natural environment. Sensitivity analysis results are obtained through Sobol global sensitivity analysis to identify core controlling factors, overcoming the shortcomings of traditional methods that struggle to quantify parameter coupling effects. Combining elastic matrix analysis and Sobol sensitivity analysis results, matching conservation measures can be formulated, enabling parallel simulation of multiple conservation scenarios. The evaluation stage uses the uninterrupted original population trajectory as a benchmark, and compares the improvement in population size and extinction probability under different schemes based on parameter sensitivity patterns, providing quantitative support for endangered species conservation decisions.

[0028] Example 1 Please see Figure 1 , Figure 1This is a flowchart illustrating a method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures, as disclosed in an embodiment of the present invention. The execution entity of the method described in this embodiment is an entity composed of software and / or hardware. This entity can receive relevant information via wired or / or wireless means and can send certain instructions. It may also have certain processing and storage functions. This entity can control multiple devices, such as remote physical servers or cloud servers and related software, or local hosts or servers and related software that perform related operations on devices located in a specific location. In some scenarios, multiple storage devices can also be controlled; these storage devices may be located in the same place as the devices or in different places. Figure 1 As shown, this method for simulating the population dynamics of the Indo-Pacific humpback dolphin and assessing conservation measures includes the following steps: 101. Collect population dynamics parameter sets of Indo-Pacific humpback dolphins through field monitoring and data recording and databases, and construct a standardized population life table based on the population dynamics parameter sets of Indo-Pacific humpback dolphins; the population dynamics parameter sets include at least the initial population size, survival rate, reproductive rate and environmental carrying capacity.

[0029] Population dynamics parameters include: initial population size, carrying capacity, initial reproductive age, maximum lifespan, sex ratio, reproductive rate, mortality rate, reproductive mode, occurrence of disasters, Allee effect, and survival rate. As an optional measure, mortality rate can be estimated based on the population's individual identification history data using a MARK model for capture-recapture analysis to estimate age-related survival and mortality rates.

[0030] In this embodiment, a field survey of the Indo-Pacific humpback dolphin population in Zhanjiang was conducted, using "Web of Science" and "China National Knowledge Infrastructure" as the primary data sources, with the keywords being Indo-Pacific humpback dolphin, Chinese white dolphin, Sousachinese, Indo The Pacific Humpback Dolphin search was used to determine the population parameters by reading each result. Specifically, these parameters included: initial population size (1485 individuals), carrying capacity (2970 individuals), disaster factor (no collective accidental deaths occurred in the Zhanjiang population's history, so no disaster factor was set), initial reproductive age (13 years), maximum lifespan (43 years), sex ratio (female to male ratio of 50:50), reproductive rate (25%), and mortality rate (39% for 0-1 years; 18.5% for 2-4 years; 10% for females aged 5-9 years and males aged 5-12 years; and 4.9% for females older than 9 years and males older than 12 years).

[0031] 102. Based on the standardized population life table, predefine the growth stage structure of the Indo-Pacific humpback dolphin, and obtain the survival rate and reproduction rate of the Indo-Pacific humpback dolphin. Construct a projection matrix according to the growth stage structure, survival rate and reproduction rate, predefine the population iteration formula, set the simulation duration and number of iterations, and obtain the initial population vector. Construct a basic model based on the projection matrix, population iteration formula, number of iterations and initial population vector.

[0032] The projection matrix is ​​the Leslie projection matrix; constructing the projection matrix based on the growth stage structure, survival rate, and reproduction rate includes: determining the row and column dimensions of the Leslie projection matrix based on the growth stage structure, wherein the first row of the Leslie projection matrix is ​​assigned a value based on the reproduction rate of different growth stages included in the growth stage structure, with only the adult stage having a non-zero value; the second diagonal of the Leslie projection matrix is ​​assigned a value sequentially based on the survival rate of adjacent growth stages; and the remaining positions of the Leslie projection matrix are assigned a value of 0.

[0033] The growth stages include the calf stage, juvenile stage, sub-adult stage, and adult reproductive stage. A basic model is constructed using predefined population dynamics parameters, with 1000 iterations simulated over four generations of the Indo-Pacific humpback dolphin, approximately 100 years, with each year's cycle coinciding with the natural year. Figure 2 and Figure 3 As shown in the output of the basic model, after four generations, the Zhanjiang population shows a downward trend, with a high probability of functional extinction, but not absolute extinction.

[0034] 103. Establish a quantitative standard for the extinction of the Chinese white dolphin based on the population attributes, and perform multiple population dynamic projections based on the basic model and simulation duration to obtain the population trajectory for the corresponding number of times, wherein each population dynamic projection is subject to random environmental sampling.

[0035] The extinction quantification criteria include: a population consisting of only individuals of a single sex (i.e., complete absence of males or females), or a population size that is consistently below a pre-set minimum viable population threshold (e.g., 50 individuals). The criteria also include: a population consisting of only individuals of a single sex, or a population size consistently below 50 individuals, is considered functionally extinct; a population size of 0 individuals is considered absolutely extinct.

[0036] In the embodiments, the functional extinction of the Zhanjiang Indo-Pacific humpback dolphin population is defined as fewer than 50 individuals and fewer than 1 individual as absolutely extinct.

[0037] Using the established basic model and the Popbio package in R Studio, multiple Monte Carlo simulations were performed, each independently projecting population dynamics over N years. Each simulation independently sampled environmental randomness to obtain different population trajectories.

[0038] 104. Select several parameters from the population dynamics parameter set, and set a perturbation interval for uniform distribution of the selected parameters to perform Sobol global sensitivity analysis to obtain sensitivity analysis results. The sensitivity analysis results include the key indices and interaction relationships of the selected parameters.

[0039] Set a disturbance range for the uniform distribution of the selected parameters, including: the selected parameters are survival rate, reproduction rate and environmental carrying capacity, the disturbance range for the survival rate is set to 0.9-1.1 times the baseline value of the survival rate, the disturbance range for the reproduction rate is set to 0.9-1.1 times the baseline value of the reproduction rate, and the disturbance range for the environmental carrying capacity is set to 0.8-1.2 times the baseline value of the environmental carrying capacity.

[0040] The selected parameters include, for example, carrying capacity, female reproductive rate, offspring and adolescent mortality rate, and sex ratio. Multiple different parameter combinations are generated using Saltelli sequences; for example, 1600 combinations are generated. For each parameter combination, the Leslie projection matrix corresponding to four different growth stages and the basic model output are run. Each market simulation lasts 100 years, and the output results represent the population size at the end of 100 years. Variance decomposition is performed on the output results corresponding to the multiple parameter combinations to obtain first-order indices, total effect indices, and second-order interaction indices. When there are 1600 parameter combinations, there are 1600 output results, and variance decomposition is performed on these 1600 output results. The key indices include first-order indices, total effect indices, and second-order interaction indices. A noise threshold is set; when the second-order interaction index exceeds the noise threshold, it is determined that the selected parameters have a valid interaction relationship.

[0041] like Figure 4-6 As shown, survival rate is the absolute dominant parameter (S1=0.770), explaining 77% of the output variance alone. Management should focus on improving survival rate. S2 (survival rate x fertility) = 0.068, which exceeds the estimated noise threshold (approximately 0.03), indicating a certain positive synergistic effect between survival rate and fertility. Under high survival rate, the effect of fertility will be amplified.

[0042] 105. Based on the standardized population life table, projection matrix, basic model, population trajectory and sensitivity analysis results, determine the survival threat factors, set protection measures conditions that match the survival threat factors and quantify them as key parameters to input into the basic model, so as to output the new population trajectory under the protection measures conditions.

[0043] Conservation measures include: increasing the genetic diversity of populations by introducing exogenous individuals for gene exchange, such as individuals from ex-situ conservation populations or neighboring healthy populations; controlling disasters caused by human activities; and implementing habitat quality management, such as water quality improvement, food resource enhancement, and restoration of key habitats.

[0044] Habitat management measures are set at three levels: low, medium, and high. Low level habitat management (increase in population survival and reproductive capacity by 1%), low level habitat management (increase in population survival and reproductive capacity by 5%, not exceeding 1%), and low level habitat management (increase in population survival and reproductive capacity by 10%, not exceeding 1%).

[0045] 106. Evaluate the effectiveness of the protection measures based on the population trajectory, new population trajectory, and sensitivity analysis results. Compare the population trajectory with the new population trajectory, and determine whether the difference between the new population trajectory and the population trajectory corresponding to different selected parameters is greater than a set interval. If it is greater than the set interval, the key parameter and the corresponding protection measures are deemed effective.

[0046] Taking the Zhanjiang Indo-Pacific humpback dolphin population as an example: A model was built using parameters such as the initial population size of 1485 individuals, the carrying capacity of 2970 individuals, mortality rates at different ages, and reproductive rates. The model was set with 1000 iterations and a 100-year simulation period. Basic simulations showed a declining population trend and a high risk of functional extinction. Sensitivity analysis confirmed that the survival rate of juveniles and subadults is the core influencing factor, and that survival rate and reproductive rate have a synergistic effect. Subsequently, three levels of habitat management scenarios (low, medium, and high) were set up, and four time-series schemes were designed: constant management, early-stage reinforcement, gradual reinforcement, and pulsed management. Results showed that high-level habitat restoration could increase the population to 795 individuals after 100 years. The continuous management model of early-stage reinforcement and gradual reinforcement could reduce the extinction risk from 100% to 13.5%–20%, while the optimal range for survival rate management intensity was determined to be 1.05–1.07. This method enables pre-emptive prediction and quantitative assessment of conservation measures and can also provide a reference for the conservation of other endangered species.

[0047] Example 2 Please see Figure 7 , Figure 7 This is a schematic diagram of the structure of the Indo-Pacific humpback dolphin population dynamics simulation and conservation measure evaluation device disclosed in an embodiment of the present invention. Figure 7As shown, the Indo-Pacific humpback dolphin population dynamics simulation and conservation measure evaluation device may include: a data collection module 701, a model building module 702, a population projection module 703, a parameter analysis module 704, a scenario protection module 705, and an effectiveness evaluation module 706. The data collection module 701 is used to collect a set of Indo-Pacific humpback dolphin population dynamics parameters through field monitoring records and databases, and to construct a standardized population life table based on the set of parameters. The population dynamics parameter set includes at least mortality rate, survival rate, reproductive rate, and carrying capacity. The model building module 702 is used to predefine the growth stage structure of the Indo-Pacific humpback dolphin based on the standardized population life table, obtain the survival rate and reproductive rate, construct a projection matrix based on the growth stage structure, survival rate, and reproductive rate, predefine a population iteration formula, set the simulation duration and number of iterations, obtain an initial population vector, and construct a basic model based on the projection matrix, population iteration formula, number of iterations, and initial population vector. The system includes: a population projection module 703, used to establish a quantitative standard for the extinction of the Chinese white dolphin based on the population attributes, and to perform multiple population dynamic projections based on the basic model and simulation duration to obtain the population trajectory for each number of projections. Each population dynamic projection involves random environmental sampling. A parameter analysis module 704 is used to select several parameters from the population dynamics parameter set and set a uniformly distributed perturbation interval for the selected parameters to perform a Sobol global sensitivity analysis to obtain sensitivity analysis results. The sensitivity analysis results include the key indices and interaction relationships of the selected parameters. A scenario protection module 705 is used to determine survival threat factors based on the standardized population life table, projection matrix, basic model, population trajectory, and sensitivity analysis results. It sets protection measures conditions matching the survival threat factors and quantifies them as key parameters, inputting them into the basic model to output the new population trajectory under the protection measures conditions. An effectiveness evaluation module 706 is used to evaluate the effectiveness of the protection measures conditions based on the population trajectory, the new population trajectory, and the sensitivity analysis results.

[0048] This invention addresses the issue that large mammals may lose their ability to sustain themselves and reproduce normally under natural conditions due to small population sizes. It explicitly defines population extinction as a population size of less than 50 individuals, enabling a more accurate assessment of the actual extinction risk and effectively avoiding the assessment bias caused by ambiguous extinction criteria in existing technologies. Secondly, it introduces Sobol global sensitivity analysis for uncertain parameters, quantitatively evaluating the response of various parameter changes to population dynamics simulation results, effectively solving the technical deficiency in existing technologies that lack systematic quantitative analysis of key factors affecting population dynamics. Thirdly, by setting different protection measure scenarios and conducting effectiveness assessments, it achieves a quantitative comparison of the effects of various protection measures, providing a quantifiable basis and operability for comparing the differences in effects between different measures. This significantly improves the scientific and rational allocation of conservation resources. For the first time, it constructs a nonlinear relationship curve between management intensity and population response, identifying the optimal management interval and providing quantitative support for endangered species conservation decisions. Finally, this invention can also provide a reference for the protection and management of other endangered animals, avoiding missing critical windows for endangered population protection due to information lag or misjudgment.

[0049] Example 3 Please see Figure 8 , Figure 8 This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of the present invention. The electronic device can be a computer, a server, etc. Of course, in certain cases, it can also be a mobile phone, tablet computer, monitoring terminal, or other smart device, as well as an image acquisition device with processing capabilities. Figure 8 As shown, the electronic device may include: Memory 801 storing executable program code; Processor 802 coupled to memory 801; The processor 802 calls the executable program code stored in the memory 801 to execute some or all of the steps in the method for simulating the population dynamics of the Chinese white dolphin and evaluating protection measures in Embodiment 1.

[0050] This invention discloses a computer-readable storage medium storing a computer program that enables a computer to perform some or all of the steps in the method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures in Embodiment 1.

[0051] This invention also discloses a computer program product, wherein when the computer program product is run on a computer, the computer executes some or all of the steps in the method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating protection measures in Embodiment 1.

[0052] This invention also discloses an application publishing platform, which is used to publish computer program products. When the computer program products are run on a computer, the computer executes some or all of the steps in the method for simulating the population dynamics of the Chinese white dolphin and evaluating protection measures in Embodiment 1.

[0053] In various embodiments of the present invention, it should be understood that the sequence number of each process does not necessarily imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0054] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; they can be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0055] Furthermore, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0056] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-accessible memory. Based on this understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several requests to cause a computer device (which can be a personal computer, server, or network device, specifically a processor in the computer device) to execute some or all of the steps of the methods described in the various embodiments of the present invention.

[0057] In the embodiments provided by this invention, it should be understood that "B corresponding to A" means that B is associated with A, and B can be determined based on A. However, it should also be understood that determining B based on A does not mean determining B solely based on A; B can also be determined based on A and / or other information.

[0058] Those skilled in the art will understand that some or all of the steps in the various methods of the embodiments described can be implemented by a program instructing related hardware. This program can be stored in a computer-readable storage medium, including read-only memory (ROM), random access memory (RAM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), one-time programmable read-only memory (OTPROM), electrically-Erasable Programmable Read-Only Memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, disk storage, magnetic tape storage, or any other computer-readable medium capable of carrying or storing data.

[0059] The foregoing has provided a detailed description of the method, apparatus, electronic device, and storage medium for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures, as disclosed in the embodiments of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the embodiments above are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures, characterized in that, include: The population dynamics parameter set of the Indo-Pacific humpback dolphin was collected by field monitoring and data recording and database, and a standardized population life table was constructed based on the population dynamics parameter set of the Indo-Pacific humpback dolphin; the parameters included in the population dynamics parameter set are at least the initial population size, survival rate, reproductive rate and environmental carrying capacity; The growth stage structure of the Indo-Pacific humpback dolphin is predefined based on the standardized population life table, and the survival rate and reproduction rate of the Indo-Pacific humpback dolphin are obtained. A projection matrix is ​​constructed based on the growth stage structure, survival rate and reproduction rate, a population iteration formula is predefined, the simulation duration and number of iterations are set, and an initial population vector is obtained. A basic model is constructed based on the projection matrix, the population iteration formula, the number of iterations and the initial population vector. Based on the population attributes, a quantitative standard for the extinction of the Chinese white dolphin is established, and multiple population dynamic projections are performed based on the basic model and simulation duration to obtain the population trajectory for the corresponding number of times. Each population dynamic projection involves random environmental sampling. Several parameters are selected from the population dynamics parameter set, and a perturbation interval for the uniform distribution of the selected parameters is set to perform a global sensitivity analysis of Sobol to obtain the sensitivity analysis results. The sensitivity analysis results include the key indices and interaction relationships of the selected parameters. Based on the standardized population life table, projection matrix, basic model, population trajectory and sensitivity analysis results, survival threat factors are determined, protection measures conditions matching the survival threat factors are set and quantified as key parameters and input into the basic model to output the new population trajectory under the protection measures conditions. The effectiveness of the protection measures was evaluated based on population trajectory, new population trajectory, and sensitivity analysis results.

2. The method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures according to claim 1, characterized in that, The extinction quantification criteria include: functional extinction is defined as the population containing only individuals of a single sex or the population size consistently below 50 individuals; and absolute extinction is defined as the population size being 0 individuals.

3. The method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures according to claim 1, characterized in that, The projection matrix is ​​the Leslie projection matrix; the projection matrix is ​​constructed based on the growth stage structure, survival rate, and reproduction rate, including: The row and column dimensions of the Leslie projection matrix are determined based on the growth stage structure. The first row of the Leslie projection matrix is ​​assigned a value according to the reproduction rate of different growth stages included in the growth stage structure. The second diagonal of the Leslie projection matrix is ​​assigned a value according to the survival rate of adjacent growth stages. The remaining positions of the Leslie projection matrix are assigned a value of 0.

4. The method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures according to claim 1, characterized in that, The growth stage structure includes the juvenile stage, adolescent stage, sub-adult stage, and adult reproductive stage.

5. The method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures according to claim 4, characterized in that, The set disturbance range with uniformly distributed parameters includes: The selected parameters are survival rate, reproduction rate, and environmental carrying capacity. The perturbation range for the survival rate is set to 0.9-1.1 times the baseline value for the survival rate, the perturbation range for the reproduction rate is set to 0.9-1.1 times the baseline value for the reproduction rate, and the perturbation range for the environmental carrying capacity is set to 0.8-1.2 times the baseline value for the environmental carrying capacity.

6. The method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures according to claim 5, characterized in that, The process of performing global sensitivity analysis on Sobol and obtaining the sensitivity analysis results includes: Multiple sets of different parameter combinations are generated using Saltelli sequences. For each set of parameter combinations, the Leslie projection matrix and basic model corresponding to the growth stage structure are run and output. The duration of a single simulation is 100 years. The output result is the population size at the end of 100 years. The variance decomposition of the output results corresponding to multiple sets of different parameter combinations yields the first-order index, the total effect index, and the second-order interaction index; among which, the key indices include the first-order index, the total effect index, and the second-order interaction index. A noise threshold is set, and when the second-order interaction exponent exceeds the noise threshold, it is determined that the selected parameters have a valid interaction relationship.

7. The method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures according to claim 1, characterized in that, The effectiveness of the conservation measures was evaluated based on population trajectory, new population trajectory, and sensitivity analysis results, including: The population trajectory is compared with the new population trajectory to determine whether the difference between the new population trajectory corresponding to different selected parameters and the basic model population trajectory is greater than a set interval. If it is greater than the set interval, the key parameter and the corresponding protection measures are deemed to be effective.

8. A device for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures, characterized in that, include: Data collection module: used to collect population dynamics parameter sets of Indo-Pacific humpback dolphins through field monitoring and data recording and database, and to construct a standardized population life table based on the population dynamics parameter sets of Indo-Pacific humpback dolphins; the population dynamics parameter sets include at least the initial population size, survival rate, reproductive rate, and environmental carrying capacity; Model building module: used to predefine the growth stage structure of the Indo-Pacific humpback dolphin based on the standardized population life table, obtain the survival rate and reproduction rate of the Indo-Pacific humpback dolphin, construct a projection matrix based on the growth stage structure, survival rate and reproduction rate, predefine the population iteration formula, set the simulation duration and number of iterations, obtain the initial population vector, and construct a basic model based on the projection matrix, population iteration formula, number of iterations and initial population vector; Population projection module: used to establish a quantitative standard for the extinction of the Indo-Pacific humpback dolphin based on the population attributes, and to perform multiple dynamic projections of the population based on the basic model and simulation duration to obtain the population trajectory for each number of projections. Each dynamic projection involves random environmental sampling. Parameter analysis module: used to select several parameters from the population dynamics parameter set and set a perturbation interval for uniform distribution of the selected parameters to perform global sensitivity analysis of Sobol and obtain sensitivity analysis results. The sensitivity analysis results include the key indices and interaction relationships of the selected parameters. Scenario Protection Module: This module is used to determine survival threat factors based on standardized population life tables, projection matrices, basic models, population trajectories, and sensitivity analysis results; set protection measures conditions that match the survival threat factors; quantify these conditions into key parameters; input them into the basic model; and output new population trajectories under the protection measures conditions. Effective evaluation module: used to evaluate the effectiveness of the protection measures based on population trajectory, new population trajectory, and sensitivity analysis results.

9. An electronic device, characterized in that, include: Memory containing executable program code; A processor coupled to the memory; The processor calls the executable program code stored in the memory to execute the method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures as described in any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, wherein the computer program causes a computer to execute the method for simulating the population dynamics of the Indo-Pacific humpback dolphin and evaluating conservation measures as described in any one of claims 1 to 7.

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