Marine carbon sink data survey method and system

Abstract

The invention provides an ocean carbon sink data investigation method and system, and relates to the technical field of carbon sink management investigation, and the method comprises the steps: obtaining initial data in ocean carbon sink ecology, carrying out the carbon sink element analysis based on the initial data, determining carbon reserves and impact factors, building a dynamic change model based on the initial data and impact factors in the ocean carbon sink ecology, and obtaining an ocean carbon sink data investigation result. The method comprises the following steps: calculating an initial carbon sink prediction result, constructing a temperature feedback model correction model, carrying out temperature feedback correction on an obtained carbon sink prediction result, introducing a biological density and competition feedback mechanism based on the corrected carbon sink prediction result, constructing a multi-dimensional dynamic carbon sink optimization model, and obtaining a final optimized carbon sink prediction result. By introducing a dynamic change model, a temperature feedback model and a biological density and population competition feedback mechanism, static reserves of carbon sequestration in a marine ecosystem are considered, multi-dimensional dynamic feedback factors are integrated, and a carbon sequestration prediction result can be adjusted in different time steps.

Description

Technical Field

[0001] The present invention relates to the technical field of carbon sink management investigation, and in particular to a method and system for investigating marine carbon sink data. Background Art

[0002] Marine carbon sinks, also known as blue carbon, are processes, activities and mechanisms that use marine activities and marine organisms to absorb carbon dioxide from the atmosphere and fix and store it in marine ecosystems. The ocean has abundant carbon sink resources such as salt marshes, seagrass beds, algae and shellfish farming, and is the largest active carbon reservoir. Studies have shown that about one-third of the carbon dioxide emitted by humans each year is absorbed by the ocean, and the ocean has great potential for carbon fixation.

[0003] Current methods for investigating marine carbon sink data are mainly based on simple carbon storage statistics and temperature feedback models. However, these methods usually only consider the initial data of carbon storage and basic environmental factors, such as the impact of temperature on carbon sinks, and fail to fully consider dynamic feedback mechanisms such as biological density and population competition, making it difficult to accurately reflect the complex interactions within marine ecosystems.

[0004] In addition, the existing methods set a relatively simple time step for carbon sink changes, which cannot adapt to the multi-dimensional and multi-scale dynamic changes in marine ecosystems, resulting in low accuracy and applicability of the prediction results.

[0005] Therefore, it is urgent to propose a method and system for investigating marine carbon sink data. Summary of the invention

[0006] The present invention provides a marine carbon sink data survey method and system, aiming to solve the technical problem that it is difficult to accurately reflect the complex interactions within the marine ecosystem in related technologies, thereby avoiding the practical problem of being unable to adapt to the dynamic changes of multiple dimensions and scales in the marine ecosystem, thereby avoiding the subsequent problems of low accuracy and applicability of the prediction results.

[0007] To achieve the above object, the present invention provides the following technical solutions: A method for investigating marine carbon sink data includes the following steps: Step S100, obtaining initial data in the marine carbon sink ecology, and performing carbon sink element analysis based on the initial data to determine carbon storage and influencing factors; Step S200: construct a dynamic change model based on the initial data and influencing factors in the marine carbon sink ecology, and calculate the initial carbon sink prediction result; Step S300, constructing a temperature feedback model correction model, and performing temperature feedback correction on the carbon sink prediction result obtained in step S200; Step S400: Based on the revised carbon sink prediction result in step S300, biological density and competition feedback mechanism are introduced to construct a multi-dimensional dynamic carbon sink optimization model to obtain the final optimized carbon sink prediction result.

[0008] In this application, the initial data in the marine carbon sink ecology is obtained, and the carbon sink element analysis is performed based on the initial data to determine the carbon storage and influencing factors. Based on the initial data and influencing factors in the marine carbon sink ecology, a dynamic change model is constructed, the initial carbon sink prediction results are calculated, and a temperature feedback model correction model is constructed. The obtained carbon sink prediction results are corrected by temperature feedback. Based on the corrected carbon sink prediction results, the biological density and competition feedback mechanism are introduced to construct a multidimensional dynamic carbon sink optimization model to obtain the final optimized carbon sink prediction results. By introducing a dynamic change model, a temperature feedback model, and a biological density and population competition feedback mechanism, the accuracy and reliability of carbon sink prediction are significantly improved. Compared with the disclosed technology, the present invention not only considers the static reserves of carbon sinks in marine ecosystems, but also integrates multidimensional dynamic feedback factors, and can adjust the carbon sink prediction results within different time steps. In addition, the present invention can more accurately reflect the dynamic change trend of marine carbon sinks by optimizing the output mechanism, effectively solving the problems of inaccurate prediction results and poor adaptability in the prior art.

[0009] As a preferred solution of the present invention, initial data of marine carbon sink ecology is obtained, and carbon sink element analysis is performed based on the initial data to determine carbon storage and influencing factors, specifically including: Step S101: Initial data in the marine carbon sink ecology include above-ground carbon storage data, underground carbon storage data and sediment carbon storage data.

[0010] Step S102: Carbon sink element analysis, specifically: Aboveground carbon storage analysis, calculate the aboveground carbon storage in marine ecosystems: ; In the formula, is the aboveground biomass, is the carbon content coefficient, It is the data of above-ground carbon storage.

[0011] Underground carbon storage analysis, calculate the carbon storage of the underground part of the marine ecosystem: ; In the formula, is the underground biomass, is the carbon content coefficient, It is the underground carbon storage data.

[0012] Sediment carbon storage analysis, calculate the carbon storage of sediments in marine ecosystems: ; In the formula, is the sediment density, is the sediment depth, is the sediment organic carbon content, Represents sediment carbon storage data.

[0013] Step S103: Based on the acquired initial data and the carbon sink element analysis results, a statistical regression analysis method is used to determine the influencing factors of carbon storage.

[0014] As a preferred solution of the present invention, based on the initial data and influencing factors in the marine carbon sink ecology, a dynamic change model is constructed to calculate the initial carbon sink prediction results, specifically including: Step S201: Before constructing the dynamic change model, the respiration rate and the primary productivity in the marine ecology are calculated.

[0015] Among them, the respiration rate in marine ecology represents the respiratory consumption process of marine carbon sink ecology. The respiration rate in marine ecology changes with changes in temperature, salinity and dissolved oxygen concentration.

[0016] Calculate the respiration rate in marine ecosystems, specifically: ; In the formula, represents the respiratory rate coefficient, represents the effect of temperature on respiration rate, represents the comprehensive influence function of salinity and dissolved oxygen concentration, Represents the respiration rate in marine ecosystems.

[0017] Among them, primary productivity in marine ecology refers to the carbon storage increased by marine carbon sink ecology through photosynthesis and nutrient utilization.

[0018] Calculate primary productivity in marine ecosystems, specifically: ; In the formula, Represents the primary productivity in marine ecology, represents the primary productivity coefficient, represents the temperature influence function, Represents the influence function of nutrient concentration.

[0019] Step S202: Based on the initial data and influencing factors in the marine carbon sink ecology in step S100, the primary productivity in the marine ecology and the respiration rate in the marine ecology are input to construct a dynamic change model, specifically: ; In the formula, Initial carbon sink prediction results, represents the initial carbon storage, Primary productivity in marine ecosystems, represents the respiration rate in marine ecology, and t represents the prediction time step; Step S203: Calculate the carbon sink change in each time step based on the dynamic change model obtained in step S202, and accumulate the result to the initial carbon storage to obtain the initial carbon sink prediction result of the carbon sink.

[0020] As a preferred solution of the present invention, the carbon sink change in each time step is calculated based on the dynamic change model obtained in step S202, and the result is accumulated to the initial carbon storage to obtain the preliminary prediction result of the carbon sink, which is specifically: ; In the formula, represents the initial carbon sink prediction result, represents the carbon sink at the previous time step, The time step is The net change in carbon stocks, Represents the time step.

[0021] In the dynamic change model, the time step is set based on the time range and accuracy of the study. ,The event step length of this dynamic change model is set to seven days as a time step to calculate and accumulate the increase and decrease of carbon storage.

[0022] As a preferred solution of the present invention, a temperature feedback model correction model is constructed to perform temperature feedback correction on the carbon sink prediction result obtained in step S200, specifically including: Step S301, obtain current temperature data, set the optimal temperature, calculate the temperature deviation value, and the optimal temperature is determined based on the ecological type and historical data.

[0023] Among them, the optimal temperature is the optimal temperature value in the marine carbon sink ecology. At this temperature, the primary productivity and respiration rate are at their optimal state, and the carbon sink capacity reaches its maximum value.

[0024] Calculate the temperature deviation value, calculate the current temperature T and the optimal temperature The deviation between them is: ; In the formula, represents the optimal temperature, T represents the current temperature, Indicates temperature deviation.

[0025] Among them, if If the temperature is small, it means that the temperature is close to the optimal value and the carbon sink capacity is close to the maximum value. If it is larger, the temperature deviates from the optimal value and the carbon sequestration capacity decreases.

[0026] Step S302: construct a temperature feedback model, specifically: ; In the formula, represents the revised carbon sink prediction result, represents the initial carbon sink prediction result, T represents the ambient temperature at the current time step, represents the optimal temperature, Represents the temperature sensitivity coefficient.

[0027] Step S303: feedback correction: Based on the temperature feedback model obtained in step S302, the initial carbon sink prediction result obtained in step S200 is corrected, and the temperature deviation is Substitute into the temperature feedback model to correct the initial carbon sink prediction result obtained in step S200, specifically: ; In the formula, represents the revised carbon sink prediction result, represents the initial carbon sink prediction result, represents the temperature sensitivity coefficient, e represents the base of the natural logarithm, Indicates temperature deviation.

[0028] Step S304: derive a revised carbon sink prediction result based on step S303.

[0029] When the temperature is close to the optimal temperature When the correction result Close to initial prediction results If the temperature deviates from the optimal temperature, the correction result will be less than , reflecting the negative impact of temperature deviation on carbon sink capacity.

[0030] As a preferred solution of the present invention, the temperature sensitivity coefficient is calculated by MATLAB The function performs regression analysis on the initial data of the marine carbon sink ecology obtained in step S100, fits the carbon sink change data under different temperatures, and finally determines the temperature sensitivity coefficient.

[0031] As a preferred solution of the present invention, based on the corrected carbon sink prediction result in step S300, the biomass density and competition feedback mechanism are introduced to construct a multidimensional dynamic carbon sink optimization model to obtain the final optimized carbon sink prediction result, which specifically includes: Step S401, obtaining biomass density data and calculating biomass density feedback factors, specifically: ; In the formula, represents the current biomass density, Indicates the maximum permissible value of biomass density, Represents the adjustment coefficient.

[0032] When the biomass density is close to hour, It will approach 0, indicating a decrease in carbon sink capacity.

[0033] Step S402: Obtain inter-population competition data and calculate population competition feedback factors, specifically: ; In the formula, , , Expressed as the carbon storage of different biological populations, Represents the population competition feedback factor.

[0034] Among them, when a certain species is more competitive and dominant, the carbon sink capacity will tilt towards this species, but the overall carbon sink capacity may be affected by the decline in biodiversity, so this feedback mechanism is introduced.

[0035] Step S403: Based on the carbon sink prediction amount corrected by temperature feedback obtained in step S300, the population competition feedback factor and the biological density feedback factor are input to construct a multidimensional dynamic carbon sink optimization model, and the final carbon sink prediction result is output based on the model, specifically: ; In the formula, represents the predicted carbon sink after temperature feedback correction, represents the biomass density feedback factor, represents the population competition feedback factor, Represents the final carbon sink prediction result.

[0036] This application also provides a marine carbon sink data survey system, including the following: The analysis and determination unit is used to obtain the initial data of the marine carbon sink ecology, and to analyze the carbon sink elements based on the initial data to determine the carbon storage and influencing factors; The preliminary prediction unit is used to build a dynamic change model based on the initial data and influencing factors in the marine carbon sink ecology and calculate the initial carbon sink prediction results; A feedback correction unit is used to construct a temperature feedback model correction model and to perform temperature feedback correction on the obtained carbon sink prediction results; The optimization output unit is used to introduce biological density and competition feedback mechanism based on the revised carbon sink prediction results, conduct multi-dimensional dynamic carbon sink optimization, and obtain the final optimized carbon sink prediction results.

[0037] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention collects initial data of marine carbon sink ecosystems and combines dynamic analysis and environmental correction models to accurately calculate changes in marine carbon sinks. Specifically, by combining and optimizing multiple formulas, external factors affecting carbon sinks are included in the analysis to further improve prediction accuracy. Compared with traditional methods that only use static data, this method more accurately reflects changes in marine carbon sinks under complex ecological environments.

[0038] 2. The present invention not only stops at the acquisition and prediction of carbon sink data, but also introduces an internal feedback mechanism to further optimize the prediction results of carbon sink amount. The internal feedback mechanism allows the addition of ecological feedback effects in data analysis, thereby simulating the dynamic changes of the actual marine carbon sink system.

[0039] 3. By applying this method in different marine carbon sink environments, the present invention can obtain and analyze carbon sink data under different ecological environments. Moreover, this method has additional scalability and can adapt to different ecological environments. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 A flow chart of a method for investigating marine carbon sink data provided in an embodiment of the present application.

[0041] Figure 2 A schematic diagram of an ocean carbon sink data survey system provided in an embodiment of the present application.

[0042] Reference numerals: 230, analysis and determination unit; 231, preliminary prediction unit; 232, feedback correction unit; 233, optimization output unit. DETAILED DESCRIPTION

[0043] The following will combine the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention. Figure 1 , Figure 1 A flow chart of a method for investigating marine carbon sink data is provided for an embodiment of the present application.

[0044] In this embodiment, a method for investigating marine carbon sink data may include step S100, step S200, step S300 and step S400.

[0045] Step S100: Acquire initial data of marine carbon sink ecology, and perform carbon sink element analysis based on the initial data to determine carbon storage and influencing factors.

[0046] Specifically, they include: Step S101: Initial data in the marine carbon sink ecology include above-ground carbon storage data, underground carbon storage data and sediment carbon storage data.

[0047] Step S102: Carbon sink element analysis, specifically: Aboveground carbon storage analysis, calculate the aboveground carbon storage in marine ecosystems: ; In the formula, is the aboveground biomass, is the carbon content coefficient, It is the data of above-ground carbon storage.

[0048] Underground carbon storage analysis, calculate the carbon storage of the underground part of the marine ecosystem: ; In the formula, is the underground biomass, is the carbon content coefficient, It is the underground carbon storage data.

[0049] Sediment carbon storage analysis, calculate the carbon storage of sediments in marine ecosystems: ; In the formula, is the sediment density, is the sediment depth, is the sediment organic carbon content, Represents sediment carbon storage data.

[0050] Step S103: Based on the acquired initial data and the carbon sink element analysis results, a statistical regression analysis method is used to determine the influencing factors of carbon storage.

[0051] Step S200: Based on the initial data and influencing factors in the marine carbon sink ecology, a dynamic change model is constructed to calculate the initial carbon sink prediction result.

[0052] Specifically, they include: Step S201: Before constructing the dynamic change model, the respiration rate and the primary productivity in the marine ecology are calculated.

[0053] Calculate the respiration rate in marine ecosystems, specifically: ; In the formula, represents the respiratory rate coefficient, represents the effect of temperature on respiration rate, represents the comprehensive influence function of salinity and dissolved oxygen concentration, Represents the respiration rate in marine ecosystems.

[0054] Calculate primary productivity in marine ecosystems, specifically: ; In the formula, Represents the primary productivity in marine ecology, represents the primary productivity coefficient, represents the temperature influence function, Represents the influence function of nutrient concentration.

[0055] Step S202: Based on the initial data and influencing factors in the marine carbon sink ecology in step S100, the primary productivity in the marine ecology and the respiration rate in the marine ecology are input to construct a dynamic change model, specifically: ; In the formula, Initial carbon sink prediction results, represents the initial carbon storage, Primary productivity in marine ecosystems, represents the respiration rate in marine ecology and t represents the prediction time step.

[0056] Step S203: Calculate the carbon sink change in each time step based on the dynamic change model obtained in step S202, and accumulate the results to the initial carbon storage to obtain the initial carbon sink prediction result of the carbon sink, which is specifically: ; In the formula, represents the initial carbon sink prediction result, represents the carbon sink at the previous time step, The time step is The net change in carbon stocks, Represents the time step.

[0057] Step S300: construct a temperature feedback model correction model to perform temperature feedback correction on the carbon sink prediction result obtained in step S200.

[0058] Specifically, they include: Step S301, obtain current temperature data, set the optimal temperature, calculate the temperature deviation value, and the optimal temperature is determined based on the ecological type and historical data.

[0059] Calculate the temperature deviation value, calculate the current temperature T and the optimal temperature The deviation between them is: ; In the formula, represents the optimal temperature, T represents the current temperature, Indicates temperature deviation.

[0060] Step S302: construct a temperature feedback model, specifically: ; In the formula, represents the revised carbon sink prediction result, represents the initial carbon sink prediction result, T represents the ambient temperature at the current time step, represents the optimal temperature, Represents the temperature sensitivity coefficient.

[0061] Step S303: feedback correction: Based on the temperature feedback model obtained in step S302, the initial carbon sink prediction result obtained in step S200 is corrected, and the temperature deviation is Substitute into the temperature feedback model to correct the initial carbon sink prediction result obtained in step S200, specifically: ; In the formula, represents the revised carbon sink prediction result, represents the initial carbon sink prediction result, represents the temperature sensitivity coefficient, e represents the base of the natural logarithm, Indicates temperature deviation.

[0062] Step S304: derive a revised carbon sink prediction result based on step S303.

[0063] It should be noted that the temperature sensitivity coefficient is calculated by MATLAB The function performs regression analysis on the initial data of the marine carbon sink ecology obtained in step S100, fits the carbon sink change data under different temperatures, and finally determines the temperature sensitivity coefficient.

[0064] Step S400: Based on the revised carbon sink prediction result in step S300, biological density and competition feedback mechanism are introduced to construct a multi-dimensional dynamic carbon sink optimization model to obtain the final optimized carbon sink prediction result.

[0065] Specifically, they include: Step S401, obtaining biomass density data and calculating biomass density feedback factors, specifically: ; In the formula, represents the current biomass density, Indicates the maximum permissible value of biomass density, Represents the adjustment coefficient.

[0066] Step S402: Obtain inter-population competition data and calculate population competition feedback factors, specifically: ; In the formula, , , Expressed as the carbon storage of different biological populations, Represents the population competition feedback factor.

[0067] Step S403: Based on the carbon sink prediction amount corrected by temperature feedback obtained in step S300, the population competition feedback factor and the biological density feedback factor are input to construct a multidimensional dynamic carbon sink optimization model, and the final carbon sink prediction result is output based on the model, specifically: ; In the formula, represents the predicted carbon sink after temperature feedback correction, represents the biomass density feedback factor, represents the population competition feedback factor, Represents the final carbon sink prediction result.

[0068] Among them, illustratively, a set of experimental data is substituted as follows to demonstrate the specific process of the method.

[0069] First, obtain the initial data of marine carbon sink ecology. The initial data set is as follows: The aboveground carbon storage data is , underground carbon storage data is , the sediment carbon storage data is , sediment depth is 50cm, organic carbon content It is 2%.

[0070] Substitute the data for calculation, specifically: Above-ground carbon storage is: ; The amount of carbon stored in the ground is: ; Sediment carbon storage is: ; A dynamic change model was constructed to calculate the initial carbon sink prediction results, assuming that the primary productivity and respiration rate are as follows: Primary productivity .

[0071] Respiratory rate .

[0072] Then the initial carbon sink prediction result of the dynamic change model is: ; Construct temperature feedback model correction, assuming the current temperature is The optimal temperature is , then the temperature deviation , using the temperature feedback model, specifically: ; In the formula, .

[0073] ; Based on the correction results, the biological density and population competition feedback mechanism is introduced to optimize the carbon sink prediction, specifically: Assume the current biomass density is , maximum biomass density , calculate the biodensity feedback factor: ; Obtain the value of the biodensity feedback factor.

[0074] Assume that there are currently two main populations, with carbon storages: and ; Calculate the population competition feedback factor: ; Obtain the value of population competition feedback factor.

[0075] Substituting the values ​​of population competition feedback factor and biological density feedback factor into the formula, the final optimized carbon sink prediction result is: ; The carbon sink prediction result value after the prediction area is optimized is obtained. After the value is obtained, it is compared with the actual calculated value, and a survey report is generated based on the comparison result to realize the carbon sink data survey and processing.

[0076] See also Figure 2 , Figure 2 A flow chart of an ocean carbon sink data survey system is provided for an embodiment of the present application.

[0077] In this embodiment, a marine carbon sink data survey system may include: The analysis and determination unit 230 is used to obtain initial data in the marine carbon sink ecology, and perform carbon sink element analysis based on the initial data to determine the carbon storage and influencing factors.

[0078] The preliminary prediction unit 231 is used to construct a dynamic change model based on the initial data and influencing factors in the marine carbon sink ecology and calculate the initial carbon sink prediction results.

[0079] The feedback correction unit 232 constructs a temperature feedback model correction model to perform temperature feedback correction on the obtained carbon sink prediction result.

[0080] The optimization output unit 233 is used to introduce biological density and competition feedback mechanism based on the revised carbon sink prediction result, perform multi-dimensional dynamic carbon sink optimization, and obtain the final optimized carbon sink prediction result.

[0081] Among them, the initial data of marine carbon sink ecology is obtained by analyzing and determining the unit, and carbon sink element analysis is performed to determine carbon storage and influencing factors. This unit is connected to the database through a sensor network to collect basic data on above-ground, underground and sediment carbon storage, and based on the preliminary prediction unit, a dynamic change model is constructed to calculate the initial carbon sink prediction results. The system runs based on the set model, automatically calculates the carbon sink change amount at each time step, and after obtaining the initial carbon sink prediction results, feedback correction is performed according to the actual environmental conditions through the feedback correction unit, a temperature feedback model is constructed and the prediction results are corrected. The feedback correction unit obtains temperature data from an external meteorological database, compares it with the preset optimal temperature, and corrects the carbon sink prediction results. Finally, through the optimization output unit, based on the corrected prediction results, a biological density and competition feedback mechanism is introduced to construct a multidimensional dynamic carbon sink optimization model, and the final carbon sink prediction results are output. The system will automatically adjust parameters such as biological density and population competition to optimize the final results. After obtaining the numerical value, the obtained numerical value is compared with the actual calculated numerical value, and a survey report is generated based on the comparison results to realize carbon sink data survey and processing.

[0082] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A method for investigating marine carbon sink data. It is characterized in that These include: S100, obtain initial data on marine carbon sink ecology, and analyze carbon sink elements based on the initial data to determine carbon storage and influencing factors; S200, based on the initial data and influencing factors in the marine carbon sink ecology, build a dynamic change model and calculate the initial carbon sink prediction results; S300, constructing a temperature feedback model correction model to perform temperature feedback correction on the carbon sink prediction result obtained in S200; S400: Based on the revised carbon sink prediction results in S300, the biological density and competition feedback mechanism are introduced to construct a multi-dimensional dynamic carbon sink optimization model to obtain the final optimized carbon sink prediction results.

2. A method for investigating marine carbon sink data according to claim 1, It is characterized in that Obtain initial data on marine carbon sink ecology, and conduct carbon sink factor analysis based on the initial data to determine carbon storage and influencing factors, including: S101. The initial data in the marine carbon sink ecology includes above-ground carbon storage data, underground carbon storage data and sediment carbon storage data; S102. Carbon sink element analysis, specifically: Aboveground carbon storage analysis, calculate the aboveground carbon storage in marine ecosystems: ； In the formula, is the aboveground biomass, is the carbon content coefficient, is the above-ground carbon storage data; Underground carbon storage analysis, calculate the carbon storage of the underground part of the marine ecosystem: ； In the formula, is the underground biomass, is the carbon content coefficient, For underground carbon storage data; Sediment carbon storage analysis, calculate the carbon storage of sediments in marine ecosystems: ； In the formula, is the sediment density, is the sediment depth, is the sediment organic carbon content, represents sediment carbon storage data; S103. Based on the obtained initial data and the carbon sink factor analysis results, use statistical regression analysis processing methods to determine the influencing factors of carbon storage.

3. A method for investigating marine carbon sink data according to claim 2, It is characterized in that Based on the initial data and influencing factors in the marine carbon sink ecology, a dynamic change model is constructed to calculate the initial carbon sink prediction results, including: S201. Before constructing the dynamic change model, the respiration rate and primary productivity in the marine ecology are calculated; Calculate the respiration rate in marine ecosystems, specifically: ； In the formula, represents the respiratory rate coefficient, represents the effect of temperature on respiration rate, represents the comprehensive influence function of salinity and dissolved oxygen concentration, Represents the respiration rate in marine ecology; Calculate primary productivity in marine ecosystems, specifically: ； In the formula, Represents the primary productivity in marine ecology, represents the primary productivity coefficient, represents the temperature influence function, represents the influence function of nutrient concentration; S202: Based on the initial data and influencing factors of the marine carbon sink ecology in S100, the primary productivity and respiration rate in the marine ecology are input to construct a dynamic change model, specifically: ； In the formula, Initial carbon sink prediction results, represents the initial carbon stock, Primary productivity in marine ecosystems, represents the respiration rate in marine ecology, and t represents the prediction time step; S203. Based on the dynamic change model obtained in S202, the carbon sink change in each time step is calculated, and the result is accumulated to the initial carbon storage to obtain the initial carbon sink prediction result of the carbon sink.

4. A method for investigating marine carbon sink data according to claim 3, It is characterized in that Based on the dynamic change model obtained in S202, the carbon sink changes in each time step are calculated, and the results are accumulated to the initial carbon storage to obtain the preliminary prediction results of the carbon sink, which are as follows: ; In the formula, represents the initial carbon sink prediction result, represents the carbon sink at the previous time step, The time step is The net change in carbon stocks, Represents the time step.

5. A method for investigating marine carbon sink data according to claim 4, It is characterized in that A temperature feedback model correction model is constructed to perform temperature feedback correction on the carbon sink prediction results obtained in S200, specifically including: S301, obtaining current temperature data, setting an optimal temperature, and calculating a temperature deviation value, wherein the optimal temperature is determined based on the ecological type and historical data; Calculate the temperature deviation value, calculate the current temperature T and the optimal temperature The deviation between them is: ; In the formula, represents the optimal temperature, T represents the current temperature, Indicates temperature deviation; S302: Construct a temperature feedback model, specifically: ; In the formula, represents the revised carbon sink prediction result, represents the initial carbon sink prediction result, T represents the ambient temperature at the current time step, represents the optimal temperature, represents the temperature sensitivity coefficient; S303, feedback correction, based on the temperature feedback model obtained in S302, correct the initial carbon sink prediction result obtained in S200, and adjust the temperature deviation Substitute it into the temperature feedback model, specifically: ; In the formula, represents the revised carbon sink prediction result, represents the initial carbon sink prediction result, represents the temperature sensitivity coefficient, e represents the base of the natural logarithm, Indicates temperature deviation; S304. Obtain a revised carbon sink prediction result based on S303.

6. A method for investigating marine carbon sink data according to claim 5, It is characterized in that The temperature sensitivity coefficient is calculated by MATLAB The function performs regression analysis on the initial data of marine carbon sink ecology obtained in S100, fits the carbon sink change data under different temperatures, and finally determines the temperature sensitivity coefficient.

7. A method for investigating marine carbon sink data according to claim 5, It is characterized in that Based on the revised carbon sink prediction results in S300, the biomass density and competition feedback mechanism were introduced to construct a multi-dimensional dynamic carbon sink optimization model, and the final optimized carbon sink prediction results were obtained, including: S401. Obtain biomass density data and calculate biomass density feedback factors, specifically: ; In the formula, represents the current biomass density, Indicates the maximum permissible value of biomass density, represents the adjustment coefficient; S402, obtaining inter-population competition data and calculating population competition feedback factors, specifically: ; In the formula, , , Expressed as the carbon storage of different biological populations, represents the population competition feedback factor; S403, based on the carbon sink prediction amount corrected by temperature feedback obtained in S300, the population competition feedback factor and the biological density feedback factor are input to build a multi-dimensional dynamic carbon sink optimization model, and the final carbon sink prediction result is output based on the model, specifically: ； In the formula, represents the predicted carbon sink after temperature feedback correction, represents the biomass density feedback factor, represents the population competition feedback factor, Represents the final carbon sink prediction result.

8. A marine carbon sink data survey system, using a marine carbon sink data survey method as claimed in any one of claims 1 to 7, It is characterized in that These include: The analysis and determination unit is used to obtain the initial data of the marine carbon sink ecology, and to analyze the carbon sink elements based on the initial data to determine the carbon storage and influencing factors; The preliminary prediction unit is used to build a dynamic change model based on the initial data and influencing factors in the marine carbon sink ecology and calculate the initial carbon sink prediction results; A feedback correction unit is used to construct a temperature feedback model correction model and to perform temperature feedback correction on the obtained carbon sink prediction results; The optimization output unit is used to introduce biological density and competition feedback mechanism based on the revised carbon sink prediction results, conduct multi-dimensional dynamic carbon sink optimization, and obtain the final optimized carbon sink prediction results.

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