Coastal salt marsh ecosystem climate regulation service material quantity accounting method

Abstract

The invention relates to the field of ecological environment monitoring technology and ecological value evaluation accounting, in particular to a coastal salt marsh ecosystem climate regulation service material quantity accounting method, which comprises the following steps: S1, based on years of meteorological and ecological investigation monitoring data, extracting a response relationship of temperature and humidity to climate regulation positive utility, and calculating the climate regulation service material quantity of a coastal salt marsh ecosystem; constructing a response curve and dividing an enhancement region, an attenuation region and a reversal region; s2, screening forward contribution time periods according to utility partitions, identifying boundary fluctuation and mutation behaviors, and generating an adjustment utility validity period list; and S3, generating a contribution settlement table and converting the contribution settlement table into energy and matter quantity indexes according to the ecological type and the adjustment effectiveness in the block settlement validity period, and completing the adjustment service matter quantity accounting. According to the invention, through critical zone identification, validity period screening and multi-stage mapping conversion, high-precision, space-time sensitive and energy equivalent accounting of the climate regulation service material quality of the coastal salt marsh ecosystem is realized.

Description

Technical Field

[0001] This invention relates to the field of ecological environment monitoring technology, and in particular to a method for calculating the quality of climate regulation services in coastal salt marsh ecosystems. Background Technology

[0002] As the global climate change situation becomes increasingly severe, coastal salt marsh ecosystems have become key ecological resources due to their significant carbon sink potential and climate regulation function. These ecosystems can significantly enhance the climate resilience of coastal areas by cooling, humidifying, and buffering extreme climate events. Their regulation capacity is driven by meteorological factors and exhibits spatiotemporal heterogeneity and seasonal responsiveness. Against this backdrop, how to scientifically identify and quantify the climate regulation effect of coastal salt marsh ecosystems under different climatic conditions has become an important foundation for ecological accounting and carbon asset assessment.

[0003] Current research on the regulatory services of coastal salt marsh ecosystems mainly focuses on carbon accumulation and ecological value assessment, lacking a dynamic identification mechanism for regulatory effectiveness under short-term meteorological fluctuations. This makes it difficult to reveal the actual contribution of regulatory services to regional climate at different time periods. In addition, most existing methods fail to combine the response relationship between temperature-humidity meteorological combination characteristics and ecosystem types, lack clear identification mechanisms for areas of enhanced and reversed regulatory effectiveness, and have not established a systematic accounting path to convert regulatory contributions into standard energy and material indicators. This results in problems such as low spatial resolution, inconsistent indicators, and poor climate adaptability in the accounting results of regulatory services. Summary of the Invention

[0004] This invention provides a method for calculating the mass of climate regulation services in coastal salt marsh ecosystems. By constructing a temperature-humidity driven regulation utility response model, it achieves full-process modeling of spatial zoning of regulation utility, temporal stability determination, and contribution to sedimentation transformation. Furthermore, under the premise of ensuring that the utility makes a positive contribution, it outputs the regulation mass results of the ecosystem in different spatial blocks and time scales in a refined manner. This method has the advantages of high identification accuracy, strong time adaptability, and unified and comparable accounting indicators, providing quantitative support for the assessment of ecosystem service value, the construction of ecological compensation mechanisms, and the optimization of regional climate strategies in coastal salt marsh ecosystems.

[0005] A method for accounting for the quality of climate regulation services in coastal salt marsh ecosystems includes the following steps: S1, based on years of meteorological observation data and coastal salt marsh ecosystem cover information, extracts the historical response relationship between temperature and humidity to the cooling and humidifying effects of the ecosystem, forms climate regulation utility response curves to characterize the trend of regulation utility changes under different meteorological combinations, and outputs utility zoning results including utility enhancement zone, utility decay zone and utility reversal zone. S2, based on the utility partitioning results, filter the time segments where the moderating utility has not entered the utility decay zone or utility reversal zone, and generate a utility validity list by determining the time period when the utility boundary appears, the duration of the boundary and the type of mutation triggering. S3. Based on the utility validity period list, the regulation utility is gradually reduced to the regional contribution value according to the ecosystem type and spatial block, and a regulation contribution reduction table is generated. Then, based on the regulation contribution reduction table, the regulation contribution of each region is converted into energy equivalent value to obtain the target accounting result that reflects the quality of climate regulation services of the coastal salt marsh ecosystem.

[0006] Optionally, S1 includes: S11, based on multi-year continuous meteorological observation data of the target area, constructs a meteorological combination space with daily average temperature and daily average relative humidity as two variables. In the meteorological combination space, the historical transpiration intensity and evaporation response value of the ecosystem under different meteorological conditions are statistically analyzed, and the meteorological state is correlated with the actual temperature regulation or humidification effect. The nonlinear response trend of the effect value with the change of meteorological combination is extracted to form a climate regulation response map, which is used to reveal the coupling mechanism between regulation capacity and environmental state. Based on the climate regulation response map, S12 identifies the evolutionary critical point of the regulation effect of the ecosystem in different meteorological sections, fits a continuous regulation effect response curve, and divides the meteorological combination space into functional zones, namely the effect enhancement zone, the effect decline zone, and the effect reversal zone.

[0007] Optionally, S11 includes: S111 transforms multi-year diurnal meteorological observation data of the target area into a meteorological composite space with daily average temperature and daily average relative humidity as two-dimensional coordinate axes. A sliding window is then used to partition the data into two-dimensional partitions, forming a discretized sample grid. ,in, Let be the center value of the k-th daily average temperature interval. This is the center value of the l-th daily average relative humidity interval; S112, traversing the discretized sample grid for each meteorological combination space. The average transpiration intensity of the ecosystem under this combination of conditions was statistically analyzed. With average evaporation intensity ; S113, average transpiration intensity With average evaporation intensity Utility mapping was performed on the human body's temperature regulation needs or humidification needs, and the regulatory utility value was calculated. And construct a climate regulation response map.

[0008] Optionally, S12 includes: S121. Based on the climate regulation response map, a two-dimensional gradient analysis is performed on the meteorological combination space to calculate the response rate of the regulation utility to changes in temperature and humidity, reflecting the sensitivity and abrupt change trend of the regulation utility. By the peak value of the gradient modulus and the flipping of the gradient sign, the evolutionary critical point of the regulation utility with changes in meteorology is identified. S122, after identifying the evolutionary critical point of the moderating utility, the evolutionary critical point is connected according to the grid sequence of the meteorological combination space, and used as nodes to fit a continuous moderating utility response curve, thereby obtaining the fitted moderating utility surface function value. This is used to express the smooth variation trend of the moderating effect throughout the entire meteorological combination space; S123, the fitted adjustment utility surface function value Projecting back into the meteorological combination space, each meteorological combination is classified according to the sign of its moderating effect and the direction of its slope, forming functional zones, represented as follows: ; in, For functional partition categories, To fit the partial derivative of the utility function with respect to temperature, This is the partial derivative of the fitted utility function with respect to humidity.

[0009] Optionally, S2 includes: S21. Based on the functional zoning results in the meteorological composite space, all meteorological composite points classified as utility enhancement zones are screened, and their corresponding historical observation dates are mapped to candidate regulation service validity periods. By comparing the daily average temperature and relative humidity of each day in the meteorological observation data of previous years, it is determined whether the composite grid to which it falls is in the enhancement zone. If the conditions are met, the date is included in the candidate regulation service day list. S22, based on the candidate list of adjustment service days, analyzes the changing trend of adjustment utility values ​​in adjacent time periods using a sliding window approach, identifies adjustment boundary behaviors including short-term abrupt changes, boundary fluctuations, and insufficient continuity, performs a removal operation on time periods that do not have temporal stability, removes potential pseudo-adjustment contribution dates, and forms the final list of adjustment utility validity periods.

[0010] Optionally, S21 includes: S211, Extract daily records from historical meteorological observation data of the target area and construct a daily-scale meteorological index table. Each record in the table includes the daily average temperature for that day. and daily average relative humidity ; S212, based on the established spatial division criteria for meteorological combinations, including temperature step size. With humidity step The average daily temperature and daily average relative humidity Mapped to the composite mesh in which it resides ; S213, the combined grid obtained by mapping each day According to functional area category Determine whether the combination point belongs to the utility enhancement region. If it satisfies... Then, day d will be included in the candidate adjustment service day list. .

[0011] Optionally, S22 includes: S221, Regarding the Candidate Adjustment Service Day List Extract the fitted adjustment utility value for each day in chronological order. Forming a time series Perform a sliding window analysis on the time series to calculate the change in utility between adjacent dates. ; S222, Based on the results of sliding window analysis, identify adjustment boundary behaviors that lack temporal stability from the time series, specifically including: Short-term mutation: The direction of utility reverses sign within two consecutive days, i.e. ; Boundary fluctuations: The fitted adjustment utility value continuously approaches the zero threshold, i.e. The number of days continuously exceeds the window limit, among which, The threshold for determining the zero-value neighborhood; Insufficient continuity: Continuous length of candidate valid daily series It does not meet the minimum length requirement for continuity, where L is the length of a continuous time period within the candidate's validity period. =5 is the minimum consecutive valid day length threshold; S223, mark the dates that satisfy any adjustment boundary behavior as unstable periods, and remove the corresponding dates from the candidate adjustment service date list according to the set difference operation to form the final adjustment utility validity period list. .

[0012] Optionally, S3 includes: S31. Based on the obtained list of regulation utility validity periods, according to the type and spatial distribution grid of the coastal ecosystem, the regulation utility value at each time point is mapped to the corresponding spatial block to form an hourly partitioned regulation utility value matrix. The regulation utility value of each spatial block is accumulated over the entire validity period to form a regulation contribution settling table reflecting the regulation contribution of different ecological units at different time scales, which is used to describe the total regulation efficiency output of each spatial block. S32, based on the established regulation contribution subsidence table, performs energy equivalence transformation on the regulation contribution values ​​of different spatial blocks, converts them into standardized energy indicators according to the unit energy regulation equivalence coefficient of each ecosystem type, and then combines the climate regulation contribution factors of the ecosystem to transform them into material indicators. Finally, it outputs the quantitative contribution of the coastal salt marsh ecosystem to regional climate regulation during its effective period, that is, the regulation service material quality accounting results.

[0013] Optionally, S31 includes: S311 divides the study area into a set of spatial grids. Each grid cell All were labeled with their ecosystem type. And establish a mapping table ,in, For spatial coordinates, N is the number of spatial grids. It is a coastal wetland ecosystem. For mangrove ecosystems, It is a coastal salt marsh ecosystem; S312, based on each effective time point t in the selected list of effective adjustment periods, obtain its corresponding meteorological state. The utility value is calculated from the fitted adjustment utility surface function. Then, based on the effective time point t and the location of the ecological block, the value is mapped to the grid cell in which it is located. The time-series spatial adjustment contribution matrix is ​​obtained. ; S313, for each spatial grid cell Time-sequential spatial adjustment contribution matrix The total settlement contribution is calculated by summing the values ​​over the entire effective time period. And construct a settlement adjustment contribution table.

[0014] Optionally, S32 includes: S321, for each spatial grid cell The adjustment contribution of total settlement Based on its corresponding ecosystem type unit adjustment energy efficiency coefficient Converted into energy equivalent value ; S322, based on ecosystem type The moderating contribution of quality factors energy and other values Transformation into climate moderating properties of coastal salt marsh ecosystems ; S323 spatially integrates the mass contribution values ​​of all spatial grid cells to obtain the total mass of climate regulation services in the entire study area. .

[0015] The beneficial effects of this invention are: This invention, by constructing a bivariate meteorological combination space of temperature and humidity and extracting the nonlinear relationship between the intensity of ecosystem transpiration and evaporation response, systematically identifies for the first time the critical variation law of climate regulation services under different meteorological conditions. It achieves accurate division of the zones of enhanced, diminished and reversed regulation effectiveness, thereby significantly improving the discrimination ability and mechanism explanation in the process of regulation service accounting, and avoiding the problem of overestimation or biased estimation of effectiveness caused by ignoring the critical interval in traditional methods.

[0016] This invention introduces a sliding window trend analysis and a zero-value neighborhood determination mechanism, and combines the regulation utility response function to screen the stability of daily-scale historical meteorological data. This enables the dynamic identification of pseudo-regulation contribution segments and the formation of a high-confidence utility validity list. It effectively solves the problem of misjudgment due to year-round averaging in existing technologies, making the temporal distribution of regulation utility more consistent with physical processes and improving the scientificity and reliability of climate regulation substance quality assessment.

[0017] This invention designs a spatial grid structure for labeling ecosystem types and establishes a three-level mapping mechanism of zonal contribution, energy equivalence, and material conversion. This accurately reduces the output of ecosystem climate regulation services from the functional level to the carbon sink equivalent level, forming a material accounting framework with a clear structure, comparability, and accumulative capabilities. This framework can provide data support and technical foundation for the quantitative assessment of coastal salt marsh value, the calculation of total ecological product value, and the formulation of ecological compensation strategies. Attached Figure Description

[0018] To more clearly illustrate the technical solutions in this invention or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only for this invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a schematic diagram of the accounting method flow according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the utility partitioning process in an embodiment of the present invention. Detailed Implementation

[0020] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments. Those skilled in the art may employ other alternative methods to implement some well-known technologies; moreover, the accompanying drawings are only for more specific description of the embodiments and are not intended to specifically limit the present invention.

[0021] like Figures 1-2 As shown, the method for accounting for the quality of climate regulation services in coastal salt marsh ecosystems includes the following steps: S1, based on years of meteorological observation data and coastal salt marsh ecosystem cover information, extracts the historical response relationship between temperature and humidity to the cooling and humidifying effects of the ecosystem, forms climate regulation utility response curves to characterize the trend of regulation utility changes under different meteorological combinations, and outputs utility zoning results including utility enhancement zone, utility decay zone and utility reversal zone. S2, based on the utility partitioning results, filters the time segments in which moderating utility has not entered the utility decay region or utility reversal region, and generates a utility validity period list that can ensure that moderating utility makes a positive contribution by determining the time period when the utility boundary appears, the duration of the boundary and the type of mutation triggering. S3, based on the utility validity period list, according to ecosystem type and spatial block, the regulation utility is settled into the zonal contribution value hourly and the regulation contribution settlement table is generated cumulatively. Then, based on the regulation contribution settlement table, the regulation contribution of each zonal is converted into energy equivalent to obtain the target accounting results that reflect the quality of climate regulation services of coastal salt marsh ecosystem.

[0022] S1 includes: S11, based on multi-year continuous meteorological observation data of the target area, constructs a meteorological combination space with daily average temperature and daily average relative humidity as two variables. In the meteorological combination space, the historical transpiration intensity and evaporation response value of the ecosystem under different meteorological conditions are statistically analyzed, and the meteorological state is correlated with the actual temperature regulation or humidification effect. The nonlinear response trend of the effect value with the change of meteorological combination is extracted to form a climate regulation response map, which is used to reveal the coupling mechanism between regulation capacity and environmental state. Based on the climate regulation response map, S12 identifies the evolutionary critical point of the regulation effect of the ecosystem in different meteorological sections, fits a continuous regulation effect response curve, and divides the meteorological combination space into functional zones, namely the effect enhancement zone, the effect decline zone, and the effect reversal zone.

[0023] S11 includes: S111 transforms multi-year diurnal meteorological observation data of the target area into a meteorological composite space with daily average temperature and daily average relative humidity as two-dimensional coordinate axes. A sliding window is then used to partition the data into two-dimensional partitions, forming a discretized sample grid. ,in, Let be the center value of the k-th daily average temperature interval. This is the center value of the l-th daily average relative humidity interval; S112, traversing the discretized sample grid for each meteorological combination space. The average transpiration intensity of the ecosystem under this combination of conditions was statistically analyzed. With average evaporation intensity , represented as: ; ; in, To fall into the combined interval The number of historical days The measured transpiration intensity of the vegetation area on day d. The measured evaporation intensity in the wetland area on day d; S113, average transpiration intensity With average evaporation intensity Utility mapping was performed on the human body's temperature regulation needs or humidification needs, and the regulatory utility value was calculated. And construct a climate regulation response map, represented as: ; in, , These are the corresponding weighting coefficients.

[0024] S12 includes: S121, based on the climate regulation response map, a two-dimensional gradient analysis is performed on the meteorological combination space to calculate the response rate of the regulation utility to changes in temperature and humidity, reflecting the sensitivity and abrupt change trend of the regulation utility. By analyzing the peak value of the gradient modulus and the sign reversal of the gradient, the critical point of the evolution of the regulation utility with meteorological changes is identified, expressed as: ; in, To adjust the magnitude of the utility response gradient, For the partial derivative of utility with respect to temperature, The partial derivative of utility with respect to humidity; Evolutionary critical points include the utility enhancement threshold, the boundary decay interval, and the utility reversal mutation point, denoted as: Rapid gradient ascent → utility enhancement threshold; Gradient decreases significantly → Boundary decay interval; Gradient sign reversal (positive → negative) → utility reversal mutation point; S122, after identifying the evolutionary critical point of the moderating utility, the evolutionary critical point is connected according to the grid sequence of the meteorological combination space, and used as nodes to fit a continuous moderating utility response curve, thereby obtaining the fitted moderating utility surface function value. This is used to express the smooth variation trend of the moderating effect throughout the entire meteorological combination space, and is represented as: ; ; in, For the fitting function, , , , , , These are the corresponding fitting coefficients; S123, the fitted adjustment utility surface function value Projecting back into the meteorological combination space, each meteorological combination is classified according to the sign of its moderating effect and the direction of its slope, forming functional zones, represented as follows: ; in, For functional partition categories, To fit the partial derivative of the utility function with respect to temperature, This is the partial derivative of the fitted utility function with respect to humidity.

[0025] S2 includes: S21. Based on the functional zoning results in the meteorological composite space, all meteorological composite points classified as utility enhancement zones are screened, and their corresponding historical observation dates are mapped to candidate regulation service validity periods. By comparing the daily average temperature and relative humidity of each day in the meteorological observation data of previous years, it is determined whether the composite grid to which it falls is in the enhancement zone. If the conditions are met, the date is included in the candidate regulation service day list. S22, based on the candidate list of adjustment service days, analyzes the changing trend of adjustment utility values ​​in adjacent time periods using a sliding window approach, identifies adjustment boundary behaviors including short-term abrupt changes, boundary fluctuations, and insufficient continuity, performs a removal operation on time periods that do not have temporal stability, removes potential pseudo-adjustment contribution dates, and forms the final list of adjustment utility validity periods.

[0026] S21 includes: S211, Extract daily records from historical meteorological observation data of the target area and construct a daily-scale meteorological index table. Each record in the table includes the daily average temperature for that day. and daily average relative humidity ; S212, based on the established spatial division criteria for meteorological combinations, including temperature step size. With humidity step The average daily temperature and daily average relative humidity Mapped to the composite mesh in which it resides , represented as: ; ; in, , These are the temperature and humidity index numbers corresponding to the meteorological combined grid. , These are the initial values ​​corresponding to the combinatorial space. This is the floor symbol; S213, the combined grid obtained by mapping each day According to functional area category Determine whether the combination point belongs to the utility enhancement region. If it satisfies... Then, day d will be included in the candidate adjustment service day list. , represented as: .

[0027] S22 includes: S221, Regarding the Candidate Adjustment Service Day List Extract the fitted adjustment utility value for each day in chronological order. Forming a time series Perform a sliding window analysis on the time series to calculate the change in utility between adjacent dates. , represented as: ; in, , These are the (i+1)th and ith dates in the candidate adjustment service day list, respectively. S222, Based on the results of sliding window analysis, identify adjustment boundary behaviors that lack temporal stability from the time series, specifically including: Short-term mutation: The direction of utility reverses sign within two consecutive days, i.e. ; Boundary fluctuations: The fitted adjustment utility value continuously approaches the zero threshold, i.e. The number of days continuously exceeds the window limit, among which, The threshold for determining the zero-value neighborhood. , The fitted adjustment utility surface function value The maximum value; Insufficient continuity: Continuous length of candidate valid daily series It does not meet the minimum length requirement for continuity, where L is the length of a continuous time period within the candidate's validity period. =5 is the minimum consecutive valid day length threshold; S223, mark the dates that satisfy any adjustment boundary behavior as unstable periods, and remove the corresponding dates from the candidate adjustment service date list according to the set difference operation to form the final adjustment utility validity period list. , represented as: ; in, The set of dates determined to lack stable regulatory utility.

[0028] S3 includes: S31. Based on the obtained list of regulation utility validity periods, according to the type and spatial distribution grid of the coastal ecosystem, the regulation utility value at each time point is mapped to the corresponding spatial block to form an hourly partitioned regulation utility value matrix. The regulation utility value of each spatial block is accumulated over the entire validity period to form a regulation contribution settling table reflecting the regulation contribution of different ecological units at different time scales, which is used to describe the total regulation efficiency output of each spatial block. S32, based on the established regulation contribution subsidence table, performs energy equivalence transformation on the regulation contribution values ​​of different spatial blocks, converts them into standardized energy indicators according to the unit energy regulation equivalence coefficient of each ecosystem type, and then combines the climate regulation contribution factors of the ecosystem to transform them into material indicators. Finally, it outputs the quantitative contribution of the coastal salt marsh ecosystem to regional climate regulation during its effective period, that is, the regulation service material quality accounting results.

[0029] S31 includes: S311 divides the study area into a set of spatial grids. Each grid cell All were labeled with their ecosystem type. And establish a mapping table ,in, For spatial coordinates, N is the number of spatial grids. It is a coastal wetland ecosystem. For mangrove ecosystems, It is a coastal salt marsh ecosystem; S312, based on each effective time point t in the selected list of effective adjustment periods, obtain its corresponding meteorological state. The utility value is calculated from the fitted adjustment utility surface function. Then, based on the effective time point t and the location of the ecological block, the value is mapped to the grid cell in which it is located. The time-series spatial adjustment contribution matrix is ​​obtained. , represented as: ; in, The function is an indicator function. If the i-th grid is within the validity period at time t and the weather falls into the enhancement zone, it is 1; otherwise, it is 0. S313, for each spatial grid cell Time-sequential spatial adjustment contribution matrix The total settlement contribution is calculated by summing the values ​​over the entire effective time period. And construct a settlement adjustment contribution table, represented as follows: ; ; in, For the valid time interval, For time step, This represents the total regulation output value for each ecological grid unit within its validity period.

[0030] S32 includes: S321, for each spatial grid cell The adjustment contribution of total settlement Based on its corresponding ecosystem type unit adjustment energy efficiency coefficient Converted into energy equivalent value , represented as: ; S322, based on ecosystem type The moderating contribution of quality factors energy and other values Transformation into climate moderating properties of coastal salt marsh ecosystems , represented as: ; S323 spatially integrates the mass contribution values ​​of all spatial grid cells to obtain the total mass of climate regulation services in the entire study area. , represented as: ; Where N is the total number of grid cells.

[0031] This invention encompasses any substitutions, modifications, equivalent methods, and solutions made within the spirit and scope of this invention. To provide the public with a thorough understanding of this invention, specific details are described in detail in the following preferred embodiments; however, those skilled in the art will fully understand the invention even without these details. Furthermore, to avoid unnecessary misunderstanding of the essence of this invention, well-known methods, processes, procedures, components, and circuits are not described in detail.

[0032] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of the present invention, and these improvements and modifications should also be considered within the scope of protection of the present invention.

Claims

1. A method for accounting for the quantity of climate regulation services in coastal salt marsh ecosystems, characterized in that, Includes the following steps: S1, based on years of meteorological observation data and coastal salt marsh ecosystem cover information, extracts the historical response relationship between temperature and humidity to the cooling and humidifying effects of the ecosystem, forms climate regulation utility response curves to characterize the trend of regulation utility changes under different meteorological combinations, and outputs utility zoning results including utility enhancement zone, utility decay zone and utility reversal zone. S2, based on the utility partitioning results, filter the time segments where the moderating utility has not entered the utility decay zone or utility reversal zone, and generate a utility validity list by determining the time period when the utility boundary appears, the duration of the boundary and the type of mutation triggering. S3. Based on the utility validity period list, the regulation utility is gradually reduced to the regional contribution value according to the ecosystem type and spatial block, and a regulation contribution reduction table is generated. Then, based on the regulation contribution reduction table, the regulation contribution of each region is converted into energy equivalent value to obtain the target accounting result that reflects the quality of climate regulation services of the coastal salt marsh ecosystem.

2. The method for calculating the quantity of climate regulation services in coastal salt marsh ecosystems according to claim 1, characterized in that, S1 includes: S11, based on multi-year continuous meteorological observation data of the target area, constructs a meteorological combination space with daily average temperature and daily average relative humidity as two variables. In the meteorological combination space, the historical transpiration intensity and evaporation response value of the ecosystem under different meteorological conditions are statistically analyzed, and the meteorological state is correlated with the actual temperature regulation or humidification effect. The nonlinear response trend of the effect value with the change of meteorological combination is extracted to form a climate regulation response map, which is used to reveal the coupling mechanism between regulation capacity and environmental state. Based on the climate regulation response map, S12 identifies the evolutionary critical point of the regulation effect of the ecosystem in different meteorological sections, fits a continuous regulation effect response curve, and divides the meteorological combination space into functional zones, namely the effect enhancement zone, the effect decline zone, and the effect reversal zone.

3. The method for calculating the quantity of climate regulation services in coastal salt marsh ecosystems according to claim 2, characterized in that, S11 includes: S111 transforms multi-year diurnal meteorological observation data of the target area into a meteorological composite space with daily average temperature and daily average relative humidity as two-dimensional coordinate axes. A sliding window is then used to partition the data into two-dimensional partitions, forming a discretized sample grid. ,in, Let be the center value of the k-th daily average temperature interval. This is the center value of the l-th daily average relative humidity interval; S112, traversing the discretized sample grid for each meteorological combination space. The average transpiration intensity of the ecosystem under this combination of conditions was statistically analyzed. With average evaporation intensity ; S113, average transpiration intensity With average evaporation intensity Utility mapping was performed on the human body's temperature regulation needs or humidification needs, and the regulatory utility value was calculated. And construct a climate regulation response map.

4. The method for calculating the quantity of climate regulation services in coastal salt marsh ecosystems according to claim 3, characterized in that, S12 includes: S121. Based on the climate regulation response map, a two-dimensional gradient analysis is performed on the meteorological combination space to calculate the response rate of the regulation utility to changes in temperature and humidity, reflecting the sensitivity and abrupt change trend of the regulation utility. By the peak value of the gradient modulus and the flipping of the gradient sign, the evolutionary critical point of the regulation utility with changes in meteorology is identified. S122, after identifying the evolutionary critical point of the moderating utility, the evolutionary critical point is connected according to the grid sequence of the meteorological combination space, and used as nodes to fit a continuous moderating utility response curve, thereby obtaining the fitted moderating utility surface function value. This is used to express the smooth variation trend of the moderating effect throughout the entire meteorological combination space; S123, the fitted adjustment utility surface function value Projecting back into the meteorological combination space, each meteorological combination is classified according to the sign of its moderating effect and the direction of its slope, forming functional zones, represented as follows: ； in, For functional partition categories, To fit the partial derivative of the utility function with respect to temperature, This is the partial derivative of the fitted utility function with respect to humidity.

5. The method for calculating the quantity of climate regulation services in coastal salt marsh ecosystems according to claim 4, characterized in that, S2 includes: S21. Based on the functional zoning results in the meteorological composite space, all meteorological composite points classified as utility enhancement zones are screened, and their corresponding historical observation dates are mapped to candidate regulation service validity periods. By comparing the daily average temperature and relative humidity of each day in the meteorological observation data of previous years, it is determined whether the composite grid to which it falls is in the enhancement zone. If the conditions are met, the date is included in the candidate regulation service day list. S22, based on the candidate list of adjustment service days, analyzes the changing trend of adjustment utility values ​​in adjacent time periods using a sliding window approach, identifies adjustment boundary behaviors including short-term abrupt changes, boundary fluctuations, and insufficient continuity, performs a removal operation on time periods that do not have temporal stability, removes potential pseudo-adjustment contribution dates, and forms the final list of adjustment utility validity periods.

6. The method for calculating the quantity of climate regulation services in coastal salt marsh ecosystems according to claim 5, characterized in that, S21 includes: S211, Extract daily records from historical meteorological observation data of the target area and construct a daily-scale meteorological index table. Each record in the table includes the daily average temperature for that day. and daily average relative humidity ; S212, based on the established spatial division criteria for meteorological combinations, including temperature step size. With humidity step The average daily temperature and daily average relative humidity Mapped to the composite mesh in which it resides ; S213, the combined grid obtained by mapping each day According to functional area category Determine whether the combination point belongs to the utility enhancement region. If it satisfies... Then, day d will be included in the candidate adjustment service day list. .

7. The method for calculating the quantity of climate regulation services in coastal salt marsh ecosystems according to claim 6, characterized in that, S22 includes: S221, Regarding the Candidate Adjustment Service Day List Extract the fitted adjustment utility value for each day in chronological order. Forming a time series Perform a sliding window analysis on the time series to calculate the change in utility between adjacent dates. ; S222, Based on the results of sliding window analysis, identify adjustment boundary behaviors that lack temporal stability from the time series, specifically including: Short-term mutation: The direction of utility reverses sign within two consecutive days, i.e. ; Boundary fluctuations: The fitted adjustment utility value continuously approaches the zero threshold, i.e. The number of days continuously exceeds the window limit, among which, The threshold for determining the zero-value neighborhood; Insufficient continuity: Continuous length of candidate valid daily series It does not meet the minimum length requirement for continuity, where L is the length of a continuous time period within the candidate's validity period. The minimum consecutive valid day length threshold; S223, mark the dates that satisfy any adjustment boundary behavior as unstable periods, and remove the corresponding dates from the candidate adjustment service date list according to the set difference operation to form the final adjustment utility validity period list. .

8. The method for calculating the quantity of climate regulation services in coastal salt marsh ecosystems according to claim 7, characterized in that, S3 includes: S31. Based on the obtained list of regulation utility validity periods, according to the type and spatial distribution grid of the coastal ecosystem, the regulation utility value at each time point is mapped to the corresponding spatial block to form an hourly partitioned regulation utility value matrix. The regulation utility value of each spatial block is accumulated over the entire validity period to form a regulation contribution settling table reflecting the regulation contribution of different ecological units at different time scales, which is used to describe the total regulation efficiency output of each spatial block. S32, based on the established regulation contribution subsidence table, performs energy equivalence transformation on the regulation contribution values ​​of different spatial blocks, converts them into standardized energy indicators according to the unit energy regulation equivalence coefficient of each ecosystem type, and then combines the climate regulation contribution factors of the ecosystem to transform them into material indicators. Finally, it outputs the quantitative contribution of the coastal salt marsh ecosystem to regional climate regulation during its effective period, that is, the regulation service material quality accounting results.

9. The method for calculating the quantity of climate regulation services in coastal salt marsh ecosystems according to claim 8, characterized in that, S31 includes: S311 divides the study area into a set of spatial grids. Each grid cell All were labeled with their ecosystem type. And establish a mapping table ,in, For spatial coordinates, N is the number of spatial grids. It is a coastal wetland ecosystem. For mangrove ecosystems, It is a coastal salt marsh ecosystem; S312, based on each effective time point t in the selected list of effective adjustment periods, obtain its corresponding meteorological state. The utility value is calculated from the fitted adjustment utility surface function. Then, based on the effective time point t and the location of the ecological block, the value is mapped to the grid cell in which it is located. The time-series spatial adjustment contribution matrix is ​​obtained. ; S313, for each spatial grid cell Time-sequential spatial adjustment contribution matrix The total settlement contribution is calculated by summing the values ​​over the entire effective time period. And construct a settlement adjustment contribution table.

10. The method for calculating the quantity of climate regulation services in coastal salt marsh ecosystems according to claim 9, characterized in that, S32 includes: S321, for each spatial grid cell The adjustment contribution of total settlement Based on its corresponding ecosystem type unit adjustment energy efficiency coefficient Converted into energy equivalent value ; S322, based on ecosystem type The moderating contribution of quality factors energy and other values Transformation into climate moderating properties of coastal salt marsh ecosystems ; S323 spatially integrates the mass contribution values ​​of all spatial grid cells to obtain the total mass of climate regulation services in the entire study area. .

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