Estimation method and system for total carbon reserve of target ecosystem carbon library

Abstract

The invention discloses a method and system for estimating the total carbon reserve of a target ecological system carbon library, and relates to the technical field of forestry information, and the method comprises the following steps: carrying out the sample collection of a target ecological system; the vegetation type of the target ecological system is a subtropical evergreen broad-leaved forest, cypress, masson pine, alder and quercus acutissima are taken as main materials, the altitude is 182-954 m, the gradient is 0-45 degrees, the soil is yellow soil and purple soil, and the thickness of a dry branch and fallen leaf layer is 0-15 cm; the sample comprises at least one of a soil sample, a vegetation sample and a litter layer sample; carrying out analysis and calculation on the basis of the sample to obtain the total carbon reserve and carbon density of the target ecological system; the total carbon reserves and carbon density distribution characteristics of the target ecological system comprise the carbon density of a vegetation layer, the carbon reserves of the vegetation layer, the carbon density of a soil layer, the carbon reserves of the soil layer, the carbon density of a litter layer and the carbon reserves of the litter layer.

Description

Technical Field

[0001] This application relates to the field of forestry information technology, specifically to a method and system for estimating the total carbon storage of a target ecosystem carbon pool. Background Technology

[0002] Ancient and famous trees, as a core component of forest ecosystems, are important carriers of long-term carbon sequestration. The Shudao Cuiyun Corridor Ancient Cypress Forest, the world's oldest, largest, and best-preserved grove of ancient artificially planted cypress trees along a post road, is dominated by cypress and Chinese arborvitae, boasting over 12,000 ancient cypress trees, some as old as 2,300 years. They play an irreplaceable ecological role in water conservation, carbon sequestration and oxygen release, and soil conservation. Together with the soil, the ancient cypress forest constitutes a rich carbon pool, significantly influencing regional carbon cycling and climate change regulation.

[0003] Currently, there are no reports on specific studies focusing on the carbon pool characteristics of the ancient forest cypress forest ecosystem in the Cuiyun Corridor of the Shu Road. Specifically: First, existing forest carbon pool studies mostly focus on ordinary forest stands or single carbon pools, lacking systematic attention to special ecosystems like ancient forest cypress forests with extremely long tree ages and a long history of human disturbance, especially lacking comprehensive research on the carbon pool across all dimensions, including vegetation, soil, litter, and deadwood layers; Second, as a unique ancient artificial post road forest, the carbon accumulation patterns, spatial and temporal distribution characteristics of carbon storage, and influencing factors of the Cuiyun Corridor ancient forest cypress forest are fundamentally different from those of natural forests or modern plantations, and existing research results cannot be directly applied, resulting in a lack of scientifically quantified data on the carbon sequestration capacity of this region; Third, the dynamic changes in carbon density, the spatial distribution patterns of soil organic carbon, and their regulatory mechanisms in ancient forest cypress forests of different ages are still unclear.

[0004] Therefore, those skilled in the art urgently need to conduct a special study on the carbon sink characteristics of the ancient cypress forest ecosystem in the Cuiyun Corridor of Shudao, to clarify its carbon storage composition, spatiotemporal distribution patterns and key influencing factors, fill the research gap in this field, and provide important theoretical basis and data support for accurately assessing the carbon sink value of the ancient cypress forest and formulating scientific carbon sink management and carbon sink enhancement measures. Summary of the Invention

[0005] The main purpose of this application is to provide a method and system for estimating the total carbon storage of a target ecosystem carbon pool, aiming to address the shortcomings of existing technologies.

[0006] To achieve the above objectives, the technical solutions adopted in the embodiments of this application are as follows: In a first aspect, embodiments of this application provide a method for estimating the total carbon storage of a target ecosystem's carbon pool, comprising the following steps: Samples were collected from the target ecosystem. The vegetation type of the target ecosystem is subtropical evergreen broad-leaved forest, mainly composed of cypress, Masson pine, alder, and oak. The altitude ranges from 182 m to 954 m, the slope ranges from 0° to 45°, the soil is yellow soil and purple soil, and the litter layer is 0 cm to 15 cm thick. The samples include at least one of soil samples, vegetation samples, and litter layer samples. Based on the analysis and calculation of the sample, the total carbon storage and carbon density of the target ecosystem are obtained; the distribution characteristics of the total carbon storage and carbon density of the target ecosystem include: carbon density and carbon storage of the vegetation layer, carbon density and carbon storage of the soil layer, and carbon density and carbon storage of the litter layer.

[0007] As some optional embodiments of this application, the target ecosystem has a maximum tree height of 33.40m, an average tree height of 7.30m, and a tree height concentration range of 15m to 20m; a maximum tree diameter at breast height of 840cm, an average tree diameter of 275.48cm, and a concentration range of 200cm to 300cm; and a maximum tree crown width of 34.30m, an average tree width of 10.45m, and a concentration range of 5m to 10m.

[0008] As some optional embodiments of this application, the carbon density and carbon storage of the vegetation layer satisfy the following relationship: C i =B i ×F i C di =C i / A i； In the formula, C i This represents the carbon storage of tree species / group i, in Mg; F i C represents the carbon content coefficient of tree species / group i; di This represents the carbon density of tree species / group i, in units of Mg·hm². -2 A i This represents the area of ​​tree species / group i, in hem. 2 B i This represents the total biomass of tree species / group i.

[0009] As some optional embodiments of this application, the total forest biomass refers to the biomass of living trees in the forest stand, including arbor forests, sparse forests, and shrub forests, and includes the biomass of herbaceous layer and deadwood layer; The total biomass of the forest trees was obtained using the volume source biomass method.

[0010] As some optional embodiments of this application, the total biomass of the tree species / group i satisfies the following relationship: ; Among them, B ij B represents the forest biomass of tree species in age group j / group i, in units of Mg; i V represents the total biomass of tree species / group i; ij This represents the volume per unit area of ​​tree species / group i in the j-th age group, in m³. 3 ·hm -2 ;D i This represents the wood density of tree species group i, in Mg·m³. -3 ; R represents the biomass expansion factor of tree species / group i in age group j; ij A represents the root-to-stem ratio of tree species in age group j to group i; ij This represents the area of ​​tree species in age group j / group i, in hectares. 2 .

[0011] As some optional embodiments of this application, the carbon density of the soil layer satisfies the following relationship: ;

[0012] In the formula, SOCD ih T represents the soil organic carbon density of the i-th grid region at soil profile h, in Mg / ha; n is the soil layer number; T i C represents the soil thickness of the i-th layer in the soil profile, in cm. i P represents the soil carbon content of the i-th layer of the soil profile, in g / kg. i The soil bulk density of the i-th layer in the soil profile is expressed in g / cm³. 3 Q i % represents the gravel content coefficient of the i-th layer of the soil profile, where the gravel diameter is >2 mm.

[0013] As some optional embodiments of this application, the carbon storage of the soil layer satisfies the following relationship: ; In the formula, SOCS h denoted as Total Organic Carbon (SOCD) at forest soil profile h, in Tg C; n is the total number of grid cells; i is the i-th grid cell; SOCD ih The soil organic carbon density of the i-th grid region at soil profile h is expressed in Mg / ha. grid The area of ​​each grid region, in meters. 2 .

[0014] As some optional embodiments of this application, the carbon density of the litter layer satisfies the following relationship: Y=10 4 ×a×X / 3; In the formula, Y is the dry mass of litter per unit area, in Mg / ha; a is the percentage of the dry mass of litter brought into the laboratory, in %; and X is the fresh mass of litter in three 1 m × 1 m quadrats, in Mg.

[0015] As some optional embodiments of this application, the carbon storage of the litter layer satisfies the following relationship: FLCD=b×Y; In the formula, FLCD represents the carbon mass of litter per unit area within the study area, in Mg / ha; b represents the percentage of carbon in the litter as determined by the elemental analyzer; and Y represents the dry mass of litter per unit area, in Mg / ha.

[0016] Secondly, embodiments of this application also provide a system for estimating the total carbon storage of a target ecosystem carbon pool, comprising: The sample collection module is used to collect samples from the target ecosystem. The vegetation type of the target ecosystem is subtropical evergreen broad-leaved forest, mainly composed of cypress, Masson pine, alder, and oak, with an altitude of 182 m to 954 m, a slope of 0° to 45°, and soils of yellow soil and purple soil. The thickness of the litter layer is 0 cm to 15 cm. The samples include at least one of soil samples, vegetation samples, and litter layer samples. The analysis and calculation module is used to analyze and calculate based on the sample to obtain the total carbon storage and carbon density of the target ecosystem. The distribution characteristics of the total carbon storage and carbon density of the target ecosystem include: carbon density and carbon storage of the vegetation layer, carbon density and carbon storage of the soil layer, and carbon density and carbon storage of the litter layer.

[0017] Compared with existing technologies, this application proposes a method and system for estimating the total carbon storage of a target ecosystem carbon pool. By collecting samples from the target ecosystem and calculating carbon storage and carbon density based on sample analysis, it can integrate multi-dimensional parameters of vegetation layer, soil layer and litter layer, accurately quantify carbon storage distribution characteristics, solve the limitations of existing technologies in carbon pool assessment for special ecosystems, accurately quantify the carbon storage and carbon density distribution characteristics of target ecosystems, solve the carbon pool assessment problem for special ecosystems such as gulfling forests, and improve the scientificity and accuracy of carbon sink capacity assessment. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating the steps of the method for estimating the total carbon storage of a target ecosystem carbon pool in an embodiment of this application. Figure 2 These are the main arbor forest data structure features involved in the embodiments of this application. Detailed Implementation

[0019] The technical solutions of this application will now be clearly and completely described with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. The components of this application described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of this application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely to illustrate selected embodiments of this application. All other embodiments obtained by those skilled in the art based on the embodiments of this application without inventive effort are within the scope of protection of this application.

[0020] Traditional forest carbon pool studies have largely focused on ordinary forest stands or single carbon pools, lacking systematic attention to special ecosystems with exceptionally long tree ages and significant human disturbance (such as ancient forest groves). Existing research findings cannot be directly applied to unique ancient artificial trail forest stands, resulting in a lack of scientifically quantifiable data on their carbon sequestration capacity. Furthermore, the dynamic changes in carbon density, the spatial distribution patterns of soil organic carbon, and their regulatory mechanisms in ancient forest groves of different ages remain unclear, making it difficult to support the consolidation and enhancement of the carbon sequestration capacity of ancient forest grove ecosystems.

[0021] In response, this application proposes a method for estimating the total carbon storage of a target ecosystem's carbon pool, such as... Figure 1 As shown, it includes the following steps: Samples were collected from the target ecosystem. The vegetation type of the target ecosystem is subtropical evergreen broad-leaved forest, mainly composed of cypress, Masson pine, alder, and oak. The altitude ranges from 182 m to 954 m, the slope ranges from 0° to 45°, and the soil is yellow soil and purple soil. The thickness of the litter layer ranges from 0 cm to 15 cm. The samples include at least one of soil samples, vegetation samples, and litter layer samples. Based on the samples, the total carbon storage and carbon density of the target ecosystem were analyzed and calculated. The distribution characteristics of the total carbon storage and carbon density of the target ecosystem include: carbon density and carbon storage of the vegetation layer, carbon density and carbon storage of the soil layer, and carbon density and carbon storage of the litter layer.

[0022] For ease of understanding, the following explains some key terms in this embodiment: Target ecosystem: refers to the specific ecological area targeted by this method, whose vegetation type is limited to subtropical evergreen broad-leaved forest, with main tree species including cypress, Masson pine, alder, and oak. The geographical characteristics of this ecosystem are defined as an altitude range of 182 m to 954 m, a slope range of 0° to 45°, soil types of yellow soil and purple soil, and a litter layer thickness between 0 cm and 15 cm. This system is the research object for carbon pool estimation; for example, the Cuiyun Corridor ancient cypress grove area in Guangyuan City. Guangyuan City has a total of 10,825 ancient and famous trees, including 7,778 cypress trees. The Cuiyun Corridor ancient cypress grove is composed of cypress (Cupressus funebris) and Chinese arborvitae (Platycladus orientalis), and the structural characteristics of the grove are shown in Table 1. Table 1:

[0023] Sample collection: refers to the process of obtaining material samples from a target ecosystem for subsequent analysis. This process aims to obtain physical materials that can represent the characteristics of the carbon pool of the target ecosystem.

[0024] Sample: refers to the specific material obtained through the sample collection process, which may include at least one of soil samples, vegetation samples, and litter layer samples; these samples are the basis for carbon storage and carbon density analysis.

[0025] Carbon storage: refers to the total amount of organic matter in the form of carbon in a specific carbon pool of a target ecosystem (such as vegetation layer, soil layer, litter layer); it is usually measured in units of mass (such as Mg or Tg C).

[0026] Carbon density: refers to the amount of carbon stored in a specific carbon pool per unit area. It is usually expressed in mass per unit area (e.g., Mg·hm²). -2 It is measured by (or Mg / ha), reflecting the spatial density of carbon distribution.

[0027] Vegetation layer: refers to the part of the target ecosystem consisting of all living plants (such as trees, shrubs, and herbs) and their biomass. This layer is an important component of carbon sinks and carbon pools.

[0028] Soil layer: refers to the loose cover layer below the surface of the target ecosystem, composed of minerals, organic matter, water, air and organisms. Soil organic carbon is one of the largest carbon pools in terrestrial ecosystems.

[0029] Litter layer: refers to the cover layer on the surface of the target ecosystem, which consists of plant remains (such as dead branches, fallen leaves, fruits, etc.) and their decomposition products. This layer plays an important role in the carbon cycle.

[0030] This embodiment provides a method for estimating the total carbon storage of a target ecosystem's carbon pool, and its specific implementation can be as follows: First, samples are collected from the target ecosystem. This target ecosystem is defined as an area with specific geographical and biological characteristics; for example, its vegetation type is identified as subtropical evergreen broad-leaved forest, with main tree species including cypress, Masson pine, alder, and oak. The elevation range of this area is defined as 182 m to 954 m, the slope range as 0° to 45°, the soil type as yellow soil and purple soil, and the thickness of the litter layer is measured as 0 cm to 15 cm. During sample collection, a random or systematic sampling method can be used to establish multiple quadrats or sampling points within the target ecosystem. For example, representative areas can be manually selected for sampling, or sampling points can be selected based on experience. Collected samples can include at least one of soil samples, vegetation samples, and litter layer samples. Specifically, soil samples can be collected at different depths using a soil auger or ring cutter; vegetation samples can include representative samples of trees, shrubs, and herbaceous plants. For example, standard timber can be felled or plant material from specific parts can be collected; litter layer samples can be collected by setting up small quadrats to collect dead branches and leaves from the ground.

[0031] Furthermore, based on the sample, analysis and calculations are performed to obtain the total carbon storage and carbon density of the target ecosystem. After obtaining the samples, laboratory analyses can be conducted. For example, for vegetation samples, they can be dried, weighed, and then their carbon content can be determined using an elemental analyzer to calculate the carbon storage and carbon density of the vegetation layer. For soil samples, they can be air-dried, ground, and sieved, and then the soil organic carbon content can be determined using the potassium dichromate oxidation-external heating method or an elemental analyzer. The carbon storage and carbon density of the soil layer can then be calculated by combining the soil bulk density and soil layer thickness. For litter layer samples, they can be dried, weighed, and their carbon content can be determined using an elemental analyzer to calculate the carbon storage and carbon density of the litter layer. During the calculation process, a simple weighted average method or a direct summation method can be used to summarize the carbon storage and carbon density of each sample plot to obtain the total carbon storage and total carbon density of the entire target ecosystem. The overall carbon storage and carbon density distribution characteristics of the target ecosystem include the carbon density and carbon storage of the vegetation layer, the carbon density and carbon storage of the soil layer, and the carbon density and carbon storage of the litter layer. Obtaining these characteristics helps to comprehensively understand the distribution of carbon in different components of the ecosystem.

[0032] The method provided in this application, through systematic sampling of target ecosystems with specific geographical and biological characteristics, and analysis and calculation based on the collected soil, vegetation, and litter layer samples, can comprehensively and accurately obtain the total carbon storage and carbon density of the ecosystem, as well as the carbon density and carbon storage distribution characteristics of each carbon pool (vegetation layer, soil layer, and litter layer). This overcomes the problems of insufficient research and lack of data on the carbon pool characteristics of special ecosystems in existing technologies, and provides a scientific data foundation and technical support for accurately assessing the carbon sink value of unique ancient artificial post road forest stands such as the Shudao Cuiyun Corridor Ancient Cypress Forest.

[0033] In some of the embodiments described above in this application, a method is proposed for collecting samples from a target ecosystem and analyzing and calculating the total carbon storage and carbon density based on the samples. However, in practice, the lack of a detailed quantitative description of the vegetation structure characteristics of the target ecosystem may lead to insufficient accuracy and representativeness of the carbon storage estimation results, making it difficult to accurately reflect the actual situation of a specific ecosystem.

[0034] In this regard, this application further proposes that the maximum tree height of the target ecosystem is 33.40m, the average tree height is 7.30m, and the tree height concentration range is 15m~20m; the maximum tree diameter at breast height is 840cm, the average is 275.48cm, and the concentration range is 200cm~300cm; the maximum tree crown width is 34.30m, the average is 10.45m, and the concentration range is 5m~10m.

[0035] Specifically, the maximum tree height, average tree height, and tree height concentration range collectively depict the vertical structure of the vegetation in the target ecosystem. Maximum tree height indicates the upper limit of the individual growth potential within the stand, average tree height provides a general measure of the overall height of the stand, and tree height concentration range reveals the height distribution range of dominant tree species or major growth stages within the stand. These data are typically obtained through field measurements, such as individual or sampled measurements of trees within the plot using altimeters or laser rangefinders, and are key input parameters for constructing biomass allometric growth equations and assessing stand productivity.

[0036] The maximum, average, and concentration range of tree diameters at breast height (DBH) are among the most commonly used parameters in forest biomass estimation, reflecting the thickness growth of trees. Maximum DBH indicates the presence of large-diameter trees in the stand, which often contribute significantly to biomass; average DBH provides the average level of overall stand thickness; and the concentration range indicates the DBH class of the most numerous trees in the stand. These data are typically obtained by measuring at breast height (usually 1.3 meters above ground) using a circumference or diameter gauge and are fundamental data for calculating individual tree biomass and total stand biomass.

[0037] The maximum, average, and concentrated range of tree crown widths reflect the horizontal expansion capacity of trees and their efficiency in utilizing light resources. They are also important indicators for assessing stand canopy closure, competition, and biomass. Maximum crown width indicates the tree with the largest horizontal projected area in the stand, average crown width provides the average level of overall stand canopy size, and concentrated crown width shows the canopy size distribution of the majority of trees in the stand. These data can be obtained through ground measurements (e.g., measuring crown width in two vertical directions using a measuring tape and averaging) or through remote sensing image analysis, contributing to a more comprehensive understanding of stand structure and its contribution to carbon storage.

[0038] The aforementioned technical solution provides a detailed and quantitative description of the vegetation structure characteristics of the target ecosystem, including maximum tree height, average tree height, and tree height concentration range; as well as the maximum, average, and concentration range of tree diameter at breast height (DBH); and the maximum, average, and concentration range of tree crown width. The introduction of these specific parameters allows for more precise selection and application of biomass allometric growth equations and carbon content coefficients applicable to this specific forest stand structure when estimating carbon storage. This not only significantly improves the accuracy and reliability of vegetation layer carbon density and carbon storage estimation but also ensures that the estimation results truly reflect the unique biological and structural characteristics of this subtropical evergreen broad-leaved forest ecosystem, thus effectively solving the problem of insufficient estimation accuracy caused by a lack of detailed vegetation structure data.

[0039] In some embodiments described above, this application proposes collecting samples from the target ecosystem and analyzing and calculating them to obtain the total carbon storage and carbon density of the target ecosystem, including the carbon density and carbon storage of the vegetation layer. However, in practice, without a clear calculation model and parameter definition, the specific quantification process of vegetation layer carbon density and carbon storage may be uncertain, affecting the accuracy and comparability of the estimation results and making it difficult to achieve refined and standardized carbon storage assessment.

[0040] In this regard, this application further proposes that the carbon density and carbon storage of the vegetation layer satisfy the following relationship: C i =B i ×F i Cd i =C i / A i； Among them, C i This represents the carbon storage of tree species / group i, in Mg; F i C represents the carbon content coefficient of tree species / group i; di This represents the carbon density of tree species / group i, in units of Mg·hm². -2 A iThis represents the area of ​​tree species / group i, in hem. 2 B i This represents the total biomass of tree species / group i.

[0041] Specifically, B i F represents the total biomass of tree species / group i, which can be obtained through various methods, such as estimation using measured data, allometric growth equations, or volumetric biomass methods. i The carbon content coefficient represents the carbon content of tree species / group i. This coefficient is typically a percentage of the average carbon content for a specific tree species or vegetation type and can be determined through laboratory elemental analysis or by referring to published literature data. By multiplying the total forest biomass by its carbon content coefficient, biomass can be accurately converted into carbon storage, laying the foundation for subsequent carbon density calculations.

[0042] Based on this, C i For the carbon storage of tree species / group i obtained from the aforementioned calculations, A i The area representing tree species / group i typically refers to the estimated plot area or the actual area occupied by that tree species / group within the study area. By dividing the carbon storage by the corresponding area, the carbon content per unit area, i.e., carbon density, can be obtained. This helps to assess the carbon storage capacity per unit area of ​​different regions or different vegetation types and to analyze spatial distribution characteristics.

[0043] Through the above technical solution, this application provides a clear and quantifiable method for calculating vegetation layer carbon density and carbon storage. By introducing specific mathematical relationships, key parameters such as total forest biomass, carbon content coefficient, and area of ​​the vegetation layer are directly linked to carbon storage and carbon density, thereby solving the problems of unclear calculation processes and inaccurate results that may exist in traditional estimation methods. This method makes the estimation process of vegetation layer carbon storage and carbon density more standardized and refined, improves the scientificity and repeatability of the estimation results, and provides a solid data foundation for accurately assessing the vegetation component of the carbon pool of a target ecosystem. In addition, by calculating separately for different tree species / groups i, a deeper understanding of the contribution of different vegetation components to the overall carbon pool can be obtained, providing more instructive information for ecosystem management and carbon sink monitoring. Based on the above formula, the following can be obtained: Figure 2 The main structural features of the arbor forest data are shown.

[0044] In some embodiments described above in this application, a method for estimating vegetation layer carbon density and carbon storage through specific relationships is proposed, which involves the calculation of total forest biomass. However, if the specific composition and acquisition method of total forest biomass are not clearly defined, the comprehensiveness and accuracy of the estimation results may be insufficient, making it difficult to accurately reflect the carbon storage contribution of all living trees in the ecosystem. Therefore, this application further proposes that the total forest biomass refers to the biomass of living trees in a forest stand, including arbor forests, sparse forests, and shrub forests, containing the biomass of the herbaceous layer and the deadwood layer; the total forest biomass is obtained using the volume source biomass method.

[0045] Specifically, the total forest biomass refers to the sum of the biomass of all surviving woody plants (including trees and shrubs), herbaceous plants, and deadwood within a specific forest stand area. Arbor forests typically refer to forest types dominated by arbor species, and their biomass can be calculated by measuring the diameter at breast height (DBH) and height of individual trees, combined with species-specific allometric growth equations. Sparse forests refer to forests with low canopy density, and their biomass estimation methods are similar to those for arbor forests. Shrub forests are dominated by shrubs, and their biomass can be obtained by setting up small quadrats within a sample plot, harvesting, drying, and weighing all the shrubs within the quadrats. Furthermore, herbaceous layer biomass refers to the biomass of understory herbaceous plants, which is also typically measured using harvesting methods. Deadwood layer biomass refers to the biomass of the dead woody parts of fallen and standing trees in the forest, which can be estimated by measuring their volume and density. By separately measuring and summing the biomass of each of the above components, the biomass of the living trees in the forest stand can be obtained.

[0046] The total biomass of the forest was obtained using the volume-based biomass method. The volume-based biomass method is a method for estimating biomass based on timber volume. This method typically begins by measuring the diameter at breast height (DBH) and tree height of the trees, and then calculating the volume of an individual tree using local or regional volume tables or equations. The volume is then multiplied by a biomass conversion factor (or biomass expansion factor, BEF) and timber density to obtain the biomass of an individual tree. The biomass conversion factor converts the volume into biomass that includes all parts of the tree, such as the trunk, branches, leaves, and roots. Timber density reflects the mass per unit volume of timber. By performing the above calculations on all trees in the sample plot and summing the results, the total stand biomass can be obtained. This method avoids direct logging and weighing, has high efficiency and applicability, and is particularly suitable for large-scale forest resource surveys.

[0047] By clarifying that total forest biomass encompasses not only the living trees of arbor forests, sparse forests, and shrublands, but also the biomass of the herbaceous and deadwood layers, this application ensures the comprehensiveness of carbon storage estimation and effectively avoids estimation biases caused by the omission of certain biomass components. Simultaneously, employing the volume-source biomass method to obtain total forest biomass provides a standardized and efficient estimation approach, making the estimation process more operable and accurate. This method can scientifically extrapolate the biomass of the entire forest stand based on easily measurable timber volume data, combined with biomass conversion factors and timber density. This significantly improves the accuracy and reliability of vegetation layer carbon density and carbon storage estimation, providing a solid foundation for the accurate assessment of the total carbon storage of the target ecosystem's carbon pool.

[0048] In some embodiments described above in this application, a method for estimating the total carbon storage of a target ecosystem is proposed using the carbon density and carbon storage of the vegetation layer, wherein the carbon storage and carbon density of the vegetation layer depend on the total forest biomass. However, in practice, if the calculation of total forest biomass relies solely on simple empirical coefficients, it may not adequately reflect the differences in biomass among different tree species, different growth stages, and different environmental conditions, thereby affecting the accuracy and reliability of the carbon storage estimation results.

[0049] In this regard, this application further proposes that the total biomass of the tree species / group i satisfies the following relationship: ; Among them B ij B represents the forest biomass of tree species in age group j / group i, in units of Mg; i V represents the total biomass of tree species / group i; ij This represents the volume per unit area of ​​tree species / group i in the j-th age group, in m³. 3 ·hm -2 ;D i This represents the wood density of tree species group i, in Mg·m³. -3 ; R represents the biomass expansion factor of tree species / group i in age group j; ij A represents the root-to-stem ratio of tree species in age group j to group i; ij This represents the area of ​​tree species in age group j / group i, in hectares. 2 .

[0050] Specifically, B i Representing the total biomass of a specific tree species or species group throughout the entire study area, it is a key parameter for calculating vegetation layer carbon storage. Its calculation requires comprehensive consideration of the biomass contributions from different age groups. ijThis represents the biomass of a specific tree species or species group at a specific age group j. By subdividing the total biomass into the biomass of different age groups, the impact of stand structure on biomass can be reflected more precisely, improving the accuracy of estimation. ij This refers to the total volume of living trees per unit area for a specific tree species or species group in the j-th age group. This parameter is usually obtained through field surveys (such as measuring diameter at breast height and tree height in sample plots and calculating using volume tables or volume equations) or inversion from remote sensing data, and is the basic data for estimating aboveground biomass. i Timber density refers to the mass per unit volume of timber in a specific tree species group i. Timber density is an important parameter in biomass estimation, and the density varies significantly among different tree species. This parameter can be obtained by consulting relevant literature, national standards, or by laboratory testing of collected timber samples (such as the water displacement method or the kiln-drying method). R is a coefficient that converts timber volume or aboveground biomass into biomass encompassing all aboveground parts, including trunks, branches, and leaves. This factor takes into account the influence of tree morphology, growth stage, and environmental conditions on biomass allocation, and is typically obtained by establishing allometric growth equations or consulting biomass expansion factor tables for specific tree species and age groups. ij The root-to-stem ratio refers to the ratio of underground biomass (roots) to aboveground biomass (stems, branches, and leaves) for a specific tree species or species group at age j. This ratio is used to estimate underground biomass and is an important component of carbon storage estimation. The root-to-stem ratio is usually obtained through excavation, root modeling, or by consulting relevant research literature, and its value is affected by various factors such as tree species, age, soil type, and climate. ij This refers to the forest area occupied by a specific tree species or species group in the j-th age group. This parameter is used to extend the biomass or stock volume per unit area to the entire study area and can be obtained through plot surveys, forest compartment maps, or geographic information system (GIS) analysis.

[0051] Through the above technical solution, this application provides a more refined and accurate method for calculating total forest biomass. This method calculates the total forest biomass B... i Biomass B is broken down into different age groups j. ij The sum of, and further B ij Decomposed into volume V per unit area ij Wood density D i Biomass expansion factor R to rootstock ijThe product of these parameters allows for a comprehensive consideration of the growth characteristics, morphological structures, and differences in the distribution of aboveground and belowground biomass among different tree species and age groups. This multi-parameter, age-group-based calculation method significantly improves the accuracy and reliability of total forest biomass estimation, avoiding errors caused by parameter generalization in traditional methods. Since vegetation layer carbon storage and carbon density are calculated based on total forest biomass, the more accurate total forest biomass obtained through this scheme can directly improve the accuracy of vegetation layer carbon storage and carbon density estimation in the target ecosystem. This, in turn, makes the estimation results of the total carbon storage of the entire target ecosystem carbon pool more scientific and reliable, providing a more solid data foundation for ecosystem carbon cycle research and carbon sink management.

[0052] In some embodiments described above, this application proposes collecting samples from the target ecosystem and calculating the soil carbon density based on sample analysis. However, in practice, simply measuring carbon content is insufficient to accurately reflect the true spatial and vertical distribution and storage of soil carbon, especially in ecosystems with complex soil physicochemical properties and high heterogeneity. If the physical structure characteristics of the soil are not fully considered, the soil carbon density estimation results may have significant deviations, affecting the accurate assessment of the total carbon pool storage.

[0053] In this regard, this application further proposes that the carbon density of the soil layer satisfies the following relationship: ; In the formula, SOCD ih T represents the soil organic carbon density of the i-th grid region at soil profile h, in Mg / ha; n is the soil layer number; T i C represents the soil thickness of the i-th layer in the soil profile, in cm. i P represents the soil carbon content of the i-th layer of the soil profile, in g / kg. i The soil bulk density of the i-th layer in the soil profile is expressed in g / cm³. 3 Q i % represents the gravel content coefficient of the i-th layer of the soil profile, where the gravel diameter is >2 mm.

[0054] This formula ensures the accuracy and representativeness of the calculation results by comprehensively considering multiple physical and chemical parameters of the soil. Here, represents the soil organic carbon density (Mg / ha) at soil profile h in the i-th grid region of the sample plot. This parameter indicates that, in estimating soil carbon density, not only is horizontal spatial heterogeneity (through grid region division) considered, but also vertical depth heterogeneity (through soil profile h), thus enabling a more refined characterization of soil carbon distribution. n represents the number of soil layers, indicating that the soil profile is divided into multiple layers for measurement and analysis. Soil physicochemical properties typically vary with depth; layered measurements capture this vertical variation, making the carbon density calculation for each soil layer more targeted, thereby improving the accuracy of the overall soil profile carbon density estimation. represents the soil thickness of the i-th layer of the soil profile, in cm; soil thickness is a key geometric parameter for calculating soil carbon density. In stratified measurements, accurately obtaining the thickness of each layer ensures that the volume or depth range of the soil is correctly considered when converting the carbon content per unit mass to the carbon density per unit area, avoiding errors caused by inaccurate thickness estimation. i P represents the soil carbon content of the i-th layer of the soil profile, expressed in g / kg. This parameter represents the mass fraction of carbon in the soil sample and is the fundamental data for soil carbon density. It is typically determined through laboratory analytical methods (such as dry burning with an elemental analyzer or potassium dichromate oxidation-volume method) and reflects the actual amount of organic carbon contained in the soil. i The soil bulk density of the i-th layer in the soil profile is expressed in g / cm³. 3 Soil bulk density, also known as soil volumetric density, is the mass of a unit volume of dry soil. It is a key parameter for converting soil carbon content (mass fraction) into carbon content (mass concentration) per unit volume. Accurately measuring soil bulk density reflects the compactness and porosity of the soil, thus converting soil carbon content from a mass basis to a volume basis, and subsequently calculating the carbon density per unit area. i The percentage represents the gravel content coefficient of the i-th layer of the soil profile, where gravel diameter is >2 mm. Gravel refers to soil particles with a diameter greater than 2 mm. Since gravel typically does not contain organic carbon and occupies a certain volume of soil, the volume or mass proportion occupied by gravel needs to be deducted when calculating soil organic carbon density. The introduction of the gravel content coefficient ensures that carbon density calculations are based on the actual fine soil portion containing organic matter, thus avoiding underestimation or overestimation of carbon density due to the presence of gravel.

[0055] The above-described technical solution overcomes the estimation biases caused by traditional methods that do not adequately consider soil physical structure and heterogeneity when estimating the carbon density of the soil layer in a target ecosystem. Specifically, this method introduces parameters such as soil profile stratification, soil layer thickness, soil bulk density, and gravel content coefficient, making the calculation of soil organic carbon density more refined and accurate. The division of sample plot grid areas and soil profile stratification consider the spatial variability of soil carbon in both horizontal and vertical directions, ensuring the representativeness of the estimation results. The introduction of soil bulk density converts carbon content from a mass basis to a volume basis, more realistically reflecting the carbon storage per unit volume of soil. Simultaneously, deducting gravel content avoids interference from non-carbon-containing substances in the carbon density calculation, allowing the calculation results to accurately reflect the density of the actual carbon-containing soil portion. Therefore, this scheme significantly improves the accuracy and reliability of soil carbon density estimation, providing a solid data foundation for the accurate assessment of the total carbon storage of the carbon pool in the target ecosystem.

[0056] In some of the embodiments described above in this application, after collecting samples from the target ecosystem and calculating the carbon density of the soil layer based on sample analysis, how to effectively integrate these discrete, local carbon density data and accurately estimate the total organic carbon storage of the entire forest soil profile at a specific depth is a technical problem that needs to be solved. Simply averaging or summing local densities may not accurately reflect the carbon storage of the entire area, especially when spatial heterogeneity exists within the ecosystem.

[0057] In this regard, this application further proposes that the carbon storage of the soil layer satisfies the following relationship: The carbon storage of the soil layer satisfies the following relationship: ; In the formula, SOCSh represents the total organic carbon storage in the soil at soil profile h, and its unit is Tg C. This parameter represents the total amount of organic carbon contained in the soil layer of the entire target ecosystem at a specific soil depth h, and is an important indicator for assessing the carbon sink function of the ecosystem.

[0058] n represents the total number of raster cells. To accurately estimate soil carbon storage over large-scale regions, the study area is typically divided into several discrete raster cells with the same or different areas, where n is the total number of these raster cells. This rasterization process helps to capture spatial heterogeneity within the region.

[0059] i represents the i-th grid cell. In the rasterization process, each grid cell is assigned a unique identifier i to facilitate the independent calculation and management of the carbon density and area of ​​each local region.

[0060] SOCD ihThis represents the soil organic carbon density of the i-th grid region at soil profile h, expressed in Mg / ha. This density value reflects the mass of organic carbon contained per unit area of ​​soil at a specific grid cell i and a specific soil depth h. This data is typically calculated through laboratory analysis of soil samples within the grid region, combined with parameters such as soil bulk density.

[0061] Area grid This represents the area of ​​each grid region, expressed in meters (m²). 2 The area is a key parameter for calculating the soil organic carbon storage within a single grid cell. The organic carbon storage of a grid cell can be obtained by multiplying its organic carbon density by its area.

[0062] By measuring the organic carbon density (SOCD) of each grid region ih Its corresponding area grid Multiplying these values ​​yields the organic carbon storage for each grid region. Then, summing the organic carbon storage for all grid regions gives the total soil organic carbon storage (SOCS) for the entire forest soil profile at time h. h .

[0063] Through the above technical solution, this application employs a gridded method to divide the target ecosystem into multiple discrete grid regions and accurately calculates the soil organic carbon density of each grid region at a specific soil profile depth. By multiplying the organic carbon density of each grid region by its area, the organic carbon storage of a single grid is obtained. Then, the organic carbon storage of all grids is summed to accurately estimate the total organic carbon storage of the entire forest soil profile at a specific depth. This method effectively solves the technical challenge of accurately integrating local carbon density data into the total regional carbon storage when dealing with large-scale, spatially heterogeneous ecosystems. It avoids errors caused by simple averaging or coarse estimation, significantly improving the accuracy and reliability of soil carbon storage estimation results, and providing a more solid data foundation for carbon sink assessment and ecosystem management.

[0064] In some specific embodiments, the soil samples described in this application are collected through the following steps: A grid sampling method is used, with each grid measuring 4 km × 6 km. Soil profile samples are collected, avoiding traces of human activity such as large trees and road ditches. Each profile is divided into 0–10 cm, 10–30 cm, 30–60 cm, and 60–100 cm sections. If the soil layer thickness is less than 100 cm, the actual soil layer thickness is used. Approximately 1 kg of soil is taken from each layer, and its bulk density is measured using the ring cutter method. In this study, the 0–100 cm soil layer is the primary focus. The collected soil samples are transported to an indoor laboratory. Fresh soil samples from each layer are taken, air-dried at room temperature, ground, and sieved (2 mm and 0.25 mm) before soil organic carbon determination. The soil organic carbon determination is performed using the potassium dichromate external heating method.

[0065] In some of the embodiments described above in this application, although the carbon density of the litter layer of the target ecosystem is obtained, in practice, how to accurately and efficiently convert the litter sample data collected in the field into the dry mass of litter per unit area and then calculate the carbon density of the litter layer is a problem that requires specific quantification and standardization, especially when dealing with a large number of samples and ensuring data consistency.

[0066] In this regard, this application further proposes that the carbon density of the litter layer satisfies the following relationship: The carbon density of the litter layer satisfies the following relationship: Y=10 4 ×a×X / 3; In the formula, Y is the dry mass of litter per unit area, in Mg / ha; a is the percentage of the dry mass of litter brought into the laboratory, in %; and X is the fresh mass of litter in three 1 m × 1 m quadrats, in Mg.

[0067] Specifically, the dry weight of litter per unit area, Y, is an important indicator for measuring litter biomass, directly reflecting the material accumulation in the litter layer of an ecosystem. Its unit is Mg / ha, representing the dry weight of litter per hectare of land. In practice, accurate acquisition of litter dry weight is fundamental for subsequent carbon storage calculations. The percentage of litter dry weight, 'a', brought to the laboratory is necessary because litter samples collected in the field typically contain varying degrees of moisture, and their fresh weight cannot be directly used for carbon storage calculations. Therefore, a portion of the litter collected in the field is randomly selected and brought back to the laboratory, where its dry weight is determined using methods such as drying, and the percentage of dry weight to fresh weight is calculated. This percentage, 'a', is used to convert the fresh weight X of litter measured in the field to dry weight. For example, the sample can be dried at 105°C to constant weight to ensure complete moisture removal. The fresh weight X of litter within three 1 m × 1 m quadrats represents the raw data obtained through field surveys within the target ecosystem. To ensure data representativeness and reduce errors caused by spatial heterogeneity, multiple (e.g., three) representative 1 m × 1 m square quadrats are typically selected for litter collection. Within each quadrat, all litter (including undecomposed branches, leaves, fruits, etc.) is collected and its fresh weight is measured. The fresh weights of these three quadrats are summed to obtain the total fresh weight X of litter.

[0068] Through the above technical solution, this application provides a specific, operable, and standardized method for accurately converting fresh weight data of litter collected in the field into dry weight per unit area of ​​litter by combining laboratory-measured dry weight percentage. This method effectively solves the technical challenges of accurately and consistently handling differences in litter moisture content and extending point sampling data to a regional scale during actual estimation. Through clear formulas and parameter definitions, the scientific validity and repeatability of litter layer carbon density estimation are ensured, thereby improving the accuracy and reliability of the total carbon storage estimation results for the entire target ecosystem.

[0069] In some of the embodiments described above in this application, it is proposed to collect samples from the target ecosystem and calculate the carbon density and carbon storage of the litter layer based on sample analysis. However, after obtaining the dry mass per unit area of ​​the litter layer, how to accurately and scientifically convert it into the carbon storage of the litter layer to ensure the accuracy of carbon pool estimation still requires further clarification of specific calculation methods and key parameter acquisition pathways.

[0070] In this regard, this application further proposes that the carbon storage of the litter layer satisfies the following relationship: FLCD=b×Y; In the formula, FLCD represents the carbon mass of litter per unit area within the study area, in Mg / ha; b represents the percentage of carbon in the litter as determined by the elemental analyzer; and Y represents the dry mass of litter per unit area, in Mg / ha.

[0071] This formula provides a direct and quantitative method for converting the dry mass per unit area of ​​litter layer into its carbon storage. By introducing the percentage of carbon in the litter, b, the formula accurately reflects the actual carbon content in the litter, thus avoiding errors that may arise from estimations based solely on dry mass. This calculation method ensures the scientific rigor and accuracy of litter carbon storage estimation. FLCD represents the total carbon stored in litter per hectare within a specific study area. This indicator is a crucial parameter for assessing the carbon sink function of ecosystems, and its accurate acquisition is essential for understanding ecosystem carbon cycling and assessing the impacts of climate change. The unit Mg / ha ensures the standardization and comparability of the results. Parameter b is the percentage of carbon by mass in the litter sample, obtained through elemental analysis. Elemental analysis allows for precise elemental composition analysis of the sample, thus obtaining the true proportion of carbon in the litter. This direct experimental determination method ensures the accuracy of parameter b, thereby improving the reliability of litter carbon storage estimation. Y represents the total dry mass of litter per hectare within the study area. This parameter is fundamental data for estimating litter carbon storage. Obtaining it typically involves collecting, drying, and weighing litter samples, and then calculating the results based on the sample plot area. The accuracy of Y directly affects the final accuracy of the carbon storage estimate (FLCD).

[0072] In some specific embodiments, the litter layer samples can be obtained by the following steps: set up three 10 m × 10 m replicate quadrats in each forest plot, and randomly set up three 1 m × 1 m litter subplots in each quadrat. Use an iron rake to collect all the dead branches and leaves in the subplots, put them into woven bags, weigh and record the weight, bring them back to the laboratory, dry them in an oven at 105°C, and then grind and pulverize them.

[0073] The above technical solution, based on the already obtained dry mass Y per unit area of ​​litter layer, introduces the percentage of carbon in litter, b, measured by an elemental analyzer, and directly calculates the carbon storage FLCD of the litter layer using this relationship. This method effectively solves the problem that it is difficult to accurately quantify the carbon content of litter based solely on its dry mass. By accurately measuring the actual proportion of carbon in litter, this method can transform litter dry matter into ecologically significant carbon storage data, thereby significantly improving the scientific rigor and accuracy of litter carbon pool estimation. This makes the estimation of the total carbon pool of the target ecosystem more comprehensive and reliable, providing a more solid data foundation for ecosystem carbon cycle research and management.

[0074] Traditional forest carbon pool studies have largely focused on ordinary forest stands or single carbon pools, lacking systematic attention to special ecosystems with exceptionally long tree ages and significant human disturbance (such as ancient forest groves). Existing research findings cannot be directly applied to unique ancient artificial trail forest stands, resulting in a lack of scientifically quantifiable data on their carbon sequestration capacity. Furthermore, the dynamic changes in carbon density, the spatial distribution patterns of soil organic carbon, and their regulatory mechanisms in ancient forest groves of different ages remain unclear, making it difficult to support the consolidation and enhancement of the carbon sequestration capacity of ancient forest grove ecosystems.

[0075] In response, this application proposes a system for estimating the total carbon storage of a target ecosystem, comprising: a sample collection module for collecting samples from the target ecosystem; the vegetation type of the target ecosystem is subtropical evergreen broad-leaved forest, mainly composed of cypress, Masson pine, alder, and oak, with an altitude of 182 m to 954 m, a slope of 0° to 45°, and soils of yellow soil and purple soil, with a litter layer thickness of 0 cm to 15 cm; the sample includes at least one of soil samples, vegetation samples, and litter layer samples; and an analysis and calculation module for analyzing and calculating based on the sample to obtain the total carbon storage and carbon density of the target ecosystem; the distribution characteristics of the total carbon storage and carbon density of the target ecosystem include: carbon density and carbon storage of the vegetation layer, carbon density and carbon storage of the soil layer, and carbon density and carbon storage of the litter layer.

[0076] The core innovation of this embodiment lies in the systematic combination of the sample collection module and the analysis and calculation module, and the limitation of the vegetation type of the target ecosystem to subtropical evergreen broad-leaved forest, specific tree species composition and geographical parameters. This enables the comprehensive quantification of the carbon pool in the vegetation layer, soil layer and litter layer, solving the key problem of lack of scientific quantitative data on the carbon sequestration capacity of special ecosystems such as the ancient cypress forest of the Shu Road Cuiyun Corridor, and achieving the effect of accurately assessing the value of carbon sequestration. Specifically, the sample collection module collects samples from subtropical evergreen broad-leaved forests dominated by cypress, Masson pine, alder, and oak, based on the specific geographical and biological characteristics of the target ecosystem, within an altitude range of 182 m to 954 m and a slope range of 0° to 45°. This ensures that the obtained soil, vegetation, and litter layer samples can accurately reflect the ecological characteristics of the litter layer thickness in yellow and purple soil areas, ranging from 0 cm to 15 cm. The analysis and calculation module, based on the above samples, calculates the carbon density and carbon storage distribution characteristics of the vegetation layer, soil layer, and litter layer through a systematic analysis process, thereby fully presenting the total carbon storage and carbon density of the target ecosystem.

[0077] In the specific implementation process, the sample collection module first sets up quadrats within the target ecosystem that meets the specified conditions, collecting representative soil, vegetation, and litter layer samples. Subsequently, the analysis and calculation module performs laboratory processing on the samples, calculates the parameters of each carbon pool based on the sample characteristics, and finally summarizes the total carbon storage and carbon density distribution characteristics of the entire ecosystem. This technical solution effectively overcomes the limitations of existing technologies in studying carbon pools in special ecosystems, providing a scientific and systematic quantitative basis for the carbon sequestration capacity of unique ancient artificial post road forests such as the Shudao Cuiyun Corridor Ancient Cypress Forest, thereby supporting the precise formulation of carbon pool management and carbon sequestration enhancement measures.

[0078] In summary, this application takes the ancient cypress forest ecosystem of Cuiyun Corridor as the research object. Through GIS grid layout and in combination with relevant data from the Guangyuan Forestry Bureau Monitoring Center, it uses a combination of Moran's I, geostatistics, and GIS technologies to first measure the biomass of individual ancient cypress trees and estimate the carbon density of the ancient cypress tree layer, vegetation layer, understory shrubs, and grass layer. Then, it measures the carbon storage in the understory litter layer, samples, and the carbon storage of cypress forest ecosystems in plots of different ages. Finally, it analyzes the impact of different forest ages on the biomass and carbon storage of the ancient cypress forest.

[0079] The above description is only a preferred embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for estimating the total carbon storage of a target ecosystem carbon pool, characterized in that, Includes the following steps: Samples were collected from the target ecosystem. The vegetation type of the target ecosystem is subtropical evergreen broad-leaved forest, mainly composed of cypress, Masson pine, alder, and oak. The altitude ranges from 182 m to 954 m, the slope ranges from 0° to 45°, the soil is yellow soil and purple soil, and the litter layer is 0 cm to 15 cm thick. The samples include at least one of soil samples, vegetation samples, and litter layer samples. Based on the analysis and calculation of the samples, the total carbon storage and carbon density of the target ecosystem were obtained; The total carbon storage and carbon density distribution characteristics of the target ecosystem include: carbon density and carbon storage of the vegetation layer, carbon density and carbon storage of the soil layer, and carbon density and carbon storage of the litter layer.

2. The method for estimating the total carbon storage of the target ecosystem carbon pool according to claim 1, characterized in that, The target ecosystem has a maximum tree height of 33.40m, an average tree height of 7.30m, and a tree height concentration range of 15m to 20m; a maximum tree diameter at breast height (DBH) of 840cm, an average of 275.48cm, and a concentration range of 200cm to 300cm; and a maximum tree crown width of 34.30m, an average of 10.45m, and a concentration range of 5m to 10m.

3. The method for estimating the total carbon storage of the target ecosystem carbon pool according to claim 1, characterized in that, The carbon density and carbon storage of the vegetation layer satisfy the following relationship: C i =B i ×F i C di =C i / A i； In the formula, C i This represents the carbon storage of tree species / group i, in Mg; F i C represents the carbon content coefficient of tree species / group i; di This represents the carbon density of tree species / group i, in units of Mg·hm². -2 A i This represents the area of ​​tree species / group i, in hem. 2 B i This represents the total biomass of trees in tree species / group i.

4. The method for estimating the total carbon storage of the target ecosystem carbon pool according to claim 3, characterized in that, The total forest biomass refers to the biomass of living trees in a forest stand, including arbor forests, sparse forests, and shrub forests, and includes the biomass of the herbaceous layer and the deadwood layer; The total biomass of the forest trees was obtained using the volume source biomass method.

5. The method for estimating the total carbon storage of the target ecosystem carbon pool according to claim 3, characterized in that, The total biomass of the trees in species / group i satisfies the following relationship: ； Among them, B ij B represents the forest biomass of tree species in age group j / group i, in Mg. i V represents the total biomass of tree species / group i; ij This represents the volume per unit area of ​​tree species / group i in the j-th age group, in m³. 3 ·hm -2 ;D i This represents the wood density of tree species group i, in Mg·m³. -3 ; R represents the biomass expansion factor of tree species / group i in age group j; ij A represents the root-to-stem ratio of tree species in age group j to group i; ij This represents the area of ​​tree species in age group j / group i, in hectares. 2 .

6. The method for estimating the total carbon storage of the target ecosystem carbon pool according to claim 1, characterized in that, The carbon density of the soil layer satisfies the following relationship: ； In the formula, SOCD ih T represents the soil organic carbon density of the i-th grid region at soil profile h, in Mg / ha; n is the soil layer number; T i C represents the soil thickness of the i-th layer in the soil profile, in cm. i P represents the soil carbon content of the i-th layer of the soil profile, in g / kg. i The soil bulk density of the i-th layer in the soil profile is expressed in g / cm³. 3 Q i % represents the gravel content coefficient of the i-th layer of the soil profile, where the gravel diameter is >2 mm.

7. The method for estimating the total carbon storage of the target ecosystem carbon pool according to claim 1, characterized in that, The carbon storage of the soil layer satisfies the following relationship: ； In the formula, SOCS h denoted as Total Organic Carbon (SOCD) at forest soil profile h, in Tg C; n is the total number of grid cells; i is the i-th grid cell; SOCD ih The soil organic carbon density of the i-th grid region at soil profile h is expressed in Mg / ha. grid The area of ​​each grid region, in meters. 2 .

8. The method for estimating the total carbon storage of the target ecosystem carbon pool according to claim 1, characterized in that, The carbon density of the litter layer satisfies the following relationship: ； In the formula, Y is the dry mass of litter per unit area, in Mg / ha; a is the percentage of the dry mass of litter brought into the laboratory, in %; and X is the fresh mass of litter in three 1 m × 1 m quadrats, in Mg.

9. The method for estimating the total carbon storage of the target ecosystem carbon pool according to claim 8, characterized in that, The carbon storage of the litter layer satisfies the following relationship: ； In the formula, FLCD represents the carbon mass of litter per unit area within the study area, in Mg / ha; b represents the percentage of carbon in the litter as determined by the elemental analyzer; and Y represents the dry mass of litter per unit area, in Mg / ha.

10. A system for estimating the total carbon storage of a target ecosystem carbon pool, characterized in that, include: The sample collection module is used to collect samples from the target ecosystem. The vegetation type of the target ecosystem is subtropical evergreen broad-leaved forest, mainly composed of cypress, Masson pine, alder, and oak, with an altitude of 182 m to 954 m, a slope of 0° to 45°, and soils of yellow soil and purple soil. The thickness of the litter layer is 0 cm to 15 cm. The samples include at least one of soil samples, vegetation samples, and litter layer samples. The analysis and calculation module is used to analyze and calculate based on the sample to obtain the total carbon storage and carbon density of the target ecosystem; The total carbon storage and carbon density distribution characteristics of the target ecosystem include: carbon density and carbon storage of the vegetation layer, carbon density and carbon storage of the soil layer, and carbon density and carbon storage of the litter layer.

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