Acta Prataculturae Sinica ›› 2026, Vol. 35 ›› Issue (10): 222-236.DOI: 10.11686/cyxb2025429
Jie LI1(
), Xue-ting YU1(
), Shu-ke ZHAO2, Qiu-ga YIXI3, Dong-zhou GAMA3, Hao WU1, Yu-lin SHAN1, He-ying YU1
Received:2025-10-18
Revised:2025-12-25
Online:2026-10-20
Published:2026-09-09
Contact:
Jie LI
Jie LI, Xue-ting YU, Shu-ke ZHAO, Qiu-ga YIXI, Dong-zhou GAMA, Hao WU, Yu-lin SHAN, He-ying YU. Progress in research on methods for estimating carbon stock in grassland ecosystems and factors influencing it[J]. Acta Prataculturae Sinica, 2026, 35(10): 222-236.
方法 Method | 估算方法 Estimation methods | 优点 Advantages | 缺点 Disadvantages |
|---|---|---|---|
传统方法 Traditional methods | 样地实测法(直接估算法) Field measurement method(direct estimation method) | 操作简便、成本低廉、小尺度高精度、强数据兼容性。Simple operation, low cost, high precision at small scales, and strong data compatibility. | 工作量大、小尺度适用、随尺度扩大误差显著增加。A high workload is applicable to small scales, with errors increasing significantly as the scale expands. |
生物量回归模型法(间接估算法) Biomass regression modeling method (indirect estimation method | 快速、低成本,适用于大区域研究。It is fast, low cost, and suitable for large-scale studies. | 依赖本地参数、跨区域需校准。It depends on local parameters, and cross-region calibration is required. | |
新兴方法 Emerging methods | 遥感技术Remote sensing technology | 适用于大范围快速监测、支持动态评估。It is suitable for large-scale rapid monitoring and supports dynamic assessments. | 依赖地面数据校准,易受云层、分辨率限制。It relies on ground-based data calibration, making it susceptible to cloud cover and resolution limitations. |
| 无人机技术Drone technology | 易获取高分辨率图像、轻便灵活、适用于小范围。High-resolution images are easily obtained, light weight, flexible, and suitable for small areas. | 覆盖范围有限、数据处理复杂、易受环境限制。These methods have limited coverage, complex data processing, and are susceptible to environmental constraints. | |
| 多源数据分析Multi-source data analysis | 克服单一数据局限性、提高精度、支持长期动态监测。Overcome the limitations of single data source, improve accuracy, and support long-term dynamic monitoring. | 数据异质性处理复杂、模型依赖性高、技术门槛高。Data heterogeneity poses complex challenges, exhibits high model dependency, and requires high technical expertise. |
Table 1 Methods for estimating above-ground carbon stocks in grassland vegetation and their advantages and disadvantages
方法 Method | 估算方法 Estimation methods | 优点 Advantages | 缺点 Disadvantages |
|---|---|---|---|
传统方法 Traditional methods | 样地实测法(直接估算法) Field measurement method(direct estimation method) | 操作简便、成本低廉、小尺度高精度、强数据兼容性。Simple operation, low cost, high precision at small scales, and strong data compatibility. | 工作量大、小尺度适用、随尺度扩大误差显著增加。A high workload is applicable to small scales, with errors increasing significantly as the scale expands. |
生物量回归模型法(间接估算法) Biomass regression modeling method (indirect estimation method | 快速、低成本,适用于大区域研究。It is fast, low cost, and suitable for large-scale studies. | 依赖本地参数、跨区域需校准。It depends on local parameters, and cross-region calibration is required. | |
新兴方法 Emerging methods | 遥感技术Remote sensing technology | 适用于大范围快速监测、支持动态评估。It is suitable for large-scale rapid monitoring and supports dynamic assessments. | 依赖地面数据校准,易受云层、分辨率限制。It relies on ground-based data calibration, making it susceptible to cloud cover and resolution limitations. |
| 无人机技术Drone technology | 易获取高分辨率图像、轻便灵活、适用于小范围。High-resolution images are easily obtained, light weight, flexible, and suitable for small areas. | 覆盖范围有限、数据处理复杂、易受环境限制。These methods have limited coverage, complex data processing, and are susceptible to environmental constraints. | |
| 多源数据分析Multi-source data analysis | 克服单一数据局限性、提高精度、支持长期动态监测。Overcome the limitations of single data source, improve accuracy, and support long-term dynamic monitoring. | 数据异质性处理复杂、模型依赖性高、技术门槛高。Data heterogeneity poses complex challenges, exhibits high model dependency, and requires high technical expertise. |
估算方法 Estimation methods | 优点 Advantages | 缺点 Disadvantages | |
|---|---|---|---|
根系采样法 Root sampling methods | 挖土块法Block excavation method | 应用范围广、操作简便、可获取大量重复数据。They have a wide range of applications, are easy to operate, and can obtain large amounts of duplicate data. | 耗时耗力、破坏性采样、动态监测易中断。Time-consuming and labor-intensive, destructive sampling and dynamic monitoring are prone to interruption. |
| 根钻法Root drilling method | 操作简便,对样地破坏性小,采样率高。It is simple to operate, minimally disruptive to sample plots, and has a high sampling rate. | 根系易缺失,且采样面积小而导致数据代表性较差。Root systems are prone to loss, and small sampling areas result in poor data representativeness. | |
| 内生长土芯法Internal growth soil core method | 根易采集,样地破坏小,可精准测定土壤初级生产力季节动态。Root systems are easy to collect, cause minimal disturbance to plots, and enable precise measurements of seasonal dynamics in soil primary productivity. | 易受到环境因素的干扰,产生误差。It is susceptible to interference from environmental factors, leading to errors. | |
微根区管法 Micro-root zone tube method | 省时省力,精确采样,样本代表性高,准确可靠。Time-saving and effort-saving, precise sampling, highly representative samples, accurate and reliable. | 成本高、测量范围小,不能全面反映植物根系的特征。The high cost and limited measurement range prevent it from fully reflecting the characteristics of plant root systems. | |
根冠比法 Root-shoot ratio method | 操作简便,简化生物量估算,对样地破坏小。Simple operation, streamlined biomass estimation, and minimal disturbance to the plot. | 样本代表性较差,物种类型差异显著,易受环境影响。The sample lacks representativeness, exhibits significant variations in species composition, and is highly susceptible to environmental influences. | |
相关关系法 Correlation method | 非线性优化、估算效率提高。Nonlinear optimization improves estimation efficiency. | 根系-地上部生长异步性显著,模型假设可靠性不足。The significant asynchrony between root and shoot growth indicates insufficient reliability of the model assumption. | |
Table 2 Methods for estimating below-ground carbon stocks in grassland vegetation and their advantages and disadvantages
估算方法 Estimation methods | 优点 Advantages | 缺点 Disadvantages | |
|---|---|---|---|
根系采样法 Root sampling methods | 挖土块法Block excavation method | 应用范围广、操作简便、可获取大量重复数据。They have a wide range of applications, are easy to operate, and can obtain large amounts of duplicate data. | 耗时耗力、破坏性采样、动态监测易中断。Time-consuming and labor-intensive, destructive sampling and dynamic monitoring are prone to interruption. |
| 根钻法Root drilling method | 操作简便,对样地破坏性小,采样率高。It is simple to operate, minimally disruptive to sample plots, and has a high sampling rate. | 根系易缺失,且采样面积小而导致数据代表性较差。Root systems are prone to loss, and small sampling areas result in poor data representativeness. | |
| 内生长土芯法Internal growth soil core method | 根易采集,样地破坏小,可精准测定土壤初级生产力季节动态。Root systems are easy to collect, cause minimal disturbance to plots, and enable precise measurements of seasonal dynamics in soil primary productivity. | 易受到环境因素的干扰,产生误差。It is susceptible to interference from environmental factors, leading to errors. | |
微根区管法 Micro-root zone tube method | 省时省力,精确采样,样本代表性高,准确可靠。Time-saving and effort-saving, precise sampling, highly representative samples, accurate and reliable. | 成本高、测量范围小,不能全面反映植物根系的特征。The high cost and limited measurement range prevent it from fully reflecting the characteristics of plant root systems. | |
根冠比法 Root-shoot ratio method | 操作简便,简化生物量估算,对样地破坏小。Simple operation, streamlined biomass estimation, and minimal disturbance to the plot. | 样本代表性较差,物种类型差异显著,易受环境影响。The sample lacks representativeness, exhibits significant variations in species composition, and is highly susceptible to environmental influences. | |
相关关系法 Correlation method | 非线性优化、估算效率提高。Nonlinear optimization improves estimation efficiency. | 根系-地上部生长异步性显著,模型假设可靠性不足。The significant asynchrony between root and shoot growth indicates insufficient reliability of the model assumption. | |
方法 Method | 估算方法 Estimation methods | 优点 Advantages | 缺点 Disadvantages |
|---|---|---|---|
传统方法 Traditional methods | 土壤类型法Soil classification method | 适用于大尺度范围监测、精准估算。It is suitable for large-scale monitoring and precise estimation. | 依赖高精度数据,但数据获取难度大。It relies on high-precision data, but obtaining such data is challenging. |
| 生命地带、生态系统类型法和植被类型法Life zones, ecosystem classification method, and vegetation classification method | 一定程度上可以反映植物与气候之间的关系,精度较高。To a certain extent, this can reflect the relationship between plants and climate with high accuracy. | 生态类型与面积统计误差大,模型无法捕捉土壤碳非线性变化。Large statistical errors exist in the ecosystem type and area data, preventing the model from capturing nonlinear changes in soil carbon. | |
| 相关关系统计法Correlation statistics method | 能揭示土壤有机质与其驱动因子间的关联性,精度较高。This can reveal the relationship between soil organic matter and its driving factors with high precision. | 模型局限性强,大尺度下少样点建模可信度不足。The model has strong limitations, with insufficient reliability for large-scale modeling owing to sparse data points. | |
新兴方法 Emerging methods | 模型模拟法Model simulation method | 可综合多因子影响,具有较好的系统性和完整性。It can integrate the influence of multiple factors, demonstrating good systematics and completeness. | 空间数据需要采集、数据量大,模型需要长期训练。Spatial data require collection and involve large volumes, whereas models require long-term training. |
| 地理信息系统估算法Geographic information system (GIS) estimation method | 适合大尺度研究,估算精度较高。It is suitable for large-scale studies with relatively high estimation accuracy. | 所需参数较多,且也需要地区的空间特性数据。A large number of parameters are required, and regional spatial characteristic data are also needed. | |
| 13C同位素示踪法13C isotope tracing method | 适用于微尺度研究,可精准分辨土壤碳转化路径,揭示微观碳储量动态[ | 仅适用于小规模定量核算,大尺度应用时数据准确性受限。Applicable only to small-scale quantitative calculations; data accuracy is limited when applied to large-scale applications. |
Table 3 Methods for estimating soil carbon stocks and their advantages and disadvantages
方法 Method | 估算方法 Estimation methods | 优点 Advantages | 缺点 Disadvantages |
|---|---|---|---|
传统方法 Traditional methods | 土壤类型法Soil classification method | 适用于大尺度范围监测、精准估算。It is suitable for large-scale monitoring and precise estimation. | 依赖高精度数据,但数据获取难度大。It relies on high-precision data, but obtaining such data is challenging. |
| 生命地带、生态系统类型法和植被类型法Life zones, ecosystem classification method, and vegetation classification method | 一定程度上可以反映植物与气候之间的关系,精度较高。To a certain extent, this can reflect the relationship between plants and climate with high accuracy. | 生态类型与面积统计误差大,模型无法捕捉土壤碳非线性变化。Large statistical errors exist in the ecosystem type and area data, preventing the model from capturing nonlinear changes in soil carbon. | |
| 相关关系统计法Correlation statistics method | 能揭示土壤有机质与其驱动因子间的关联性,精度较高。This can reveal the relationship between soil organic matter and its driving factors with high precision. | 模型局限性强,大尺度下少样点建模可信度不足。The model has strong limitations, with insufficient reliability for large-scale modeling owing to sparse data points. | |
新兴方法 Emerging methods | 模型模拟法Model simulation method | 可综合多因子影响,具有较好的系统性和完整性。It can integrate the influence of multiple factors, demonstrating good systematics and completeness. | 空间数据需要采集、数据量大,模型需要长期训练。Spatial data require collection and involve large volumes, whereas models require long-term training. |
| 地理信息系统估算法Geographic information system (GIS) estimation method | 适合大尺度研究,估算精度较高。It is suitable for large-scale studies with relatively high estimation accuracy. | 所需参数较多,且也需要地区的空间特性数据。A large number of parameters are required, and regional spatial characteristic data are also needed. | |
| 13C同位素示踪法13C isotope tracing method | 适用于微尺度研究,可精准分辨土壤碳转化路径,揭示微观碳储量动态[ | 仅适用于小规模定量核算,大尺度应用时数据准确性受限。Applicable only to small-scale quantitative calculations; data accuracy is limited when applied to large-scale applications. |
排名 Ranking | 按出现频次排名Ranked by frequency of occurrence | 按中介中心性排名Ranked by intermediary centrality | ||
|---|---|---|---|---|
| 关键词Keywords | 出现频次Occurrence frequency | 关键词Keywords | 中介中心性Intermediary centrality | |
| 1 | 草地类型Grassland types | 265 | 草地类型Grassland types | 0.52 |
| 2 | 草地Grassland | 179 | 草地Grassland | 0.44 |
| 3 | 气候变化Climate change | 82 | 天然草地Natural grassland | 0.12 |
| 4 | 天然草地Natural grassland | 80 | 草地资源Grassland resources | 0.12 |
| 5 | 青藏高原Qinghai-Tibet plateau | 80 | 气候变化Climate change | 0.08 |
| 6 | 高寒草地Alpine grasslands | 76 | 高寒草地Alpine grasslands | 0.08 |
| 7 | 遥感Remote sensing | 44 | 遥感Remote sensing | 0.08 |
| 8 | 碳储量Carbon stock | 44 | 青藏高原Qinghai-Tibet plateau | 0.07 |
| 9 | 草地资源Grassland resources | 38 | 产草量Forage yield | 0.06 |
| 10 | 生物量Biomass | 37 | 生物量Biomass | 0.04 |
Table 4 Top 10 keywords by frequency and intermediary centrality in the China national knowledge infrastructure (CNKI) database
排名 Ranking | 按出现频次排名Ranked by frequency of occurrence | 按中介中心性排名Ranked by intermediary centrality | ||
|---|---|---|---|---|
| 关键词Keywords | 出现频次Occurrence frequency | 关键词Keywords | 中介中心性Intermediary centrality | |
| 1 | 草地类型Grassland types | 265 | 草地类型Grassland types | 0.52 |
| 2 | 草地Grassland | 179 | 草地Grassland | 0.44 |
| 3 | 气候变化Climate change | 82 | 天然草地Natural grassland | 0.12 |
| 4 | 天然草地Natural grassland | 80 | 草地资源Grassland resources | 0.12 |
| 5 | 青藏高原Qinghai-Tibet plateau | 80 | 气候变化Climate change | 0.08 |
| 6 | 高寒草地Alpine grasslands | 76 | 高寒草地Alpine grasslands | 0.08 |
| 7 | 遥感Remote sensing | 44 | 遥感Remote sensing | 0.08 |
| 8 | 碳储量Carbon stock | 44 | 青藏高原Qinghai-Tibet plateau | 0.07 |
| 9 | 草地资源Grassland resources | 38 | 产草量Forage yield | 0.06 |
| 10 | 生物量Biomass | 37 | 生物量Biomass | 0.04 |
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