构建了一个全球性的土壤有机碳矿化数据集，旨在深入理解土壤有机碳分解对温度的响应规律，并评估和改进当前地球系统模型中的相关预测。该数据集整合了来自191项研究的721种土壤，共包含近2.2万个数据点，涵盖了从-10°C到60°C的多种培养条件。\n
样本主要来自中国、欧洲和美国，严重缺乏非洲、高纬度等关键区域的代表；84%的样本集中于0-30厘米的表层土壤，忽略了储存大量碳的深层土壤；此外，大多数实验的培养温度与采样点的实际环境温度存在较大差异，这可能影响温度敏感性估算的准确性。", "ds_source": "
数据来源于https://doi.org/10.6084/m9.figshare.25808698 。", "ds_process_way": "
本数据集通过系统的文献检索与标准化流程构建。首先，从文中直接提取数值数据，并使用WebPlotDigitizer对图形数据进行数字化。随后，将所有碳矿化速率统一标准化为以土壤和有机碳为基准的单位，确保数据可比性。同时，整合了土壤性质、培养条件等元数据，并基于采样点坐标从WorldClim数据库提取了标准化气候变量。最终，将所有经过提取、标准化和整合的数据进行质量核查后归档发布。", "ds_quality": "
数据集通过标准化流程整合了全球土壤培养实验数据，但其科学解释力受限于当前研究的系统性偏差。数据在空间上集中于中纬度地区，深度上严重缺乏深层土壤样本，且61%的实验温度设计与实地环境失准。这些局限性影响了其对全球碳循环的代表性，但数据集内部通过统一的单位换算、元数据匹配和气候数据补充，保证了自身的一致性与可追溯性，为评估模型偏差和研究空白提供了重要基准。", "ds_acq_start_time": "1990-01-01 00:00:00", "ds_acq_end_time": "2019-12-31 00:00:00", "ds_acq_place": "全球", "ds_acq_lon_east": 180.0, "ds_acq_lat_south": -90.0, "ds_acq_lon_west": -180.0, "ds_acq_lat_north": 90.0, "ds_acq_alt_low": null, "ds_acq_alt_high": null, "ds_share_type": "login-access", "ds_total_size": 5827531, "ds_files_count": 3, "ds_format": "*.csv", "ds_space_res": "", "ds_time_res": "", "ds_coordinate": "无", "ds_projection": "", "ds_thumbnail": "0d041b0a-f69c-4f5e-bf22-2b8cc65ffca3.png", "ds_thumb_from": 0, "ds_ref_way": "", "paper_ref_way": "", "ds_ref_instruction": "", "ds_from_station": null, "organization_id": "a4dd5849-78f2-44c5-b0f1-3450e952b2a2", "ds_serv_man": "敏玉芳", "ds_serv_phone": "0931-4967596", "ds_serv_mail": "ncdc@lzb.ac.cn", "doi_value": "", "subject_codes": [ "170.45" ], "quality_level": 3, "publish_time": "2025-10-30 18:06:35", "last_updated": "2026-01-13 16:42:21", "protected": false, "protected_to": null, "lang": "zh", "cstr": "11738.11.NCDC.FIGSHARE.DB6983.2025", "i18n": { "en": { "title": "A global dataset of soil organic carbon mineralization in response to incubation temperature changes", "ds_format": "*.csv", "ds_source": "
The data is sourced from https://doi.org/10.6084/m9.figshare.25808698 .", "ds_quality": "
The dataset integrates global soil culture experiment data through standardized processes, but its scientific interpretability is limited by systematic biases in current research. The data is concentrated in mid latitude regions spatially, with a severe lack of deep soil samples at depth, and 61% of experimental temperature designs are inaccurate with the field environment. These limitations affect its representativeness of the global carbon cycle, but the dataset ensures its consistency and traceability through unified unit conversions, metadata matching, and climate data supplementation, providing important benchmarks for evaluating model biases and research gaps.", "ds_ref_way": "", "ds_abstract": "
We have constructed a global soil organic carbon mineralization dataset aimed at gaining a deeper understanding of the response of soil organic carbon decomposition to temperature, and evaluating and improving relevant predictions in current Earth system models. This dataset integrates 721 types of soil from 191 studies, containing nearly 22000 data points and covering various cultivation conditions from -10 ° C to 60 ° C.\n
The samples mainly come from China, Europe, and the United States, with a severe lack of representatives from key regions such as Africa and high latitudes; 84% of the samples are concentrated in the surface soil of 0-30 centimeters, ignoring the deep soil that stores a large amount of carbon; In addition, there is a significant difference between the cultivation temperature of most experiments and the actual environmental temperature of the sampling points, which may affect the accuracy of temperature sensitivity estimation.
", "ds_time_res": "", "ds_acq_place": "global", "ds_space_res": "", "ds_projection": "", "ds_process_way": "This dataset was constructed through a systematic literature search and standardization process. Firstly, extract numerical data directly from the text and digitize the graphical data using WebPlotDigitizer. Subsequently, all carbon mineralization rates were standardized into units based on soil and organic carbon to ensure data comparability. At the same time, metadata such as soil properties and cultivation conditions were integrated, and standardized climate variables were extracted from the WorldClim database based on sampling point coordinates. Finally, all extracted, standardized, and integrated data will undergo quality verification before being archived and released.", "ds_ref_instruction": "" } }, "submit_center_id": "ncdc", "data_level": 0, "license_type": "CC BY 4.0", "doi_reg_from": "reg_outside", "cstr_reg_from": "reg_outside", "doi_not_reg_reason": null, "cstr_not_reg_reason": null, "is_paper_in_submitting": false, "ds_topic_tags": [ "土壤有机碳矿化", "温度敏感性", "碳-气候反馈" ], "ds_subject_tags": [ "地理学" ], "ds_class_tags": [], "ds_locus_tags": [ "全球" ], "ds_time_tags": [ 1990, 2019 ], "ds_contributors": [ { "true_name": "罗忠奎", "email": "luozk@zju.edu.cn", "work_for": "浙江大学", "country": "中国" } ], "ds_meta_authors": [ { "true_name": "罗忠奎", "email": "luozk@zju.edu.cn", "work_for": "浙江大学", "country": "中国" } ], "ds_managers": [ { "true_name": "罗忠奎", "email": "luozk@zju.edu.cn", "work_for": "浙江大学", "country": "中国" } ], "category": "生态" }