Raw Meta-analysis Dataset of Soil Organic Carbon and Soil Organic Matter in Rice-Wheat Rotation Croplands

The source literature includes full-text, publicly available field experiment papers published up to December 2024, primarily retrieved from China National Knowledge Infrastructure (CNKI) and Web of Science. The retrieval queries were "(SOC + SOM + 土壤有机碳 + 土壤有机质)

• 稻麦轮作" for CNKI and "(SOC OR SOM OR soil organic carbon OR soil organic matter) AND (rice-wheat rotation)" for Web of Science. A total of 187 Chinese-language papers and 453 English-language papers were initially identified.The dataset was screened using the following criteria: (1) the study reported clear geographic coordinates or a detailed site address; (2) the experiment included a control treatment and replications; (3) information on soil properties, agricultural management practices, measurement methods, and experimental duration was sufficiently reported; (4) when repeated observations were available from the same site, data from the most recent year were retained; and (5) the study focused on rice-wheat rotation croplands. After screening and deduplication, 86 publications were retained, yielding 379 valid paired observations.The extracted variables mainly include SOC or SOM content, experimental site information, soil properties, management practices, experimental duration, replication number, and error statistics. To improve comparability across studies, data were standardized before compilation. Reported SOC stocks or densities were converted to SOC content using soil depth and bulk density. Reported SOM values were converted to SOC content using a conventional conversion coefficient. Missing bulk density values were estimated using the empirical equation proposed by Pan et al. (2010). For studies lacking standard deviation (SD), SD was calculated from standard error (SE) and replication number when SE was available; otherwise, SD was estimated as 10% of the mean value following Skinner et al. (2014).Data reported in text or tables were extracted manually, while values presented only in line charts or bar charts were digitized using GetData Graph Digitizer 2.2. Data collation, coding, checking, and quality control can be completed using spreadsheet tools such as Microsoft Excel. This dataset can support studies on SOC variation in rice-wheat rotation systems, the effects of agricultural management practices, regional comparisons, and evidence synthesis through meta-analysis.