Dataset on the effects of biochar derived from different feedstocks on soil microbial nutrient limitation in a Phyllostachys edulis forest.

Biochar was uniformly applied to the soil at a rate of 20 t/hm² and thoroughly mixed. In mid-June 2022, soil samples from the 0–15 cm layer were collected using the five-point sampling method and mixed into composite samples. After removing plant residues and stones, the soils were sieved through a 2 mm mesh.

One portion was stored fresh at 4°C for the determination of microbial biomass and enzyme activities, while the other portion was air-dried for the analysis of soil physicochemical properties. The equipment and tools used mainly included a microplate spectrophotometer (for enzyme activity assays), a real-time quantitative PCR instrument (for functional gene quantification), along with Excel 2019, SPSS 26, and R language (for data calculation, statistical analysis, and plotting).The dataset is stored in a tabular format, where rows represent different treatment groups and columns represent the measured indicators.

The specific indicators and their meanings are as follows: Soil physicochemical properties include pH (dimensionless, determined by a pH meter at a 2.5:1 water-to-soil ratio), soil organic carbon (SOC, g/kg), total nitrogen (TN, g/kg), total phosphorus (TP, g/kg), alkaline-hydrolyzable nitrogen (AN, mg/kg), available potassium (AK, mg/kg), and available phosphorus (AP, mg/kg); Microbial biomass includes microbial biomass carbon (MBC, mg/kg), microbial biomass nitrogen (MBN, mg/kg), and microbial biomass phosphorus (MBP, mg/kg), as well as their stoichiometric ratios (e.g., SOC:TN, SOC:TP, TN:TP, MBC:MBN, MBC:MBP, MBN:MBP, dimensionless).

Soil enzyme activities include β-glucosidase (BG), cellobiohydrolase (CBH), β-xylosidase (XYL), leucine aminopeptidase (LAP), β-N-acetylglucosaminidase (NAG), and acid phosphatase (ACP), all expressed in units of nmol·g⁻¹·h⁻¹, along with their enzymatic activity ratios. Based on enzymatic stoichiometry, vector length (indicating the degree of C limitation, dimensionless) and vector angle (in degrees, °, indicating N vs. P limitation; an angle > 45° indicates P limitation, while < 45° indicates N limitation) were calculated; microbial carbon use efficiency (CUE, dimensionless, ranging from 0 to 1) is also included; and carbon-degrading functional gene abundances (e.g., genes degrading starch, cellulose, hemicellulose, chitin, and lignin, in copies/g).

A minimal number of missing values exist in this dataset, primarily manifesting as missing data for individual carbon-degrading functional genes. This absence is due to the failure of qPCR amplification curves to emerge, rather than manual omission. Data errors primarily stem from systematic errors in indoor instrument measurements and random errors introduced by micropipette operations.

Additionally, enzyme activity assays may introduce minor deviations due to variations in substrate incubation time and colorimetric reaction time.The dataset contains one data file in the standard .xlsx format, which can be directly read and processed using software such as Microsoft Excel, WPS, and R. The file content is divided into 3 main sheets: (1) Soil chemical properties: includes treatment types, all soil chemical property indicators, microbial biomass C, N, and P, and their ratios; (2) Hydrolase activities: includes the 6 enzyme activities, enzymatic stoichiometric ratios, vector length, vector angle, and microbial carbon use efficiency (CUE); (3) Functional genes: includes the absolute abundance data of various carbon-degrading functional genes.