Data · dataset · 2026
data of stoichiometric characteristics of soil microbial biomass carbon, nitrogen, and phosphorus under different postfire regeneration forest types in the Greater Khingan Mountains, China.
Listed in ScienceDB
Data Description for Soil Microbial Biomass C, N, P Stoichiometry in Different Post-fire Regeneration Forest Types in the Greater Khingan Range1.
Description
Background and ObjectiveThis dataset originates from a study examining the effects of different regeneration approaches and forest types on soil microbial biomass carbon (C), nitrogen (N), and phosphorus (P) stoichiometry following severe fire disturbance in a cold-temperate zone.
Data were collected from five typical forest stands that regenerated via different pathways after the catastrophic "May 6" fire in 1987 in the Greater Khingan Range. The objective is to reveal differences in microbial biomass and stoichiometric ratios under various restoration modes (artificial vs. natural regeneration) and tree species compositions, thereby elucidating nutrient cycling efficiency and resource limitation mechanisms in post-fire forest soils.2.
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Site Design and SamplingStudy area: Xiufeng Forest Farm, Tahe Forestry Bureau, Greater Khingan Range, Heilongjiang Province (51°24'–52°44' N, 124°12'–125°14' E).Plot design: Five representative stand types were selected, with 3 replicate plots (30 m × 20 m) per type, totaling 15 plots. All plots are located on north-facing slopes, mid-to-lower slope positions, with slopes of 11–13°.
Historical fire assessments confirmed that all stands were dominated by Larix gmelinii before the fire, ensuring consistent fire severity.Stand type codes:L: Artificial Larix gmelinii plantationP: Artificial Pinus sylvestris var. mongolica plantationLB: Larix gmelinii – Betula platyphylla mixed plantationPB: Pinus sylvestris var. mongolica – Betula platyphylla mixed plantationNF: Naturally regenerated Larix gmelinii forest (control)Sampling: Samples were collected in mid-July 2022 (peak growing season).
In each plot, the "five-point" method was used to collect surface soil (0–15 cm) after removing litter. Five cores per plot were composited into one sample. All samples were sealed, refrigerated in the field, and transported to the laboratory promptly.3.
Data File Contents and NamingThe dataset is contained in a single CSV file named:soil_microbial_biomass_stoichiometry_Daxinganling.csvThe file records soil physicochemical properties, microbial biomass, stoichiometric ratios, microbial quotients, and soil–microbe stoichiometric imbalances for 5 stand types × 3 replicates (15 plots in total). Units are provided within the file.4. Analytical Methods4.1 Laboratory assaysSoil properties: SOC – dichromate oxidation-titration; TN – elemental analyzer; TP – acid digestion-molybdate colorimetry.Microbial biomass (MBC, MBN, MBP): Chloroform fumigation-extraction.
MBC and MBN extracted with 0.5 M K₂SO₄, conversion factors 0.38 and 0.54, respectively. MBP extracted with 0.5 M NaHCO₃ (pH 8.5), conversion factor 0.40.4.2 Calculations and statisticsStoichiometric ratios: Calculated directly from mass-based MBC, MBN, MBP values.Microbial quotients & stoichiometric imbalances: Computed using formulas provided in the associated paper (soil C:N / MBC:MBN, etc.).Statistics: One-way ANOVA following normality and homogeneity tests; Mantel tests and redundancy analysis (RDA) with Monte Carlo permutations (999 times) to identify driving factors.
Significance level: *p* < 0.05.5. Usage Notes and AcknowledgmentsData integrity: All data are raw measured values from replicates; no outliers were removed or imputed.
Citation
Users should cite the associated research paper and acknowledge ScienceDB per its data policy.Limitations: Data reflect conditions only during the 2022 growing season and should not be extrapolated to other seasons or long-term trends. Reuse should consider site-specific conditions (cold-temperate, severely burned and regenerated stands).
Links
Where it is published
- DOI doi.org/10.57760/sciencedb.cjae.00098 ↗
DOI / persistent id · from scidb cn
Catalogue records · 1
- OAI-PMH record scidb.cn/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=10.57760%2… ↗
metadata API · from scidb cn
Topics
- From keywords
- Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Forestry biomass and bioproducts 77%
Provenance · 1 source records, 11 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| ScienceDB | 10.57760/sciencedb.cjae.00098 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].anzsrc:field:300705 | enrichment · scidb cn | taxonomy-embedding@1.0.0 | title+keywords+description (77%) |
| concepts[field].local:field:earth-environmental | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:engineering | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:humanities | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| concepts[field].local:field:social-science | mapping · scidb cn | connector:scidb_cn@1.0.0 | |
| description | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/description |
| license_text | source · scidb cn | connector:scidb_cn@1.0.0 | |
| publication_date | source · scidb cn | connector:scidb_cn@1.0.0 | |
| title | source · scidb cn | connector:scidb_cn@1.0.0 | /metadata/dc/title |