2026-10-13T15:21:36Z https://www.scidb.cn/oai

10.57760/sciencedb.cjae.00067 2026-06-14T14:36:15Z

2026-06-14 Dataset of Soil Nematode Community Characteristics in Burned and Unburned Forests of Xianshan Mountain, Xinyang doi:10.57760/sciencedb.cjae.00067 en This dataset was established to investigate the effects of fire disturbance on soil nematode communities in forests of the subtropical-warm temperate transition zone. Data were collected in Xianshan Mountain, Xinyang City, Henan Province, covering burned plots and adjacent unburned control plots across three forest types: broadleaf forest, coniferous-broadleaf mixed forest, and coniferous forest. Soil nematodes were isolated using the modified Baermann funnel method, counted and identified to trophic groups (bacterivorous, fungivorous, herbivorous, and omnivorous-predaceous nematodes) under a stereomicroscope. Total nematode abundance (unit: individuals per 100 g dry soil) and relative abundance of each trophic group (unit: %) were recorded. Based on community composition, we calculated core indices including the Shannon-Wiener diversity index, Pielou evenness index, Margalef richness index, maturity index, and enrichment index. Nematode biomass (unit: μg C per 100 g dry soil) for each trophic group, enrichment footprint, structure footprint, and functional metabolic footprint were derived using standard biomass conversion formulas. We further quantified energy flow distribution across different channels and energy flow evenness in the soil micro-food web. This dataset is stored in Microsoft Excel format, consisting of 19 rows and 30 columns with no missing values. Rows 1–9 present the arithmetic mean values of all indicators, while rows 11–19 present the corresponding standard errors. All data have undergone rigorous experimental standardization and statistical validation, providing fundamental support for post-fire soil ecosystem research in temperate-subtropical transition forests. Soil nematodes; Fire disturbance; Forest ecosystem; Community structure Wang Dong Qi Xinyu RESTRICTED dataset Science Data Bank