Biochar is increasingly being used for soil improvement, but the effects on microbial diversity in soil are still ambiguous due to contrasting results reported in the literature. We conducted a meta-analysis to clarify the effect of biochar addition on soil bacterial and fungal diversity with an increase in Shannon or Chao1 index as the outcome. Different experimental setups, quantitative levels of biochar addition, various biochar source materials and preparation temperatures, and the effect of natural precipitation in field experiments were the investigated variables. From a total of 95 publications identified for analysis, 384 datasets for Shannon index and 277 datasets for Chao1 index were extracted that described the bacterial diversity in the soils, of which field experiments and locations in China dominated. The application of biochar in soil significantly increased the diversity of soil bacteria but it had no significant effect on the diversity of fungi. Of the different experimental setups, the largest increase in bacterial diversity was seen for field experiments, followed by pot experiments, but laboratory and greenhouse settings did not report a significant increase. In field experiments, natural precipitation had a strong effect, and biochar increased bacterial diversity most in humid conditions (mean annual precipitation, MAP > 800 mm), followed by semi-arid conditions (MAP 200–400 mm). Biochar prepared from herbaceous materials was more effective to increase bacterial diversity than other raw materials and the optimal pyrolysis temperature was 350–550 °C. Addition of biochar at various levels produced inconclusive data for Chao1 and Shannon indices, and its effect was less strong than that of the other assessed variables.

This study assessed the effects of Betula dahurica (BD), Betula platyphylla (BP), Larix gmelinii (LG), Quercus mongolica (QM), and a mixed conifer–broadleaf forest composed of LG and QM (LGQM) on the soil physicochemical parameters and community structure of fungi in the Zhongyangzhan Black-billed Capercaillie Nature Reserve. Fungal community structures were characterized via ITS rRNA sequencing. The effects of soil parameters on the community structure of soil fungi were assessed by Pearson correlation analysis and redundancy analysis (RDA). LGQM exhibited lower C/N, available nitrogen (AN), total phosphorus (TP), and available phosphorus (AP) compared with the QM broadleaf forest. The fungal Shannon and Simpson diversity indices were highest in BP, whereas LG exhibited the highest ACE index. The Basidiomycota, Ascomycota, Mortierellomycota, and Mucoromycota fungal phyla were dominant across all vegetation types. Each of the different vegetation types studied herein exhibited a unique fungal community structure. The RDA results indicated that fungal community structures were primarily shaped by the total N, available N, and available P of soil. Our findings thus indicated that forests restored with different species of trees may exhibit variations in soil quality and characteristics despite sharing the same climate. Furthermore, broadleaved and coniferous forests exhibited a unique fungal community diversity and composition.

The soil microbiome is an important component of wetland ecosystems and plays a pivotal role in nutrient cycling and climate regulation. Nitrogen (N) addition influences the soil’s microbial diversity, composition, and function by affecting the soil’s nutrient status. The change in soil bacterial diversity and composition in temperate wetland ecosystems in response to high ammonium nitrogen additions remains unclear. In this study, we used high-throughput sequencing technology to study the changes of soil bacterial diversity and community structure with increasing ammonium concentrations [CK (control, 0 kg ha⁻¹ a⁻¹), LN (low nitrogen addition, 40 kg ha⁻¹ a⁻¹), and HN (high nitrogen addition, 80 kg ha⁻¹ a⁻¹)] at a field experimental site in the Sanjiang Plain wetland, China. Our results showed that except for soil organic carbon (SOC), other soil physicochemical parameters, i.e., soil moisture content (SMC), dissolved organic nitrogen (DON), total nitrogen (TN), pH, ammonium nitrogen (NH₄⁺), and dissolved organic carbon (DOC), changed significantly among three ammonium nitrogen addition concentrations (p < 0.05). Compared to CK, LN did not change soil bacterial α-diversity (p > 0.05), and HN only decreased the Shannon (p < 0.05) and did not change the Chao (p > 0.05) indices of soil bacterial community. Ammonium nitrogen addition did not significantly affect the soil’s bacterial community structure based on non-metric multidimensional scaling (NMDS) and PERMANOVA (ADONIS) analyses. Acidobacteriota (24.96–31.11%), Proteobacteria (16.82–26.78%), Chloroflexi (10.34–18.09%), Verrucomicrobiota (5.23–11.56%), and Actinobacteriota (5.63–8.75%) were the most abundant bacterial phyla in the soils. Nitrogen addition changed the complexity and stability of the bacterial network. SMC, NO₃⁻, and pH were the main drivers of the bacterial community structure. These findings indicate that enhanced atmospheric nitrogen addition may have an impact on bacterial communities in soil, and this study will allow us to better understand the response of the soil microbiome in wetland ecosystems in the framework of increasing nitrogen deposition.

The wetlands in China’s Sanjiang Plain have experienced intensive anthropogenic disturbance recently, and this has obviously changed their environmental characteristics. Soil microorganisms play an important role in wetland ecosystems. However, the effects of different wetland types on soil microbial diversity and community composition remain largely unclear. Therefore, we assessed the effects of three typical wetland types—permanently flooded wetlands, seasonally flooded wetlands and non-flooded wetlands—on soil microbial communities in the Sanjiang Plain, using phospholipid fatty acid analysis (PLFA) technology. A total of 56 different PLFA compounds were identified, of which 10 are typically produced by uncharacterized bacteria, 15 by Gram-positive bacteria, and 11 by Gram-negative bacteria. In addition, 2 fungal groups were identified, based on four PLFAs, and four PLFAs typical for protozoa were detected. High levels were detected for 16:0 (attributed to bacteria) and i17:1ω9c (produced by Gram-positive bacteria). The latter (i17:1ω9c) was exceptionally high in non-flooded soil (8407.15 ± 2675.84 ng/g). High levels of 18:1ω7c (1939.15 ± 666.13 ng/g) and 18:1ω9c (1713.26 ± 360.65 ng/g) were detected in permanently flooded wetlands and about the same in seasonally flooded wetlands, but lower ranks were present in the drier non-flooded wetlands. The Shannon-Wiener diversity index decreased with permanently flooded wetlands (3.05) > seasonally flooded wetlands (3.02) > non-flooded wetlands (2.12). Redundancy analysis showed that the two axes could explain a total of 94.48% of soil microbial communities. Soil water content, total and available phosphorus, and total and available nitrogen correlated significantly with soil microbial communities of three wetland types. Cluster analysis of correlations between individual PLFA biomarkers and soil physiochemical properties demonstrated the complexity of the community responses to the three different habitats. This study demonstrates that microbial diversity and composition changed sensitivity among the three wetland types, and soil moisture content was the key environmental factor to affect the soil microbial communities.