Changes in species composition across communities, i.e., β-diversity, is a central focus of ecology. Compared to macroorganisms, the β-diversity of soil microbes and its drivers are less studied. Whether the determinants of soil microbial β-diversity are consistent between soil depths and between abundant and rare microorganisms remains controversial. Here, using the 16S-rRNA of soil bacteria and archaea sampled at different soil depths (0–10 and 30–50 cm) from 32 sites along an aridity gradient of 1500 km in the temperate grasslands in northern China, we compared the effects of deterministic and stochastic processes on the taxonomic and phylogenetic β-diversity of soil microbes. Using variation partitioning and null models, we found that the taxonomic β-diversity of the overall bacterial communities was more strongly determined by deterministic processes in both soil layers (the explanatory power of environmental distance in topsoil: 25.4%; subsoil: 47.4%), while their phylogenetic counterpart was more strongly determined by stochastic processes (the explanatory power of spatial distance in topsoil: 42.1; subsoil 24.7%). However, in terms of abundance, both the taxonomic and phylogenetic β-diversity of the abundant bacteria in both soil layers was more strongly determined by deterministic processes, while those of rare bacteria were more strongly determined by stochastic processes. In comparison with bacteria, both the taxonomic and phylogenetic β-diversity of the overall abundant and rare archaea were strongly determined by deterministic processes. Among the variables representing deterministic processes, contemporary and historical climate and aboveground vegetation dominated the microbial β-diversity of the overall and abundant microbes of both domains in topsoils, but soil geochemistry dominated in subsoils. This study presents a comprehensive understanding on the β-diversity of soil microbial communities in the temperate grasslands in northern China. Our findings highlight the importance of soil depth, phylogenetic turnover, and species abundance in the assembly processes of soil microbial communities.

Understanding the contribution of forest ecosystems to regulating greenhouse gas emissions and maintaining the atmospheric CO₂ balance requires the accurate quantification of above-ground biomass (AGB) at the individual tree species level. The main objective of this study was to develop species-specific allometric equations for the total AGB and various biomass components, including stem, branch, and foliage biomass in Khangai region, northern Mongolia. We destructively sampled a total of 183 trees of five species (22–74 trees per species), including Siberian stone pine (Pinus sibirica Du Tour.), Asian white birch (Betula platyphylla Sukacz.), Mongolian poplar (Populus suaveolens Fisch.), Siberian spruce (Picea obovata Ldb.), and Siberian larch (Larix sibirica Ldb.), across this region. The results showed that for the five species, the average biomass proportion for the stems was 75%, followed by branches at 20% and foliage at 5%. The species-specific component and total AGB models for the Khangai region were developed using tree diameter at breast height (D) and D² and tree height (H) combined ( ${\mathrm{D}}^2\mathrm{H}$ ); and both D and H were used as independent variables. The best allometric model was lnŶ = lna + b × lnD + c × lnH for the various components and total AGB of B. platyphylla and L. sibirica, for the stems and total AGB of P. suaveolens, and for the stem and branch biomass of P. obovata. The equation lnŶ = lna + b × ln( ${\mathrm{D}}^2\times \mathrm{H}$ ) was best for the various components and total AGB of P. sibirica, for the branch and foliage biomass of P. suaveolens, and for AGB of P. obovata. The equation lnŶ = lna + b × ln(D) was best only for the foliage biomass of P. obovata. Our results highlight that developing species-specific tree AGB models is very important for accurately estimating the biomass in the Khangai forest region of Mongolia. Our biomass models will be used at the tree level inventories with sample plots in the Khangai forest region.

To explore the pattern of the leaf functional traits of shrub species along a latitudinal gradient in eastern China and determine the driving factors of leaf trait variation at a large scale. We investigated the leaf thickness (LT), leaf area (LA), specific leaf area (SLA) and leaf dry mass content (LDMC) of 185 shrub species from 13 sites across eastern China. The trends of these four leaf traits were analyzed with respect to latitude, and the differences between different life forms (e.g., evergreen and deciduous) and habitats (e.g., understory and typical) were compared. We quantified the effects of the plant life forms and environmental factors on the leaf traits via mixed-model analyses. The LT and LA decreased, whilst and the LDMC increased, as the latitude increased, and significant differences in these traits were observed between the different plant life forms. The LT and LA were smaller, whereas the SLA and LDMC were larger in deciduous shrubs than in evergreen shrubs. Among the different habitats, the LA and SLA were larger, while the LDMC was smaller in understory shrubs than in typical shrub species. These results indicate that typical shrub species are better adapted to drier environments, as indicated by a reduced LT and increased LDMC. Furthermore, general linear models showed that variations in the four leaf traits with respect to latitude were mainly caused by a shift in plant life forms.

Microbial stoichiometry and its potential driving factors play crucial roles in understanding the balance of chemical elements in ecological interactions and nutrient limitations along the aridity gradient. However, little is known about the variation in these features along the aridity gradient due to the lack of comprehensive field investigations. Additionally, previous studies focused on the topsoil (0–10 or 0–20 cm); however, the minimum sampling depth for topsoil could impact the results of the vertical distribution of microbial stoichiometry. In the present study, we measured the variation in microbial stoichiometry, examined the major influential factors (climatic, edaphic, and biotic factors) along an aridity gradient, and determined whether the sampling depth affected microbial C : N : P stoichiometry. From the topsoil to the subsoil, the microbial C : N, C : P, and N : P ratios varied from 6.59 to 6.83, from 60.2 to 60.5, and from 9.29 to 8.91, respectively. Only the microbial C : N ratio significantly increased with soil depth. The microbial C : N ratio significantly increased with increasing aridity in both topsoil and subsoil, while the microbial N : P ratio decreased along the aridity gradient only for the topsoil. This result implied that drought-stimulated microbes tend to be more N conservative, especially those in topsoil. Among all the factors, the soil organic carbon (SOC) content and the fungi-to-bacteria ratio exerted the largest influence on the microbial C : N, C : P, and N : P ratios at both soil depths, implying that the substrate supply and microbial structure together controlled the microbial stoichiometry. The results also revealed that the aridity index (AI) and plant aboveground biomass (AGB) exerted negative impacts on the microbial C : N ratio at both soil depths, and the effects of AI decreased in the subsoil. The results of this study suggested that the flexibility of the microbial N : P ratio should be considered when establishing the sampling depth for microbial stoichiometry study.