The spatial and temporal dynamic monitoring of the heavy metal concentration in agricultural soils can help us to understand the extent and changes of regional soil heavy metal pollution, allowing us safeguard food safety and human health and provide basic data for the prevention and control of heavy metal pollution in agricultural soils. The heavy metals’ concentrations, including Cd, Cr, Cu, Hg, Ni, Pb, Zn, and As, were measured in surface (0–20 cm) soil samples collected in 2017 and 2021 from agriculture land to evaluate their pollution levels in the Ningxia Hui Autonomous Region (Hereinafter referred to as Ningxia), northwest of China. A correlation analysis, principal component analysis, and positive matrix factorization were used jointly to identify possible sources. The results showed that, for most soils, the concentrations of As, Cr, Cu, Ni, Pb, and Zn were lower than the contamination thresholds stipulated by the national guideline. The average concentrations of As, Cd, Zn, and Ni in 2021 were significantly lower than the levels in 2017 (p < 0.05), but the average concentration of Cu was significantly higher in 2021 than in 2017 (p < 0.05), and the average concentrations of Cr, Pb, and Hg did not change significantly during the last five years. According to the pollution assessment index (mean I_geo values), Cd and Hg were found to accumulate in the farmland environment and were the major pollutants in the region, and the hotspots with high concentrations of heavy metals were mainly located in the Yellow River irrigation area in Northern Ningxia. Four main sources of heavy metals in the soils were identified: As mainly originated from natural sources; Pb, Cd, and Ni from atmospheric deposition and industrial activities; Cr, Zn, and Cu from agricultural activities; and Hg from the coal-related industrial activities. The concentration of heavy metals from anthropogenic sources accounted for 77.10% in agricultural soils, indicating the strong influence of this source on soil heavy metal accumulation. These findings provide scientific evidence and valuable information to prevent heavy metal contamination and control of farmland.

Microbial necromass carbon (MNC) is a significant source of soil organic carbon (SOC). However, the contribution of microbial necromass to different organic carbon fractions and their influencing factors in various soil layers under different grassland types remains unclear. This study was conducted through a comprehensive investigation of soil profiles (0–20, 20–40, and 40–100 cm) across four grassland types in Ningxia, China, encompassing meadow steppe, typical steppe, desert steppe, and steppe desert. We quantified mineral-associated organic carbon (MAOC), particulate organic carbon (POC), and their respective microbial necromass components, including total microbial necromass carbon (TNC), fungal necromass carbon (FNC), and bacterial necromass carbon (BNC), and analyzed the contributions to SOC fractions and influencing factors. Our findings reveal three key insights. First, the contents of MAOC and POC in the 0–100 cm soil layer were in the following order of magnitude: Meadow steppe > Typical steppe > Desert steppe > Steppe desert, with the average content of POC being 9.3 g kg⁻¹, which was higher than the average content of MAOC (8.73 g kg⁻¹). Second, the content of microbial TNC in MAOC and POC decreased with soil depth, the average content of FNC was 3.02 and 3.85 g kg⁻¹, which were higher than the average content of BNC (1.64 and 2.08 g kg⁻¹). FNC dominated both MAOC and POC, and its contribution was higher than the contribution of BNC. Third, through regression analysis and random forest modeling, we identified key environmental drivers of MNC dynamics: mean annual rainfall, electrical conductance, and soil total nitrogen emerged as primary regulators in surface soils (0–20 cm), while available potassium, SOC, and mean annual temperature dominated deeper soil layers (20–100 cm). This research contributes by: (1) establishing the vertical distribution patterns of MNC and SOC fractions in soil profiles; (2) quantifying the relative contributions of MNC to SOC fractions across different grassland ecosystems soil profiles and elucidating their environmental controls, offers a deeper understanding of the mechanisms driving MNC accumulation in SOC fractions in diverse grassland ecosystems, and providing data support for further research on the microbiological mechanisms of soil organic carbon formation and accumulation in arid and semi-arid regions.

As an important barrier against desert invasion in Northwest China, Helan Mountains (HL), Luoshan Mountains (LS) and their natural forests have an extremely important ecological status. It is of great significance to study the relationship between forest growth and climate in this region under the background of global change. At present, relevant research mostly focuses on the Chinese pine (Pinus tabulaeformis Carr.), and little is known about how Qinghai spruce (Picea crassifolia Kom.) responds to climate change. To investigate the potential relationships between radial growth of P. crassifolia and climatic conditions in Ningxia, China, we collected tree-ring samples from P. crassifolia growing in the HL and LS and then established the standard tree-ring width chronologies for the two sites. Correlation analysis together with multivariate linear regression and relative contribution analyses were used, and results showed that radial growth in the HL was determined by the precipitation in the previous September, by the standardized evapotranspiration index (SPEI) in the current March and June, and by the maximum air temperature in the current September. The maximum air temperature in the current September contributed the most (0.348) to the radial growth in the HL. In the LS, radial growth was determined by the precipitation in the previous September and in the current March and by the minimum air temperature in the current July. The factor that made the most contribution was the precipitation in the current March (0.489). Our results suggested that in the wetting and warming future, growth of P. crassifolia in the HL will increase while that in the LS needs further investigation. Our results also provide a basis for predicting how P. crassifolia in northwest China will grow under the background of future climate change and provide a reference for formulating relevant management measures to achieve ecological protection and sustainable development policies.

Insights into what limits the growth of soil microorganisms in mountain ecosystems increase our understanding of microbial functions and processes. Although the distribution pattern of soil microorganisms in mountain ecosystems has been widely studied, their role in biogeochemical cycles along elevation gradients of mountain ecosystems in arid regions is poorly understood. In this study we analyzed the soil physicochemical properties, soil microbial community structure, extracellular enzymatic activities, ecoenzymatic stoichiometry, microbial metabolism, and their relationships along the 1,300–2,500 m elevational gradient of the Helan Mountains, northwest China. The results showed that the total microbial biomass and its components did not significantly vary with elevation. The GP:GN (gram-positive: gram-negative bacteria) ratios at low elevations were higher than those at the mid and high elevations, indicating enrichment of oligotrophic bacteria at low elevations. The five extracellular enzymes significantly differed with elevation gradient, while the levels of carbon (C)- and nitrogen (N)- acquiring enzymes first increased and then decreased with increasing elevations. Ecoenzymatic stoichiometry indicated that significant limitation of microbial growth by carbon (C) and phosphorus (P) levels occurred at high and medium elevations. Soil physicochemical characteristics, microbial community composition, and ecoenzymatic activities accounted for 43.94 and 22.21% of the microbial C and P restriction, respectively. Our study suggests that mountain ecosystems with high organic C storage possess abundant microbial populations limited by relative C and P. The study also provides important insights linking microbial metabolisms to the environmental gradients in arid mountain ecosystems.

Studying the effects of environmental factors on microbial community assemblies is crucial for understanding microbial biodiversity and ecosystem processes. Although numerous studies have explored the spatial patterns of microbial communities in surface soils, bacterial community distributions in subsurface layers remain poorly understood. We investigated multiple community metrics of soil bacteria in arid and semi-arid grasslands in China, and the V4 region of 16S rDNA was analyzed using soil property measurements, fluorescent PCR, and high-throughput sequencing techniques. Specifically, copiotrophic taxa dominate the topsoil, whereas oligotrophic taxa are prevalent in nutrient-limited subsoil. Bacterial diversity decreases from the topsoil to subsoil, and bacterial distribution and ecological community composition exhibit a strong dependence on environmental factors. Moreover, microbial interaction networks demonstrated a progressive simplification with increasing soil depth: topsoil communities displayed higher modularity and a greater prevalence of positive interactions, whereas subsoil networks were significantly less complex. Null model analyses evidenced assembly mechanisms: deterministic processes (particularly homogeneous selection) dominated the bacterial community assembly, but their influence weakened with depth, whereas stochastic processes (e.g., dispersal limitation) increased progressively from the topsoil to subsoil. The PLS-PM analysis demonstrated that the relative influence of abiotic factors (e.g., climatic conditions and nutrient availability), biotic factors (interspecific interactions), along with drift and dispersal limitations on fungal community assembly exhibited depth-dependent patterns. This study provides novel insights into the vertical stratification of bacterial community in arid and semi-arid grasslands, and advances our understanding of pedogenic process under climate change and microbial adaptive strategies in heterogeneous soil environments.