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• Warming-induced desiccation of the fertile topsoil layer could lead to decreased nutrient diffusion, mobility, mineralization and uptake by roots. Increased vertical decoupling between nutrients in topsoil and water availability in subsoil/bedrock layers under warming could thereby reduce cumulative nutrient uptake over the growing season. • We used a Mediterranean semiarid shrubland as model system to assess the impacts of warming-induced topsoil desiccation on plant water- and nutrient-use patterns. A 6 yr manipulative field experiment examined the effects of warming (2.5°C), rainfall reduction (30%) and their combination on soil resource utilization by Helianthemum squamatum shrubs. • A drier fertile topsoil (‘growth pool’) under warming led to greater proportional utilization of water from deeper, wetter, but less fertile subsoil/bedrock layers (‘maintenance pool’) by plants. This was linked to decreased cumulative nutrient uptake, increased nonstomatal (nutritional) limitation of photosynthesis and reduced water-use efficiency, above-ground biomass growth and drought survival. • Whereas a shift to greater utilization of water stored in deep subsoil/bedrock may buffer the negative impact of warming-induced topsoil desiccation on transpiration, this plastic response cannot compensate for the associated reduction in cumulative nutrient uptake and carbon assimilation, which may compromise the capacity of plants to adjust to a warmer and drier climate.

Soil organic carbon (SOC) in shrublands is an important component of global carbon cycling. However, there is a dearth of large-scale systematic observations of SOC stocks at different soil depths, and it remains uncertain whether and how the relative importance of biotic and abiotic variables in regulating SOC stocks changes with soil depth. Here, we quantified large-scale patterns and controlling factors of SOC storage per area (SOCD, kg m−2) for both topsoils (0–30 cm) and subsoils (30–100 cm) by taking full advantage of a consistent stratified random sampling study of one-meter soil profiles across 1211 sites in Chinese shrublands. We found that subsoils stored about 53.30% of total SOCD, falling into the range of previously reported values for terrestrial ecosystems. SoilGrids250m model-derived assessments overestimated SOCD by 13.72 and 65.49% for topsoils and subsoils, respectively. The effects of climate means and seasonality on SOCD were equally strong in both topsoils and subsoils. The predominant effects of edaphic properties on SOCD were more robust in subsoils than in topsoils. Belowground biomass of shrublands was the only significant predictor of topsoil SOCD, but it did not predict subsoil SOCD accurately. These findings have refined our understanding of the pivotal role of shrublands in SOC storage and sequestration potential and could serve as an ecologically valuable baseline for large-scale improvement and validation of depth-dependent SOC dynamics for multilayer SOC modules in Earth Systems Models.

AimsTree species mixing is an essential measure used to increase soil carbon (C) sinks and enhance nutrient cycling, while enzyme catalysis is the rate-limiting step of soil C mineralization and nutrient release. The study aimed to determine how mixing affects soil C and nitrogen (N) hydrolases kinetics in subtropical plantations.MethodsThe topsoil (0–15 cm) and subsoil (45–60 cm) from two monoculture coniferous plantations and two mixed plantations formed by replanting broad-leaved trees in the two coniferous plantations were collected to analyze the maximum activity (Vmax), half-saturation constant (Km) and catalytic efficiency (Vmax/Km) of four hydrolases involved in C (β-glucosidase, BG; cellobioside, CB) and N (β-N-acetylglucosaminidase, NAG; leucine aminopeptidase, LAP) cycling.ResultsMixing decreased the Vmax of BG but increased the Vmax of NAG in the topsoil, indicating the differential response of C and N enzyme activities to mixing. The Km of NAG and LAP increased, while the Vmax/Km of CB and NAG decreased after mixing in the topsoil. Mixing decreased the Vmax of CB and NAG and the Vmax/Km of BG and CB in the subsoil. The Vmax/Km values of C and N hydrolases were negatively correlated with SOC, total N and mineral N and positively correlated with the aromatic/aliphatic compound ratio, which illustrated that the hydrolases kinetics were mediated by changes in soil quality.ConclusionMixing decreased the catalytic efficiency of soil C and N hydrolases in subtropical plantations, although the mixing effect on soil hydrolase kinetic parameters depended on the enzyme type and soil depth.

Purpose While well-designed drainage systems could improve crop growth and yield by mitigating waterlogging and salinity stresses, field evidence of the yield responses to changes in plant-water relations and ion concentrations in leaves is scarce. We investigated the changes in ion concentrations in leaves and plant-water relations of sunflower caused by drainage in waterlogged saline soil, and their relationships to growth and yield. Methods Over two growing seasons, we tested four drainage treatments: undrained, surface drains (SD; 0.1 m deep, 1.8 m apart), subsoil drains (SSD; 0.5 m deep, 4.5 m apart) and SSD + SD. All plots were inundated (2–3 cm depth; water salinity, EC w , 1.5–2.5 dS m –1 ) for 24 h at vegetative emergence and at the 8-leaf stage before opening drains. Results Relative to the most drained treatment (SSD + SD), the undrained treatment caused higher waterlogging at 0–30 cm depth, and decreased solute potential (Ψ s ) of soil at 7.5 cm to 52–374 kPa, leaf K + by 5–20%, stomatal conductance by 5–37% and leaf greenness by 12–25%, but increased leaf Na + by 25–70%, Na + /K + ratio by 38–100% and leaf water potential by 90–250 kPa throughout the cropping season; these changes were closely related to reduced growth and yield. Conclusions The improved yield from the combination of shallow surface and sub-surface drains was attributed to an alleviation of salinity-waterlogging stress early in the season and to increased soil water late in the season that increased Ψ s and decreased Na + /K + ratio in leaves.

Understanding the geotechnical characteristics of subsoil is important for safety and efficiency in design and construction processes. In particular, the subsoil in the Bangkok Metropolitan area has accumulated soft marine clay over a long period, resulting in a thick layer of soft clay, which poses challenges for engineers. This study presents an approach to modelling the subsoil of the Bangkok Metropolitan region by utilising a large dataset of borehole data, enhanced with a Deep Neural Network (DNN) model, to develop a 3D geotechnical map. The hyperparameters of the DNN were tuned to fit the dataset for classifying the soil layers and the regression models were generated to predict the geotechnical engineering properties of the Bangkok subsoil, including the bulk unit weight, water content, plasticity index, undrained shear strength, and SPT-N values. The DNN model performance has been evaluated to ensure the accuracy and reliability of its predictions. The generated 3D geotechnical map was compared with the map obtained from the traditional kriging method to verify the map accuracy and differences in results between these two approaches. This study demonstrates the potential of machine learning techniques for improving geotechnical mapping and geotechnical engineering information. The outcomes of this research also support Sustainable Development Goals (SDGs), particularly SDG 9, by providing accurate geotechnical data to enhance sustainable infrastructure planning, and SDG 11, by refining the subsoil model in urban areas, which contributes to safer and more sustainable urban development while reducing environmental risks in construction.

Soil temperature (ST) is an important property of soils and driver of below ground biogeochemical processes. Global change is responsible that besides variable meteorological conditions, climate-driven shifts in ST are observed throughout the world. In this study, we examined long-term records in ST by a trend decomposition procedure from eleven stations in western Germany starting from earliest in 1951 until 2018. Concomitantly to ST data from multiple depths (5, 10, 20, 50, and 100 cm), various meteorological variables were measured and included in the multivariate statistical analysis to explain spatiotemporal trends in soil warming. A significant positive increase in temperature was more pronounced for ST (1.76 ± 0.59 °C) compared with air temperature (AT; 1.35 ± 0.35 °C) among all study sites. Air temperature was the best explanatory variable to explain trends in soil warming by an average 0.29 ± 0.21 °C per decade and the trend peaked during the period from 1991–2000. Especially, the summer months (June to August) contributed most to the soil warming effect, whereby the increase in maximum ST (STmax) was nearby fivefold with 4.89 °C compared with an increase of minimum ST (STmin) of 1.02 °C. This widening between STmax and STmin fostered enhanced diurnal ST fluctuations at ten out of eleven stations. Subsoil warming up to + 2.3 °C in 100-cm depth is critical in many ways for ecosystem behavior, e.g., by enhanced mineral weathering or organic carbon decomposition rates. Thus, spatiotemporal patterns of soil warming need to be evaluated by trend decomposition procedures under a changing climate.

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.

Background Even with extensive root growth, plants may fail to access subsoil water and nutrients when root-restricting soil layers are present. Biopores, created from decaying roots or soil fauna, reduce penetration resistance and channel root growth into the deeper soil. Further positive effects on plants result from biopore traits, as the pore walls are enriched in nutrients, microbial abundance, and activity relative to bulk soil. However, negative effects on plant growth have also been observed due to root clumping in biopores, less root-soil contact than in the surrounding bulk soil and leaching of nutrients. Scope We discuss methods for biopore research, properties of biopores and their impact plant performance based on a literature review and own data. We elucidate potential implications of altered root-soil contact for plant growth and the consequences of root growth in pores for the rhizosphere microbiome. Conclusions Biopores play an important but ambiguous role in soils. The effects of biopores on plant growth depend on soil properties such as compaction and moisture in an as-yet-unresolved manner. However, pore properties and root-soil contact are key parameters affecting plant yield. Knowledge gaps exist on signaling pathways controlling root growth in pores and on mechanisms modifying rhizosphere properties inside biopores. The degree to which negative effects of biopores on plant growth are compensated in the bulk soil is also unclear. Answering these questions requires interdisciplinary research efforts and novel imaging methods to improve our dynamic understanding of root growth and rhizosphere processes within biopores and at the rhizosphere-biopore interface.

Background and aims To assess the impacts of soil microbes and plant genotype on the composition of maize associated bacterial communities. Methods Two genotypes of Brazilian maize were planted indoors on sterile sand, a deep underground subsoil, and a nutrient-rich topsoil from the Amazon jungle (terra preta). DNA was extracted from rhizospheres, phyllospheres, and surface sterilized roots for 16S rDNA fingerprinting and next generation sequencing. Results Neither plant genotype nor soil type appeared to influence bacterial diversity in phyllospheres or endospheres. Rhizospheres showed strikingly similar 16S rDNA ordination of both fingerprinting and sequencing data, with soil type driving grouping patterns and genotype having a significant impact only on sterile sand. Rhizospheres grown in non-sterile soils contained greater bacterial diversity than sterile-sand grown ones, however the dominant OTUs (species of Proteobacteria and Bacteroidetes) were found in all rhizospheres suggesting seeds as a common source of inoculum. Rhizospheres of the commercial hybrid appeared to contain less bacterial diversity than the landrace. Conclusions Maize rhizospheres receive diverse bacteria from soil, are influenced by the genotype or treatment of the seed, and are dominated by species of Proteobacteria, Actinobacteria, Bacteroidetes, and Firmicutes. As many dominant 16S rDNA sequences were observed in rhizospheres grown in both sterile and non-sterile substrate, we conclude that the most common bacterial cells in juvenile maize rhizospheres are seed transmitted.