Explore the vast range of titles available.

• 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.

• The intensity and frequency of droughts events are projected to increase in future with expected adverse effects for forests. Thus, information on the dynamics of tree water uptake from different soil layers during and after drought is crucial. • We applied an in situ water isotopologue monitoring system to determine the oxygen isotope composition in soil and xylem water of European beech with a 2-h resolution together with measurements of soil water content, transpiration and tree water deficit. Using a Bayesian isotope mixing model, we inferred the relative and absolute contribution of water from four different soil layers to tree water use. • Beech took up more than 50% of its water from the uppermost 5 cm soil layer at the beginning of the 2018 drought, but then reduced absolute water uptake from the drying topsoil by 84%. The trees were not able to quantitatively compensate for restricted topsoil water availability by additional uptake from deeper soil layers, which is related to the fine root depth distribution. Absolute water uptake from the topsoil was restored to pre-drought levels within 3 wk after rewetting. • These uptake patterns help to explain both the drought sensitivity of beech and its high recovery potential after drought release.

Time-domain electromagnetic (TDEM) has been widely used to investigate the subsurface aquifer. In this research, the TDEM method with a central loop configuration was employed to define the aquifer zone in the southern area of the Institut Teknologi Bandung (ITB) campus in Bandung, Indonesia. Moreover, TDEM is effective for mapping aquifers due to its sensitivity to subsurface conductivity. The acquisition consists of five sounding points spaced 20 meters apart, along with a W-E profile in the southern area of ITB. The data were interpreted using 1D inversion software (1X1D, Interpex, USA), utilizing weights from a smoothing constraint scheme (Occam) to obtain the resistivity distribution of the subsurface structure. The interpretation results indicate three layers from top to bottom: (a) the topsoil was interpreted as a sand layer with resistivity of 100 to 350 Ωm; (b) beneath it lies a shale layer with resistivity ranging from 5 to 100 Ωm that has good porosity to allow water from the surface to flow into the ground; and (c) further down, there is a clay layer with low resistivity of 1 to 5 Ωm which act as impermeable layer.

Cyanobacteria are a key biotic component as primary producers in biocrusts, topsoil communities that have important roles in the functioning of drylands. Yet, major knowledge gaps exist regarding the composition of biocrust cyanobacterial diversity and distribution in Mediterranean ecosystems. We describe cyanobacterial diversity in Mediterranean semiarid soil crusts along an aridity gradient by using next-generation sequencing and bioinformatics analyses, and detect clear shifts along it in cyanobacterial dominance. Statistical analyses show that temperature and precipitation were major parameters determining cyanobacterial composition, suggesting the presence of differentiated climatic niches for distinct cyanobacteria. The responses to temperature of a set of cultivated, pedigreed strains representative of the field populations lend direct support to that contention, with psychrotolerant vs thermotolerant physiology being strain dependent, and consistent with their dominance along the natural gradient. Our results suggest a possible replacement, as global warming proceeds, of cool-adapted by warm-adapted nitrogen-fixing cyanobacteria (such as Scytonema) and a switch in the dominance of Microcoleus vaginatus by thermotolerant, novel phylotypes of bundle-forming cyanobacteria. These differential sensitivities of cyanobacteria to rising temperatures and decreasing precipitation, their ubiquity, and their low generation time point to their potential as bioindicators of global change.

Soil organic carbon (SOC) changes under future climate warming are difficult to quantify in situ. Here we apply an innovative approach combining space-for-time substitution with meta-analysis to SOC measurements in 113,013 soil profiles across the globe to estimate the effect of future climate warming on steady-state SOC stocks. We find that SOC stock will reduce by 6.0 ± 1.6% (mean±95% confidence interval), 4.8 ± 2.3% and 1.3 ± 4.0% at 0–0.3, 0.3–1 and 1–2 m soil depths, respectively, under 1 °C air warming, with additional 4.2%, 2.2% and 1.4% losses per every additional 1 °C warming, respectively. The largest proportional SOC losses occur in boreal forests. Existing SOC level is the predominant determinant of the spatial variability of SOC changes with higher percentage losses in SOC-rich soils. Our work demonstrates that warming induces more proportional SOC losses in topsoil than in subsoil, particularly from high-latitudinal SOC-rich systems. The response of soil organic carbon to climate warming may be soil depth-dependent, but remains unquantified in situ. Here the authors show that warming induces more proportional soil carbon losses in topsoil than in subsoil, particularly from high-latitudinal carbon-rich soils.

Nutrient-efficient crops are a solution to the two grand challenges of modern agriculture: improving food security while reducing environmental impacts. The primary challenges are (1) nitrogen (N) and phosphorus (P) efficiency; (2) potassium (K), calcium (Ca), and magnesium (Mg) efficiency for acid soils; and (3) iron (Fe) and zinc (Zn) efficiency for alkaline soils. Root phenotypes are promising breeding targets for each of these. The Topsoil Foraging ideotype is beneficial for P capture and should also be useful for capture of K, Ca, and Mg in acid soils. The Steep, Cheap, and Deep ideotype for subsoil foraging is beneficial for N and water capture. Fe and Zn capture can be improved by targeting mechanisms of metal mobilization in the rhizosphere. Root hairs and phenes that reduce the metabolic cost of soil exploration should be prioritized in breeding programs. Nutrient-efficient crops should provide benefits at all input levels. Although our current understanding is sufficient to deploy root phenotypes for improved nutrient capture in crop breeding, this complex topic does not receive the resources it merits in either applied or basic plant biology. Renewed emphasis on these topics is needed in order to develop the nutrient-efficient crops urgently needed in global agriculture.

Effective land-based solutions to climate change mitigation require actions that maximize soil carbon storage without generating surplus nitrogen. Land management for carbon sequestration is most often informed by bulk soil carbon inventories, without considering the form in which carbon is stored, its capacity, persistency and nitrogen demand. Here, we present coupling of European-wide databases with soil organic matter physical fractionation to determine continental-scale forest and grassland topsoil carbon and nitrogen stocks and their distribution between mineral-associated and particulate organic matter pools. Grasslands and arbuscular mycorrhizal forests store more soil carbon in mineral-associated organic carbon, which is more persistent but has a higher nitrogen demand and saturates. Ectomycorrhizal forests store more carbon in particulate organic matter, which is more vulnerable to disturbance but has a lower nitrogen demand and can potentially accumulate indefinitely. The share of carbon between mineral-associated and particulate organic matter and the ratio between carbon and nitrogen affect soil carbon stocks and mediate the effects of other variables on soil carbon stocks. Understanding the physical distribution of organic matter in pools of mineral-associated versus particulate organic matter can inform land management for nitrogen-efficient carbon sequestration, which should be driven by the inherent soil carbon capacity and nitrogen availability in ecosystems.

Reflectance of light across the visible, near-infrared and shortwave infrared (VIS-NIR-SWIR, 0.4–2.5 µm) spectral region is very useful for investigating mineralogical, physical and chemical properties of soils, which can reduce the need for traditional wet chemistry analyses. As many collections of multispectral satellite data are available for environmental studies, a large extent with medium resolution mapping could be benefited from the spectral measurements made from remote sensors. In this paper, we explored the use of bare soil composites generated from the large historical collections of Landsat images for mapping cropland topsoil attributes across the European extent. For this task, we used the Geospatial Soil Sensing System (GEOS3) for generating two bare soil composites of 30 m resolution (named synthetic soil images, SYSI), which were employed to represent the median topsoil reflectance of bare fields. The first (framed SYSI) was made with multitemporal images (2006–2012) framed to the survey time of the Land-Use/Land-Cover Area Frame Survey (LUCAS) soil dataset (2009), seeking to be more compatible to the soil condition upon the sampling campaign. The second (full SYSI) was generated from the full collection of Landsat images (1982–2018), which although displaced to the field survey, yields a higher proportion of bare areas for soil mapping. For evaluating the two SYSIs, we used the laboratory spectral data as a reference of topsoil reflectance to calculate the Spearman correlation coefficient. Furthermore, both SYSIs employed machine learning for calibrating prediction models of clay, sand, soil organic carbon (SOC), calcium carbonates (CaCO3), cation exchange capacity (CEC), and pH determined in water, using the gradient boosting regression algorithm. The original LUCAS laboratory spectra and a version of the data resampled to the Landsat multispectral bands were also used as reference of prediction performance using VIS-NIR-SWIR multispectral data. Our results suggest that generating a bare soil composite displaced to the survey time of soil observations did not improve the quality of topsoil reflectance, and consequently, the prediction performance of soil attributes. Despite the lower spectral resolution and the variability of soils in Europe, a SYSI calculated from the full collection of Landsat images can be employed for topsoil prediction of clay and CaCO3 contents with a moderate performance (testing R2, root mean square error (RMSE) and ratio of performance to interquartile range (RPIQ) of 0.44, 9.59, 1.77, and 0.36, 13.99, 1.54, respectively). Thus, this study shows that although there exist some constraints due to the spatial and temporal variation of soil exposures and among the Landsat sensors, it is possible to use bare soil composites for mapping key soil attributes of croplands across the European extent.

1. The temporal and spatial dynamics of soil water are closely interlinked with terrestrial ecosystems functioning. The interaction between plant community properties such as species composition and richness and soil water mirrors fundamental ecological processes determining above-ground-below-ground feedbacks. Plantwater relations and water stress have attracted considerable attention in biodiversity experiments. Yet, although soil scientific research suggests an influence of ecosystem productivity on soil hydraulic properties, temporal changes of the soil water content and soil hydraulic properties remain largely understudied in biodiversity experiments. Thus, insights on how plant diversity—productivity relationships affect soil water are lacking. 2. Here, we determine which factors related to plant community composition (species and functional group richness, presence of plant functional groups) and soil (organic carbon concentration) affect soil water in a long-term grassland biodiversity experiment (The Jena Experiment). 3. Both plant species richness and the presence of particular functional groups affected soil water content, while functional group richness played no role. The effect of species richness changed from positive to negative and expanded to deeper soil with time. Shortly after establishment, increased topsoil water content was related to higher leaf area index in species-rich plots, which enhanced shading. In later years, higher species richness increased topsoil organic carbon, likely improving soil aggregation. Improved aggregation, in turn, dried topsoils in species-rich plots due to faster drainage of rainwater. Functional groups affected soil water distribution, likely due to plant traits affecting root water uptake depths, shading, or water-use efficiency. For instance, topsoils in plots containing grasses were generally drier, while plots with legumes were moister. 4. Synthesis. Our decade-long experiment reveals that the maturation of grasslands changes the effects of plant richness from influencing soil water content through shading effects to altering soil physical characteristics in addition to modification of water uptake depth. Functional groups affected the soil water distribution by characteristic shifts of root water uptake depth, but did not enhance exploitation of the overall soil water storage. Our results reconcile previous seemingly contradictory results on the relation between grassland species diversity and soil moisture and highlight the role of vegetation composition for soil processes.

Soil organic carbon (SOC) persistence is predominantly governed by mineral protection, consequently, soil mineral-associated (MAOC) and particulate organic carbon (POC) turnovers have different impacts on the vulnerability of SOC to climate change. Here, we generate the global MAOC and POC maps using 8341 observations and then infer the turnover times of MAOC and POC by a data-model integration approach. Global MAOC and POC storages are 975 964 987 Pg C (mean with 5% and 95% quantiles) and 330 323 337 Pg C, while global mean MAOC and POC turnover times are 129 45 383 yr and 23 5 82 yr in the top meter, respectively. Climate warming-induced acceleration of MAOC and POC decomposition is greater in subsoil than that in topsoil. Overall, the global atlas of MAOC and POC turnover, together with the global distributions of MAOC and POC stocks, provide a benchmark for Earth system models to diagnose SOC-climate change feedback. Separating soil organic carbon into mineral-associated and particulate organic carbon enables a more accurate prediction of soil vulnerability to climate change. The authors generate the global atlas of stocks and turnover times of these two fractions.