查看更多>>摘要：? 2022Soil bacteria play core roles in mediating the functional linkage between above- and belowground components during forest restoration. However, the pattern and mechanism through which plants and soils influence bacterial communities remain unclear. This study aimed to quantify the contributions of plant community and soil characteristics to shifts in bacterial composition and diversity along a tropical forest restoration chronosequence in the Xishuangbanna. We found a negative effect of forest restoration on bacterial composition and a positive impact on the diversity. Forest restoration changed bacterial communities from being oligotrophic Acidobacteria and Actinobacteria dominated to copiotrophic Proteobacteria and Firmicutes dominated. Forest restoration also induced a 1.5–1.6 fold increase in OTU richness and diversity of bacterial communities. Soil variables, including plant litter, contributed 46.3–58.1% to the variations in bacterial composition and diversity, while the contribution of plant community was 6.4–13.8%. Furthermore, the increase in plant richness and diversity had minor contribution to variations in bacterial diversity and composition during forest restoration. Soil bacterial diversity was primarily explained by the elevated levels of carbon and nitrogen stoichiometry in the litter-soil-microbe continuum, but litter was explained by the increased plant diversity. In contrast, soil bacterial composition was negatively correlated with biomass, nitrogen, and carbon:nitrogen of the litter, as well as the level of soil carbon and nitrogen pools. Our data suggested that the carbon and nitrogen stoichiometry in litter-soil-microbe continuum rather than plant diversity primarily shaped the changes in bacterial composition and diversity along tropical forest restoration.
查看更多>>摘要：? 2022 The AuthorsSubsoil compaction is an increasing problem in modern agriculture, but is not easily recognized in practice, also because of possible within-field spatial variations. This paper addresses the question of how within-field spatial variations in soil bulk density and other soil characteristics relate to within-field spatial variations in crop yield and potential CO2 and N2O emissions from soil. Four fields (5 to 20 ha each) were selected at the suggestion of crop farmers, and sampled using a random soil sampling design (100 samples per field). Undisturbed soil samples were taken at depth of 5–10, 30–35, and 50–55 cm and soil bulk density and potential CO2 and N2O emissions measured under controlled conditions. At each sampling point, also top soil (0–20 cm) samples were taken for determination of pH, texture, SOM, and (micro)nutrients, and soil penetration resistance measurements and visual assessments of soil structure were made. Wheat yields were recorded with harvesters equipped with GPS and yield recorders. Mean soil bulk density in the sub-soil (30–35 cm) ranged between fields from 1.36 ± 0.08 to 1.60 ± 0.11 g cm?3. Mean wheat yields ranged between fields and years from 7.6 ± 0.6 and 11.3 ± 2.4 Mg ha?1. Semi-variogram analyses showed that crop yields and soil properties were mostly spatially dependent; nugget-to-sill ratios were < 25% with ranges of 137 to 773 m. The ratio of CO2 emissions to N2O emissions was negatively related to soil bulk density, especially following N application. In conclusion, within-field spatial variations in subsoil bulk density were successfully related to spatial variations in crop yield and potential CO2 and N2O emissions. The ratio of CO2 emissions to N2O emissions had a much greater response to spatial variations in soil bulk density than wheat yield. Our study suggests that N2O emission factors may depend on (sub)soil bulk density.
查看更多>>摘要：? 2022 Elsevier B.V.Drylands represent 45 % of the Earth's surface and can contain up to 32 % of the organic carbon (C) of all soils on the planet. In this study, we used 91 soil profiles (from the surface to the rock) to estimate the total stocks of C and nitrogen (N) accumulated in the profiles and the surface and subsurface C/N ratio along a gradient of aridity, ranging from 30.81 (semi-arid) to 60.92 (dry sub-humid), in order to understand the effects of increased humidity in the environment on the dynamics of C and N accumulation in tropical drylands. For data analysis, we used linear regression, non-parametric tests (Wilcoxon-Mann-Whitney and Kruskal-Wallis tests) and principal components analysis (PCA). We concluded that the increase in the humidity of the environment positively influenced the C stock and no influence on N stock and C/N ratio. We observed an increase of 24.7% in organic C accumulation under the more humid climate, which was accompanied by greater aboveground plant biomass, with a predominance of deciduous and subdeciduous forests and an increase in of 48.0% in the thickness of the profiles (1.75 ± 0.21 m), when compared with profiles under semi-arid climate (1.18 ± 0.56 m). Under dry sub-humid climate, soils under the influence of deciduous forests, presented an average of 45.4% and 79.4% more C than soils under the influence of hypoxerophytic and hyperxerophilous forests respectively, predominant vegetation of semi-arid climate. Individually, the aridity index did not show any relationship with the stocks of C and N and with the C/N ratio of the studied soils, which indicates the need to carry out comprehensive and integrated studies that address several environmental variables together, to better understand the C and N dynamics of soils in tropical drylands.
查看更多>>摘要：? 2022 Elsevier B.V.Direct evidence on how the determinants of soil microbial biomass and N mineralization differ with sampling depth and layer at a regional scale is lacking. We sampled 132 plots along aridity gradients on the Mongolian Plateau and determined the soil bacterial and fungal biomass and N mineralization rates at four soil sampling depths (0–20, 0–40, 0–60, and 0–100 cm) and layers (0–20, 20–40, 40–60, and 60–100 cm). We found that the determinants of microbial biomass and soil N mineralization differed among the four soil sampling depths or layers. At 0–20 cm, both bacterial and fungal biomasses were directly related to aridity and soil substrate quantity. Bacterial biomass was directly related to aridity and soil substrate quality at 0–100 cm soil depth and was directly related to aridity and plant substrate quantity in the 60–100 cm soil layer. Fungal biomass was directly related to aridity and the soil environment at 0–100 cm soil depth and in the 60–100 cm soil layer. The magnitude of these direct effects on microbial variables differed with soil depth and layer. For example, the direct effects of aridity (negative) and soil substrate quality (positive) on bacterial biomass increased with soil depth but not with soil layer. Soil N mineralization was directly associated with soil the environment and substrates across the four soil sampling depths, but was directly associated with soil substrates and plant quality across the four soil sampling layers. Our results provide the first regional-scale evidence that the determinants associated with soil microbial biomass and N mineralization depend on the sampling depth and layer. These findings indicate that studies based on surface soils may not accurately identify the determinants of microbial communities or ecosystem functions across the entire soil profile of drylands globally.
查看更多>>摘要：? 2022 Elsevier B.V.The damage caused by rainfall-induced landslides has increased globally. The development of urbanisation has led to the expansion of residential areas in mountainous areas, and human activities have accelerated slope instability. However, the limited data records in mountainous zones have resulted in low-precision landslide rainfall thresholds. Establishing a landslide early warning model in areas with scarce data is an unresolved problem. This study uses the Bailong River Basin in western China as an example. By downscaling Tropical Rainfall Measuring Mission (TRMM) data to a daily resolution of 1 km and conditionally merging it with ground station rainfall, we obtain high-precision rainfall data to establish rainfall threshold curves based on Bayes' theorem and the frequency method. Subsequently, a landslide susceptibility map based on deep learning was integrated to construct a regional landslide early warning model. The results are as follows: First, compared with downscaling rainfall and rain gauge interpolation data, the daily rainfall data with a resolution of 1 km that combines the two has better overall performance and higher accuracy. Second, we generated the event-rainfall-and-duration threshold curves of 5%, 20%, and 50% probability by combining the frequency method and Bayesian theorem, and show that with a probability of landslide occurrence of 50%, while the intercept of Bayes' theorem is greater than that of the frequency method, the overall trend is consistent. Finally, by using a typical mass rainfall event to test the performance, the results show that the early warning capability of the model integrated with the rainfall threshold and landslide susceptibility map is more accurate than that of using a separate rainfall threshold. The outcomes of this research are expected to provide efficient support for early warning and risk management of geological disasters in mountainous areas with scarce data.
查看更多>>摘要：? 2022 Elsevier B.V.Deep roots can uptake deep soil water to support plant growth and mitigate climate change in water-limited ecosystems. Few studies have been conducted on the deep root characteristics in the soil profile as limited field data are available. To explore the relationship between the deep root characteristics, depth, and soil water status, we obtained the distribution pattern of deep roots and soil water content along a 21-m soil profile (n = 22) in a mature Robinia pseudoacacia plantation. The maximum rooting depth, mean root biomass, and mean depths corresponding to 50% and 90% of the total root biomass of 17-year-old R. pseudoacacia trees were >20 m, 0.083 ± 0.029 g·cm?2, 1.17 ± 1.74, and 6.15 ± 3.98 m, respectively. We established an exponential power model to fit the relationship between the deep root biomass and soil depth, which had a higher goodness-of-fit than the typical exponential model, logistic model, and piecewise linear model. The root morphological characteristics along the 21-m vertical profile rapidly decreased with depth in the 0–1-m layer, and then stabilized, while the specific root length (SRL) and specific root area (SRA) increased with depth. The relationships between the SRL, SRA, and soil water content in the dried soil layers with roots (SWC-DSL) were significantly positive (both p < 0.01), while those between average root diameter density and SWC-DSL were significantly negative (p < 0.001), suggesting that roots increased their length rather than diameter to acquire water resources with relatively low carbon investment. The soil depth and soil water availability co-controlled root biomass and root morphological characteristics. Our findings highlight the importance and complexity of deep roots and their morphological characteristics, which are fundamental for forest models and management to maintain sustainable development between soil water and root water uptake.
查看更多>>摘要：? 2022 Elsevier B.V.Soil respiration, as an important process in global carbon cycle, is drastically stimulated by warming. Changing plant carbon inputs caused by intensified human disturbances and climate change can complexly influence soil respiration and its temperature sensitivity (Q10). Although a number of experiments have been established in the world to explore the effects of changing carbon inputs, it remains a challenge to predict the direction and magnitude of changes in soil respiration and Q10 due to high spatiotemporal variability of climatic zone and ecosystem. Therefore, we conducted a field manipulative experiment to examine the impact of litter removal and root exclusion on soil respiration and Q10 in a deciduous broad-leaved forest in transition zone between subtropical and warm temperate zone. The results showed that litter removal significantly reduced soil respiration, microbial biomass carbon, soil organic carbon, total nitrogen and soil moisture. In addition, litter removal altered soil microbial community composition, expressed in increase of Gram-positive / Gram-negative bacteria ratio and percentage of actinomycetes, and enhanced microbial physiological stress index. Root exclusion significantly increased Q10 by elevating soil C/N ratio, which supporting “C quality-temperature” hypothesis. The study indicates that root exclusion may accelerate soil respiration under warming. Our study provides insights to improve carbon cycling models and accurately predict the consequences of climate change.
查看更多>>摘要：? 2022 The Author(s)Soil erosion is time compressed into a number of episodic erosive rainfall events with an associated potential to detach and transport soil particles (rainfall erosivity), each possessing unique spatial and temporal characteristics. Rainfall erosivity events in Europe follow extreme value distributions in which a limited number of rainstorms dominate the long-term budget of available erosive energy. To combat soil erosion in Europe in a targeted manor, timely erosion mitigation measures should derive from dynamic model simulations that incorporate spatially and temporally distributed estimations of rainfall erosivity. Rain gauge measurements from singular points are typically used to quantify rainfall erosivity, however the spatial uniqueness of rainfall presents a key limitation to dynamically model rainfall across broad spatial scales with a limited number of point measurements. Discretised gridded precipitation datasets with a widespread (e.g. continental) spatial coverage potentially offer an opportunity to adequately replicate the dynamics of rainfall erosivity events, however their performance remains poorly tested in the pan-European context. This study builds upon the comprehensive Rainfall Erosivity Database at European Scale (REDES) archive of over 300,000 events from 1181 gauge stations to develop a two-step modelling process: 1) firstly, optimal monthly models were fitted and evaluated between gauge-recorded rainfall depth and rainfall erosivity (EI30) across European climatic regions to develop a European-scale parameter surface, 2) secondly, three datasets (EMO-5 (6-hr), E-OBS (24-hr), UERRA MESCAN-SURFEX (24hr)) were directly evaluated via a grid-to-point analysis based on their ability to simulate the station-specific event rainfall erosivity timeseries at a random selection of 32 locations. EMO-5 (Nash-Sutcliffe model efficiency mean = 0.24) outperformed other tested gridded datasets, showing the capability to adequately replicate the event number, timing, and their average magnitude. A higher model performance in Northern compared with Southern European climatic regions, in which characteristically higher and spatially-complex event rainfall erosivity magnitudes are found, was symptomatic of a poor ability of grid-based simulations to replicate the magnitudes of events in the outer extents of the frequency-magnitude spectrum. The absence of a clear global systematic predictive bias amongst simulated locations suggests the need for future upscaling of this analysis to the entire European REDES dataset to fully understand and correct for the method-derived bias in a climate region-specific way.
查看更多>>摘要：? 2022 Elsevier B.V.The influence of grass cover on surface runoff and erosion processes on hillslopes differs with plant morphology and grass components (e.g., leaves, stems and roots). However, the importance of grass components, especially stolons, in reducing runoff and sediment yield is not fully understood. Thirty field simulation experiments with rainfall intensities of 90 mm h?1 were performed to study the effects of three grass species (Trifolium repens, Cynodon dactylon and Eremochloa ophiuroides) and their aboveground and belowground components on runoff, hydrodynamic parameters and sediment reductions during rainstorms. To examine the effects of different grass components on soil erosion, three management treatments, intact grass plants (IG), grass stems and roots (SR) and only grass roots (OR), were applied to each grass species. The results showed that the three grass species effectively reduced runoff and soil erosion, and the erosion reduction was greater than the runoff reduction. The highest reduction in runoff (78.2%) and sediment yield (97.9%) was observed for E. ophiuroides, followed by the T. repens and C. dactylon plots. The overland flow velocity and runoff energy increased with the sequential removal of grass aboveground components and led to increasing runoff and erosion. The effects of grass components on runoff and erosion reduction varied with grass species and plant morphology. The aboveground components had a greater impact on runoff reduction, and the roots primarily contributed to sediment reduction in T. repens and C. dactylon, which have erect stems. However, the contribution rates of grass stems to runoff and erosion reduction were highest for E. ophiuroides with well-developed stolons at 41.51% and 61.04%, respectively, which were much higher than the leaves and roots. This finding indicated that grass stolons played an important role in reducing runoff and sediment with efficiencies of 32.44% and 59.79%, respectively. These results help guide the selection of grass species with the best traits for erosion control and highlight the importance of grass stolons in preventing water erosion caused by extreme rainstorms.
查看更多>>摘要：? 2022 Elsevier B.V.Preferential infiltration occurs widely in loess deposits and has a major impact on water movement and redistribution. However, preferential infiltration is a complex process, and previous research has focused principally on its qualitative description. Few studies have carried out infiltration tests to assess preferential infiltration in loess. In this study we conducted five soil column infiltration field tests in the Heifangtai area of Gansu Province, China, to explore preferential infiltration processes and the characteristics of loess. Based on the test data, the preferential infiltration is qualitatively assessed, and a quantitative calculation method for the preferential infiltration of loess with vertical cracks is proposed. The following conclusions were drawn: 1) The relationship between the infiltration rate of loess and the reciprocal of wetting front depth is a positive linear relationship under homogeneous infiltration, but non-linear under preferential infiltration. 2) The degree of preferential infiltration can be determined based on the distance of data points to the infiltration rate-wetting front propagation velocity gradient under homogeneous infiltration. 3) Based on the principle of similarity of infiltration of adjacent soil, we calculate that the preferential infiltration rate of closed cracks is two to three orders of magnitude greater that the homogeneous infiltration rate, and that the contribution of stable preferential infiltration to the total infiltration is about 20%. Quantitative evaluations of preferential infiltration are helpful in calculating slope seepage, evaluating slope stability, and researching landslide initiation mechanisms.
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