Soil & Tillage Research最新文献

Sustainable cropland management requires preservation of soil organic matter (SOM). In spite of in depth understanding gained from ample field and laboratory studies, we have a poor understanding of landscape scale spatial variation of fresh organic matter (OM) decomposition and its conversion into soil organic carbon (SOC). Particularly, local topographic position may be expected to co-control these processes via soil hydrology. In this study, we sought to identify if such control is significant by setting up a field experiment with two contrasting positions across 10 gently sloping cropland fields covering three different soil texture groups, i.e. loamy sand, (sandy) loam and silt loam. We wanted to link OM decomposition to within-field differences in soil moisture, whilst keeping variation in other soil and management factors minimal. Specifically, mesocosms with ¹³C enriched ryegrass (the OM source) were incorporated in the fields for ten weeks and afterwards, soil was separated into > 500 µm, 53 – 500 µm and < 53 µm sized fractions. Overall, we found that lower located positions were wetter than higher positions with average differences of 11 %, 20 % and 16 % in water-filled pore space for the loamy sand, (sandy) loam and silt loam soil, respectively. Mineralization of added OM was surprisingly independent of landscape position, even though moisture conditions appeared wetter than optimal at the low but not at the high landscape positions. Remaining ryegrass residues > 500 µm did follow local topography-driven gradients in soil moisture with higher amounts in low landscape positions. In other words, drier conditions at high landscape positions improved coarse OM decomposition, with consequently more ryegrass-carbon (C) ending up in finer soil fractions (< 500 µm). Additionally, soil texture affected decomposition of the smallest fraction (< 53 µm) with a stabilizing effect for finer-textured (silt loam) soils. We conclude that, despite significant contrasts in moisture conditions between landscape positions, within-field spatial variability of OM mineralization was overall limited during the observed wet summer period. Nevertheless, landscape position affected the quality of remnant unmineralized C, with relatively more conversion of freshly added OM into OM associated with silt and clay at the drier higher positions, potentially improving the long-term stability of SOM. Likewise observations under different weather conditions are needed to evaluate the necessity of precise modelling of local soil hydrology for predicting SOC stock evolution on the landscape scale.

Biochar is a promising carbon sequestration strategy, however, the mechanisms underlying the regulation of microbial-derived carbon (M-C) and plant-derived carbon (P-C) in soil organic carbon (SOC) formation and stabilisation remain elusive, constraining accurate predictions of the organic carbon pool. This study examined the soil biotic and abiotic factors that influence the plant and microbial biomarkers in SOC accumulation. A 5-year field experiment was conducted in a temperate wheat-maize agroecosystem in north-western China, with three treatments: (i) no straw incorporation (C), (ii) straw incorporation (S), and (iii) straw incorporation + biochar (SB). The results showed that M-C reached the microbial carrying capacity gradually, whereas P-C was selectively and continuously accumulated, displaying a complementary S-curve pattern. Straw incorporation increased SOC, microbial biomass carbon (MBC), and dissolved organic carbon (DOC) contents, which stimulated microbial richness and enzyme activities, resulting in a 29.1 % and 25.5 % increase in M-C and P-C in SOC, respectively. The stimulated SOC mineralisation (26.2 %) led to significantly lower SOC content in S compared to the SB practice. Biochar combined with straw decreased DOC content (18.5 %) in comparison with straw incorporation, which suppressed microbial and enzyme activities, particularly in Actinobacteriota (12.3 %) and β-N-acetyl-glucosaminidase (24.2 %). It resulted in a 10.9 % and 14.3 % increase in M-C and fungal-to-bacterial necromass carbon ratio (F/B), respectively, while decreasing P-C by 9.6 % over the 5 years. Overall, straw incorporation with biochar effectively enhanced M-C in SOC and reduced SOC mineralisation, suggesting its potential to augment the quantity and stability of SOC pools and mitigate global climate change.

Gully erosion, with an enormous threat to global economic development and ecological security, results from the comprehensive effect of soil inherent properties and external geo-environmental factors. Previous studies on gully causative factors were mainly conducted on a specific site, case, or region, and limited systematic investigation has been performed on their spatial variation. Based on gully inventory in the seven provinces of southern China, this study investigated the spatial variation of thresholds for fifteen potential causative factors by the frequency ratio model, and analyzed the contribution of these factors to gully erosion by the Boruta algorithm. The results showed that gully density generally increased from north to south, characterized by a clustered distribution within a specific range, but the threshold of each potential factor exhibited a slight difference. Particularly, gully formation was predominantly influenced by multi-year average rainfall erosivity, multi-year average rainfall, and population density. However, the relative importance of these factors to gully erosion showed significant spatial heterogeneity. The relative importance increased from north to south for the factors of rainfall erosivity (8.25 %-13.56 %), rainfall (8.62 %-12.01 %), and slope aspect (0.35 %-1.22 %), but decreased for the factors of slope gradient (2.93 %-6.24 %), temperature (5.23 %-8.89 %), normalized difference vegetation index (NDVI) (5.25 %-7.80 %), and fraction vegetation coverage (FVC) (4.11 %-7.23 %). Overall, climatic factors exhibited an increasing contribution to gully erosion from north to south, whereas the influence of topography and vegetation coverage decreased along the same gradient. These findings will facilitate a better gully erosion control in southern China.

Continuous rotary tillage has resulted in several issues, including a thin tillage layer with low soil organic carbon (SOC) and soil compaction, impeding crop root development and resulting in low crop yields, especially in clay soils. Although deep tillage can increase crop yields by loosening the soil structure and expanding the tillage layer it is rarely applied in soils with high clay contents (such as lime concretion black soil) because of its high energy consumption and low economic benefit. This study aimed at investigating the modified tillage practice with lower energy consumption (combining rotary and deep tillage to return crop straw into different depths among different years) in the higher crop yield on a clay soil. We conducted a 5-year (2017–2021) field experiment in a lime concretion black soil with high clay content. The experiment included four treatments: conventional tillage (CT) to return crop straw into the 15-cm layer without and with fertilizer addition, modified tillage (MT) to return crop straw into different depths (i.e., 35 cm in 2017, 20 cm in 2018, 10 cm in 2019, and 20 cm in 2020) with fertilizer addition, and MT combined with fertilizer and activator addition. We investigated the crop yields, soil physicochemical properties, and microbial communities at the topsoil (0–15 cm) and subsoil (15–30 cm) layers. Compared with CT, MT increased maize (Zea mays Linn.) and wheat (Triticum aestivum L.) yields by 9.8 % and 11.4 %, respectively, by enhancing the SOC content and improving the soil physical properties of the subsoil (i.e., aggregate stability, macroaggregate proportion, soil porosity, and the proportion of large and small pores). We suggest a scientific tillage practice for future attempts to increase SOC sequestration and promote crop productivity in agricultural soils, especially those with a high clay content.

Excessive application of synthetic fertilizer has resulted in serious soil degradation and significant greenhouse gases (GHGs) fluxes in farmlands. Partial organic substitution for synthetic fertilizer was considered as a possible strategy for sustainable agricultural development, but its potential effects on soil quality, GHGs emissions, and crop productivity remain unclear. A field experiment across 3-year was conducted to evaluate the responses of soil quality, nitrous oxide (N₂O), carbon dioxide (CO₂), and methane (CH₄) emissions, and crop yields to different ratios of organic fertilizer (OF) to synthetic fertilizer (SF). Six treatments were included: non-fertilization (CK); total SF; total OF; 15 %, 30 %, and 45 % organic substitution (LO, MO, and HO). Soil cumulative N₂O emission was decreased with increasing organic substitution ratios, mainly attributing to the reducing soil NH₄⁺ content. However, organic substitution increased soil CO₂ and CH₄ emissions due to the high manure-driven C input, consequently promoting global warming potential (GWP). Meanwhile, soil organic C, total N, P, available P, K, and C-acquisition enzyme activities were increased with organic substitution, resulting the higher soil quality index (SQI) under HO and OF. HO enhanced the annual yield of wheat and maize by 7.2 % and 13.0 % compared with SF and OF, respectively. The positive relationship between crop yield and SQI indicated that the yield-enhancing effect with partial organic substitution was mainly attributed to the improved synchronization in nutrient supply and soil fertility. Overall, partial organic substitution, especially 45 % organic substitution represents a viable strategy to improve soil quality and crop productivity while mitigating N₂O emission in wheat-maize rotation systems. However, organic substitution promoted the GWP through stimulating soil CO₂ and CH₄ emissions. Further investigations of optimize fertilization managements are still needed to reduce manure-induced CO₂ and CH₄ emissions to achieve higher climate change mitigation.

Cotton (Gossypium hirsutum L.) has been a valuable economic crop in arid Xinjiang, whose cotton production accounts for 90.2 % of the grand total in China. Low phosphorus (P) bioavailability brings severe restrictions for cotton production in arid regions as a result of P precipitation caused by high soil pH and Ca²⁺ content. Therefore, how to utilize the biological potential to improve the efficiency of P utilization has become a hotspot for international research.To learn more about P bioavailability in cotton from the perspectives of root morphology, rhizosphere physiology, and mycorrhizal association, especially the synergistic effect of these three under the optimal P input on P bioavailability. A 2-year, split-plot field experiment was conducted consecutively from 2016 to 2017, in which the main plots contained three cotton varieties (XLZ57, XLZ19, and XLZ13) and the subplots were treated with five P levels (0, 75, 150, 300, and 450 kg P₂O₅ ha⁻¹). Optimal P input (P fertilizer application: 75–150 kg P₂O₅ ha⁻¹ or soil available P content in topsoil: 11–25 mg kg⁻¹) was found to not only improve the distribution of root system and mycorrhiza in soil but also promote the secretion of protons and alkaline phosphatase in the rhizosphere, leading to higher P uptake and cotton yield. Although high P input (300–450 kg P₂O₅ ha⁻¹) increased soil available P content, it inhibited root growth, mycorrhizal infection and phosphatase activity, thus reducing P uptake and product. To obtain a relatively high yield (5500–6500 kg ha⁻¹ unginned cotton) and high P accumulation (120–130 kg P₂O₅ ha⁻¹), an ideotype cotton root/rhizosphere should be characterized by high root length density (4–5 m 1000 cm⁻³), large hyphal density (15–18 m g⁻¹), and greater exudation of protons and alkaline phosphatase (60–70 μg g⁻¹ h⁻¹) in topsoil, as well as a large microbial P (MBP) value (25–28 mg kg⁻¹).Compared to mycorrhizal symbiosis (reflected by hyphal density), rhizosphere secretion of protons and alkaline phosphatase (rhizosphere physiology) and root length density (architecture) pose greater contributions to higher rhizosphere P availability and cotton P uptake. Moreover, the rhizosphere process and P use efficiency (PUE) of the P-efficient cultivar (XLZ19) were higher compared to the P-inefficient one (XLZ13).The results suggest that maximizing root/rhizosphere efficiency under optimal P input may improve cotton productivity and P uptake efficiency in mulched cotton fertigation systems in arid and semi-arid areas.

Plastic film mulching (PFM) and nitrogen (N) fertilization are two important agricultural management methods that are used to enhance crop yields in semi-arid dryland agriculture. However, the impacts of PFM and N fertilization on the temperature sensitivity (Q₁₀) of soil respiration (R_t), particularly its heterotrophic (R_h) and autotrophic (R_a) components, remain unclear. To investigate this, a trenching experiment was carried out between 2019 and 2021 in a rainfed maize-cultivated cropland that had been under cultivation for 7 years. There were four treatments: no PFM and N fertilization (control), full PFM without N fertilization (PFM), 150 kg N ha^–1 fertilization without PFM (Nfer), and full PFM with 150 kg N ha^–1 fertilization (PFM+Nfer). PFM and N fertilization not only enhanced crop yield and root biomass but also increased soil total respiration (R_t) and its components, due to improved soil hydrothermal conditions with PFM and increased N availability with N fertilization. Soil hydrothermal conditions and root biomass were identified as the most important factors influencing R_h and R_a, respectively. The greater increase in R_a (84 %–212 %) compared to R_h (9 %–29 %) resulted in a decrease in the proportion of R_h in R_t decreasing from 81.2 % in the control to 58 % under the PFM+Nfer treatment. The R_h/R_t ratio decreased in all three treatments compared to the control (p < 0.05). The increase in R_h under PFM led to a decrease in soil organic carbon (SOC) by 17 %. Specifically, the soil labile C content (i.e. LFOC 44 %) decreased more under PFM and PFM+Nfer (p < 0.05) compared to control, but not under the Nfer treatment (p > 0.05). Plastic film mulching increased the Q₁₀ of R_h (p < 0.05) through decrease the content of soil labile C, whereas N fertilization had no effect (p > 0.05). Both PFM and N fertilization increased the Q₁₀ of R_a (p < 0.05) by increasing root biomass. The impact of R_a’s Q₁₀ (0.66) on R_t’s Q₁₀ is greater compared to R_h’s Q₁₀ (0.31). To our knowledge, this is the first long-term field study to examine the response of R_t components and their Q₁₀ to PFM and N fertilization. Our results highlight that soil labile C and root biomass are the determining factors for the Q₁₀ of R_h and R_a, respectively. We emphasize the importance of accurately modeling the temperature responses of R_h and R_a when predicting R_t under climate change scenarios.

Mapping the soil organic matter (SOM) content of cultivated lands at the regional scale is of great significance for evaluating the cultivated land quality and monitoring the soil carbon cycle, especially in the fertile black-soil area of China. The large paddy fields area is one of the characteristics of the black-soil area in Northeast China. The vast differences between paddy fields and dry lands may pose a major challenge in mapping the SOM contents of local cultivated lands. In this study, the SOM of cultivated lands in Northeast China is taken as the research object, and all available Landsat-8 images from 2014 to 2022 and the main environmental covariates (climate and terrain) are obtained. By combining the random forest regression algorithm, SOM prediction models of paddy fields and dry lands are established to evaluate the optimal window period and appropriate environmental covariates for paddy fields and dry lands. Finally, the accuracy difference between the global regression and local regression results for distinguishing paddy fields and dry lands is compared. The results showed that (1) the SOM content in Northeast China increased gradually from south to north, and the average SOM content in paddy fields was approximately 0.4 % higher than that in dry lands; (2) the SOM mapping time windows in paddy fields and dry lands in Northeast China differed, with paddy fields mapped in April and dry lands mapped in May; (3) the addition of environmental covariates improved the SOM prediction accuracy, with a greater importance for mapping SOM in paddy fields than in dry lands; and (4) the local regression results based on the division of paddy fields and dry lands achieved the highest prediction accuracy, with the highest determination coefficient (R²) being 0.653 and lowest root mean square error (RMSE) being 1.144 %. This study proves that different types of arable land have a great impact on the SOM prediction accuracy. Researchers should adopt different strategies to map the SOM contents of paddy fields and dry lands.

Understanding the effects of liming plus phosphate fertilization on soil physical and chemical properties, as well as carbon stock, is critical for improving soil fertility management under conventional till (CT) and no-till (NT) systems. This study aimed to quantify changes in these soil properties resulting from incorporation (CT) or not (NT) of limestone and phosphorus (P) in a subtropical Ferralsol in southern Brazil. The experiment was conducted in Campo Mourão, Paraná State, Brazil, according to a randomized complete block design with a 6 × 4 factorial arrangement and four replications. The treatments comprised six strategies for limestone and P management and four soil depth layers (0–0.05, 0.05–0.10, 0.10–0.20 and 0.20–0.40 m), as follows: NLNT - no liming under no-till; NLCT - no liming under conventional till; LPNT - liming and P fertilization under no-till; LPCT - liming and P fertilization under conventional till; LNT - liming under no-till; and LCT - liming under conventional till. In 2012, 5.0 Mg ha⁻¹ dolomitic limestone and 53.3 kg ha⁻¹ P were applied. In 2016, dolomitic limestone was reapplied to a soybean–wheat rotation. Liming and liming plus P treatments influenced soil properties up to a depth of 0.10 m, increasing pH and decreasing Al³⁺, without significant differences between CT and NT. Higher levels of Ca²⁺ and Mg²⁺ were observed at 0–0.05 m, except in unlimed treatments. Liming and liming plus P fertilization treatments resulted in mean increments of 1.83 and 1.37 cmol_c dm⁻³ in Ca²⁺ and Mg²⁺ levels, respectively, regardless of the tillage system. Base saturation did not differ between treatments in the 0.10 m layer. However, LPCT resulted in higher base saturation in the 0.10–0.20 m (55 %) and 0.20–0.40 m (53 %) layers. P contents were affected up to 0.10 m depth, being 30 % higher in LPNT than in LPCT at 0–0.05 m. In the 0–0.05 m layer, soil bulk density was highest in NLCT and LPCT, and macroporosity was lowest in LPCT. Carbon stock was not affected by tillage practices, liming, or P fertilization. There was a positive correlation between P content and carbon stock at 0.20–0.40 m, suggesting that increased P availability at depth contributes to carbon sequestration. At 0–0.05 m, soil physical properties were negatively influenced by the combined application of liming and P fertilization under CT, indicating possible simultaneous effects on clay dispersion and pore obstruction.

Accurately mapping the spatial distribution of soil organic matter (SOM) content is critical for informed land management decisions and comprehensive climate change analyses. Remote sensing-based SOM mapping models during periods of bare soil exposure have demonstrated efficacy in various regional studies. However, integrating bare soil imagery with growing season imagery for SOM content mapping remains a complex process. We conducted a study in Youyi Farm, a representative area of black soil in Northeast China. We collected 574 soil samples (0–20 cm) with SOM content through field sampling and laboratory analysis. Additionally, cloud-free Sentinel-2 images were obtained from the Google Earth Engine (GEE) platform for both the bare soil period (April-June, October) and crop growth period (July-September) from 2019 to 2021. To assess the influence of crop growth information on SOM mapping, we incorporated remote sensing imagery during the crop growth period, considering different crop type zones (maize (Zea mays L.), soybean (Glycine max L.), and rice (Oryza sativa L.)). We conducted overall and zonal regressions using the random forest (RF) model to validate the prediction results through cross-validation. Our findings indicate that: (1) adding crop growth period images to the bare soil period images in different years can improve the accuracy of SOM mapping. For example, in the overall regression model of 2020, the highest accuracy was achieved by using the combination of May-July images, with an R² value of 0.70 and an RMSE value of 0.71 %; (2) zonal regression by differentiating crop types can effectively improve the SOM mapping accuracy. In 2019, using zonal regression, the R² of SOM mapping accuracy was improved by 0.02 and the RMSE was reduced by 0.03 % compared with the overall regression; (3) precipitation is an important factor affecting the accuracy of SOM prediction, and the lower the precipitation, the higher the accuracy of SOM prediction. In summary, the results of this study show that in the SOM remote sensing mapping of the black soil area, the growing period remote sensing information of different crop types should be comprehensively considered and combined with the image data of the years of lower precipitation, the accuracy of the SOM mapping can be effectively improved, which provides a new technological path and an application basis for the enhancement of the accuracy in remote sensing mapping with soil attributes.