Topsoil pH Research Articles

Integration of Grain Legumes and Mbeya Manure Improves Maize Productivity on Smallholder Farms in Central Malawi

Legumes are integrated in maize-based systems to improve soil fertility and crop productivity. However, the ecosystem services from legumes vary. Crop rotation on-farm studies were conducted over two cropping seasons (2018/19 and 2019/20) in Mkanakhoti and Kaluluma Extension Planning Areas (EPAs) in Kasungu district, central Malawi. The main objective of this study was to evaluate maize response to legume cropping systems and mbeya manure. In the first season (2018/19), five treatments including sole groundnut (Gn), sole soybean (soy), sole pigeon pea (PP), and doubled-up legumes (legume + legume intercrop) - pigeon pea intercropped with groundnut (Gn+PP), and pigeon pea intercropped with soybean (Soy+PP) were grown. In the second season (2019/20), maize was planted on plots that had either sole or doubled-up legumes. These plots were split into two, one half was top dressed with 23kg N ha-1 only and the other half received 23kg N ha-1+1000kg ha-1 mbeya manure. The experiments were replicated in 2019/2020 and 2020/2021 seasons. Soil fertility was low and highly variable between farms in the study sites. Soil pH, total nitrogen (N), available phosphorus (P), organic matter (SOM) and active carbon in topsoil (0-15cm) averaged 5.1±0.5, 0.19±0.18%, 31±19.6 ppm, 1.4±0.34 %, and 193±74 mg kg-1, respectively. Application of mbeya manure to maize increased leaf chlorophyll and plant height (p<0.05). There were variations in maize yield responses to legumes with higher benefits obtained from maize rotated with doubled-up legumes than sole legumes. The results also showed that on non-responsive soils, overall, the use of mbeya manure in combination with legume systems increased the rotational maize grain yield by 88% over maize following legumes only (p<0.05), with highest yields from doubled up legumes/maize rotations followed by groundnut/maize rotations. It is therefore recommended that on highly degraded soils, farmers can increase maize productivity through integrated soil fertility management involving a combination of 23kg N/ha and 1000kg/ha of mbeya manure applied to maize rotated with doubled-up legumes (Gn+PP or Soy+PP) and sole groundnut (Gn). Key words: Doubled-up legumes, crop rotation, groundnut, pigeon pea, soybean, maize, mbeya manure

Effects of Tillage Depth and Lime Application on Acidification Reduction and Nutrient Availability in Vertisol Soil

Cropland acidification seriously restricts sustainable agricultural development. The main purpose of this study was to determine whether deeper tilling could alleviate topsoil acidification to improve the quality of arable land. A soil column incubation experiment simulating tillage depths (10 cm, 30 cm and 50 cm) and lime addition was conducted to determine their effects on soil acidification improvement. The changes in soil pH, exchangeable acidity, ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3−-N), available phosphorus (AP), and microbial phospholipid fatty acids (PLFA) were analyzed. Tillage depth, lime application, and their interaction all had significant impacts on soil pH. T50 (simulated tillage depth of 50 cm) and T50+Lime (simulated tillage depth of 50 cm plus lime) treatments significantly increased the topsoil pH from 5.41 to 6.35 and 7.12, respectively. T50 treatment significantly reduced the soil exchangeable acid content compared to the T10 treatment. The nutrient accumulation along soil column indicated that the T50 and T50+Lime treatments significantly increased NO3−-N and AP content in the >30–50 cm soil layer. Compared with T30, NO3−-N accumulation in the >30–50 cm soil layers of T50 and T50+Lime treatments was 6.62 and 7.93 times higher, respectively. The accumulation of AP in the >30–50 cm soil layers of the T50 and T50+Lime treatments was 1.33 and 1.54 times higher than in the T30 treatment, respectively. These findings imply tillage up to 50 cm without exogenous materials could be a potential measure to reduce topsoil acidification and increase nutrition availability of >30–50 cm soil layers. Tillage of up to 30 cm combined with lime application confers greater benefits, which would particularly impact crops with shallow root systems. Subsequent field experiments will be conducted to further investigate the efficacy of these strategies in enhancing crop yield.

DYNAMIC SOIL PROPERTIES AFFECT THE ACIDITY OF ARTIFICIAL WETLANDS: A CASE STUDY IN THUNG YIEW PAK PHLI OF NAKHON NAYOK PROVINCE, THAILAND

This study examined the soil elements and properties of an area becoming an artificial wetland and compared them with those of an agricultural area. The study site is an artificial wetland in Nakhon Nayok Province, Thailand. Its soil properties and element content were compared with a nearby agricultural area using a one-way analysis of variance (ANOVA). The results of the study found this artificial wetland to be within the soil acidity zone of central Thailand, with an average soil pH above 3.99 ± 0.49 and a topsoil organic matter average of 17090 ± 2685 mg kg-1, with aluminium (Al) and iron (Fe) as the major soil minerals. Compared to the agricultural area, the soil properties of the artificial wetland had slightly lower topsoil pH but significantly lower pH in the soil layer 100 cm deep in the agricultural area, and the EC in the artificial wetland was higher than in the agricultural area. However, there are three distinct patterns in the elemental composition of the artificial wetland: (1) A lower-quantity soil surface that improves with depth, (2) a high-quantity of topsoil that worsens with depth, and (3) highly variable soil quality below 50-100 cm. In the soil, the organic carbon in artificial wetlands has a ratio of 1:0.17:0.51 to reference area 1 and reference area 2, indicating that wetlands can store carbon in the soil. The element content of the topsoil and 50 cm soil layer is potentially influenced by land use and beneficial microbial activity, and the soil 100-150 cm layer has an element quantity shared with its parent soil. In this study, we sought to understand the physics and chemical composition of soil in an area transitioning to an artificial wetland over approximately 30 years.

Anthropogenic vs. natural habitats: Higher microbial biodiversity pays the trade-off of lower connectivity

Climate change and anthropogenic disturbances are known to influence soil biodiversity. The objectives of this study were to compare the community composition, species coexistence patterns, and ecological assembly processes of soil microbial communities in a paired setting featuring a natural and an anthropogenic ecosystem facing each other at identical climatic, pedological, and vegetational conditions. A transect gradient from forest to seashore allowed for sampling across different habitats within both sites. The field survey was carried out at two adjacent strips of land within the Po River delta lagoon system (Veneto, Italy) one of which is protected within a natural preserve and the other has been converted for decades into a tourist resort. The anthropogenic pressure interestingly led to an increase in the α-diversity of soil microbes but was accompanied by a reduction in β-diversity. The community assembly mechanisms of microbial communities differentiate in natural and anthropic ecosystems: for bacteria, in natural ecosystems deterministic variables and homogeneous selection play a main role (51.92%), while stochastic dispersal limitation (52.15%) is critical in anthropized ecosystems; for fungi, stochastic dispersal limitation increases from 38.1% to 66.09% passing from natural to anthropized ecosystems. We are on calcareous sandy soils and in more natural ecosystems a variation of topsoil pH favors the deterministic selection of bacterial communities, while a divergence of K availability favors stochastic selection. In more anthropized ecosystems, the deterministic variable selection is influenced by the values of SOC. Microbial networks in the natural system exhibited higher numbers of nodes and network edges, as well as higher averages of path length, weighted degree, clustering coefficient, and density than its equivalent sites in the more anthropically impacted environment. The latter on the other hand presented a stronger modularity. Although the influence of stochastic processes increases in anthropized habitats, niche-based selection also proves to impose constraints on communities. Overall, the functionality of the relationships between groups of microorganisms co-existing in communities appeared more relevant to the concept of functional biodiversity in comparison to the plain number of their different taxa. Fewer but functionally more organized lineages displayed traits underscoring a better use of the resources than higher absolute numbers of taxa when those are not equally interconnected in their habitat exploitation. However, considering that network complexity can have important implications for microbial stability and ecosystem multifunctionality, the extinction of complex ecological interactions in anthropogenic habitats may impair important ecosystem services that soils provide us.

Carbon sequestration and nitrogen loss drive the evolution of French forest soils

The temporal change of soil chemistry in the forest floor and mineral soil down to a depth of 40 cm was assessed for the 102 permanent plots of the French Network for the Monitoring of Forest Ecosystems (RENECOFOR), over a 15-year period (from 1993–1995 to 2007–2012). In examining the separate and joint evolutions of a large set of parameters, many significant changes were detected reflecting the fact that French forest soils were not in a steady state. A significant increase in soil organic carbon (SOC) stocks was found, mainly in the surface soil (13.0% increase over the forest floor and the 0–10 cm layer). Conversely, the relative increase of the total nitrogen (Ntot) stocks was lower in the surface soil (4.8% increase), and a general and sharp decline of Ntot was detected between 10 and 40 cm depth (12.0% decrease). These results led to a substantial raise of C/N ratio over the whole soil profile. Another major finding is the difference in soil acidification recovery depending on the initial trophic level. In highly acidified contexts (top soil pH H2O < 4.5), increased soil acidification (pH and base saturation decrease, exchangeable Al increase) over the profile was observed while exchangeable base cation (Ca, Mg, K) pools increased. On the other hand, less acidic soils saw their global buffer capacity enhanced. These observations contrast with what is measured in other European inventories. While a previous study carried out on the same plots and over the same period highlighted SOC as a major driver of soil evolution in the top mineral soil, the possible mechanisms behind the large N decrease in the lower mineral soil remain to be confirmed.

VIS-NIR spectroscopy and environmental factors coupled with PLSR models to predict soil organic carbon and nitrogen

Soil profile organic carbon (OC) and total nitrogen (TN) are influenced by topographic attributes, and land use. The visible and near-infrared (Vis-NIR) spectroscopy method can be used for the prediction of OC and TN because it is reliable, nondestructive, fast, and cost-effective. VIS-NIR soil spectral and environmental data were combined with the Partial least squares regression (PLSR) model to examine the effect of topography attributes and land use on topsoil and subsoil OC and TN stocks. After this, based on the soil depth, 114 soil samples were collected from 0 to 20 cm (topsoil) and 20–50 cm (subsoil) under three land uses, as well as OC and TN, along with several soil properties including soil particles (sand, silt, clay), pH, and bulk density in both topsoil and subsoil samples were measured. A DEM with a resolution of 30 m was used to derive the topography factors and remote sensing data was used to calculate the vegetation index. Soils (0–50 cm) under orchard land use had the highest stock of SOC (7.4 kg m−2) as well as TN (2.4 kg m−2). There was a significant increase in the organic matter stock of soils located on the south aspect (8.3 kg m−2) compared to soils located on other aspects, particularly on the north aspect (3.9% increase). Soils on the south aspect contain higher soil-water contents and lower temperatures, resulting in a decrease in the decomposition of soil organic matter. A strong positive correlation was demonstrated between topography wetness index (0.57–0.63) and topography TN stocks (0.54–0.66) as well as the highest loading score among terrain attributes, suggesting that topography is the primary factor controlling SOC stocks, particularly subsoil stocks. Additionally, we found that soils on the south-facing aspects (N aspects) had the highest spectra. Additionally, the PLSR, which showed an R2 of 0.82, a RMSE of 0.15 %, and a RPD of 0.39 indicated excellent prediction capabilities for the OC content. We concluded that the PLSR model coupled with Vis-NIR spectroscopy is able to predict topsoil and subsoil OC and N content under different aspect slopes.

Fine-resolution mapping of cropland topsoil pH of Southern China and its environmental application

Soil pH is one of the critical indicators of soil quality. A fine resolution map of soil pH is urgently required to address practical issues of agricultural production, environmental protection, and ecosystem functioning, which often fall short of meeting the demands for local applications. To fill this gap, we used data from an extensive survey of 13,424 surface soil samples (0–0.2 m) across the cropland of Jiangxi Province in Southern China. Using digital soil mapping techniques with 46 covariates, we produced a 30 m resolution soil map of topsoil pH in cropland of Southern China. We integrate different variable selection algorithms and machine learning methods. Our results indicate the Random Forest with covariates selected by recursive feature selection had the best performance for mapping soil pH with r of 0.583 and RMSE of 0.41. The prediction interval coverage probability for our prediction was 0.92, indicating a low estimated prediction uncertainty. Climate was identified as the most critical variable for predicting soil pH with a contribution of 37.42 %, followed by soil properties (29.09 %), soil management (21.86 %), parent material (6.22 %), and biota (5.39 %) factors. The mean topsoil pH in the cropland of Jiangxi Province was 5.21, indicating a great pressure of soil acidification in this region. The high soil pH values were mainly distributed in the Northern, Western, and Eastern parts of the survey region while low soil pH values were majorly located in the central part. Compared with past surveys in 1980 s, there was no significant soil pH change in the surveyed region. Our soil pH map can provide important implications and guidance decisions on soil heavy metal pollution remediation, precision agriculture, and prevention of soil acidification.

Fate and migration of enhanced rock weathering products through soil horizons; implications of irrigation and percolation regimes

Terrestrial enhanced rock weathering (ERW) is reckoned as a robust method to contribute to stabilizing atmospheric carbon and combat global warming. The method is particularly a matter of interest in agricultural soil, offering a vast opportunity for the application of crushed silicate minerals and secondary carbonate accumulation and migration. Although the applicability of this practice is well acknowledged, its impact on the geochemical alteration of soil vertical profile, particularly deeper layers, is less discussed in the literature. Moreover, the effect of irrigation and percolation regimes, as influenced by ambient conditions, is also not well-reported and characterized. In the present study, we utilized a high amendment rate (50 t/ha) of wollastonite skarn, a fast-weathering silicate mineral, to uncover the alterations in topsoil and subsoil as well as effluent water over a through a soil column experiment over five months, under more controlled (indoor) and less controlled (outdoor) ambient and irrigation conditions. The results indicate more conspicuous modification of parameters in shallow layers of soil compared to deeper ones, explicitly in the rain-fed setup. Silicate amendment induced an increase of 6.53 and 2.85 tCO2/ha (in the form of pedogenic carbonate (PC)) over the profile of soil (0–60 cm) under periodic and rain-fed water regimes, respectively. The silicate treatment was also found to be effective toward rising pH and electrical conductivity of topsoil (0–15 and 15–30 cm layers) and leachate, and a measurably greater release of Ca2+ and Mg2+ in the column effluent. We estimate a carbon drawdown ratio (carbonate/bicarbonate) of ≈15:1 in this study, showing that PC formation is a more significant weathering indicator than leachate bicarbonate export in the shorter term for a fast-weathering mineral in pH-neutral soils and moderate irrigation regime. Such observations are valuable for developing carbon drawdown quantification methods suitable for a variety of agricultural lands and global regions.

Relationship between spatio-temporal evolution of soil pH and geological environment/surface cover in the eastern Nenjiang River Basin of Northeast China during the past 30 years

Soil pH plays an important role in crop growth and soil fertility. The status, variations and controlling factors of soil pH are of great significance to understand soil acidification and alkalization processes and to make decisions on maintaining soil productivity and ecological functions. In this paper, we analyzed the distribution and spatio-temporal variation characteristics of soil pH in the Nenjiang River Basin and the geochemical driving mechanism of soil pH distribution pattern, based on the National Multi-objective Regional Geochemical Survey data of topsoil, the Second National Soil Survey data and Normalized Difference Vegetation Index (NDVI). The results demonstrated that the topsoil pH had changed from neutral and alkaline levels to acidic and strongly alkaline levels in the past 30 years. NDVI decreased with the increase of soil pH when soil pH > 8.0, and decreased with the decrease of soil pH when soil pH < 5.0. There were significant differences in soil pH with various surface cover types. The weathering products of rocks and minerals rich in K2O, Na2O, CaO and MgO from the Daxing'an Mountains and Xiaoxing'an Mountains entered into the southern low plain and were enriched in different parts by water transportation, river and lake deposition.

Mapping topsoil pH using different predictive models and covariate sets in Henan Province, Central China

Spatial prediction and mapping of soil properties are synergistically influenced by models and environmental covariates. However, selecting the best modeling technique for a given landscape has been a challenge for mapping soil property. Typically, the conventional variable set (such as soil factors, climatic factors, terrain factors, and organism factors) is widely used to predict soil pH. However, certain covariates are difficult to obtain for some regions with poor data. Additionally, the effectiveness of vegetation indices (such as normalized difference vegetation index, NDVI) and phenological variables that can monitor vegetation growth dynamics based on satellite remote sensing for soil pH mapping are largely unclear. Accordingly, this study aimed to set up five environmental variable sets, such as NDVI, phenological variables, conventional variable set, conventional variable set + NDVI (C + N), and conventional variable set + phenological variables (C + P). The random forest (RF) model and convolutional neural network (CNN) model were used to compare the performance of these five environmental variable sets for spatial prediction for topsoil pH. In total, 4332 soil samples were applied and randomly divided into calibration (80%) and validation sets (20%) in this study. The model performance was evaluated using the coefficient of determination (R2) and root mean square error (RMSE). The results showed that among the five environmental variable sets, the conventional variable set was the best to predict soil pH (R2 = 0.85, RMSE = 0.41). Further, among the remote sensing variables, the phenological variables outperformed NDVI, explaining up to 67% of the variation in topsoil pH. The RF model could achieved higher accuracy than the CNN model regardless of the variables selected. Moreover, the conventional variable set could predict topsoil pH, and exhibited the potential of phenological variables. The results indicated when the conventional variable set was difficult to obtain or was missing, phenological variables can be used to predict soil properties and perform digital mapping instead of the conventional variable set.

A tradeoff between denitrification and nitrate leaching into the subsoil in nitrate-rich vegetable soils treated by reductive soil disinfestation

Intensive vegetable cultivation often leads to substantial accumulation of nitrate (NO3−-N) in the topsoil, thus posing serious threat to groundwater safety by NO3−-N leaching and food safety by excessive uptake of NO3−-N by vegetables. Reductive soil disinfestation (RSD) may remove over-accumulated NO3−-N in the topsoil due to its water-saturated, strongly reductive, and carbon-rich characteristics that favor the removal of NO3−-N via denitrification, immobilization, and leaching. However, how RSD affects the fates of NO3−-N of the topsoil in intensive vegetable lands remains largely unknown. Here, a soil column experiment using 15N tracing technique was conducted to quantify the fates of NO3−-N in the topsoil under RSD in six representative intensive vegetable soils in China. The results showed that an average of 99.7% of the added 15NO3−-N in the topsoil was removed by RSD in all intensive vegetable lands. Denitrification in the entire soil profile and leaching of NO3−-N into the subsoil were responsible for 21.8–78.3% and 14.9–68.4% of the removed 15NO3−-N, respectively, whereas microbial NO3−-N immobilization and dissimilatory nitrate reduction to ammonium in the topsoil played a negligible role in removing 15NO3−-N. A tradeoff was found between denitrification and leaching of NO3−-N into the subsoil among the six soils under RSD. The structural equation modeling demonstrated that the positive effects of RSD on topsoil pH, dissolved organic carbon, and bacterial abundance decreased the leaching of NO3−-N into the subsoil by enhancing denitrification. Overall, the results provided the first direct evidence for complete removal of NO3−-N in the topsoil by RSD. Such an evidence has implications for controlling NO3−-N accumulation through implementing RSD in intensive vegetable soils.

Using a variety of machine learning approaches to predict and map topsoil pH of arable land on a regional scale

AbstractIn order to accurately predict soil properties, various machine learning (ML) approaches and hybrid models constructed by integrating ML into regression kriging framework were used to predict and map arable land topsoil pH in Henan province, central China. Random forest (RF), cubist (Cu), support vector machine, artificial neural network, multiple linear regression, classification and regression trees (CART) and their hybrid models were compared for pH accuracy prediction. Among all standalone ML models, RF had the best predictive performance, in terms of the metrics employed in this study, followed by Cu, and CART was the worst. Compared with their ML counterparts, hybrid models could improve the accuracy of topsoil pH prediction to various extents. The accuracy improvement of the hybrid models constructed based on the simple ML was much greater than that based on the complex ensemble ML. Except for artificial neural network kriging , there was no significant difference between different hybrid models in the predicted results of topsoil pH. The outputs from the best predictive models showed that weak acidic soils and weak alkaline soils were the dominant arable soils in the study region, accounting for more than 30% and more than 50% of the total arable land area respectively, the topsoil pH of arable land in the north of the study area is generally higher than that in the south. Boruta variable selection revealed that altitude, climatic covariates closely related to soil moisture availability and some soil properties were the most critical factors affecting and controlling the topsoil pH of arable land.

Effects of the construction of fertile and cultivated soil layer on soil fertility and maize yield in Albic soil.

We examined the effects of fertile soil layer construction technology on soil fertility and maize yield with a 3-year field experiment in Albic soil in Fujin, Heilongjiang Province. There were five treatments, including conventional tillage (T15, without organic matter return) and fertile soil layer construction methods [deep tillage (0-35 cm) with straw return, T35+S; deep tillage with organic manure, T35+M; deep tillage with straw and organic manure return, T35+S+M; deep tillage with straw, organic manure return and chemical fertilizer, T35+S+M+F]. The results showed that: 1) compared with the T15 treatment, maize yield was significantly increased by 15.4%-50.9% under fertile layer construction treatments. 2) There was no significant difference of soil pH among all treatments in the first two years, but fertile soil layer construction treatments significantly increased soil pH of topsoil (0-15 cm soil layer) in the third year. The pH of subsoil (15-35 cm soil layer) significantly increased under T35+S+M+F, T35+S+M, and T35+M treatments, while no significant difference was observed for T35+S treatment, compared with T15 treatment. 3) The fertile soil layer construction treatments could improve the nutrient contents of the topsoil and subsoil layer, especially in the subsoil layer, with the contents of organic matter, total nitrogen, available phosphorus, alkali-hydrolyzed nitrogen and available potassium being increased by 3.2%-46.6%, 9.1%-51.8%, 17.5%-130.1%, 4.4%-62.8%, 22.2%-68.7% under the subsoil layer, respectively. The fertility richness indices were increased in the subsoil layer, and nutrient contents of the subsoil layer were close to those of topsoil layer, indicating that 0-35 cm fertile soil layer had been constructed. 4) Soil organic matter contents in the 0-35 cm layer were increased by 8.8%-23.2% and 13.2%-30.1% in the second and third years of fertile soil layer construction, respectively. Soil organic carbon storage was also gradually increased under fertile soil layer construction treatments. 5) The carbon conversion rate of organic matter was 9.3%-20.9% under T35+S treatment, and 10.6%-24.6% under T35+M, T35+S+M, and T35+S+M+F treatments. The carbon sequestration rate was 815.7-3066.4 kg·hm-2·a-1 in fertile soil layer construction treatments. The carbon sequestration rate of T35+S treatment increased with experimental periods, and soil carbon content under T35+M, T35+S+M and T35+S+M+F treatments reached saturation point in the experimental second year. Construction of fertile soil layers could improve the fertility of topsoil and subsoil and maize yield. In term of economic benefits, combination application of maize straw, organic material and chemical fertilizer within 0-35 cm soil, cooperating with conservation tillage, is recommended for the Albic soil fertility improvement.

Mapping Topsoil Total Nitrogen Using Random Forest and Modified Regression Kriging in Agricultural Areas of Central China

Accurate understanding of spatial distribution and variability of soil total nitrogen (TN) is critical for the site-specific nitrogen management. Based on 4337 newly obtained soil observations and 33 covariates, this study applied the random forest (RF) algorithm and modified regression kriging (RF combined with residual kriging: RFK, hereafter) model to spatially predict and map topsoil TN content in agricultural areas of Henan Province, central China. According to the RFK prediction, topsoil TN content ranged from 0.52 to 1.81 g kg-1, and the farmland with the topsoil TN contents of 1.00-1.23 g kg-1 and 0.80-1.23 g kg-1 accounted for 48.2% and 81.2% of the total farmland area, respectively. Spatially, the topsoil TN in the study area was generally higher in the west and lower in the east. By using the Boruta variable selection algorithm, soil organic matter (SOM) and available potassium contents in topsoil, nitrogen deposition, average annual precipitation, livestock discharges, and topsoil pH were identified as the main factors driving the spatial distribution and variation of soil TN in the study area. The RF and RFK models used showed the expected performance and achieved acceptable TN prediction accuracy. In comparison, RFK performed slightly better than the RF model. The R2 and RMSE achieved by the RFK model were improved by 4.5% and 4.5%, respectively, compared with that by the RF model. However, the results suggest that RFK was inferior to the RF model in quantifying prediction uncertainty and thus may have a slight disadvantage in model reliability.

Initial responses of soil chemical properties to simulated warming in Norway spruce (Picea abies (L.) H.Karst.) stands in the Western Carpathians

The present-day decline observed in Norway spruce stands in the Western Carpathians is particularly worrying given the large forest area of this species. Relatively little attention has been paid to the contribution of soil chemistry to the Norway spruce decline in the context of global warming. We conducted a field experiment to simulate warming for almost 500 days in the Western Carpathians, in a mature Norway spruce stand. Soil samples were collected approximately every 3 months from the organic and mineral topsoil horizons. Total carbon, total nitrogen, pH, dissolved organic carbon (DOC), total dissolved nitrogen (TDN), nitrate (NO3-N), and ammonium (NH4-N) nitrogen concentrations were estimated. Warming caused increase in DOC, TDN, NH4-N, and pH in organic horizon, as well as increased pH in mineral topsoil. A trend for increasing total carbon and total nitrogen concentrations in the warmed organic horizon was observed. Increased concentrations of DOC and TDN may be associated with decrease in SOM stability or increase in production of biomass of the understory vegetation or soil microbial activity. Increased pH in warmed soil may be associated with the increased NH4-N and may contribute to the decrease in soil ability to adsorb DOC. We conclude that soil warming negatively stimulates soil organic matter stability, resulting in higher concentrations of easy migrating labile forms, mostly organic acid anions. Observed changes may contribute to the deterioration of Norway spruce stands.

Exploring the safe utilization strategy of calcareous agricultural land irrigated with wastewater for over 50 years

The trace element (TE) contamination of farmland caused by wastewater irrigation threatens food security and food safety. We selected a typical calcareous soil area in western China that has been irrigated with wastewater for >50 years to explore safe use strategies for flax farmland contaminated by cadmium (Cd) and arsenic (As). We found that Cd and As were mainly accumulated in flax roots rather than seeds. However, regardless of the type of TE and acceptor, direct ingestion of the flaxseed would seriously endanger human health (hazard quotient >1). According to the results of redundancy analysis and Pearson correlation analysis, the concentration of Cd and As in flaxseed depended on the concentration of soil total TE, Olsen phosphorus, dissolved organic carbon, soil organic matter, and active calcium carbonate (CaCO3). This was largely because the pH and total CaCO3 content in topsoil of flax farmland decreased by 1.05 units and 37 %, respectively, compared with their background levels before wastewater irrigation. Interestingly, after pressing, Cd and As in flaxseed transferred to flaxseed oil were 3.87–10.55 % and 17.21–30.48 %, respectively, which led to an acceptable risk of adults and children (hazard quotient <1) consuming flaxseed oil. Our results suggest that with the production of flaxseed oil as the goal, the long-term wastewater-irrigated calcareous land can be safely utilized while obtaining income.

The driving factors and buffering mechanism regulating cropland soil acidification across the Sichuan Basin of China

Cropland soil has a higher acidification risk, with the driving factors and the soil buffering capacity controlling the degree of soil acidification. However, the relative importance of the main driving factors at broad geographic scales remains unclear, and the evidence on the acid-buffering process is rarely examined by large-scale observations. Using 4101 soil samples obtained in 1980s and 4348 soil samples collected in 2010s, this study explored topsoil pH changes of cropland across the Sichuan Basin of China and identified the relative importance of the main affecting factors. The results showed that topsoil pH (20 cm) has decreased by an average of 0.30 units (p < 0.001). Spatially, soil pH decline mainly occurred in the periphery of the Sichuan Basin where the initial pH (1980s) were less than 7.5. The magnitudes of soil pH decline were positively correlated with precipitation, base cation removal by crops and nitrogen fertilizer rates. Precipitation was identified as the most important factor in driving soil acidification. Moreover, the soil pH decrease was primarily buffered by soil carbonates and secondarily by soil CEC, and this study identified a critical level of 36.76 g kg−1 for soil carbonates, above which the acid-buffering capacity was mainly provided by soil carbonates, otherwise by soil CEC. These findings emphasize the importance of formulating precipitation-based optimizing agronomic management practices for preventing or mitigating cropland soil acidification, and also provide a regional observation-dependent evidence for the changing acid-buffering process during the soil acidification process.

Richness and distribution of endangered orchid species under different climate scenarios on the Qinghai-Tibetan Plateau.

Predicting the potential influences of climate change on the richness and distribution is essential for the protection of endangered species. Most orchid species are narrowly distributed in specific habitats and are very vulnerable to habitat disturbance, especially for endangered orchid species on the Qinghai-Tibetan Plateau (QTP). In this study, we simulated the potential influences of climate change on the richness and distribution of 17 endangered orchid species on the QTP using the MaxEnt model based on the shared socioeconomic pathways scenarios (SSPs) in the 2050s and 2070s. The results showed that aspect, annual precipitation, elevation, mean temperature of driest quarter, topsoil pH (H2O), and topsoil sand fraction had a large influence on the potential distribution of endangered orchid species on the QTP. The area of potential distribution for orchid species richness ranging from 6 to 11 under the current climate scenario was 14,462 km2 (accounting for 0.56% of QTP), and it was mostly distributed in the southeastern part of QTP. The area of orchid species richness ranging from 6 to 11 under SSP370 in the 2070s was the smallest (9,370 km2: only accounting for 0.36% of QTP). The largest area of potential distribution for orchid species richness ranging from 6 to 11 was 45,394 km2 (accounting for 1.77% of QTP) under SSP585 in the 2070s. The total potential distribution area of 17 orchid species richness all increased from the 2050s to the 2070s under SSP126, SSP245, SSP370, and SSP585. The orchid species richness basically declined with the increasing elevation under current and future climate scenarios. The mean elevation of potential distribution for orchid species richness ranging from 6 to 11 under different climate scenarios was between 3,267 and 3,463 m. The mean elevation of potential distribution for orchid species richness ranging from 6 to 11 decreased from SSP126 (3,457 m) to SSP585 (3,267 m) in the 2070s. Based on these findings, future conservation plans should be concentrated on the selection of protected areas in the southeastern part of QTP to protect the endangered orchid species.

How well does digital soil mapping represent soil geography? An investigation from the USA

Abstract. We present methods to evaluate the spatial patterns of the geographic distribution of soil properties in the USA, as shown in gridded maps produced by digital soil mapping (DSM) at global (SoilGrids v2), national (Soil Properties and Class 100 m Grids of the USA), and regional (POLARIS soil properties) scales and compare them to spatial patterns known from detailed field surveys (gNATSGO and gSSURGO). The methods are illustrated with an example, i.e. topsoil pH for an area in central New York state. A companion report examines other areas, soil properties, and depth intervals. A set of R Markdown scripts is referenced so that readers can apply the analysis for areas of their interest. For the test case, we discover and discuss substantial discrepancies between DSM products and large differences between the DSM products and legacy field surveys. These differences are in whole-map statistics, visually identifiable landscape features, level of detail, range and strength of spatial autocorrelation, landscape metrics (Shannon diversity and evenness, shape, aggregation, mean fractal dimension, and co-occurrence vectors), and spatial patterns of property maps classified by histogram equalization. Histograms and variogram analysis revealed the smoothing effect of machine learning models. Property class maps made by histogram equalization were substantially different, but there was no consistent trend in their landscape metrics. The model using only national points and covariates was not substantially different from the global model and, in some cases, introduced artefacts from a lithology covariate. Uncertainty (5 %–95 % confidence intervals) provided by SoilGrids and POLARIS were unrealistically wide compared to gNATSGO/gSSURGO low and high estimated values and show substantially different spatial patterns. We discuss the potential use of the DSM products as a (partial) replacement for field-based soil surveys. There is no substitute for actually examining and interpreting the soil–landscape relation, but despite the issues revealed in this study, DSM can be an important aid to the soil surveyor.

Practical application of high‐sodicity wasteland reclamation with flue gas desulfurization gypsum in the Songnen Plain of China

AbstractBased on global food supply demands and the need for sustainable development, it is necessary to rapidly reclaim saline‐sodic wasteland as productive land on a large scale. However, the large‐scale application of flue gas desulfurization (FGD) gypsum for the reclamation of high‐sodicity wasteland to obtain productive fields still lacks quick and concise evaluation indicators. Therefore, four FGD gypsum reclamation practices were applied in high sodicity‐affected wastelands. After 6 months, the topsoil (0–20 cm) pH, exchangeable sodium percentage (ESP), sodium adsorption ratio (SAR), electrical conductivity (EC), and paddy rice yield were evaluated. During the rice harvest, the topsoil pH, ESP, and SAR significantly decreased by 0.9–1.9 units, 29.3–67.2% and 2.3–53.7 (mmolc L−1)1/2, respectively, below initial values. Across the application sites, the interquartile range of the rice yield ranged from 1.7 to 5.8 Mg ha−1 with a median yield of 3.7 Mg ha−1. Correlation analysis between the rice yield and topsoil chemical parameters indicated that the soil pH was the primary factor of rice yield reduction, followed by ESP and SAR. To achieve a median yield, we propose that the pH, ESP and SAR of reclaimed topsoil should be lower than 8.7, 27.5%, and 8.5 (mmolc L−1)1/2, respectively, during the first season. This study provides a practical template and reference values for the salinity and sodicity of topsoil when reclaiming high sodicity‐affected wastelands via large‐scale FGD gypsum application.