Soil organic carbon (SOC) and iron (Fe) oxides are known to affect the formation and stability of soil aggregates. However, the effects of SOC and Fe oxides on soil aggregates stability under straw returning and potassium (K) fertilizer application in paddy–upland rotation systems are less well-studied. This study primarily investigated soil aggregates dynamics and their stability indices (mean weight diameter, MWD; geometric mean diameter, GMD), and soil binders (SOC and iron oxides) after rice and rape harvests under four treatments: F1，mineral nitrogen (N) and phosphorus (P) fertilizer; F2, mineral NPK fertilizer; F3, mineral NP fertilizer with straw returning; F4, mineral NPK fertilizer with straw returning in rice–rape cropping system. Straw returning treatments (F3 and F4) significantly (P <0.05) increased MWD and GMD, but the effect of K is not obvious. The soil aggregates stability was higher after the rape harvest than rice harvest, but SOC content was the opposite. Straw input can increase the contents of SOC, alkane-C and aromatic-C concentrations, especially in >0.25 mm aggregates. Long-term straw incorporation significantly increased the amorphous (Feo) and complex iron oxides (Fep) concentrations. SOC and Fep in bulk soil and >5 mm aggregates were significantly related with MWD, and significant relationship was observed between MWD and Feo in <5 mm fractions. Thus, the high levels of SOC, alkane-C, Feo and Fep in soil after straw returning were responsible for the aggregate stability, but the effect of potassium application is not obvious in a rice–rape cropping system.

The combination of plastic film mulching and subsurface organic amendment is a novel strategy for saline soil amelioration and utilization in China. However, how the strategy affect soil organic carbon (SOC) contents directly and indirectly (physical protection and microbiological regulation) were still not-documented. Therefore, four treatments, i.e., no amendment with and without plastic film mulching, subsurface (10-30 cm soil depth) organic amendment with and without plastic film mulching, were arranged and sampled after three-year filed experiment. Compared with no amendment with and without plastic film mulching, subsurface organic amendment increased the SOC content in the 0-40 cm soil depth by 70% and 90%, respectively. Plastic film mulching decreased SOC by 16% without organic amendment. Subsurface organic amendment transformed the dominant aggregation particles from <0.053 mm to 0.25-2 mm, indicating that both direct carbon input and indirect physical protection contributed to SOC increment. Conversely, SOC decreased with plastic film mulching due to the 14% lower fungal diversity compared with soil without plastic film mulching, was supported by the positive path coefficient from fungal diversity to SOC. Therefore, the combination of plastic film mulching and subsurface organic amendment increased SOC by 61% by direct carbon input and indirect physical protection and microbial regulation. In conclusion, subsurface organic amendment with plastic film mulching reinforced soil organic carbon increment through altering saline soil aggregate structure and regulating fungal community, and confirmed it is a feasible way to increase SOC for saline soil amelioration.

We explored the relative importance of climate oscillations and human-driven disturbances on the change of vegetation biomass in agroecosystems, and whether it is associated with land use. The study was carried out in the drylands of the Iberian Peninsula, NW Maghreb, Palestinian West Bank, Mozambique, China and NE Brazil, using satellite time-series and the corresponding climate fields, at ten-year observation periods with spatial and temporal resolutions of 1000 m (250 m in Palestine) and one year, respectively. For each region, we separated the relative weights of climate and time by fitting multiple-stepwise regressions to a vegetation index as the dependent variable, and annual aridity (Aridity) and year number (Time) as predictors. The relative strength of the resulting standard partial regression coefficients was then compared by the Wilcoxon Signed Ranks test, and their combined associations with land uses were determined using chi-square tests. Some points of convergence are: 1. The relative weights of Aridity and Time depend on particular regional conditions and can be determined. 2. Such weights are associated with land use intensification, such that if vegetation increases over Time, Aridity increases its relative importance with intensification; if vegetation is degrading, Aridity is always more important than Time. 3. Aridity is an indicator of vulnerability to climate warming. Resilience can be improved by reducing land use intensification. 4. Vulnerability may worsen under constant climate if agriculture is intensified. These patterns enhance an integrated understanding of Sustainable Development Goals Indicator 15.3.1, particularly its land cover and productivity trend components.

Mapping the SOC distributions in coastal wetlands plays an important role in assessing ecosystem services, predicting the greenhouse effects and investigating global carbon cycle. Few research has explored the relationships of SOC and environmental variables with seasonal changes, and the effects of multi-temporal environmental variables on Digital Soil Mapping (DSM). The results showed that the relationships between SOC and environmental variables in different months varied significantly in coastal wetlands of the Yellow River Delta (YRD). In general, the environmental variables in wet season showed stronger correlations and higher importance scores with SOC compared with those in dry season. In addition, SOC prediction models based on multi-temporal data in wet season and mono-temporal data in April had stronger prediction performance compared with those based on multi-temporal data in dry season. As a result, data fusion of multi-temporal data did not necessarily contribute to the model performance enhancement. Relative homogenous soil-landscape attributes and spectral characteristics in coastal wetlands of the YRD in dry season could not accurately explain the strong spatial variation of SOC in this area, and it might be the major reason that caused the stronger model performance of soil prediction models based on wet season than those based on dry season. Therefore, the accurate spatial prediction of soil properties requires the characterization of the seasonal dynamics of soil-landscape relationships. In general, the findings of this research demonstrated that the selection of the environmental variables in the establishment of DSM model should consider the seasonal effects of environmental variables.

The problem of farmland degradation and air pollution caused by wind erosion and particulate matter emissions is serious. Relying on biological soil crust coverage can effectively inhibit the production of wind erosion materials. However, recent studies have discussed the wind erosion and particulate matter emission processes separately and few studies analyzed both, clarifying the changes in the proportion of particulate matter emissions in the total wind erosion. Aiming at the typical farming-pastoral transition zone in the monsoon climate zone, this study used wind tunnels to analyze the wind erosion and particulate matter emissions of algae crusts and moss crusts for different wind speeds and coverage conditions. Results show that the effects of wind speed and coverage on the total wind erosion of biological soil crusts are similar. However, the emission of particulate matter is particularly sensitive to coverage of biological soil crusts. The proportion of particulate matter emissions in wind erosion decreases with increasing wind speed. According to the trend of the proportion with wind speed, the particle emission capacity of moss crust is directly proportional to the particle size and inversely proportional to the coverage. In contrast, the particle emission capacity of algae crust particles is proportional to the particle size, but the relationship with coverage is not regular. The results of this study can improve the knowledge of the relationship between wind erosion and particulate matter emissions and give relevant information for the management of wind erosion and particulate matter emissions.

Numerous studies have investigated bacterial community structure in grassland ecosystems and bacterial community responses to human management at various spatial and temporal scales; however, research on soil bacterial community assembly dynamics in the course of grassland degradation is limited. Here, the authors investigate the response and assembly processes of bacterial communities adopted in two grasslands with different degrees of degradation. Stochastic processes dominated bacterial community assembly processes in response to grassland degradation, with the bacterial diversity decreasing; however, functional gene diversity increased. Furthermore, different phyla exhibited distinct response strategies: Proteobacteria and Bacteroidetes, as r-strategists, exhibited positive responses, with increases in diversity, abundance, and niche width with an increase in grassland degradation, enhancing biodiversity and productivity; other phyla (mainly Acidobacteria) exhibited greater phylogenetic dispersion and functional redundancy, and less niche overlap, highlighting the role of K-strategy in improving community resource-use efficiency in response to resource loss in degraded grasslands. The transition from K- to r- strategy in bacterial communities following grassland degradation could help communities adapt to environmental disturbance in the form of nutrient loss. The results of the present study enhance our understanding of how nutrient loss in natural grassland ecosystems leads to shifts in bacterial community composition and assembly processes mediated by different response strategies of different phyla.

Soil oil-pollution is one of the most severe environmental issues at present. Shifts of soil metallome and microbiome are essential indicators for risk assessment and remediation of field soil pollutions, but not well studied undergoing the petroleum contamination. In this research, soil samples were collected from a short-term and long-term petroleum-contaminated oil field. The soil physicochemical properties, metallome, microbial community, and polluted and unpolluted soil network were testified. Results showed that the contents of soil total petroleum hydrocarbon, total carbon, total nitrogen, total sulfur, total phosphorus, calcium, copper, manganese, lead, and zinc were increased by petroleum contamination. In contrast, the soil pH was decreased by petroleum contamination regardless of the pollution duration. Petroleum-contamination also reduced bacterial and fungal α-diversity indices. In contrast, bacterial α-diversity was negatively correlated with soil TPH and EC, and fungal α-diversity was negatively correlated with soil EC. Moreover, the relative abundances of Proteobacteria, Ascomycota, Oleibacter, and Fusarium in soil were increased by petroleum contamination. Network analysis showed that number of links, modules and the network invulnerability decreased in PS, followed by the OS group. These results demonstrate that short-term heavy petroleum contamination can cause shifts in soil physicochemical properties, metallome, and microbiome and assemble a less complex and vulnerable soil microbial network. Moreover, natural restoration can hardly amend soil properties and microbial network structure. This research emphasizes that the uncommonly studied soil metallome may play a vital part in the reaction of soil microbial communities to petroleum-contamination and potential application value of synthetic community in bioremediation.

Global climate change is expected to increase the frequency of drought and heavy precipitation, which could create more frequent drying-rewetting cycles (DWC) in the soils. Although DWC effects on SOC decomposition has been widely studied, the effect of DWC and the subsequent legacy effect on the decomposition of different SOC pools is still unclear. We conducted a 128-d laboratory incubation to investigate the DWC effects by using soils from old-field for 15 years (OF, representing active SOC), bare-fallow for 15 years (BF), and bare-fallow for 23 years plus extra 815-d incubation (BF+, representing relatively resistant SOC). The experiment included nine 10-d DWC of three treatments: 1) constant-moisture at 60% WHC, 2) mild DWC with 10-d drying to 40% WHC and rewetting to 80% WHC, and 3) strong DWC with 10-d drying to 20% WHC and rewetting to 100% WHC. Following DWC period, there was a 10-d stabilization period (adjusting all treatments to 60% WHC), and then a 28-d extended incubation. During DWC period, the strong DWC had strong effect on CO2 release compared with the constant-moisture control, reducing the SOC decomposition from OF by 8% and BF by 10%, while increasing the SOC decomposition of BF+ by 16%. During extended period, both mild and strong DWC significantly increased SOC mineralization of OF, but decreased that of BF and BF+. This legacy effect compensated the changes in CO2 release during DWC period, resulting in the minor response of SOC decomposition of OF and BF+ to the DWC during the entire incubation.

Agroforestry systems provide soil microorganisms with a rich variety of carbon sources and a relatively stable living environment. In this study, five planting systems were investigated; a pure poplar (Populus × euramericana ‘Nanlin 895’) plantation (P) system, a pure crop (wheat [Triticum aestivum L.] and soybean [Glycine max (Linn.) Merr.]) (WS) system, a poplar + wheat + soybean agroforestry (PWS) system, a poplar + potherb mustard (Brassica juncea var. multiceps) agroforestry (PP) system, and a poplar + native chicken agroforestry (PN) system. The Biolog EcoPlate method was used to determine the vertical and seasonal variations in soil microbial metabolic capacity. The average well color development, carbon source utilization ability, and microbial diversity index values were higher throughout the soil profile, and highly stable with seasonal changes in the PWS and PP agroforestry systems. Furthermore, the influence of the planting systems and seasonal changes on the metabolic activity of soil microorganisms decreased with an increase in soil depth. Overbreeding chickens in the forest reduced the metabolic activity of soil microorganisms. It was also found that plants influenced soil microbial metabolism through the available carbon source types. Therefore, agroforestry systems improved the metabolic potential of the soil microbial community. Our results demonstrated that soil microbial communities are affected by the planting system and soil depth. The findings enhance our understanding of the functional diversity of soil microorganisms in agroforestry systems.

This study explored the application of a Vertical Electrokinetic system (V-EK) with multilayer electrodes in shallow soil to form an “Electric Sieve” to mitigate and prevent the soil salinization caused by salts rising from shallow groundwater in the coastal areas. In the model V-EK system, the electric resistances of soil column, reversely corresponding to salinity, at the applied voltages 4, 10 and 20 V were 266, 487 and 1272 Ω, respectively. Meanwhile, lower electrical conductivity (EC, between 67-230 μs/cm) were observed in the soil within 50 cm below the surface at the voltages of 10 V and 20 V, which was much lower than the minimum value (581 μs/cm) of the control with no current applied. For the control column without EK treatment (0 V), soil in the surface layer had the highest EC value at 1721 μS/cm due to the salts rising from the bottom, and the EC values of soil beneath the surface were in the range of 581-1127 μS/cm. Compared to control column, the level of ions in the surface soil significantly declined after V-EK treatment, especially for the column with voltage at 10 V and 20V. When voltage was at 20 V, Na+ was detected at a range of 0.06-0.08mg/g in the surface soil, a >99% reduction when compared to the controls. Similar efficacy was observed for chloride (Cl-), in the V-EK column with the voltages at 10 V and 20V.

The aim of this paper was to compare the prediction performance of three strategies: general global Partial least squares regression (PLSR) using CSSL with and without spiking samples, memory-based learning (MBL) using CSSL with and without spiking samples and general PLSR using only spiking samples to predict soil organic matter in the target area. When using spiked subsets, we also investigated the prediction performance of the extra-weighted subsets. A series of spiking subsets randomly selected from the total spiking samples were selected by conditioned Latin hypercube sampling (cLHS) from the target sites. We calculated the mean squared Euclidean distance (msd) of different spiking subsets with the distribution density function of their vis–NIR spectra only and statistically inferred the optimal sampling set size to be 30. Our study showed that when the number of spiking were lower than 30, the predicted accuracy derived from global PLSR using CSSL spiked with and without extra-weighted samples was greater than the predicted accuracy derived from the general PLSR using the corresponding number of spiking samples only (RMSE 5.57–5.98 v.s. RMSE 6.76). Global PLSR using CSSL spiked with the statistically optimal local samples can achieve higher predicted performance (with a mean RMSE of 5.75). MBL spiked with five extra-weighted optimal spiking samples achieved the best accuracy with an RMSE of 3.98, an R2 of 0.70, a bias of 0.04 and an LCCC of 0.81. The msd is a simple and effective method to determine an adequate spiking size using only vis–NIR data.

To determine the mechanisms underlying the response of microbial interactions to vegetation restoration under different climate conditions, we examined the changes occurring at two temperature levels in soil bacterial, fungal, and protist microbiomes under a reference cropland and a plantation forest and a shrubland. Bacterial and protist diversity levels in the high-temperature region of Guangxi (20.9 °C) were higher in cropland than in shrubland or plantation forest. By contrast, fungal richness was lower under cropland than shrubland. The bacterial phyla Cyanobacteria, Gemmatimonadetes, and Nitrospirae, the fungal taxa Ascomycota and Mucoromycota, and the protist groups Ciliophora, Lobosa, and Ochrophyta had lower abundance under vegetation restoration than cropland. There were no significant differences between shrubland and plantation forest in terms of bacterial, fungal, or protist diversity or community composition. A co-occurrence network revealed higher numbers of correlated links among bacterial, fungal, and protist taxa in the low-temperature region of Guizhou (14.6 °C) than Guangxi. Stronger interactions were observed among microbial taxa under cropland than under vegetation restoration. Protist groups Cercozoa and Lobosa showed the highest numbers of links with bacterial phyla Acidobacteria and Proteobacteria and with fungal phylum Ascomycota. Hence, a strong food web existed among these microbiomes. Proteobacteria, Acidobacteria, Ascomycota, and Cercozoa were correlated with soil nutrient levels. Therefore, these dominant taxa determined nutrient availability. The predation of bacteria and fungi by protists was more intense at low temperature than high temperature. Key bacterial, fungal, and protist groups, their co-occurrence networks, and environmental temperature influence soil nutrient accumulation during vegetation restoration.

Rapidly and effectively assessing environmental degradation is essential for promoting regional sustainable development in the transnational area of Changbai Mountain (TACM). However, comprehensively understanding environmental degradation in the TACM is still inadequate. In this study, we developed an environmental degradation index (EDI) by using multiple remote sensing data, including enhanced vegetation index (EVI), gross primary productivity (GPP), land surface temperature (LST), and MODIS surface reflectance products. We then evaluated its performance comparing with the remote sensing ecological index (RSEI), and assessed the environmental degradation across the whole TACM, in the subregions of China, the Democratic People’s Republic of Korea (DPRK), and Russia during 2000-2019. The results indicated that the EDI had the advantages of simplicity and rapidity, which can assess the environmental degradation in the TACM across long-time scales and large spatial extent. The TACM experienced a downward trend of environmental changes from 2000 to 2019. Degraded environment areas (49,329.50 km2) accounted for 30.09% of the entire TACM. The largest area of the degraded environment was on the DPRK’s side (i.e., 25,395.00 km2), which was 5.6 times larger than that on the Russian side and 1.3 times larger than that on the Chinese side. Hotspot areas that experienced significant environmental degradation just covered 17.69% of the land area of the TACM, the area of environmental degradation in them accounted for 33.89% of the total degraded environment across the whole TACM. We suggest that international cooperation policies and measures ought to be enacted to promote regional sustainable development.

In the Sahel, exacerbated soils degradation is an ecological indicator of ecosystem vulnerability. This study examines the effects of restoration of degraded lands on soils physicochemical properties and adaptability of planted woody species over a period of 4-6 years. It is based on: 1) Physicochemical analyses of soils (granulometry, calcimetry, and organic matter) carried out on 102 samples taken in the upper 10 centimeters of the soil profile of the rehabilitated and control sites, 2) measures carried out for the dimensioning of anti-erosion structures, 3) dendrometric measurements on woody species planting in 20 plots each with a rectangular shape 60 m × 30 m as well as characterization of the structure of their root systems. Physicochemical analyses show an improvement in soil quality and structure thanks to the erosion control measures. The degradation of anti-erosion structures, inferred from the rate of siltation of micro-basins, the subsidence of the bulges, the formation, and extension of the breaches, is strongly influenced by the topography, precipitation, and sandy texture of the soils. The restoration activities have led to the reconstitution of vegetation cover on degraded soils. Based on dendrometric characteristics, height class structure, and root systems architecture, significant differences were observed between woody species planted in anti-erosive structures. Eucalyptus camaldulensis groups of with a tracer root system and high density, have the highest structural parameters resulting from the adaptation of this species on Sahelian degraded lands.

Root exudates can greatly modify microbial activity and soil organic matter (SOM) mineralization. However, the mechanism of root exudation and its stoichiometric ratio of C/N controlling upon paddy soil C mineralization are poorly understand. In this study, we used a mixture of glucose, oxalic acid, and alanine as root exudate mimics, employing three C/N stoichiometric ratios (CN6, CN10, and CN80) to explore the underlying mechanisms involved in C mineralization. The input of root exudates enhanced CO2 emission by 1.8–2.3-fold than that of the control. Artificial root exudates with low C/N ratios (CN6 and CN10) increased the metabolic quotient (qCO2) by 12% over those obtained at higher stoichiometric ratios (CN80 and C-only), suggesting a relatively high energy demand for microorganisms to acquire organic N from SOM by increasing N-hydrolase production. The stoichiometric ratios of enzymes (β-1,4-glucosidase to β-1,4-N-acetyl glucosaminidase) promoting organic C degradation compared to those involved in organic N degradation showed a significant positive correlation with qCO2; the stoichiometric ratios of microbial biomass (MBC/MBN) were positively correlated with carbon use efficiency. This suggests that root exudates with higher C/N ratios entail an undersupply of N for microorganisms, triggering the release of N-degrading extracellular enzymes. This in turn decreases SOM mineralization, implying the C/N ratio of root exudates to be a controlling factor. Our findings show that the C/N stoichiometry of root exudates controls C mineralization by the specific response of the microbial biomass through the release of C- and N-releasing extracellular enzymes to adjust for the microbial C/N ratio.

The complexity and uncertainty of land use and environmental factors pose challenges to the management decisions of ecological restoration and conservation.We integrated the mixed-cell CA model and Bayesian belief networks to develop an innovative method for optimizing ecosystem services under different land development scenarios, including consideration of the uncertainty and variability of factors.The southern region of Sichuan Province, China, was selected as an example.We first established three development scenarios between 2015 and 2035, namely, natural development scenario (NDS), ecological protection scenario (EPS), and cultivated land protection scenario (CLPS).The MCCA model was utilized to simulate the land use pattern in 2035 under different scenarios.We then construced a BBN-based model to investigate the carbon sequestration, grain supply, soil conservation, habitat quality, and water yield in 2035 under uncertain scenarios.After the sensitivity analysis and evaluation of the model, we determined the state combination of influential factors at various ecosystem service levels and the ecological restoration and conservation key areas.The obtained result showed that the key influencing factors impacting the ecosystem services level included NPP, Slope, forestland and ET, and the state combination corresponding to the highest level of ecosystem services was predominantly distributed in regions with the highest NPP, the highest Slope, the highest forestland area and low ET.Based on this finding, we proposed some suggestions for ecological restoration and conservation of key areas.This model considers uncertainties and is capable of providing scientific recommendations on restoration and conservation; therefore, it can serve as an effective tool to assist stakeholders in making decisions.

Underground coal mining will inevitably cause land ponding in high groundwater table, which will affect the land sustainable development. However, the traditional reclamation (TR) is poor in land rate. Thus, finding a suitable reclamation approach is crucial to alleviate the conflicts between coal exploitation and land protection. In this paper, taking Guqiao Coal Mine of China was seriously affected by mining-induced ponding as an example. Firstly, dynamic distribution of surface subsidence and land damage from 2007 to 2017 was revealed base on concurrent mining and reclamation (CMR). Second, the land-water layout of five reclamation schemes (no reclamation, TR, CMR I, CMR II and CMR III) were simulated. Then, and the dynamic filling elevation model and filling thickness model were constructed. Finally, the sequence of earthwork allocation was optimized. The results revealed that: 1) reclaimed land area: CMR III > CMR II > CMR I > TR > no reclamation; 2) The digging depth is directly proportional to earthwork volume and land area, and inversely proportional to water area, but with increase of digging depth, the increase in the reclaimed land area relatively slowed down; 3) CMRs had reclaimed 426.31~637.82 ha and 259.62~471.13 ha more than the no reclamation and TR respectively. Compared with the no reclamation and TR, CMRs can increase the proportion of reclaimed land by 33.77~50.52% and 20.57~37.32% respectively. The research results provide a reference to increase the reclamation rate of mining areas in the high phreatic table.

Vegetation plays important roles in the development and protection of permafrost; it is one of the main local and ecosystemic factors that affect the thermal stability of the underlying soil strata. Multi-period land use and cover change (LUCC) data and long-time series of air temperature were chosed. Based on these data, spatiotemporal changes in mean annual air temperature (MAAT) were simulated by the Ordinary Least Squares (OLS) method and Ordinary Kriging (OK) model in the 1980s-2010s in Northeast China. The influences of LUCC on MAAT in Northeast China and distribution of the Xing’an permafrost were analyzed and the results showed that: (1) Decadal average of MAAT increased from 4.60oC (1980s) to 5.38oC (2010s) in Northeast China, with an upward trend of 0.25oC/10a. (2) During the 1980s to 2010s, the total permafrost area showed a decreasing trend (3.668×104 km2/10a). (3) In permafrost regions, LUCC had undergone significant structural changes: forested land showed a consistent decreasing trend and other lands showed an overall increasing trend. (4) The effects of different LUCC on MAAT in the permafrost region varied substantially. The mean MAAT of forested land was the lowest (2.33oC), and; that of unused land, the highest (0.37oC). The change rate in MAAT of cultivated land was the highest (0.37oC/10a), and; that of unused land, the lowest (0.28oC/10a). (5) The degradation rates of permafrost in forested land (1.822×104 km2/10a) and grassland (1.397×104 km2/10a) were the largest from 1980s to 2010s.