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.
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.
Reclamation has been widely accepted to restore abandoned lands. Most studies focused on the improvement of land reclamation in soil nutrients and microbial activities. However, the effects of reclamation time on bacterial communities of abandoned salt pans are still unclear. The object of this study is to: i) assess the successional change of soil physicochemical properties and bacterial communities in reclaimed abandoned salt pans with different reclamation histories, and ii) figure out the main limit factors on the improvement of soil quality in reclaimed abandoned salt pans. The soils in a farmland (RTBL) and six abandoned salt pans with 1 year (RT1), 2 years (RT2), 3 years (RT3), 4 years (RT4), 8 years (RT8), and 9 years (RT9) of reclamation were sampled to investigate the temporal variation of soil properties, heavy metal content, bacterial community composition, and diversity. Results showed that the soil bulk density (BD), total dissolved salt (SS), median particle size (MMAD) decreased with the increase of reclamation time, while soil nutrient (soil organic matter, total nitrogen, available phosphorus, available potassium) showed an opposite trend. The bacterial α-diversity increased first, then decrease. Land reclamation enhanced the relative abundances of Acidobacteria, Chloroflexi, and Actinobacteria but reduced the relative abundances of Proteobacteria, Gemmatimonadetes, and Bacteroidetes. Compared with RTBL, the soil nutrients and bacterial community structure in RT1, RT2, RT3, and RT4 showed a significant difference.Therefore, reclamation time is a vital driving force for restoring soil physicochemical properties and bacterial communities in abandoned
In this research, enrichment factor (EF) and pollution load index (PLI) were utilized to estimate the features of enrichment and contamination of PTEs in farmland soil. Furthermore, combining the spatial distribution characteristics of potentially toxic elements (PTEs) and positive matrix factorization (PMF) to distinguish and quantify the sources of PTEs in farmland soil, and then the potential ecological risk (PER) and human health risk (HHR) model based on PMF are applied to quantify the ecological and human health risks from different sources. Taking Puning District as an example, four sources of PTEs in farmland soil were quantitatively allocated. For ecological risk, the study area is at moderate ecological hazard level, and industrial activities were the greatest contributor. The mean E_r^i of Hg were 69.82, reaching medium ecological risk level. For human health risks, both adults and children have no evident non-carcinogenic risk in the study area. And natural source was the largest contributor to non-carcinogenic risk, followed by agricultural activities. With regard to carcinogenic risk, tolerable risks of soil PTEs in the study area were limited not only for adults but also for children. Furthermore, compared with adults, the health risks of children, whether non-carcinogenic or carcinogenic, were higher than those of adults, and the trends in health risks for children and adults were similar. A comprehensive scheme combining source contribution and risk assessment is conducive to quantitatively assess ecological risks, health risks and priority pollution sources, thereupon provide effective suggestions for protecting human health and preventing and controlling pollution.
Diversity-stability relationships in grasslands depend on the environment. Climate change and soil degradation potentially alter soil pH and community stability within grassland environments, although it remains unclear how soil acidity and alkalinity affect diversity-stability relationships. We conducted a three-year experiment of acidification and alkalization treatments in an arid grassland in northern China, and found that increasing and decreasing soil pH reduced community species richness, community diversity, community and dominant species asynchrony, and biomass stability. Soil acidification reduced community stability by reducing dominant species stability. Soil alkalization reduced community stability by reducing species asynchrony and dominant species stability. Acidification significantly enhanced the availabilities of soil NO3—N, P, and K, but did not affect the concentrations of soil total C, N, and P. By contrast, alkalization significantly reduced soil total C and N, but did not affect the availabilities of soil N, P, and K. Structural equation model analysis revealed that altered soil pH affected soil nutrients associated with species asynchrony and community stability, which indicated the importance of soil nutrients in driving community stability. Our results suggest that soil pH–mediated community stability is mainly driven by dominant species stability rather than diversity. This study provides novel insights indicating that arid grassland stability would be weakened under changing soil pH, subsequently leading to land degradation and reducing long‐term productivity and sustainability.
Governments and international donors are actively promoting laser-land leveller (LLL) technology to produce environmental benefits (i.e., avoid soil salinity, minimize soil erosion risk, and groundwater security) that could lead to sustainable agricultural production and averting land degradation. We investigate the adoption process of laser-land leveller (LLL) technology in Punjab, Pakistan during the period 1985–2018 using survey data from 504 farming households. A discrete-time duration model is used to investigate factors that could influence the speed of adoption of LLL technology and an endogenous switching regression (ESR) model to evaluate its impact on groundwater usage. It is found that about 70% of the surveyed households had adopted the technology. The key determinants of the speed of adoption include strong legal land entitlements, farm size, and farm location along the watercourse. Information acquired through formal and informal sources and exposure to the technology potentially reduce adoption time. The adoption of LLL reduces groundwater use by about 23% in wheat crop. These results highlight the need for improved institutional arrangements such as extension services, technology exposure, and establishing legal property rights over land to enhance uptake of LLL technology.
Biochar application is currently considered to be an effective soil organic carbon (SOC) management to prevent land degradation by enhancing SOC stock. However, quantitative information on the impact of biochar application on carbon dioxide (CO2) flux and associated microbial responses is still scarce, especially in degraded tropical agroecosystems. Here, we evaluated the impact of land management (control (C), biochar (B; 8.2 Mg C ha−1), farmyard manure (FYM) (M; 1.1 Mg C ha−1 yr−1), and a mixture of both (BM; 8.2 Mg biochar-C ha−1 and 1.1 Mg FYM-C ha−1 yr−1)) on CO2 flux, SOC stock, microbial biomass C (MBC), and metabolic quotient (qCO2) in degraded tropical alkaline cropland of southern India, based on a 27-month field experiment. Cumulative CO2 flux over the experiment was 2.4, 2.7, 4.0, and 3.7 Mg C ha−1 in the C, B, M, and BM treatments, respectively. Biochar application increased soil moisture and SOC stock, though did not affect CO2 flux, MBC, and qCO2, indicating the limited response of microbes to increased soil moisture because of small amount of SOC. Combined application of biochar and FYM did not increase CO2 flux compared with FYM alone, due to little difference of microbial responses between the M and BM treatments. Additionally, SOC increment (8.9 Mg C ha−1) and the rate of C-input retention in soil (0.78) was most significant in the BM treatment. Hence, the combined application of biochar and FYM could be sustainable land management by efficient increase of SOC stock in the tropical degraded cropland.
Understanding the soil and water conservation (SWC) impact of steep-slope agricultural practices (e.g. terraces) has arguably never been more relevant than today, in the face of widespread intensifying rainfall conditions. In northern Italy, a diverse mosaic of terraced and non-terraced cultivation systems have historically developed from local traditions and more recently from the introduction of machinery. Previous studies suggested that each vineyard configuration is characterised by a specific set of soil degradation patterns. However, an extensive analysis of SWC impacts by different vineyard configurations is missing, while this is crucial for providing robust guidelines for future-proof viticulture. Here, we provide a unique extensive comparison of SWC in 50 vineyards, consisting of 10 sites of 5 distinct practices: slope-wise cultivation (SC), contour cultivation (CC), contour terracing (CT), broad-base terracing (BT) and diagonal terracing (DT). A big-data analysis of physical erosion modelling based on high-resolution LiDAR data is performed, while four predefined SWC indicators are systematically analysed and statistically quantified. Regular contour terracing (CT) ranked best across all indicators, reflecting a good combination of flow interception and homogeneous distribution of runoff and sediment under intense rainfall conditions. The least SWC-effective practices (SC, CC, and DT) were related to vineyards optimised for trafficability by access roads or uninterrupted inter-row paths, which create high upstream-downstream connectivity and are thus prone to flow accumulation. The novel large-scale approach of this study offers a robust comparison of SWC impacts under intense rainstorms, which is becoming increasingly relevant for sustainable future management of such landscapes.
Understanding vegetation evaluation is critical for exploring changes in terrestrial ecosystems and identifying upcoming challenges. However, analyses that simultaneously examine abrupt changes in vegetation greenness at the national, regional, biome and pixel scales in China are still rare. Using long-term (1982–2015) satellite time series data in conjunction with the Breaks for Additive Season and Trend (BFAST) technique, we identified breakpoints in the Normalized Difference Vegetation Index (NDVI) in China. Results showed that the annual mean NDVI gradually increased during the 34-year period. 68.8% of the vegetated area exhibited upward trends in NDVI, most of which was distributed in Southeast China and the Loess Plateau. Changes in NDVI trends occurred in 78.7% of the total vegetated areas, while hotspots were concentrated in Northwest and North China. A rapid increase in breakpoints was detected after 1999, mainly concentrated in North and Northwest China, and corresponding to the times and areas with the highest ecological engineering efforts. Positive shifts in NDVI trends were more common and generally distributed on the eastern side of the Hu Huanyong line, while browning (negative) shifts were mainly distributed on the western side and were gradually expanding, indicating a possible tendency towards environmental degradation. Although unstable vegetation areas had higher frequencies of breakpoints, the proportion of stable vegetation experiencing NDVI trend shifts was higher after 2000, probably because human intervention buffered external disturbances in unstable areas. Identifying hotspot areas of shifts in vegetation greenness can provide scientific reference for sustainable land development and carbon neutrality target achievements.