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The 2008 8.0 Ms Wenchuan earthquake caused serious ecological degradation in the northwest of China's Sichuan Province. Elucidating landscape fragmentation and spatial pattern of post-earthquake landscape is of great interest in order to improve ecological restoration and predict the spatial distribution of damaged ecosystems in earthquake-affected areas. We used four real-time remote sensing images to analyze the landscape pattern characteristics and spatial autocorrelation of the Longxi River Basin before and after the Wenchuan earthquake during the period from 2005 to 2015. In the study period, the degree of landscape fragmentation increased 1 year after the earthquake in 2009 but decreased in 2011 and 2015. The spatial distribution of forest, farmland, and shrub-grassland had significantly positive spatial correlation and the characteristics of spatial aggregation from 2005 to 2015. Construction land had no significant spatial correlation before the earthquake in 2005, but significantly positive spatial correlation after the earthquake, while traffic land had no significant spatial correlation across the study period. Unlike the other landscape types, geological disasters changed from a significantly negative spatial correlation before the earthquake to a significantly positive spatial correlation after the earthquake. However, the positive autocorrelation of all landscape types decreased with the increase of space distance, but in different distance-decay rates. The High-high spatial aggregation areas of geological disasters and construction land clustered gradually upstream of the basin and distributed in Longchi town, respectively; those of farmland distributed in the southeast of the basin increased in 2009 but then decreased, while those of forests had the opposite pattern as the dominant landscape type after the earthquake. Our results elucidated the spatial structure and distribution features of the Longxi River Basin to give a theoretical foundation for assessing the effects of ecological restoration and reconstruction management in earthquake-affected areas. [ABSTRACT FROM AUTHOR]

Amidst the swift progression and extensive use of electric vehicles, demands on lithium iron phosphate (LiFePO 4) batteries have surged, leading to an imminent scarcity of raw materials for battery manufacturing. This reality heightens the needs for effective battery recycling. This study outlines an integrated evaluation approach of combining laboratory-scale pilot experiment, Monte Carlo Simulations, and Life Cycle Assessment (LCA). An optimized recycling process for LiFePO 4 batteries was developed, aiming to salvage and retrieve valuable elements. The process involves lithium's selective leaching followed by subsequent lithium (Li) and iron (Fe) recovery, achieving efficient recovery rates for both Li and Fe. A novel evaluation, integrating economic and environmental aspects, was conducted by employing a direct costs/revenues approach, with the inclusion of stochastic uncertainties determined via Monte Carlo Simulation. Two scenarios are applied to the electric vehicles data of Guangzhou in 2022. The recycling strategy of spent lithium-ion batteries (LIBs) within the Greater Bay Area of China (Scenario A) could potentially save 373.2 million US$, and reduce carbon dioxide emissions by 96,850 tons, compared to manufacturing batteries from mined raw materials and long-distance transportation (Scenario B). This demonstrates the importance of localized, efficient industrial automotive chain within the Greater Bay Area, which besides being cost-effective, offers profound environmental benefits. Other important factors for the result are the efficiency of the developed hydrometallurgical process, the price of the sellable material, and the transport distance. Scenario modeling results from the developed integrating evaluation clearly reveal the significant potential of battery recycling, and the innovative integrating approach has the potential for broader applicability beyond the specific context of our study. [Display omitted] • An environmentally and economically process for spent LiFePO 4 batteries recycling was designed. • The recycling process was evaluated by LCA and Monte Carlo simulation based on real-world resource. • Two scenarios are applied to the electric vehicles data of Guangzhou in 2022 and 50,000 MC simulation. • The developed scenarios reveals a highly probability of cost and CO 2 emission reduction. • Results reveal eco-friendly battery recycling is a crucial step in sustainable growth. [ABSTRACT FROM AUTHOR]

Understanding how natural disasters affect soil quality and how it recovers is essential to improve soil management. We studied the effects of the 2010 Nanping landslides (China) on soil quality. We conducted an observational study using three levels of disturbance ('destroyed', 'recovering', and 'undisturbed'). The 'destroyed' areas were sampled immediately after the landslide and the others were sampled 7 years later. To assess the consistency of landslide-induced effects, we sampled these levels of disturbance in three forest types (Cunninghamia lanceolata conifer forest, Phyllostachys heterocycla bamboo forest, and secondary evergreen broadleaf forest). In total, 81 soil samples were collected and analyzed for 26 soil indicators. A minimum data set (MDS) was identified that represented the physical, chemical, and biological properties of the soils. Indicators in the MDS were then weighted and summed together to calculate a soil quality index (SQI) for each category and a total SQI. The landslide strongly affected all aspects of soil quality. After seven years of natural recovery, most aspects of soil quality were significantly improved but remained lower than in 'undisturbed' sites. Recovery was faster for biological than physical or chemical properties. Recovery was slower in bamboo forests than in other forest types, suggesting that human interventions could accelerate post-landslide soil recovery in bamboo forest. Our results provide fundamental data for evaluating impacts of natural disasters on soil and rates of natural recovery. • Landslide strongly affected all aspects of soil quality. • Most aspects of soil were significantly improved but remained low after recovery. • Soil recovery was faster for biological than physical or chemical properties. • Soil recovery was slower in bamboo forests than in other forest types. [ABSTRACT FROM AUTHOR]

Grassland is the significant composition of the terrestrial carbon pool. Its belowground carbon turnover process is sensitive to land use changes and has a huge impact on atmospheric CO 2 contents. However, the interpretation of the vertical distribution of δ13C values of soil organic carbon (SOC-δ13C), the SOC turnover rate (β value) and their changes in the soil profile remain uncertain after fencing (grazing exclusion). Grasslands that have been fenced for 39 years and grazed (as the control) on the Loess Plateau, China were selected to evaluate the vertical distribution of SOC-δ13C and β values and their influencing factors across the 0–100 cm soil profile (0–10, 10–20, 20–40, 40–60, 60–80, 80–100 cm). The results showed that SOC gradually decreased but SOC-δ13C overall increased with soil depths. Fencing significantly decreased the SOC-δ13C in 10–80 cm depth. The SOC-δ13C had a positive correlation with δ13C values of microbial biomass carbon (MBC-δ13C), but negative correlations with root biomass. Besides, the β values of 0–60 cm depth were higher in fencing grasslands (−2.70) than that in grazing grasslands (−11.38). Overall, carbon input, microbial fractionation and soil leaching contributed to the increasing trend of SOC-δ13C with soil depths, and fencing increased the SOC content in the profile but decreased the SOC turnover rate in 0–60 cm soils. The results provide direct evidence for the change of SOC-δ13C and a more comprehensive understanding of SOC-δ13C and SOC turnover dynamics with long-term fencing across the soil profile. The information on SOC dynamics and their feedback to long-term fencing can aid in developing reasonable grassland management measures. • SOC gradually decreased but SOC-δ13C overall increased with soil depths. • Grazing exclusion increased soil C contents but decreased the C turnover rate. • SOC-δ13C was positively correlated with δ13C values of microbial biomass carbon. • SOC-δ13C in grazing grasslands was affected by pH, cPOC, C/N and enzyme activity. • SOC-δ13C in fencing grasslands was affected by C/N. [ABSTRACT FROM AUTHOR]

• The HI = 0.68 is the turning point of soil microbial resource limitation. • The dry area had more microbial C limitation compared with the wet areas. • Soil microorganisms exhibited N limitation in dry area and P limitation in wet area. • The increase of humidity aggravated microbial P limitation above HI > 0.68. • Humidity and soil nutrients determined microbial resource limitations. Soil extracellular enzyme stoichiometry has been used to characterize the acquisition strategies of soil microorganisms in obtaining carbon (C), nitrogen (N) and phosphorus (P). However, the variations in soil microbial resource limitation to changing precipitation regimes and edaphic factors remain poorly understood, particularly for a highly divergent soil organic C gradient along the transect from dry to wet areas. This study investigated soil microbial C and nutrient (P/N) limitations along a 3,000-km humidity gradient. The results revealed a downward unimodal-shaped relationship between the humidity index (HI) and soil microbial P/N limitation with a threshold of HI = 0.68 (corresponding mean annual precipitation ranged from 469 mm to 551 mm). Changes in microbial C limitation, and total- and available soil P contents along the humidity gradient further revealed the presence of this threshold. Soil microbial C limitation remained constant at a humidity level below HI = 0.68, and it increased above this threshold. Microbial P limitation decreased and N limitation increased as humidity increased to HI = 0.68. Above HI = 0.68, the microbial P limitation gradually elevated with an increase in humidity. We also found that humidity and soil nutrients are critical factors explaining the variations in microbial resource limitation, and soil nutrients control microbial resource limitation on either side of the HI = 0.68 threshold. These findings suggest that the acquisition of N and P by soil microorganisms stimulates the decomposition of soil organic matter, and future predictions of ecosystem C budgets should thus consider enzymatic processes. [ABSTRACT FROM AUTHOR]

• Artificial forests had better soil C and N sequestrations than restored grasslands. • Artificial forests and grassland had a similar ability to improve soil aggregates. • N-fixing species played a crucial role in affecting on soil C and N sequestrations. Vegetation restoration is an important factor affecting soil carbon (C) and nitrogen (N) sequestration. However, the effects of the type of vegetation restoration on soil C and N sequestration varies owing to different environmental conditions. Therefore, additional studies should explore the effects of vegetation restoration type on soil C and N sequestration, especially between natural restoration and artificial afforestation. This study explored the differences in improving soil C and N sequestration between artificial forests (AF) and natural grasslands (NG) that had been converted from sloping cropland over 20 years since the implementation of GGP (Grain for Green Program) on the Central Loess Plateau, China. The results showed that NG and AF significantly increased the 0–20 cm soil organic carbon (SOC) content but had a minimal impact on the 20–100 cm SOC content after 20 years of vegetation restoration. In addition, the two vegetation restoration types significantly increased the 0–60 cm soil total nitrogen (STN) content, but they both had no significant effects on the 60–100 cm soil layer. Moreover, the C and N sequestration capacities of AF were higher than those of NG due to the AF had higher plant biomass and lower plant biomass C:N ratios compared to NG. The AF and NG both significantly increased the soil aggregate structure and stability following cropland conversions. Apart from soil aggregates playing a crucial role in affecting soil C and N sequestration, plant biomass and its C:N ratios also had the most substantial effects. The results suggested that soil aggregate stability and the quantity and quality of input organic matter have strongly influenced soil C and N sequestration post-restoration; moreover, N fixing species is more conducive to soil C and N sequestration and the artificial forests had higher C and N sequestration capacities than natural grasslands in the Loess Plateau, with a mean annual precipitation of 505 mm. [ABSTRACT FROM AUTHOR]

Soil degradation is significantly increased driven by soil nutrient loss and soil erodibility, thus, hampering the sustainable development of the ecological environment and agricultural production. Vegetation restoration has been widely adopted to prevent soil degradation given its role in improving soil nutrients and soil erodibility. However, it is unclear which vegetation type has the best improving capacity from soil nutrient and soil erodibility perspectives. This study selected three vegetation restoration types of grasslands (GL), shrublands (SL), and forestlands (FL) along the five slope positions (i.e., top, upper, middle, lower, and foot slope), to investigate the effects of vegetation restoration types on soil nutrients and soil erodibility. All vegetation restoration types were restored for 20 years from croplands (CL). We used comprehensive soil nutrient index (CSNI) and comprehensive soil erodibility index (CSEI) formed by a weighted summation method to reflect the effect of vegetation restoration on the improving capacity of soil nutrient and erodibility. The results showed the vegetation types with the highest comprehensive soil quality index (CSQI) at the top, upper, middle, lower and foot slope were FL (1.92), FL (1.98), SL (2.15), FL (2.37) and GL (3.93), respectively. When only one vegetation type was considered on the entire slope, SL (0.59) and FL (0.59) had the highest CSNI, the SL had the lowest CSEI (0.34) and the highest CSQI (1.89). The CSNI was mainly influenced by soil structure stability index (SSSI), sand content, silt + clay particles, and CSEI was controlled by soil organic matter (SOM), macroaggregates and microaggregates. Moreover, the CSQI was influenced by pH, silt and clay content, and biome coverage (BC). The study suggested the SL were advised as the best vegetation restoration type on the whole slope from improving soil nutrients and soil erodibility., (Copyright © 2021 Elsevier Ltd. All rights reserved.)