Vegetation Traits and Litter Properties Play a Vital Role in Enhancing Soil Quality in Revegetated Sandy Land Ecosystems

Differential responses of soil quality in revegetation types to precipitation gradients on the Loess Plateau

Improvements in soil quality with vegetation succession in subtropical China karst

The effects of biochars produced from the residues of locally grown crops on soil quality variables and indexes

Deciphering spatial variability and dominant controls of soil quality under four types of grassland along a southeast-northwest transect in Tibet, southwestern China

Information about the soil quality of different land-use types and topographies is essential for the sustainable development, utilization, and protection of soil resource in coastal areas. In this study, representative topsoil samples were collected from Liandao Island, China, and soil water content (SWC), soil bulk density (BD), total nitrogen (TN), soil organic matter (SOM), ammonium nitrogen (NH4+-N), nitrate nitrogen (NO3--N), available phosphorus (AP), available potassium (AK), soil salt content (SSC), and pH were recorded. The suitable minimum soil data set (MDS) was computed by principal component analysis (PCA) and the soil quality index (SQI) was then determined. The spatial distribution of the SQI was analyzed using ordinary kriging interpolation. The effects of topographical parameters (digital elevation model [DEM], slope, and aspect) and land-use types (vegetation [V], water resource conservancy land [WRC], sandy land [SL], unused land [UL], and built-up land [BL]) on SQI were then analyzed in detail. The parameters included in the MDS were TN, pH, and BD, which together accounted for 84.371% of the variation in soil quality. The SQI varied from 0.189 to 0.772 in the study area. The correlation coefficients between SQI and DEM, slope, and aspect were 0.498, 0.294, and 0.137, respectively (p < 0.01). The highest SQI score was found at an elevation of 110m, with a slope of 68.2° and an aspect of 246.6, in the vegetation land-use type. Soil quality differed significantly (p = 0.0000) among the land-use types, with the following ranking: V > UL > SL > BL. Our results provide land managers with an important reference for the development, utilization, and protection of soil resource in coastal zones such as Liandao Island, China.

Different vegetation restoration methods have improved soil quality to varying degrees. This study, focused on the forest–grassland–desert transition zone in the Hebei–Inner Mongolia border region, and employed a systematic grid sampling method to establish fixed monitoring plots in the Saihanba Mechanized Forest Farm and the Ulan Buh Grassland. The differences in soil quality evolution across various vegetation restoration methods under the same climatic and soil historical conditions were analyzed, elucidating the roles of these vegetation restoration methods in degraded forest ecosystems, with the aim of providing a reference for ecological restoration under similar land conditions. This study used a grid method to establish sample points in the forest–grassland–desert transitional zone and assessed five methods of vegetation restoration sites: artificial forest composed of native species of Larix principis-rupprechtii (FL), artificial forest composed of exotic Pinus sylvestris var. mongolica (FP), natural secondary broad-leaved forest (FN), open grassland (GO), and enclosed grassland (GC). The differences in soil organic carbon (SOC), total nitrogen (TN), total phosphorus (TP), total potassium (TK), alkaline hydrolysis nitrogen (AN), rapidly available phosphorus (AP) and rapidly available potassium (AK) among the different vegetation restoration sites were compared via variance analysis, and the soil quality index (SQI) was calculated to assess the soil quality at the sample points. The SOC, TN, and AN contents of forest soil were significantly greater than those of grassland, and the TN, TP, AN, AK, and SOC contents of FL, FN, and GC were significantly greater than those of FP and GO. Among them, the TN, TP, and SOC contents were the highest in the FL, reaching 2.74, 0.39, and 47.27 g kg−1, respectively. In terms of ecological stoichiometric characteristics, the average N:P ratio in the study area was 6.68, indicating a serious lack of N in the study area. Among the different types of restoration sites, the effect was stronger in the FP than in the FL, and the TN and AN contents were only 1.48 g kg−1 and 116.69 mg kg−1, respectively. The SQI in the FL was not significantly different from that in the FN or GC, but it was significantly greater than that in the FP and GO. These findings indicate that native tree species restoration in degraded forest ecosystems significantly improved soil quality, while the introduction of exotic tree species for afforestation had a minimal effect on improving soil quality.

Effects of vegetation restoration on soil quality in degraded karst landscapes of southwest China

Mixed planting mode is the best measure to restore soil quality in alpine mines

Superior improvement on soil quality by Pennisetum sinese vegetation restoration in the dry-hot valley region, SW China

Climate warming and thawing of permafrost in the Qinghai-Tibet Plateau have resulted in soil erosion and the decline of soil quality. Determining the decadal variation of soil quality in the Qinghai-Tibet Plateau is the basis for scientific understanding of soil resources and the key to vegetation restoration and ecological reconstruction. In this study, we used eight indicators (including soil organic matter, total nitrogen, and total phosphorus) to eva-luate soil quality of montane coniferous forest zone (Tibet's natural geographical division zone Ⅱ) and montane shrubby steppe zone (zone Ⅳ) by calculating soil quality index (SQI) in the southern Qinghai-Tibet Plateau in the 1980s and 2020s. Variation partitioning (VPA) was used to examine the drivers for the heterogeneity of the spatial-temporal distribution of soil quality. The results showed that soil quality in each natural zone showed a downward trend in the past 40 years, with SQI of zone Ⅱ decreasing from 0.505 to 0.484 and that of zone Ⅳ decreasing from 0.458 to 0.425. The spatial distribution of soil nutrients and quality was heterogeneous, while soil nutrient conditions and quality in zone Ⅱ were better than those in zone Ⅳ in different periods. The VPA results indicated that the interaction of climate change, land degradation, and vegetation differences was the major cause of temporal variation in soil quality. Differences in climate and vegetation could better explain the spatial variation of SQI.

Spatiotemporal variations in the soil quality of agricultural land and its drivers in China from 1980 to 2018

Soil quality is defined as the ability of soil to function as an essential living system within land-use boundaries. The quantification of soil quality under agricultural systems to estimate the impact of management intensity on soil productivity is crucial for the timely identification of adverse effects of management practices. Farmers’ experience and indigenous knowledge provide a simple method of characterizing the status and detecting any variations in soil quality. The precise evaluation of soil quality requires the selection and interpretation of soil indicators associated with soil functions, which cannot be measured directly. A valid SQI assists in the interpretation of data from varied soil measurements and reveals whether management or land-use are having desired outcomes for productivity and environmental protection. The review will examine the concept of soil quality, associated computation, and assessments, and lastly the impact of management practices on the soil quality with an overall purpose of recognizing the practices that improve soil quality.

Scientific and reasonable vegetation restoration plays a pivotal role in enhancing soil quality, boosting ecosystem services, and ensuring the long-term stable operation of photovoltaic (PV) power stations in desert regions. To elucidate the response mechanisms of soil under different vegetation restoration implemented in PV power stations located in sandy areas, this study selected the PV power plant in Duguitala Township of the Hobq Desert as a representative research site. A systematic evaluation was conducted on the effects of four artificial vegetation restoration strategies, namely, Leymus chinensis (LC), Glycyrrhiza uralensis (GU), Artemisia ordosica (AO), and Hedysarum scoparium (HS) under panels and between panels. This analysis aimed to clarify the influence of different vegetation restoration approaches on soil quality in sandy regions and their underlying mechanisms. The findings revealed that these vegetation restoration measures significantly impacted soil texture, bulk density (BD), soil porosity (SP), soil water content, and water retention capacity. Specifically, LC and GU markedly improved soil physical structure and water retention capacities. Vegetation restoration substantially enhanced soil nutrient accumulation, with LC achieving the highest levels of multiple soil nutrient indices (total nitrogen (TN), total phosphorus (TP), and available potassium (AK)), HS exhibiting the highest level of available phosphorus (AP), and GU demonstrating superiority in total potassium (TK). These diverse vegetation restoration strategies exhibited potential advantages in improving soil fertility and promoting nutrient cycling at locations under PV panels. The soil quality index (SQI) showed that the effectiveness of the different vegetation measures in enhancing soil quality was ranked GU>LC>HS>AO>CK. This study not only provides robust theoretical support for ecological restoration in desert PV plants, but also offers practical experience applicable to vegetation restoration efforts in similar ecological environments, thereby possessing significant ecological and practical value.

IntroductionEvaluating soil quality is essential for guiding reforestation and land management strategies, particularly in degraded Chinese fir plantations where long-term productivity and successional dynamics remain poorly understood.MethodsThis study assessed ten mixed-species planting patterns to quantify the Soil Quality Index (SQI) using a Minimum Data Set (MDS) approach, which reduces data redundancy by statistically identifying key indicators from a larger dataset, thereby effectively capturing essential soil functions, and subsequently explored the relationships between SQI and stand growth, structural diversity, biomass, net primary productivity (NPP), as well as percentage of broadleaf species (PBS).ResultsSignificant differences were observed across planting patterns in diameter at breast height (DBH), tree height (TH), stand biomass (FB), structural diversity (variation in DBH [CVD] and Gini coefficient [GiniD]), and PBS. Soil properties—including physical (soil moisture), chemical (soil organic carbon [SOC], total nitrogen [TN], total phosphorus [TP], ammonium nitrogen [NH₄⁺], nitrate nitrogen [NO₃⁻], available phosphorus [AP]), microbial (microbial biomass carbon [MBC], nitrogen [MBN], and phosphorus [MBP]), and enzymatic (e.g., peroxidase [POD], alkaline phosphatase [ALP], urease [URE])—also varied significantly. SQI values ranged from 0.42 to 0.65, with patterns Fir–Mytilaria laosensis mixed (ML), Fir–Castanopsis hystrix mixed (CH), Fir–Michelia chapensis mixed (MC), and Fir–Schima superba mixed (SS) associated with both high SQI and greater biomass. Sensitivity analysis identified Fir–Cinnamomum porrectum mixed (CP), ML, and SS as particularly responsive to hybridization. Among soil factors, URE, AP, and MBC were key drivers of productivity, while URE, AP, MBC, and POD significantly predicted the proportion of broadleaf trees. Enhanced soil quality was positively associated with increases in DBH, TH, and PBS, accelerating the successional transition from fir-dominated to broadleaf-dominated stands. However, SQI was not significantly correlated with structural diversity metrics.DiscussionThese results underscore the importance of rational species selection in restoring degraded fir plantations and demonstrate that improving soil quality is a critical mechanism promoting near-natural forest succession.

Intensive agriculture is the chief cause of soil degradation, particularly in regions with low soil organic carbon status, such as semi-arid southern India. In the quest to attain sustainable yield and improved soil quality, conservation agriculture (CA) is being advocated and adopted globally, including in India. In this experiment, CA was implemented to investigate the synergistic impacts of tillage and weed management on soil quality index and system yield and to identify a remunerative treatment combination that can sustain system yield and enhance soil quality. Contrasting tillage practices (main plots) included the T1: conventional tillage with cotton–conventional tillage with maize–fallow, i.e., no Sesbania rostrata (Farmers’ practice), T2: conventional tillage with cotton–zero tillage with maize–zero tillage with Sesbania rostrata and T3: zero tillage with cotton + Sesbania rostrata residues–zero tillage with maize + cotton residues–zero tillage with Sesbania rostrata + maize stubbles. Weed management tactics (sub-plots) were W1: chemical weed control, W2: herbicide rotation, W3: integrated weed management and W4: single hand-weeded control in a split-plot design with cotton–maize–Sesbania cropping system over 3 years, in a split-plot design. Principal component analysis (PCA) was performed using the soil quality index (SQI)-CAL Version 1.0 software tool to extract minimum datasets from measured soil properties. A total of 40 soil variables were analyzed at 60 DAS and after the maize harvest, then subjected to principal component analysis (PCA) and subjected to PCA in soil quality index (SQI)-CAL software as to choose variables, minimum dataset and obtain soil quality index. The following soil properties, soil organic carbon (SOC), silt fraction, available soil zinc (Zn), iron (Fe), potassium (K), nitrogen (N), pH, electrical conductivity (EC), soil carbon to nitrogen (C:N) and cation exchange capacity (CEC), were selected as indicators based on correlations, calculated PCA and adept opinions on texture and lime concretions of experimental soil. The soil quality index improved by 23.34% in the T3W4 compared to T1W1. The system yield was 51.79% higher with the adoption of T3W3 compared to T3W4 combinations. Therefore, considering both system yield and soil quality index, T3 and W3 were remunerative and the best treatment combination among all others to sustain both soil and crop productivity in this region.