Regional land use change affects eco-environmental quality by altering ecosystem structure and function. The primitive ecosystem and environment of the Qinghai-Tibet Plateau (QTP) occupies a special position in the world, but it is very fragile. Although land use activities on the plateau have increased gradually in past decades, its effects on eco-environmental quality and the underlying mechanisms of regional heterogeneity remain unclear. In this study, an eco-environmental quality assessment index system was established to characterize the QTP, and the information entropy and elasticity methods were introduced to quantify the impact of land use dynamic trajectory on the eco-environmental quality. It provides a statistical measurement of system structure and more information than the traditional methods to reveal the land use change. The area change in land use on QTP was small from 1990 to 2015. The unused land and forest decreased, but those of grassland, water body, built-up land, and cultivated land increased. The overall eco-environmental quality on the QTP was low, and increased at a rate of 9.39% over the past 25 years, presenting a distribution of decreasing from southeast to northwest. The improvement in eco-environmental quality attributed to land use change was mainly due to the conversion of unused land into grassland, and ecological conservation projects also improved the local ecological environment. Conversely, the expansion of built-up land and land degradation contributed to decline in local eco-environmental quality in the Hengduan Mountains, northeastern plateau, and Qaidam Basin. The results indicated that under the influence of climate change, the changes in land use and eco-environmental quality were inconsistent in part regions, mainly including the central and southern Tibet and the border zone. Regions in which eco-environmental quality has been degraded by unreasonable land use are urgent to optimize land use management.

Mineral-associated soil organic matter (MAOM) is seen as the key to soil carbon sequestration, but its stability often varies with types of exogenous organic materials. Fulvic acid and manure are ones of the exogenous organic materials used for the improvement of degraded soil. However, little is known about if and how fulvic acid and manure affect the stability of MAOM. Using a field experiment of four fertilization treatments (no fertilization, mineral fertilizers, fulvic acid, and manure) and a comprehensive meta-analysis using relevant studies published prior to January 2020, we investigated effects of exogenous fulvic acid and manure applications on four MAOM stability indexes: association intensity, humus stabilization index, iron oxide complex coefficient, and aluminum oxide complex coefficient. Exogenous fulvic acid and manure applications increased soil organic carbon fractions by 26.04–48.47%, MAOM stability by 12.26–387.41%, and complexed iron/aluminum contents by 16.12–20.01%. Fulvic acid application increased MAOM stability by promoting mineral oxide complexation by 20.33% and manure application improved MAOM stability via increasing humus stabilization by 21–25%. Association intensity was positively correlated with contents of soil carbon fractions and the metal oxide complex coefficients were positively correlated with iron/aluminum oxide contents. Moreover, stable-humus exerted significantly positive direct and indirect effects on association intensity and humus stabilization index, while amorphous iron/aluminum content had significantly negative influences on metal oxide complex coefficients. The meta-analysis verified that long-term fulvic acid application improved MAOM stability more so than manure application in acidic soils. We recommend that strategies aiming to prevent land degradation should focus on the potential of fulvic acid as a soil amendment because it can significantly increase MAOM stability.

Soil erosion threatens environmental sustainability worldwide. Exploring the trajectories of soil erosion and associated drivers is of great significance for combating land degradation. This study selected the highly eroded Loess Plateau (LP) and Karst Plateau (KP) as contrasting regions to monitor soil erosion dynamics. Monitoring was performed by applying the Revised Universal Soil Loss Equation based on a GIS platform and multi-source input data to investigate associated drivers. The results established that soil erosion in both regions was substantially reduced by ecological restoration projects and significant land use/cover conversions. Landscape and geomorphological variables were found to be the dominant factors controlling soil erosion in the LP and KP, as they influenced land use patches and geomorphological patterns, respectively. The correlations between fragmentation metric indices and soil erosion indicated that the appropriately intensive fragmentation in the LP could mitigate or prevent soil erosion by disturbing its formation and transportation and ultimately positively influenced soil erosion control. Geomorphological patterns were also determinative factors, particularly for the KP, where almost all geomorphological variables were significantly correlated with the erosion modulus. Owing to the peculiar landform and landscape conditions in karst areas and loess hilly–gully areas, geomorphological and landscape variables should be considered when determining the main factors affecting soil erosion processes and integrated into the forecasting model to improve the accuracy of the simulation. The findings of this study are expected to (i) improve the efficacy of soil erosion control and (ii) promote the sustainable planning and management of land and soil resources.

Special mining methods and red soil lead to large-scale land degradation and desertification in ion-type rare earth (RE) mining areas. Therefore, it is crucial for ecological management and restoration of mining areas to accurately understand the evolution process of desertification. In this study, remote sensing Landsat images from 1986 to 2019 were used to extract desertified land information from the Lingbei mining areas, Dingnan County, Ganzhou, China. To improve the reliability of the experiment, samples selected from Google images were used for verification to compare the accuracy of the desertification difference index (DDI) model and random forest (RF) algorithm for extracting land desertification information. The results showed that compared with the DDI model, the overall accuracy and kappa coefficient of the RF model based on multiple features were improved by 7% and 9.37%, respectively, indicating its higher applicability. Spatiotemporal change analysis of desertification in the mining area showed that the total area of desertification in the mining area increased most rapidly during 1986–1994 and reached 60.75 km². The area of desertified land increased continuously from 1994 to 2004 and reached a maximum of 143.08 km² in 2004. The area of desertified land decreased by 50.27 km², but the severe desertified land (SDL) area increased by 1.69 km² during 2004–2011. The area of desertified land gradually declined and stabilized from 2011 to 2019. Analysis of the desertification process in mining areas under different disturbance conditions showed that the desertified land disturbed by RE mining was most severely damaged. There is still an area of 16.77 km² in the process of restoration, of which 2.24 km² belongs to the SDL level. Moderate desertified land (MDL) and light desertified land (LDL) have not been completely contained and require the attention of the relevant departments to ensure their timely reclamation.

The Nevado de Toluca Natural Protected Area (Zona de Protección de Flora y Fauna Nevado de Toluca, ZPFFNT), Central Mexico, encompasses one of the four highest (> 4000 m a.s.l.) volcanoes in Mexico, Nevado de Toluca; an extended area of woodland surrounds this volcano. Although identified as a remote area based on its high altitude, the ZPFFNT is not far from the urban and industrial zones of Toluca (~20 km) and Mexico (~72 km) cities, which potentially threatens the environmental health of the ZPFFNT by emitting SO₂ and NOX. Acid precipitation falling on areas with low alkaline reserve leads to environmental acidification and land degradation. To provide reliable data on the air pollution reaching the ZPFFNT and the related potential risks, our study analyzed the bulk atmospheric deposition chemistry and its temporal dynamics throughout an annual cycle. There are two well-defined seasons: (a) cold/dry with SW–NE wind direction and (b) warm/rainy with NE–SW wind direction. The pH, electric conductivity (K₂₅), cations, Cl⁻, and HCO₃⁻ were statistically higher in the cold/dry period. Differently, NO₃⁻ and SO₄²⁻ showed steadier behavior. Bulk deposition pH remained acidic at all times but reached extreme low values from July to September during the warm/rainy season. In the cold/dry season, alkaline cations were important in partially neutralizing the acidic compounds from the urban and industrial zones of Toluca and Mexico cities. Previously assumed to be safe based on its remoteness, the ZPFFNT is threatened by acid precipitation, which demand the implementation of preventative and mitigating actions as part of a management plan to avoid environmental deterioration.

Globally, land degradation is becoming a grave concern. Over the years, conditions such as drought, extreme weather events, pollution, changes in land use land cover, and desertification have intensified and led to land degradation, affecting both ecological and economic processes. Equally, during the last two centuries, population and urbanization have amplified manifold and increased the demand for additional food and shelter, resulting in alteration in land use land cover, over-grazing, and over-cultivation, loss of nutrient-rich surface soil, greater runoff from the more impermeable subsoil, and reduced water availability. Geographically, Goa is a highly diversified state. It is sandwiched between the West Coast and the Western Ghats. The state is blessed with beaches, mangroves, backwaters, wetlands, wildlife sanctuaries, evergreen forests, barren lands, and other vital ecosystems. The State of Goa, on average, receives more than 3000 millimeters of rainfall annually with high surface runoff. Using both primary and secondary data, this study sought to investigate and quantify the state’s land degradation. Secondary data came from satellites and other sources, while primary data came from field observation and ground truthing. Land degradation factors related to soil loss and the spatial pattern of soil erosion are predicted and evaluated using the Revised Universal Soil Loss Equation (RUSLE) method. Landsat-8 OLI-TIRS images were utilized to decide land use and cover (C factor), while DEM information was utilized to assess (LS factor). A soil map and rainfall data were collected to acquire a better understanding of soil erodibility (K factor) and rainfall erosivity (R factor). The kriging interpolation technique was used to gain a deeper comprehension of land degradation.The purpose of this paper is to comprehend the concept of integrated land degradation and how it affects the environment of Goa. Using remote sensing data and geostatistical methods, the study creates a comprehensive map of land degradation in the region by identifying and analyzing the various forms of land degradation in Goa. The paper also looks at how rainfall and the amount of land cover affect the rate of soil erosion in Goa. According to the findings, intense rainfall makes the eastern part of Goa particularly susceptible to soil erosion, and bare soil has a greater potential for erosion than vegetated land. The paper concludes that comprehensive land degradation mapping can be a useful tool for developing efficient land management strategies to preserve soil and encourage sustainable development in the region.

The present study analyzed the spatio-temporal variations in the Land Use Land Cover types within Ranipet Municipal town in Ranipet District, Tamil Nadu State, India, using two different platforms (QGIS and IDRISI Selva v.17.0). The possible parameters driven the net changes in the Land Use Land Cover (LULC) types were also incorporated for the analysis. Results revealed the positive net changes in the built-up area are about 26.8%, and combined other classes like vegetation, barren land, and water bodies have net negative changes during 1997-2019. Particularly barren land was found to have a reduction of 17.4% due to the massive industrialization in the study area. Further, the LULC maps were used for future prediction (2029) using the dynamic models of CA-ANN (Cellular Automata and Artificial Neural Network) and CA-Markov. Predicted maps yielded a kappa index of 81.6% and 82.6% for CA-ANN and CA-Markov, representing their respective accuracy levels. The CA-Markov model is extended for determining the probable long-term changes for 2080 in LULC with a kappa index of 76.2%. Compared to the CA-ANN model using the QGIS platform, CA-Markov provided better analysis, particularly from one cell to the other. According to the survey and the ground truth in the locality, industrialization and occupational shift were the most influential drivers of LULC dynamics. Moreover, the results of this study assist the stakeholders in the decision-making process for future sustainable land use management.

Solid wastes generated from industrial sponge iron plants (ISP) are categorized as hazardous waste due to their extremely fine, loose texture, toxic metal concentrations, and being wind borne in summer; their unscientific disposal leads to severe land degradation and environmental pollution. In the present study, phytorestoration of such a hazardous waste dump in central India was carried out through blanketing with forest soil (substratum for vegetation growth) followed by plantation with Psidium guajava (L.) saplings (2500 saplings/ha). The present study aimed to assess the efficiency of fruit orchards in restoring the soil health of waste dumps (WD) without causing any health hazards, allowing the possibility for an economically viable after use of the degraded land. Heavy metal concentration (Mn, Zn, Cu, Cr, Ni) in blanketed topsoil, plant tissues (roots, leaves, fruits), and its associated risk due to consumption of guava fruits were analysed. Soil health with reference to organic carbon (1.7%), total nitrogen (1727.7 mg kg⁻¹), and exchangeable potassium (162.3 mg kg⁻¹) at the 7-year-old restored site was significantly higher than that of the initial stage of revegetation. No probables of health risk was found due to consumption of guava fruit (growing on WD) as the target hazard quotient (THQ) of all the metals in fruit was <1. Restoration cost analysis of the present study showed that only 5% of total costs were responsible for the development of fruit orchards. Therefore, the study concluded that fruit orchards could be a sustainable alternative for phytorestoration of WD, which will also provide socio-economic return to stakeholders.

The accumulation of potential toxic elements (PTEs) in soils is usually conditioned by parental material or anthropogenic sources. To achieve correct land management and land degradation neutrality, it is necessary to spatially detect them. However, there are several areas over the world with high concentrations of PTE but without efficient maps and tools to correctly find solutions and apply control measures. The current study attempts to identify the concentrations, sources, and spatial distributions of the main PTEs such as As, Cd, Cr, Cu, Ni, Pb, and Zn in a non-explored area combining fieldwork and geostatistical analysis. In order to accomplish this goal, a total of 90 soil samples were collected in agricultural and natural areas in the Piedemonte Llanero, Colombia. The chemical analysis was conducted by acid digestion and determined through ICP-OES. Then, ordinary kriging was applied to spatially analyze the most vulnerable areas. Our results demonstrated the effectiveness of these techniques and it is noted that the agricultural areas presented the highest concentrations and represented the potential source of PTEs. On the other hand, the natural areas presented the following concentrations of PTEs Cr (17.10 mg/kg), As (2.92 mg/kg), Cu (7.57 mg/kg), Ni (8.63 mg/kg), Cd (0.17 mg/kg), Pb (8.80 mg/kg), and Zn (27.57 mg/kg) lower than agricultural soils. This information was a key first step to be presented to the policymakers and stakeholders to organize soil sustainable management plans for the Piedemonte Llanero in Colombia.

Over the past decades, the important topic of environmental sustainability, impact, and security of the fossil fuel supply has stimulated interest in using lignocellulosic feedstocks as biofuel to partially cover energy demands. Among energy no-food crops, giant reed (Arundo donax, L.), a perennial rhizomatous grass has been identified as a leading candidate crop for lignocellulosic feedstock, due to its positive energy balance, and low ecological/agro-management demands. The aim of the present study was to characterize the physiological response of Arundo donax (L.) to artificial soil contamination with three different Cu levels (200, 400, and 800 ppm), and to assess the relationship between plant Cu tolerance and S assimilation rate. The present study not only confirms the ability of Arundo donax L. to cope with Cu stress and therefore to grow in marginal, degraded lands abandoned by mainstream agricultural, but also shows that plant performance might be likely ascribed to a modulation of sulfate metabolism resulting in increased thiols content.