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Permafrost degradation may induce soil carbon (C) loss, critical for global C cycling, and be mediated by microbes. Despite larger C stored within the active layer of permafrost regions, which are more affected by warming, and the critical roles of Qinghai-Tibet Plateau in C cycling, most previous studies focused on the permafrost layer and in high-latitude areas. We demonstrate in situ that permafrost degradation alters the diversity and potentially decreases the stability of active layer microbial communities. These changes are associated with soil C loss and potentially a positive C feedback. This study provides insights into microbial-mediated mechanisms responsible for C loss within the active layer in degraded permafrost, aiding in the modeling of C emission under future scenarios.

Assessment of soil health requires complex evaluation of properties and functions responsible for a broad range of ecosystem services. Numerous soil quality indices (SQI) have been suggested for the evaluation of specific groups of soil functions, but comparison of various SQI is impossible because they are based on a combination of specific soil properties. To avoid this problem, we suggest an SQI-area approach based on the comparison of the areas on a radar diagram of a combination of chemical, biological and physical properties. The new approach is independent of the SQI principle and allows rapid and simple comparison of parameter groups and soils. Another approach analyzing the resistance and sensitivity of properties to degradation is suggested for a detailed evaluation of soil health. The resistance and sensitivity of soil properties are determined through comparison with the decrease of soil organic carbon (SOC) as a universal parameter responsible for many functions. The SQI-area and resistance/sensitivity approaches were tested based on the recovery of Phaeozems and Chernozems chronosequences after the abandonment of agricultural soils. Both the SQI-area and the resistance/sensitivity approaches are useful for basic and applied research, and for decision-makers to evaluate land-use practices and measure the degree of soil degradation.

This study investigates the effects of physical and chemical soil degradation on crop productivity in the Korekore Watershed. The watershed was categorized into level, sloping, and steep slope gradients. Within each slope gradient, one cultivated land managed with soil and water conservation and one cultivated land without soil and water conservation were selected. Selected soil physicochemical analyses were performed on 18 disturbed and undisturbed soil samples and were taken from the top 0–20 cm depths from each cultivated land with three replications. The soil degradation index (SDI) was evaluated based on the percent changes in soil properties of cultivated land without soil and water conservation to that of the cultivated land managed with soil and water conservation. The crop productivity index was determined by analyzing the percentage growth rate and its standard deviation. Soil bulk density and moisture content improved undercultivated land managed with SWC practices. Significantly higher ( p ≤ 0.05) soil organic carbon (SOC) content (2.02%), total N (0.12%), available P (4.69 ppm), and exchangeable K (1.33 cmolc/kg) were observed in cultivated land managed with SWC as compared to cultivated land without SWC measures. The value of the SDI (+243.9%) for the watershed has demonstrated that soil degradation has improved and soil and water conservation measures had a significant impact on crop yields. The average crop yield rate (CYR) (30%) was found to be lower than the estimate provided by the central statistics agency in Ethiopia. A higher CYR was observed in cultivated land managed with soil and water conservation practices. It can be concluded that physical and chemical soil degradation significantly impacts crops unless counterbalanced by soil and water conservation measures. Therefore, it is recommended to implement well‐integrated watershed management practices to improve soil quality and enhance crop productivity.

This study presents a remote sensing-based index for the prediction of soil erosion susceptibility within railway corridors. The empirically derived index, Normalized Difference Railway Erosivity Index (NDReLI), is based on the Landsat-8 SWIR spectral reflectances and takes into account the bare soil and vegetation reflectances especially in semi-arid environments. For the case study of the Botswana Railway Corridor (BRC), the NDReLI results are compared with the RUSLE and the Soil Degradation Index (SDI). The RUSLE model showed that within the BRC, the mean annual soil loss index was at 0.139 ton ha−1 year−1, and only about 1% of the corridor area is susceptible to high (1.423–3.053 ton ha−1 year−1) and very high (3.053–5.854 ton ha−1 year−1) soil loss, while SDI estimated 19.4% of the railway corridor as vulnerable to soil degradation. NDReLI results based on SWIR1 (1.57–1.65 μm) predicted the most vulnerable areas, with a very high erosivity index (0.36–0.95), while SWIR2 (2.11–2.29 μm) predicted the same regions at a high erosivity index (0.13–0.36). From empirical validation using previous soil erosion events within the BRC, the proposed NDReLI performed better than the RUSLE and SDI models in the prediction of the spatial locations and extents of susceptibility to soil erosion within the BRC.

BackgroundLand use and land cover changes have a significant impact on the dynamics of soil organic matter (SOM) and its fractions, as well as on overall soil health. This study conducted in Bharatpur Catchment, Chitwan District, Nepal, aimed to assess and quantify variations in total soil organic matter (TSOMC), labile organic matter fraction (CL), stable organic matter fraction (CS), stability ratio (SR), and carbon management index (CMI) across seven land use types: pastureland, forestland, fruit orchards, small-scale conventional agricultural land, large-scale conventional agricultural land, large-scale alternative fallow and conventional agricultural land, and organic farming agricultural land. The study also explored the potential use of the Carbon Management Index (CMI) and stability ratio (SR) as indicators of soil degradation or improvement in response to land use changes.ResultsThe findings revealed significant differences in mean values of TSOMC, CL, and CS among the different land use types. Forestland and organic farming exhibited significantly higher TSOMC (3.24%, 3.12%) compared to fruit orchard lands (2.62%), small scale conventional farming (2.22%), alternative fallow and conventional farming (2.06%), large scale conventional farming (1.84%) and pastureland (1.20%). Organic farming and Forestland also had significantly higher CL (1.85%, 1.84%) and CS (1.27%, 1.39%) compared to all other land use types. Forest and organic farming lands showed higher CMI values, while pastures and forests exhibited higher SR values compared to the rest of the land use types.ConclusionsThis study highlights the influence of various land use types on soil organic matter pools and demonstrates the potential of CMI and SR as indicators for assessing soil degradation or improvement in response to land use and land cover changes.

The vegetation and ecosystem in the source region of the Yangtze River and the Yellow River (SRYY) are fragile. Affected by climate change, extreme droughts are frequent and permafrost degradation is serious in this area. It is very important to quantify the drought–vegetation interaction in this area under the influence of climate–permafrost coupling. In this study, based on the saturated vapor pressure deficit (VPD) and soil moisture (SM) that characterize atmospheric and soil drought, as well as the Normalized Differential Vegetation Index (NDVI) and solar-induced fluorescence (SIF) that characterize vegetation greenness and function, the evolution of regional vegetation productivity and drought were systematically identified. On this basis, the technical advantages of the causal discovery algorithm Peter–Clark Momentary Conditional Independence (PCMCI) were applied to distinguish the response of vegetation to VPD and SM. Furthermore, this study delves into the response mechanisms of NDVI and SIF to atmospheric and soil drought, considering different vegetation types and permafrost degradation areas. The findings indicated that low SM and high VPD were the limiting factors for vegetation growth. The positive and negative causal effects of VPD on NDVI accounted for 47.88% and 52.12% of the total area, respectively. Shrubs were the most sensitive to SM, and the response speed of grassland to SM was faster than that of forest land. The impact of SM on vegetation in the SRYY was stronger than that of VPD, and the effect in the frozen soil degradation area was more obvious. The average causal effects of NDVI and SIF on SM in the frozen soil degradation area were 0.21 and 0.41, respectively, which were twice as high as those in the whole area, and SM dominated NDVI (SIF) changes in 62.87% (76.60%) of the frozen soil degradation area. The research results can provide important scientific basis and theoretical support for the scientific assessment and adaptation of permafrost, vegetation, and climate change in the source area and provide reference for ecological protection in permafrost regions.

Arable soil degradation poses a serious threat to global agricultural production and food security. Thus, the monitoring of its initial stages such as soil crust development is of great importance. In our study we presented an approach for such monitoring based on multi-temporal satellite data. Study region, covered by a Landsat 8 OLI scene (180 × 185 km), included the south-eastern part of Moscow, north-eastern part of Tula and western part of Ryazan regions of Russia. The suggested approach is comprised of such steps as (1) multi-temporal satellite data selection and preprocessing; (2) open soil surface identification; (3) dry soil surface detection; (4) detection of soil crust presence in a pixel. The calibration of the approach (steps (3), (4)), was performed based on the field data and the data from two laboratory experiments with soils of the studied region. The main result was a map of the probability of soil crust presence (SCP) for the studied region for the period 2016–2021, outlining the areas with different risk of soil degradation development. The field validation of the map showed that the obtained SCP values are in agreement with the indicators of soil susceptibility to the crust formation.

Soil microorganisms are important decomposers in soil, and they play important roles in litter degradation, nutrient cycle and balance, soil physicochemical property improvement, and soil fertility maintenance. To understand the influence of Eucalyptus plantations on the growth, reproduction, and activity of soil microorganisms in severely degraded land, the Leizhou Peninsula in tropical China was selected as the research area. The vegetation restoration types of Eucalyptus urophylla × grandis planted in its severely degraded red soil areas (ES: Eucalyptus–shrub, EG: Eucalyptus–grass, and ED: Eucalyptus–Dicranopteris pedata (Houtt.) Nakaike) were studied, and the nearby natural vegetation types (S: shrub, G: grass, and D: Dicranopteris pedata) served as control groups. The microbial characteristics of different vegetation restoration types were compared, and the influence of Eucalyptus plantations on the growth, reproduction, and activity of soil microorganisms in severely degraded red soil areas was discussed by setting up sample plots for investigation, sample determination, and statistical analysis. The structure of soil microorganisms differed significantly between Eucalyptus vegetation restoration (ER) and natural vegetation restoration without Eucalyptus (NER). Key organic decomposers, including bacterial genera such as Candidatus Solibacter (ER: 1.2 ± 0.4% vs. NER: 0.9 ± 0.1%), Candidatus Koribacter (ER: 1.0 ± 0.4% vs. NER: 0.7 ± 0.1%), and Edaphobacter (ER: 0.9 ± 0.1% vs. NER: 0.4 ± 0.1%), as well as fungal genera such as Rhizophagus (ER: 0.1 ± 0.0% vs. NER: 0.0 ± 0.0%), Paxillus (ER: 0.1 ± 0.0% vs. NER: 0.0 ± 0.0%), and Pisolithus (ER: 0.1 ± 0.0% vs. NER: 0.0 ± 0.0%), exhibited a significantly higher relative richness and a broader distribution in ER compared to NER (p < 0.05). Soil microbial biomass carbon, nitrogen and phosphorus (MBC, MBN, MBP), community structure (keystone taxa and symbiosis network complexity), and functional genes (for growth, reproduction, and decomposition) in ER, especially in ES, were significantly higher than in NER. This study illustrated that Eucalyptus plantations, especially ES types, can promote the growth and reproduction of soil organic decomposers, improve microbial metabolic and biological activities, and increase functional diversity and interactions among microorganisms, thus accelerating the cycle of soil carbon, nitrogen, and phosphorus nutrients, improving soil quality and fertility, and accelerating the recovery of degraded soil fertility. In areas with serious soil degradation and where natural vegetation restoration is difficult, planting Eucalyptus, especially while guiding the understory vegetation to develop into the shrub vegetation type, is an effective vegetation restoration model.

It is shown that the language of spatiotemporal values (LT methodology) can be used in soil science for assessing degradation and progradation processes in soils and lands, as well as for describing evolution of soils accompanied by variation in the soil ecosystem capacity.

Recent improvements in earth observation technologies and Geographical Information System (GIS) based spatial analysis methods require us to examine the efficiency of the different data-driven methods and decision rules for soil salinity monitoring and degradation mapping. The main objective of this study was to analyze the environmental impacts of the Lake Urmia drought on soil salinity and degradation risk in the plains surrounding the hyper-saline lake. We monitored the impacts of the lake drought on soil salinity by applying spatiotemporal indices to time-series satellite images (1990–2020) in Google Earth Engine environment. We also computed the soil salinity ratio to validate the results and determine the most efficient soil salinity monitoring techniques. We then mapped the soil degradation risk based on GIS spatial decision-making methods. Our results indicated that the Urmia Lake drought is leading to the formation of extensive salt lands, which impact the fertility of the farmlands. The land affected by soil salinity has increased from 2.86% in 1990 to 16.68% in 2020. The combined spectral response index, with a performance of 0.95, was the most efficient image processing method to assess soil salinity. The soil degradation risk map showed that 38.45% of the study area has a high or very high risk of degradation, which is a significant threat to food production. This study presents an integrated geoinformation approach for time-series soil salinity monitoring and degradation risk mapping that supports future studies by comparing the efficiency of different methods as state of the art. From a practical perspective, the results also provide key information for decision-makers, authorities, and local stakeholders in their efforts to mitigate the environmental impacts of lake drought and sustain the food production to sustain the 7.3 million residents.