Using remote sensing data to study anthropogenic land degradation in Khulna Division, Bangladesh for SDG indicator 15.3.1.

The Sustainable Development Goals (SDGs) include a goal on land degradation: indicator 15.3.1 (proportion of degraded land over total land). It is not always easy to monitor the SDGs, and remote sensing could be an effective tool for monitoring several SDGs. This study assessed land degradation in Bangladesh's Khulna Division over the past two decades. The Trends.Earth toolset was used to assess land degradation during the baseline period (2001-2015) and the reporting period (2016-2020). Inputs include data from the United Nations Convention on Desertification, and outputs include three sub-indicators: land productivity, land cover change, and soil organic carbon (SOC) stocks. Over the past 20 years, the land use and land cover, land productivity, and SOC content of the study area have undergone substantial changes. A significant change was observed in croplands, water bodies, and built-up areas. Croplands have been converted into settlements and tree cover. Nonetheless, there is an increase in land productivity in the area (>64 %) accompanied by a small percentage of decreasing productivity (approximately 9 %). Accordingly, the SOC in major land areas (84.68 %) is stable with 66,475 tons of carbon lost from croplands. Overall, this area reveals substantial progress in SDG indicator 15.3.1 with a clear transformation of degraded land (from 10.38 % to 8.46 %) into stable land (32.09 %-64.01 %). Land degradation is mostly seen in Khulna, Bagerhat, Satkhira, Kushtia, and Jashore areas. Land covers change for urbanisation, developments, water logging, and salinity intrusion cause land degradation. Despite poor representation of the SOC and normalised difference vegetation index datasets in the waterlogged areas, the Trends.Earth-generated results are informative and stand alone. With the results of this study, policymakers may be able to develop more appropriate land management plans by better understanding the complex interconnections of land change processes.

Assessment of land degradation susceptibility within the Shaqlawa subregion of Northern Iraq-Kurdistan Region via synergistic application of remotely acquired datasets and advanced predictive models.

Land degradation (LD) is the decline in a land's functional capacity and productive potential, which includes various anthropogenic and natural drivers. This study focuses on three primary manifestations of LD including soil erosion, landslides, and rockfalls, which are the most prevalent in the Shaqlawa district. A set of 22 LD conditioning factors, encompassing curvature, lithology, aspect, river density, soil type, lineament density, river distance, elevation, road distance, length slope (LS), land use land cover (LULC), stream power index (SPI), valley depth, profile curvature, slope, solar radiation, road density, lineament distance, rainfall, topographic wetness index (TWI), plan curvature, and normalized difference vegetation index (NDVI), were integrated into the analysis. Variance inflation factors (VIF) and tolerance (TOL) values from linear regression indicate that most LD factors have acceptable levels of multicollinearity. The Information Gain Ratio (IGR) identified key variables TWI, NDVI, and lithology-as pivotal factors for predicting LD. Additionally, the study evaluated degradation factors using various machine learning (ML) algorithms, including random forest (RF), Naive Bayes, logistic regression, rotation forest, forest penalized attributes (FPA), and Fisher's Linear discriminant analysis (FLDA). This facilitated categorizing the study area into five susceptibility categories. The FLDA model categorized the highest area under very high degradation risk at 26.72%, emphasizing the varied insights each algorithm brought to characterizing the degradation risk. Additionally, the receiver operating characteristic curves (ROC) were employed for model validation, identifying RF as the most successful model in the training dataset with an area under the curve (AUC) of 0.882, while FLDA outperformed in the testing dataset with an AUC of 0.883. The identified LD-prone areas will help land-use planners and emergency management officials apply effective mitigation strategies for similar terrains.

Linear relationships between aboveground biomass and plant species diversity during the initial stage of degraded grassland restoration projects.

The relationship between aboveground biomass and plant diversity has been extensively examined to understand the role of biodiversity in ecosystem functions and services. Degraded grassland restoration projects can enhance carbon sequestration. However, the relationship between biomass and diversity remains one of the most actively debated topics regarding grassland ecosystems in degraded grassland restoration projects. We speculated that establishing the linear relationships between aboveground biomass and plant species diversity could contribute to enhancing the efficacy of degraded grassland restoration projects. This study sought to determine whether these relationships were linear during the initial stages of the restoration projects of degraded grasslands in Xing'an League, China. The investigations were based on an examination of seventy-six 1 × 1 m2 plots distributed among 15 areas in which the degraded grassland was at the initial stages of restoration. To quantify the species diversity of the degraded grassland communities, we used the species richness, Shannon-Wiener, inverse Simpson's reciprocal, and Pielou's evenness indices. Our analyses revealed that aboveground biomass had clear positive linear relationships with species richness during the initial stages of degraded grassland restoration. However, there were less pronounced associations with species diversity as assessed using the Shannon and inverse Simpson indices, based on regression models. Furthermore, weed biomass was found to have significant negative effects on species richness and Pielou's evenness. The weak linear relationship between aboveground biomass and species richness could be ascribed to an increase in weed biomass. We concluded that aboveground biomass and plant species diversity could be enhanced during the initial stages of degraded grassland restoration projects and suggest that the extent of weed biomass could serve as a key indicator of the efficacy of restoration from the perspective of plant species diversity and aboveground biomass in carbon sequestration projects.

Potential of land degradation index for soil salinity mapping in irrigated agricultural land in a semi-arid region using Landsat-OLI and Sentinel-MSI data.

Irrigated agricultural lands in arid and semi-arid regions are prone to soil degradation. Remote sensing technology has proven useful for mapping and monitoring the extent of this issue. To accurately discern soil salinity, it is essential to choose appropriate spectral wavelengths. This study evaluated the potential of the land degradation index (LDI) using the visible and near infrared (VNIR) and the short wavelength infrared (SWIR) spectral bands compared to that of soil salinity indices by integrating only the VNIR wavelengths. Landsat-OLI and Sentinel-MSI data, acquired 2 weeks apart, were rigorously preprocessed and used. This research was conducted over irrigated agricultural land in Morocco, which is well known for its semi-arid climate and moderately saline soil. Furthermore, a field soil survey was conducted and 42 samples with variable electrical conductivity (EC) were collected for index calibration and validation of the results. The results showed that the visual analysis of the derived maps based on the examined indices exhibited a clear spatial pattern of gradual soil salinity changes extending from the elevated upstream plateau to the downstream of the plain, which limits agricultural activities in the southwestern sector of the study area. The results of this study show that LDI is effective in identifying soil salinity, as indicated by a coefficient of determination (R2) of 0.75 when using Sentinel-MSI and 0.72 with Landsat-OLI. The R2 value of 0.89 and root mean square error (RMSE) of 0.87 dS/m for soil salinity maps generated from LDI with Sentinel-MSI demonstrate high accuracy. In contrast, the R2 value of 0.83 and RMSE of 1.24 dS/m for maps produced from Landsat-OLI indicate lower accuracy. These findings indicate that high-resolution Sentinel-MSI data significantly improved the prediction of salinity-affected soils. Furthermore, this study highlights the benefits of using VNIR and SWIR bands for precise soil salinity mapping.

Exploration of the utilization of a new land degradation index in Lake Ebinur Basin in China.

Land degradation significantly impacts regional economic development and food security, particularly in arid river basins where soil and water conservation is crucial. Understanding the extent and causes of land degradation is pivotal for effectively prevention and management. This study employs the soil adjusted vegetation index (SAVI), the temperature vegetation dryness index (TVDI), and the salinization detection index (SDI), combined with the analytic hierarchy process and the entropy weight method, to construct a comprehensive land degradation index (LDI). Sen's slope trend analysis and the Mann-Kendall significance test were used to analyze land degradation trends in the Ebinur Lake watershed from 2002 to 2022. Additionally, the optimal parameters-based geographical detector was used to examine the underlying mechanisms of land degradation. The results indicate the following: (1) From 2002 to 2012, the degree of land degradation in the Ebinur Lake watershed worsened, particularly in the eastern and southeastern parts, as well as in the southern region of Toli County. From 2012 to 2022, land degradation significantly improved, with a notable reduction in degraded land area. (2) Over the period of 2002-2022, 93.08 % of the land in the research region exhibited a declining LDI trend, 3.95 % showed no change, and only 2.96 % showed an increasing LDI trend. (3) Moderate, severe, and very severe degradation mainly occurred on grassland and unused land, while light degradation and non-degradation primarily occurred on forest land and cultivated land. (4) Unreasonable land use and overgrazing were identified as the primary factors influencing land degradation, with elevation being a secondary factor. The interaction between land use and other factors was found to be most significant, followed by the synergistic effects of grazing quantity with elevation, annual average temperature, gross domestic product, soil moisture, and elevation with annual average precipitation, and temperature. The results of this study offer an empirical basis and taking decisions assistance for land degradation control in the Ebinur Lake Basin, as well as examples and references for assessing land degradation in other places.

Salinity-induced desertification in oasis ecosystems: challenges and future directions.

Salinity-induced desertification is a pressing environmental issue that poses a significant threat to the sustainability of oasis ecosystems worldwide. These ecosystems are vital to the livelihoods of millions of people living in hyper-arid, arid and semi-arid regions, providing essential resources such as food, water and other necessities. However, overexploitation of natural resources, changes in land use and climate change have led to the degradation of these ecosystems, resulting in soil salinisation, waterlogging and other adverse effects. Combating salinity-induced desertification requires a comprehensive approach that addresses both the underlying causes of ecosystem degradation and the direct consequences for local communities. The strategy may include measures for sustainable land use, reforestation and water conservation. It is also essential to involve local communities in these activities and to ensure that their perspectives are heard. The aim of this article is to examine the causes and processes of salinity-induced desertification in oasis ecosystems and the implications for their sustainability. It also examines strategies that are being used to prevent desertification and promote sustainable oasis management. This article aims to raise awareness of this critical issue and to promote action towards a more sustainable future.

Linking the assessment of ecological engineering construction with zoning management in the typical agro-pastoral area of China: A perspective from quantity, quality and function.

Combatting land damage has become a global priority, and China has adopted a series of ecological engineering measures, especially in the agro-pastoral area with fragile ecological environment. The effectiveness of ecological engineering construction (EEC), from a comprehensive recognition encompassing its quality, quantity, and function, has remained largely unknown. To this end, Zhangbei County, a typical agro-pastoral ecotone of northern China, was chosen as our focal area. After summarizing the timelines, aims and results of the EEC during various periods in Zhangbei, the linear spectral mixture analysis was employed to process Landsat 5 TM images in 2000 and 2010, as well as Landsat 8 OLI images in 2020. Then, a comprehensive evaluation framework of EEC was established from the perspective of "quantity-quality-function", and the ecological effectiveness of EEC was evaluated from 2000 to 2020 in Zhangbei. Results revealed that EEC played a critical role in enhancing quantity, quality and function, in spite of that, there were still numerous regions showing varying degrees of degradation in terms of these aspects. Then, by extending the three-dimensional cube as the theoretical basis for the zoning management of EEC, we merged four zones according to the space matching relationship among quantity, quality and function of EEC, namely, Ecological conservation area, Ecological improvement area, Ecological restoration area and Ecological remodeling zone. More targeted ecological measures were required for specific matching relationship among quantity, quality and function of EEC. This study is expected to present an empirical case for assessing the ecological effectiveness of EEC in areas or countries with similar restoration demand and support regional management.

Anthropogenic shrub encroachment has accelerated the degradation of desert steppe soil over the past four decades.

Anthropogenic and natural shrub encroachment have similar ecological consequences on native grassland ecosystems. In fact, there is an accelerating trend toward anthropogenic shrub encroachment, as opposed to the century-long process of natural shrub encroachment. However, the soil quality during the transition of anthropogenic shrub encroachment into grasslands remains insufficiently understood. Here, we used a soil quality assessment method that utilized three datasets and two scoring methods to evaluate changes in soil quality during the anthropogenic transition from temperate desert grassland to shrubland. Our findings demonstrated that the soil quality index decreased with increasing shrub cover, from 0.49 in the desert grassland to 0.31 in the shrubland. Our final results revealed a gradual and significant decline of 36.73 % in soil quality during the transition from desert grassland to shrubland. Reduced soil moisture levels, nutrient availability, and microbial activity characterized this decline. Nearly four decades of anthropogenic shrub encroachment have exacerbated soil drought conditions while leading to a decrease in perennial herbaceous plants and an increase in bare ground cover; these factors can explain the observed decline in soil quality. These findings emphasize the importance of considering soil moisture availability and potential thresholds when implementing revegetation strategies in arid and semiarid regions.

Assessing desertification vulnerability and mitigation strategies in northern Nigeria: A comprehensive approach.

Desertification constitutes a grave threat to the environmental and socio-economic stability of desertification frontline states in Northern Nigeria. From 2003 to 2020, this research comprehensively analyzes desertification vulnerability, integrating parameters such as NDVI, LST, TVDI, MSAVI, and Albedo. Key factors contributing to land degradation are identified, along with the spatial patterns and trends of desertification over the two-decade period. The consequences are profound, with Northern Nigeria's ecosystem experiencing a steady decline in vegetation cover. Agriculture, vital to the region's economy, faces increased aridity and reduced arable land, jeopardizing food security. Diminishing water resources exacerbates scarcity issues, placing additional strain on communities. These environmental changes lead to severe socio-economic implications, including displacement, loss of livelihoods, and heightened vulnerability to climate-related risks. Urgent, comprehensive, and strategic interventions are imperative. Policy recommendations underscore revising and enforcing land use regulations, promoting sustainable agricultural practices, and establishing monitoring systems to guide decision-making. This research contributes practical strategies to enhance the resilience of desertification frontline states, safeguard livelihoods, and align with Nigeria's sustainable development objectives. Findings from the study indicate that only a tiny percentage (6.7 %) of the study area remains unaffected by desertification. Moreover, 13.3 % exhibit light vulnerability, 20 % demonstrate moderate exposure, and 60 % fall into the severe (26.7 %) and compelling (33.3 %) vulnerability categories. These statistics underscore the gravity of desertification in the study area, emphasizing the urgent need for effective mitigation measures to address its impact comprehensively.

Rare microbial taxa as the major drivers of nutrient acquisition under moss biocrusts in karst area.

Karst rocky desertification refers to the process of land degradation caused by various factors such as climate change and human activities including deforestation and agriculture on a fragile karst substrate. Nutrient limitation is common in karst areas. Moss crust grows widely in karst areas. The microorganisms associated with bryophytes are vital to maintaining ecological functions, including climate regulation and nutrient circulation. The synergistic effect of moss crusts and microorganisms may hold great potential for restoring degraded karst ecosystems. However, our understanding of the responses of microbial communities, especially abundant and rare taxa, to nutrient limitations and acquisition in the presence of moss crusts is limited. Different moss habitats exhibit varying patterns of nutrient availability, which also affect microbial diversity and composition. Therefore, in this study, we investigated three habitats of mosses: autochthonal bryophytes under forest, lithophytic bryophytes under forest and on cliff rock. We measured soil physicochemical properties and enzymatic activities. We conducted high-throughput sequencing and analysis of soil microorganisms. Our finding revealed that autochthonal moss crusts under forest had higher nutrient availability and a higher proportion of copiotrophic microbial communities compared to lithophytic moss crusts under forest or on cliff rock. However, enzyme activities were lower in autochthonal moss crusts under forest. Additionally, rare taxa exhibited distinct structures in all three habitats. Analysis of co-occurrence network showed that rare taxa had a relatively high proportion in the main modules. Furthermore, we found that both abundant and rare taxa were primarily assembled by stochastic processes. Soil properties significantly affected the community assembly of the rare taxa, indirectly affecting microbial diversity and complexity and finally nutrient acquisition. These findings highlight the importance of rare taxa under moss crusts for nutrient acquisition. Addressing this knowledge gap is essential for guiding ongoing ecological restoration projects in karst rocky desertification regions.

Challenges for sustainable development goal of land degradation neutrality in drylands: Evidence from the Northern Slope of the Tianshan Mountains, China.

The SDG 15.3.1 target of Land Degradation Neutrality (LDN) only has 15 years from conception (in 2015) to realization (in 2030). Therefore, investigating the effectiveness and challenges of LDN has become a priority, especially in drylands, where fragile ecosystems intersect with multiple disturbances. In this study, solutions are proposed and validated based on the challenges of LDN. We chose the Northern Slope of the Tianshan Mountains as a case study and set baselines in 2005 and 2010. The region and degree of land change (including degraded, stable, and improved) were depicted at the pixel scale (100 × 100 m), and LDN realization was assessed at the regional scale (including administrative districts and 5000 × 5000 m grids). The results showed a significant disparity between the two baselines. The number of areas that realized the LDN target was rare, regardless of the scale of the administrative districts or grids. Chord plots, Spearman's correlation, and curve estimation were employed to reveal the relationship between LDN and seven natural or socioeconomic factors. We found that substantial degradation was closely related to the expansion of unused, urban, and mining land and reduction in water, glaciers, and forests. Further evidence suggests that agricultural development both positively and negatively affects LDN, whereas urbanization and mining activities are undesirable for LDN. Notably, the adverse effects of glacier melting require additional attention. Therefore, we consider the easy-to-achieve and hard-to-achieve baselines as the mandatory and desirable targets of LDN, respectively, and focus further efforts in three aspects: preventing agricultural exploitation from occupying ecological resources, defining reasonable zones for urbanization and mining, and reducing greenhouse gas emissions to mitigate warming. Overall, this study is expected to be a beneficial addition to existing LDN theoretical systems and serve as a case validation of the challenges of LDN in drylands.

Land degradation neutrality assessment and factors influencing it in China's arid and semiarid regions.

The ecosystems in China's arid and semiarid regions are notably fragile and experiencing dramatic land degradation. At the 12th Conference of the Parties (COP12) to the United Nations Convention to Combat Desertification (UNCCD) in October 2015, a definition for land degradation neutrality (LDN) was proposed and subsequently integrated into the Sustainable Development Goals (SDGs). Research on LDN has developed in terms of conceptual framework constructions, quantitative assessments, and empirical studies. However, LDN and its drivers must be clarified in China's arid and semiarid regions since some representative processes have yet to be fully considered in the assessment. Here, we develop an LDN indicator system specialised for the area, assess their LDN status, and determine the impacts of human activities and climate change on LDN. Our research aims to refine the LDN indicator system tailored for China's arid and semiarid regions by incorporating the trends of wind and water erosion. We also identify the influence of human activity and climate change on LDN, which provides insightful strategies for ecological restoration and sustainable development in drylands with climate-sensitive ecosystems. The results show that: (1) In 2020, more than half of areas of China's arid and semiarid regions achieved LDN, with more pronounced success in the southeastern areas compared to the central regions. (2) For LDN drivers, elevation shows negligible influence on LDN, whereas increased temperature promotes LDN achievement. Conversely, factors like vapour pressure deficit and v-direction wind speed hinder it. In conclusion, China's arid and semiarid regions achieved LDN, and the dominant factor that substantially influences LDN varies across geographical zones, with higher wind speeds and elevated GDP levels generally obstructing LDN in most areas.

Land potential assessment and trend-analysis using 2000-2021 FAPAR monthly time-series at 250 m spatial resolution.

The article presents results of using remote sensing images and machine learning to map and assess land potential based on time-series of potential Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) composites. Land potential here refers to the potential vegetation productivity in the hypothetical absence of short-term anthropogenic influence, such as intensive agriculture and urbanization. Knowledge on this ecological land potential could support the assessment of levels of land degradation as well as restoration potentials. Monthly aggregated FAPAR time-series of three percentiles (0.05, 0.50 and 0.95 probability) at 250 m spatial resolution were derived from the 8-day GLASS FAPAR V6 product for 2000-2021 and used to determine long-term trends in FAPAR, as well as to model potential FAPAR in the absence of human pressure. CCa 3 million training points sampled from 12,500 locations across the globe were overlaid with 68 bio-physical variables representing climate, terrain, landform, and vegetation cover, as well as several variables representing human pressure including: population count, cropland intensity, nightlights and a human footprint index. The training points were used in an ensemble machine learning model that stacks three base learners (extremely randomized trees, gradient descended trees and artificial neural network) using a linear regressor as meta-learner. The potential FAPAR was then projected by removing the impact of urbanization and intensive agriculture in the covariate layers. The results of strict cross-validation show that the global distribution of FAPAR can be explained with an R2 of 0.89, with the most important covariates being growing season length, forest cover indicator and annual precipitation. From this model, a global map of potential monthly FAPAR for the recent year (2021) was produced, and used to predict gaps in actual vs. potential FAPAR. The produced global maps of actual vs. potential FAPAR and long-term trends were each spatially matched with stable and transitional land cover classes. The assessment showed large negative FAPAR gaps (actual lower than potential) for classes: urban, needle-leave deciduous trees, and flooded shrub or herbaceous cover, while strong negative FAPAR trends were found for classes: urban, sparse vegetation and rainfed cropland. On the other hand, classes: irrigated or post-flooded cropland, tree cover mixed leaf type, and broad-leave deciduous showed largely positive trends. The framework allows land managers to assess potential land degradation from two aspects: as an actual declining trend in observed FAPAR and as a difference between actual and potential vegetation FAPAR.

Sustainable indigenous bio-mixture for restoration the soil point source pollution with special reference to chlorpyrifos.

Improper pesticide handling is the main cause of contamination of the environment in agricultural systems. This could be caused by leakage of spraying liquid, leftovers, and inappropriate washing of spraying equipment. This study assessed the ability of suggested biomixture modules for remediate repetitive cycles of high chlorpyrifos doses. In three consecutive treatments, four tested modules were contaminated with 160 µg g-1 chlorpyrifos. Chlorpyrifos residues, dehydrogenase activity, and microbial respiration were continuously monitored for 22 weeks. Six bacterial consortia were isolated at the end of the experiment from four treated modules (B+3, BF+3, S+3, and SF+3) and two from untreated modules (B and S). The isolated consortium efficiency in degrading chlorpyrifos was studied. The results revealed that the best chlorpyrifos removal efficiency was achieved when using the stimulated biomixture module (BF) recorded 98%, 100%, and 89%, at the end of three chlorpyrifos treatments, respectively. Such removal efficiency was compatible with the biological activity results of the tested modules: dehydrogenase activity and microbial respiration. There was no difference in the efficiency among the S, B, and BF+3 consortia. The results presented here demonstrate that the combination of vermicompost, wheat straw, soil, and NPK (stimulated biomixture module) can successfully reduce the risk of a point source of pesticide pollution.

Prioritising gully remediation in a Great Barrier Reef catchment: An approach using two independent methods of assessing erosion activity in 22,300 gullies.

The strategic reduction and remediation of degraded land is a global environmental priority. This is a particular priority in the Great Barrier Reef catchment area, Australia, where gully erosion a significant contributor to land degradation and water quality deterioration. Urgent action through the prioritisation and remediation of gully erosion sites is imperative to safeguard this UNESCO World Heritage site. In this study, we analyze a comprehensive dataset of 22,311 mapped gullies within a 3480 km2 portion of the lower Burdekin Basin, northeast Australia. Utilizing high-resolution lidar datasets, two independent methods - Minimum Contemporary Estimate (MCE) and Lifetime Average Estimate (LAE) - were developed to derive relative erosion rates. These methods, employing different data processing approaches and addressing different timeframes across the gully lifetime, yield erosion rates varying by up to several orders of magnitude. Despite some expected divergence, both methods exhibit strong, positive correlations with each other and additional validation data. There is a 43% agreement between the methods for the highest yielding 2% of gullies, although 80.5% of high-yielding gullies identified by either method are located within a 1 km proximity of each other. Importantly, distributions from both methods independently reveal that ∼80% of total volume of gully erosion in the study area is produced from only 20% of all gullies. Moreover, the top 2% of gullies generate 30% of the sediment loss and the majority of gullies do not significantly contribute to the overall catchment sediment yield. These results underscore the opportunity to achieve significant environmental outcomes through targeted gully management by prioritising a small cohort of high yielding gullies. Further insights and implications for management frameworks are discussed in the context of the characteristics of this cohort. Overall, this research provides a basis for informed decision-making in addressing gully erosion and advancing environmental conservation efforts.

Land degradation sensitivity and desertification risk in Harrir region, northern Iraq.

Soil degradation and desertification are persistent ecological issues that present significant challenges worldwide. An accurate evaluation of land susceptibility to desertification is essential for developing suitable strategies or policies to address it on national scales. Modified Mediterranean Desertification and Land Use (MEDALUS) model is widely utilized to assess environmental and desertification sensitivity. This study employed MEDALUS model to identify environmentally sensitive areas prone to desertification in the Harrir region, northern Iraq. A total of 102 soil samples were collected from 0 to 20 cm depth covering a land area of 279.36 km2. Environmental sensitivity area index (ESAI) was used to evaluate sensitivity of the study area to environmental changes. The results indicated that ∼68.18 km2 of the study area would be exposed to land degradation and desertification. Fragile (F) regions accounted for 39.63 km2, underscoring the need for effective management and conservation practices. Only a small portion of the region (2.81 km2) was classified as 'critical' (C). Further analysis revealed that fragile sub-classes F1, F2, and F3 accounted for 11.84%, 17.16%, and 14.19% respectively, while critical subclass C1, C2, and C3 areas accounted for 10.97%, 9.12%, and 1.006% respectively. The remaining areas were either classified as unaffected or had potential for being influenced by environmental changes. Approximately 24.41% of the study area had the potential for being influenced by environmental sensitivity. This highlights the importance of implementing effective management and conservation practices to protect fragile regions in the study area. Policymakers and land managers can effectively prioritize and implement targeted interventions to prevent further soil degradation and desertification in the Harrir region of northern Iraq.

Short-term restoration practices change the bacterial community in degraded soil from the Brazilian semiarid.

Land degradation by deforestation adversely impacts soil properties, and long-term restoration practices have been reported to potentially reverse these effects, particularly on soil microorganisms. However, there is limited knowledge regarding the short-term effects of restoration on the soil bacterial community in semiarid areas. This study evaluates the bacterial community in soils experiencing degradation (due to slash-and-burn deforestation) and restoration (utilizing stone cordons and revegetation), in comparison to a native soil in the Brazilian semiarid region. Three areas were selected: (a) under degradation; (b) undergoing short-term restoration; and (c) a native area, and the bacterial community was assessed using 16S rRNA sequencing on soil samples collected during both dry and rainy seasons. The dry and rainy seasons exhibited distinct bacterial patterns, and native sites differed from degraded and restoration sites. Chloroflexi and Proteobacteria phyla exhibited higher prevalence in degraded and restoration sites, respectively, while Acidobacteria and Actinobacteria were more abundant in sites undergoing restoration compared to degraded sites. Microbial connections varied across sites and seasons, with an increase in nodes observed in the native site during the dry season, more edges and positive connections in the restoration site, and a higher occurrence of negative connections in the degradation site during the rainy season. Niche occupancy analysis revealed that degradation favored specialists over generalists, whereas restoration exhibited a higher prevalence of generalists compared to native sites. Specifically, degraded sites showed a higher abundance of specialists in contrast to restoration sites. This study reveals that land degradation impacts the soil bacterial community, leading to differences between native and degraded sites. Restoring the soil over a short period alters the status of the bacterial community in degraded soil, fostering an increase in generalist microbes that contribute to enhanced soil stability.

Combating land degradation through human efforts: Ongoing challenges for sustainable development of global drylands.

Drylands, as highly vulnerable ecosystems, support environmental functions and human well-being. Nevertheless, widespread land degradation and desertification present significant global and regional environmental challenges, with limited consensus on their area and degree. This study used time-series vegetation productivity and meteorological data from 2000 to 2020 to quantify global land degradation trends and driving factors in drylands. The results show a notable restoration of land degradation in drylands worldwide, with the area of improved land exceeding the degraded area by 1.4 times, although the threat of degradation persists. India and China emerge as pioneers in effective land improvement strategies, offering valuable experiences for other regions. Combined effects, as quantitatively distinguished by our established model, dominate the degradation and improvement processes. Notably, human activities play a decisive role in influencing land degradation trends, with the potential for either exacerbation or reversal. This study provides new perspectives on environmental health and human activities from global and regional observations. Finally, our research provides scientific support for desertification control and contributes to the overall advancement of the SDGs globally.

Spatio-temporal characteristics and driving mechanism of land degradation sensitivity in Northwest China.

Northwest China has been experiencing severe land degradation for a long time due to various natural and social elements. Evaluating and analyzing the process of occurrence and driving mechanism of land degradation sensitivity in this area is crucial for enhancing the local ecological environment. In this study, 18 social and environmental elements were used to construct a land degradation sensitivity index (LDSI) evaluation system in the area from vegetation, climate, management, soil, and geomorphology five factors. The spatio-temporal characteristics of LDSI in Northwest China from 2000 to 2020 were evaluated on the basis of analyzing the developmental changes of each factor. Correlation analysis and multiscale geographical weighting regression (MGWR) were used to reveal the driving mechanism of land degradation sensitivity. The results indicated a high level of land degradation sensitivity in Northwest China, with >66 % of the area (190.96 × 104 km2) in the critical sensitive class from 2000 to 2020. But the land degradation sensitivity decreased in 18.52 % of the area (53.58 × 104 km2) from 2000 to 2020, the overall trend was weakening. The spatial distribution mainly showed stronger sensitivity in the northwest and weaker sensitivity in the southeast. By exploring the driving mechanism of land degradation sensitivity, it was found that vegetation and climate showed a strong correlation, with a correlation coefficient >0.8. Drought resistance played a strong role in the dynamic process of land degradation. The basic dynamic elements showed some spatial variability in land degradation in different regions. This study is of significance for land degradation prevention and sustainable development in Northwest China.