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[Display omitted] • Land use change profoundly impacts the migration of heavy metals (HMs) in the soil. • The comprehensive pollution index was in VGF>CVL>WSL>WDL. • Soil microbial and enzymatic activities did not directly affect HMs concentration. The accumulation of heavy metals (HMs) in soil has become a pressing global concern due to their persistent and non-degradable nature, resulting in the accumulation of toxic levels in the environment. In recent years, human activities have significantly altered land use patterns, leading to a marked increase in soil HM levels and subsequent land degradation. This research focused on four distinct land use patterns (vegetable fields (VGF), woodland (WDL), cultivated land (CVL), and wasteland (WSL)) commonly found in the Taojia River Basin, Hunan, China, which is facing severe HM pollution. Soil samples were collected from three different depths (0–10 cm, 10–20 cm, and 20–30 cm) to investigate HM distribution and intensity (cadmium (Cd), lead (Pb), copper (Cu), nickel (Ni), and zinc (Zn)), comprehensive soil pollution index, and their relationship with soil microbial and enzymatic activities. The results revealed that the Cd content exceeded the national standard for soil environmental quality, whereas concentrations of other HMs did not exceed the national standard across the four land use patterns. Most soil HMs were concentrated in the surface layer, with Cu, Pb, and Zn concentrations gradually decreasing with increasing soil depth. Conversely, Ni and Cd concentrations tended to increase with greater soil depth. There were significant positive correlations among HMs, indicating homogeneity among them. The pollution index across the HMs ranked as Cd > Ni > Zn > Cu and Pb, with land uses following the order of VGF (2.70) > CVL (2.12) > WSL (1.72) > WDL (1.63). Soil microbial and enzymatic activity was not the primary factor influencing HM concentration. The specific impacts of land use changes on soil HMs depend on management practices, local conditions, and the distribution characteristics of the HMs involved. [ABSTRACT FROM AUTHOR]

Soil erosion is both the cause and effect of land degradation. Land use/land cover conversion that changes the inherent landscape structure of watersheds leads to soil loss increase. Pantabangan-Carranglan Watershed (PCW) as a major source of irrigation, electricity, biodiversity, livelihood, and other ecosystem services, thus, it is imperative to spatially and temporally estimate the soil erosion within its boundary to assist and guide decision-makers in planning conservation and management of the watershed. Using the Revised Universal Soil Loss Equation (RUSLE) model, remotely sensed data, soil analysis, and geographical information system, the soil erosion rate in PCW was estimated. Results showed that there is increasing soil erosion in PCW over time. In 2010 soil erosion rate was estimated to be 134 tons·ha-1·yr-1 which increased to 141 tons·ha-1·yr-1 and 154 tons·ha-1·yr-1 in 2015 and 2020, respectively. Considering the average soil erosion rate and land cover types in PCW, annual crop and open/barren land cover types have the highest average soil erosion rate through time with moderate and catastrophic erosion levels, respectively. [ABSTRACT FROM AUTHOR]

The analysis of early studies and methods of land degradation assessment demonstrated that the existing assessment procedure does not reflect the real situation. The existing methods do not consider ecological aspects as loss of social-recreational and protective-restoration functions. The existing methods of assessing damage from the mining and processing enterprise require improvement with mandatory consideration of the environmental component. The object of the study is the land in mining and industrial regions, where minerals are extracted underground and industrial masses are formed on the surface. The main types of land use have been systematized, which makes it possible to apply an estimated aggregate approach. The loss of a number of functions of economic turnover is a classification sign of land degradation assessment. A three-criteria approach to the assessment of land degradation is proposed. This approach considers the impact of loss of social-recreational functions, loss of protective and restorative functions, and the impact of the main mining type of activity. [ABSTRACT FROM AUTHOR]

Malawi, like the majority of African countries, is experiencing land degradation as a result of climate change and unsustainable farming methods. Land degradation is a worldwide problem, but Africa is the worst affected, with 75% of arable land already degraded. Malawi is primarily an agricultural country, with 11 million people practicing small-scale subsistence farming. Given the hilly terrain, forests, and tough pastures, only one-third of the county is considered cultivable. However, agriculture accounts for 30% of Malawi's GDP, exporting 80% of its agricultural produce. Small-scale farmers are essential producers, farming 5.3 million hectares of land and accounting for over 70% of Malawi's food consumption. Unfortunately, as climate change and economic demands increase, so does land degradation. Even though indigenous knowledge has been used for generations to adapt to changing environments, there is an unmistakable distinction between scientific and indigenous knowledge, with scientific being seen as far superior. Several studies have revealed that depending entirely on one knowledge system is insufficient for effectively addressing environmental concerns. Thus, there is a need for more comparisons that allow for a complementary application of the two knowledge systems rather than their contradiction. In this work, we identify indigenous indicators of land degradation and land management practices utilized by Malawian farmers, and we investigate how indigenous and scientific knowledge systems might be combined to adapt and address the issue of land degradation swiftly. To do this, 100 semi-structured interviews were conducted with farmers in five villages. Atlas-ti software was used to do thematic content analysis on the dataset. Our findings show farmers' coping techniques are still based on IK and motivated by experiential learning from earlier climatic crises. Though most farmers know scientific land management practices, current adaption strategies rely on expensive resources and are inappropriate for indigenous farmers. The study investigates various ways scientific and indigenous knowledge could be integrated to enhance climate change adaptation against land degradation. These encompass developing indigenous indicator baselines, including new measures for measuring soil fertility, and more effective and energy-efficient irrigation technologies. [ABSTRACT FROM AUTHOR]

Agricultural innovation is a top priority on the global sustainable development agenda to solve food insecurity, land degradation, climate-change issues, poverty, and unemployment. This paper aims to identify systemic problems and socio-technical transition factors that hinder the development, dissemination, and utilization of improved maize varieties in Ethiopia. Primary data were gathered through structured and semi-structured interview schedules, and then analyzed thematically. Results show that systemic failures such as the absence of key actors, institutional problems, lack of interaction between actors, and inadequate infrastructure are the major hindrances to the systems functioning. Three functions, including entrepreneurship, knowledge development, and creating legitimacy, were found to be weaker than others in the case of improved maize varieties released by Pioneer Hi-Bred Seeds Ethiopia Plc. However, these functions were stronger in the case of improved maize seed varieties released by public research centres. Knowledge dissemination and resource mobilization were the stronger functions of Pioneer Hi-Bred Seeds Ethiopia Plc., which were found to be weak in the public research centres. The result also shows that policies and governance affected the sustainable development of improved maize varieties released by Pioneer Hi-Bred Seeds Ethiopia Plc. Promoting knowledge development and resource mobilization within networks of policymakers, the public sector, and local and foreign private sectors, and a regulation on breeders’ rights to encourage the involvement of private companies in the sector are recommended to enable the innovation system to function sustainably. [ABSTRACT FROM AUTHOR]

Land degradation poses a significant global challenge, adversely affecting soil quality and diminishing the productivity of arable land, which, in turn, impacts food production and ecosystem services. This degradation manifests in various forms, including soil compaction, salinity, nutrient depletion, loss of biodiversity, and contamination, ultimately rendering soil unproductive and exacerbating climate change. Given the challenges arising from conventional farming practices and climate change, there is an urgent necessity to develop agricultural systems that not only enhance agronomic efficiency but also improve environmental performance. This study focuses on addressing food security in Africa by investigating the role of land restoration and biodiversity in sustainable food systems through a comprehensive bibliometric analysis for documents between 2010 to 2023, identifying 64 relevant documents. The analysis reveals insights into the most-cited documents and thematic evolution, underscoring the significant contributions from Ethiopia and advocating for collaborative efforts among African nations. Key themes identified include "climate change", "food security", "biodiversity conservation", and "agroecosystems", all highlighting the importance of sustainable agricultural practices. The study anticipates a continued prioritization of agroecosystems, smart agriculture, and biodiversity conservation to tackle food security challenges in the face of climate change. Collaboration, investment in research, and practical initiatives emerge as essential components for achieving sustainable food security and mitigating climate change impacts in Africa. This research provides valuable insights into the current landscape and future trends regarding the contributions of land restoration and biodiversity to food systems in Africa, emphasizing the critical need for concerted efforts to address these pressing issues. [ABSTRACT FROM AUTHOR]

The increasing demand for water resources has resulted in environmental degradation and conflicting interests among diverse users. This research aimed to scrutinize the causes and repercussions of land use exploitation and degradation within the Samambaia River Basin (SRB), focusing on potential environmental impacts linked to the management of irrigated agriculture. The study encompassed the entire SRB. Adopting climatological data from 1981 to 2010, distinct dry and wet seasons in the SRB were delineated. A precise slope map has been produced based on an elevation dataset, while vegetation indices like the Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index (NDWI) have been computed. Indices such as the Woody Vegetation Biomass Index (WVBI), Vegetation Vulnerability Index (VVI), and Land Vulnerability Index (LVI) were derived from the NDVI. The dataset underwent descriptive statistical analysis, incorporating adjustment and validation factors. The root mean square error (RMSE) values for the daily rainfall data were notably low (7.0711 and 7.9223 mm). The years 2015, 2016, and 2018 experienced heightened rainfall during the dry season, while 2015 and 2018 recorded significant rainfall in the wet season. NDWI ranged from − 0.41 to 0.24, with positive values indicating the presence of water bodies in the SRB. During the dry season, regions with denser vegetation are largely associated to areas with central pivot irrigation. The WVBI revealed intensified vegetation in the wet seasons of 2014 and 2019. The LVI during the dry season varied from moderate to very low, with limited high-risk areas predominantly along water body boundaries. [ABSTRACT FROM AUTHOR]

Wind speed is one of the main control factors of wind erosion and dust emissions, which are major problems in arid and semiarid regions of the world. Accurately simulating highly precise hourly wind speeds is critical and cost-efficient for land management decisions with the goal of mitigating wind erosion and land degradation. The Wind Erosion Prediction System (WEPS) is a process-based, daily time-step model that simulates changes in the soil–vegetation–atmosphere. However, to date, relatively few studies have been conducted to test the ability of the WEPS in simulating hourly wind speeds. In this study, the performance of the WEPS model was tested in the Inland Pacific Northwest (iPNW), where wind erosion is a serious problem. Hourly wind speeds were observed and simulated by the WEPS at 13 meteorological stations from 2009 to 2018 using the WEPS hourly wind speed probability histogram. Owing to increasing wind shear, the model is not as precise in reproducing high wind speeds. The WEPS inadequately simulated the hourly wind speeds at six of the 13 stations, with a low index of agreement (d < 0.5). The complex regional topography may be one of the reasons for this lack of agreement, because the WEPS's performance of interpolation relies on spatial distances and surface complexity. Therefore, we validated the model using another wind-speed database to eliminate the impact of spatial interpolation. The performance of the WEPS was improved after removing the impact of spatial interpolation, producing d values > 0.5 at nine of the 13 stations. Our results suggest that the WEPS can accurately simulate hourly wind speeds and assess wind erosion in the absence of interpolation, whereas the model may be uncertain when invoking spatial interpolation. Some evidence also suggests that the model may have a tendency to underestimate observed hourly wind speeds. Pragmatically, this suggests that model users should consider the possibility that WEPS may underestimate wind erosion risk in the iPNW and plan implementation of conservation practices accordingly. [ABSTRACT FROM AUTHOR]

Climate change has brought about credible changes in arid landscapes which have resulted in further challenges for pastoralists who require good quality rangeland resources to sustain their livestock. This study assessed local level coping and adaptivemanagement strategies by pastoralists in Namibia and South Africa using a capital assets approach, and also explored non-climate related barriers that increase their vulnerability to climate change. A case study approach was used, which included focus group discussions and semi-structured interviews. The main findings of the research indicate that pastoralists have been exposed to increased temperature extremes and droughts of varying duration over time which reduced the quality and quantity of forage and resulted in losses of income and animal health. The 46 different coping and adaptation strategies used by pastoralists included financial (n =15), natural (n = 15), human (n =12), physical (n = 2) and social (n = 2) capital. Of these, 61% of the strategies were common between the two countries. Strategies included income diversification, supplementary feeding and livestock mobility. Pastoralists had to overcome a hierarchy of barriers to implement their coping and adaptation strategies, which were largely related to human capital in Namibia and to natural capital in South Africa. These barriers included a lack of access to grazing lands, land degradation and the loss of traditional knowledge to manage livestock and rangeland resources. Policy development should take these barriers into account while building on the foundation of existing adaptation strategies to reduce the vulnerability to climate change of pastoralists in dryland regions. [ABSTRACT FROM AUTHOR]

Semi-arid agroecosystems are crucial for food security and ecosystem services, but land degradation threatens their sustainability. This study assessed land degradation neutrality (LDN) in a semi-arid agroecosystem of Matabeleland North Province, Zimbabwe, leveraging trends.earth within QGIS and data from the European Space Agency Climate Change Initiative (1992–2020). We analysed land use/land cover (LULC), soil organic carbon (SOC), and land productivity to identify areas of degradation and stability. Additionally, we simulated 2050 land-use/land-cover maps using a cellular automata model within a GIS framework assuming a business-as-usual scenario. The model considered the 2015 LULC map as a baseline along with environmental variables such as the digital elevation model and slope. While historical trends (1992–2020) showed a decrease in bare areas (-71%) and an increase in settlements (+ 163%), cellular automata modeling predicted a concerning future trajectory with further expansion of bare land (+ 238%) and settlements (+ 72%) by 2050, alongside a decline in water bodies (-23%) and forests (-3.5%). Notably, around 26.5% of the land exhibited degradation, often linked to low SOC levels in croplands, while 59.55% remained stable over the study period. However, caution is necessary as increases in greenness may not always reflect positive restoration. Land cover transitions, particularly the conversion of forests to grasslands and settlements, emerged as potential drivers of degradation, likely leading to ecosystem service loss, habitat fragmentation, and potentially exacerbating the impacts of climate change. These findings highlight the urgent need for targeted restoration and land management strategies focused on improving SOC levels in croplands and conserving vital forest and grassland ecosystems to achieve LDN in this semi-arid region. Further research is needed to quantify specific degradation drivers, assess the effectiveness of intervention strategies, and explore the socio-economic dimensions of land degradation and LDN efforts. [ABSTRACT FROM AUTHOR]

From land degradation and desertification to cyclones and tropical storms, and so on, the repercussions of global change have become increasingly severe in recent years. Such environmental impacts require continuous assessment and monitoring. Thus, to study and analyse these impacts, a variety of time-series forecasting approaches have been developed, including statistical ones [i.e. Moving Average (MA), Auto-Regressive Integrated Moving Average (ARIMA), etc.], and machine-learning approaches such as Recurrent Neural Networks (RNN), Long-Short-Term Memory Network (LSTM) and Convolutional Neural Networks (CNN). In this study, accuracy of the most used forecasting approaches (i.e. MA, LSTM and Conv-LSTM) has been quantified, and three impacts (i.e. climate regions, land cover and satellite sensors) have been brought to light. Firstly, eight Mediterranean regions were selected (i.e. two hot arid regions, two cold arid regions, two regions with temperate hot summers and two regions with temperate warm summers) based on Köppen climate classification. Secondly, 654 hyperspectral images retrieved from three different satellites (i.e. Sentinel-2, Landsat-8 and MODIS) from 2016 to 2022 were computed in order to predict 29 vegetation biophysical indices (i.e. NDVI, GNDVI, EVI, CVI, etc.). Accordingly, more than 18,000 images were computed, resulting in 696 time series forecasted using the aforementioned approaches. Finally, 2088 forecasted time series have been determined, and their accuracy has been compared. As a result, Landsat-8 and Sentinel-2 images had the highest forecasting accuracy in the three approaches, reaching 86% of the computed indices being over 50% accurately predicted in LSTM model, while MODIS data had the highest forecasting accuracy only in MA model, with a percentage of 72% of the computed indices being over 50% accurately predicted. Furthermore, we have identified that region climate impacts vegetation forecasting accuracy. For instance, arid regions showed low accuracies across all models, while temperate regions showed higher accuracies in the Mediterranean region. [ABSTRACT FROM AUTHOR]

Black soil is a precious soil resource, yet it is severely affected by gully erosion, which is one of the most serious manifestations of land degradation. The determination of the location and shape of gullies is crucial for the work of gully erosion control. Traditional field measurement methods consume a large amount of human resources, so it is of great significance to use artificial intelligence techniques to automatically extract gullies from satellite remote sensing images. This study obtained the gully distribution map of the southwestern region of the Dahe Bay Farm in Inner Mongolia through field investigation and measurement and created a gully remote sensing dataset. We designed a multi-scale content structure feature extraction network to analyze remote sensing images and achieve automatic gully extraction. The multi-layer information obtained through the resnet34 network is input into the multi-scale structure extraction module and the multi-scale content extraction module designed by us, respectively, obtained richer intrinsic information about the image. We designed a structure content fusion network to further fuse structural features and content features and improve the depth of the model's understanding of the image. Finally, we designed a muti-scale feature fusion module to further fuse low-level and high-level information, enhance the comprehensive understanding of the model, and improve the ability to extract gullies. The experimental results show that the multi-scale content structure feature extraction network can effectively avoid the interference of complex backgrounds in satellite remote sensing images. Compared with the classic semantic segmentation models, DeepLabV3+, PSPNet, and UNet, our model achieved the best results in several evaluation metrics, the F1 score, recall rate, and intersection over union (IoU), with an F1 score of 0.745, a recall of 0.777, and an IoU of 0.586. These results proved that our method is a highly automated and reliable method for extracting gullies from satellite remote sensing images, which simplifies the process of gully extraction and provides us with an accurate guide to locate the location of gullies, analyze the shape of gullies, and then provide accurate guidance for gully management. [ABSTRACT FROM AUTHOR]

This review summarises the available evidence on the prospects for using microalgae or their extracts to support crop production. The evidence is limited but suggests technological promise in several distinct ways, namely, higher core productivity, enhanced resilience to biotic and abiotic stresses, and better-quality produce. The different efficacy pathways of these microalgal technologies were examined to assess their scope to help address key farmer priorities. Their scope to help farmers face climate change and land degradation was a particular focus, given the magnitude of these threats. These microalgal technologies are framed in terms of their pertinence to farmer priorities due to the centrality of farmers to food systems. Notably, farmers' technology adoption decisions are key to food system outcomes. The findings reported suggest that these crop support technologies could potentially deliver major benefits to farmers, consumers, and the environment. For the moment, however, this emerging literature remains largely neglected. Possible reasons for this are considered, as are potential ways forward. The review focuses particularly on the two most researched and widely available microalgae, the genera Arthrospira and Chlorella, in the interest of highlighting options farmers could adopt rapidly while research on the wider body of microalgae-based crop technologies continues. [ABSTRACT FROM AUTHOR]

Land degradation in communal rangelands poses significant challenges to environmental sustainability, agricultural productivity, and livelihoods in southern Africa. This study presents a bibliometric analysis of research trends, key contributors, thematic evolution, and collaborative networks in the field of land degradation in communal rangelands from 1997 to 2024. Utilizing data obtained from the Scopus database, we examined 66 publications to identify patterns in publication output, leading journals, influential articles, and prominent authors and institutions. The analysis demonstrates an overall increase in research output, with a notable surge in publications during the past decade, indicating a growing academic and policy interest in this field. Major themes identified include sustainable land management, restoration strategies, and the impacts of grazing management on ecosystem health. Networks showcasing co-authorship and keyword co-occurrence reveal robust collaborative connections among researchers and a concentrated focus on specific dominant themes. Consequently, these findings propose opportunities for expanding interdisciplinary research and exploring underrepresented areas. This study provides a comprehensive overview of the research landscape, offering insights to steer future studies and inform policy interventions aimed at mitigating land degradation and bolstering the resilience of communal rangelands in southern Africa. [ABSTRACT FROM AUTHOR]

Soil erosion is a global issue—with gully erosion recognized as one of the most important forms of land degradation. The purpose of this study is to compare and contrast the outcomes of four machine learning models, Classification and Regression (CART), eXtreme Gradient Boosting (XGBoost), Random Forest (RF), and Support Vector Machine (SVM), used for mapping susceptibility to soil gully erosion. The controlling factors of gully erosion in the Piraí Drainage Basin, Paraíba do Sul Middle Valley were analysed by image interpretation in Google Earth and gully erosion samples (n = 159) were used for modelling and spatial prediction. The XGBoost and RF models achieved identical results for the area under the receiver operating characteristic curve (AUROC = 88.50%), followed by the SVM and CART models, respectively (AUROC = 86.17%; AUROC = 85.11%). In all models analysed, the importance of the main controlling factors predominated among Lineaments, Land Use and Cover, Slope, Elevation and Rainfall, highlighting the need to understand the landscape. The XGBoost model, considering a smaller number of false negatives in spatial prediction, was considered the most appropriate, compared to the Random Forest model. It is noteworthy that the XGBoost model made it possible to validate the hypothesis of the study area, for susceptibility to gully erosion and identifying that 9.47% of the Piraí Drainage Basin is susceptible to gully erosion. Furthermore, replicable methodologies are evidenced by their rapid applicability at different scales. [ABSTRACT FROM AUTHOR]

Forest roads have been recognized as one of the significant contributors to soil erosion processes in forested areas. The construction and maintenance of forest roads can cause severe environmental impacts, including soil erosion, sedimentation, and degradation of aquatic ecosystems. The main objective of the present study is to analyze the impact of forest road networks on soil erosion and sedimentation in the context of the Zagros forestlands, Iran. This study aims to assess the soil erosion and sedimentation on forest roads in four case studies in the Zagros forestlands. This study collected data using field surveys and SEDMODL equations to determine input factors and sedimentation and erosion rates. This study found that roadside erosion is strongly correlated with geological factors, road width, and precipitation factors. The height changes of 144 benchmarks were recorded during one study year (2021–2022) on four study roads, and the measured results of erosion benchmarks indicated an average soil erosion of 3, 2.6, 4.7, and 3.5 mm per year around the Bideleh, Kohian, Nazi, and Tabarak roads, respectively. This study measured soil erosion and sedimentation at three distances (5, 15, and 25 m) from the road, and found a significant difference in the height changes of the benchmarks at varying distances from the study roads. A hot-spot analysis was conducted using GIS 10.8, and the results indicated that a significant portion of the studied forest roads had very high erosion production and hot spots. The results of the hot-spot analysis indicated that 30.8%, 22.6%, 39.8%, and 14.5% of the study forest roads, Nazi, Tabarak, Bideleh, and Kohian roads, respectively, are identified as areas with very high erosion production and hot spots. These results highlight the need for effective management strategies to minimize the impact of erosion on road infrastructure and the surrounding environment. Overall, this study provides important insights into the soil erosion and sedimentation on forest roads, and the findings presented here can be used to inform future road construction and maintenance. [ABSTRACT FROM AUTHOR]

Coal gangue hill, a significant anthropogenic interference, can cause various forms of land degradation. The promoting effect of coal gangue on soil qualities has also been discovered. However, few studies investigated the soil properties and microbiome of prolonged gangue hills. Here, we investigated soil microbial communities and chemical properties in a vegetated gangue hill and adjacent cropland and wasteland (regarded as gangue‐free lands). We did not find any significant differences in the content of organic matter, total nitrogen, and total phosphorus between the gangue hill and the cropland (Kruskal–Wallis test, p > 0.05). The content of all metals we investigated (Pb, Ni, Sb, Fe, and Al) did not exceed the risk control values (GB 15618‐2018; GB 36600‐2018). The content of Fe and soil electrical conductivity of the gangue hill was significantly higher than the gangue‐free lands (about 2 times and 20 times, respectively), which were also the key factors shaping microbial communities (Mantel's test, p < 0.05). There were no significant differences in the composition of the bacterial communities between the gangue hill and gangue‐free lands. The random‐forest model identified four species belonging to Actinobacteria and Ascomycota as the unique species in the gangue hill. Functional annotation revealed that the significant differences between the two land types were in bacterial nutrition types, fungal saprophytic types, and nitrogen cycling. Our study provided a theoretical foundation for land management and sustainable utilization in abandoned mining areas. [ABSTRACT FROM AUTHOR]

Land restoration and sustainable land management projects have now been proposed for up to a billion hectares globally, responding to continuous land degradation processes. But, a lack of reliable cost estimates hinders implementation, which results in a high perceived risk of restoration investments. This study addresses this gap, using cost data from 243 restoration projects from multiple sources to estimate the cost ranges for different types of restoration more precisely. The analysis shows median restoration costs vary from 185 $US/ha to 3012 $US/ha depending on the restoration measure, implying current global land restoration commitment cost 0.04%–0.27% of annual global GDP to implement. Since the majority of these commitments are made by developing countries, international cost‐sharing mechanisms, through climate or private finance, are required to move from goal setting to implementation. [ABSTRACT FROM AUTHOR]

Soil erosion emerged as a significant land degradation concern, causing serious threat to soil ecosystem services in the Himalayan region. The complex topography of the region poses limitations to the measurement of soil redistribution (erosion, transport, and deposition) rate, necessitated for the effective soil conservation planning. The study investigated soil redistribution processes over a typical complex hillslope of the mid‐Himalayan region using the fallout radionuclide (FRN)—137Cs method and Revised Universal Soil Loss Equation (RUSLE) model. It involved a comparison of 137Cs measured soil redistribution and the RUSLE model estimates, aiming to assess its correspondence over the complex hillslope. Analysis of 137Cs measurements revealed the highest net erosion (−13.2 t ha−1 year−1) at the upper hillslope with a convex shape, while sediment deposition occurred at the lower (36.9 t ha−1 year−1) and valley (32.5 t ha−1 year−1) hillslope positions with a concave shape. The RUSLE model also estimated the highest erosion on the upper hillslope (−12.3 t ha−1 year−1) but the lowest erosion at the lower (−0.88 t ha−1 year−1) and valley (−0.32 t ha−1 year−1) hillslopes, that differed with the 137Cs method. The 137Cs method provided soil redistribution rate (either net erosion or deposition), whereas RUSLE model only showed the gross erosion rate. Thus, the estimate from RUSLE corresponds only to hillslope positions with a convex and straight shapes. The distribution of 137Cs measurements has clearly revealed the influence of slope shape and steepness in governing erosion and deposition processes at the hillslope positions with convex and concave slope shapes, respectively. In addition, terraces effectively trap sediments from upslope areas. Investigation of soil erosion using 137Cs measurement along with the RUSLE model helped to validate erosion and deposition processes over the hillslope positions. The study will help to suggest suitable conservation measures for the various hillslope positions in the mid‐Himalayan region. [ABSTRACT FROM AUTHOR]

Assessing drought impacts is necessary for pursuing sustainable development goals relevant to food security and land degradation. Data availability is a major restriction and remote sensing has been promoted for this purpose. Version 3 of WaPOR has been released in 2023, which provides global coverage of remote sensing–derived water productivity indicators and could allow improved analysis of drought impacts, but validation is still needed. This study explores the utility of remote sensing–derived productivity data from WaPOR as a proxy indicator for agricultural drought impacts. The analysis utilized (1) production surveys, (2) meteorological measurements for drought analysis, and (3) remote sensing–derived gross and net biomass water productivities (GBWP & NBWP) and total biomass production (TBP). All layers were analyzed against the Standardized Precipitation and Standardized Precipitation Evapotranspiration Indices (SPI and SPEI) over drought-vulnerable locations in Irbid and Madaba governorates in Jordan. Strong and significant correlations (R2 0.5–0.8, P < 0.05) were obtained between drought intensities and GBWP and NBWP layers, particularly in the May–Sep periods. These correlations were higher than previously tested remotely sensed indicators for agricultural drought impacts. Water productivity and biomass production averages were lower during drier periods and higher during wet periods, but pairwise testing did not reveal significant differences. There is sufficient evidence that WaPOR data demonstrates behavior that reflects agricultural response to drought, and further assessment in other agroclimatic zones is recommended. This could potentially allow for enhanced evaluation of management strategies, decision support, and policy recommendations for drought mitigation. [ABSTRACT FROM AUTHOR]

In the Sahel region of West Africa, land degradation has raised concerns about the threat of desertification, leading to the establishment of the United Nations Convention to Combat Desertification (UNCCD) in 1994. Over time, the focus has shifted from simply combating desertification to a more comprehensive international program focused on preserving the health of our land by offsetting any damage with restoration efforts by 2030 to sustain ecosystem functions and services. This balancing process—which is in line with the Sustainable Development Goals (SDGs)—is known as Land Degradation Neutrality (LDN). We examine Land Degradation Neutrality (LDN) patterns, namely degradation and rehabilitation processes, by integrating participatory mapping with high-resolution satellite imagery with local stories, observations, historical records, and existing studies. The data elicited an understanding of the processes driving land degradation and adaptation strategies among three distinct ethnic groups of crop and livestock farmers in the village of Yallé in southern Burkina Faso. Some of these people were originally from this region, while others moved from places where the land was already degraded. Participants in the study had diverse experiences and perceptions of land degradation, its drivers, and adaptation strategies, which were influenced by their ethnicity, livelihood activities, and life experiences. These differences highlight the impact of cultural and socioeconomic factors on how people view land degradation, as well as the role of local knowledge in managing the environment. The study emphasizes the necessity of incorporating ethnoecological perspectives into projects focused on Land Degradation Neutrality (LDN) to better understand land degradation and improve land management. This integration can significantly contribute to strengthening global sustainability and community resilience. [ABSTRACT FROM AUTHOR]

Despite technological growth and worldwide advancements in various fields, the agriculture sector continues to face numerous challenges such as desertification, environmental pollution, resource scarcity, and the excessive use of pesticides and inorganic fertilizers. These unsustainable problems in agricultural field can lead to land degradation, threaten food security, affect the economy, and put human health at risk. To mitigate these global issues, it is essential for researchers and agricultural professionals to promote advancements in smart agriculture by integrating modern technologies such as Internet of Things (IoT), Unmanned Aerial Vehicles (UAVs), Wireless Sensor Networks (WSNs), and more. Among these technologies, this paper focuses on UAVs, particularly quadcopters, which can assist in each phase of the agricultural cycle and improve productivity, quality, and sustainability. With their diverse capabilities, quadcopters have become the most widely used UAVs in smart agriculture and are frequently utilized by researchers in various projects. To explore the different aspects of quadcopters' use in smart agriculture, this paper focuses on the following: (a) the unique advantages of quadcopters over other UAVs, including an examination of the quadcopter types particularly used in smart agriculture; (b) various agricultural missions where quadcopters are deployed, with examples highlighting their indispensable role; (c) the modelling of quadcopters, from configurations to the derivation of mathematical equations, to create a well-modelled system that closely represents real-world conditions; and (d) the challenges that must be addressed, along with suggestions for future research to ensure sustainable development. Although the use of UAVs in smart agriculture has been discussed in other papers, to the best of our knowledge, none have specifically examined the most popular among them, "quadcopters", and their particular use in smart agriculture in terms of types, applications, and modelling techniques. Therefore, this paper provides a comprehensive survey of quadcopters' use in smart agriculture and offers researchers and engineers valuable insights into this evolving field, presenting a roadmap for future enhancements and developments. [ABSTRACT FROM AUTHOR]

The objective of this study was to analyse the potential impact of future climate change on grassland cover in Burkina Faso. MODIS NDVI 250 m time series were used to monitor changes in grassland over 2000–2022. The random forest regression (RFR) model was fit by regressing reference data of grassland cover against current climatic and other environmental predictors to predict the current grassland cover map (2022). Projected climate model data of CMIP6 used under SSP 126 and SSP 585 scenarios were integrated into the fit RFR model to predict future change. The results revealed that grassland areas were largely dominated by non-significant productivity change (55%) during 2000–2022. In this period, grassland area knew more increased productivity (35%) than decrease (10%). Burkina Faso is predicted to face more decreased areas of grassland cover than increase by 2061–2080 under SSP 126 and SSP 585 scenarios. The findings of this study can help to set up appropriate adaptation measures to combat climate change in Burkina Faso. [ABSTRACT FROM AUTHOR]

Despite the significant biodiversity in the Cerrado, the process of occupation, subsequent economic cycles, and intensification of agriculture in a predatory manner have caused profound alterations in this biome. This study analyzed changes in land use and land cover in the Cerrado of Mato Grosso do Sul between 1985 and 2022 by mapping and also investigating the formation and dynamics of sand dunes in the Bauru sedimentary basin, focusing on the Pardo River watershed. MapBiomas Network data, collection 8, were used for land use and land cover analysis. Arenization foci cartography was conducted using brightness index 2 based on Sentinel-2 satellite images in Sentinel Application Platform software. The historical analysis of land use and cover in the Cerrado of Mato Grosso do Sul revealed a rapid transformation of the landscape, with a drastic reduction of native vegetation and an intensification of large-scale monocultures. Between 1985 and 2022, the Cerrado of Mato Grosso Sul lost 4.6 million hectares of native vegetation (forest formations, savannahs, grasslands, and wetlands), representing 24.54% of this territory. Recent changes in land use include pasture-soybean and pasture-eucalyptus. In the Pardo River watershed, arenization foci cover an area of 17,834.34 hectares, with varying dimensions ranging from less than 1 hectare to 376.41 hectares. The arenization process occurs in different slope compartments, such as the base, slope, and interfluves. The physical and chemical characteristics of Quartzipsamments, such as low organic carbon content in soil, are associated with high rates of surface exposure and weakened load-dependent structures, leading to degradation. Arenization occurs where natural vegetation has been suppressed and soil has been depleted by poorly managed production processes. [ABSTRACT FROM AUTHOR]

The pastoral station is an under-examined location space in Australia’s screen history. Using the case study of Belmont Station in far west NSW and focusing specifically on the production of television advertisements in the 1980s−1990s, this article proposes the pastoral station as a popular filming location for Australian ‘outback’ imaginaries. Furthermore, I argue that the station has embedded environmental and spatial histories that have enabled it to develop as a film-friendly screen infrastructure. Firstly, the article proposes a new approach to screen studies in Australia that draws from media infrastructures and environmental history to address previously unknown screen production histories. The article then introduces the pastoral station in line with the reoccurring aesthetics of the ‘outback’ imaginary. Finally, it examines how the environmental affordances of the station such as geography, property holdings, and in-house labour ensured a film-friendly location space. Reflecting on environmental histories, it reveals how land degradation caused by settler-colonial industries has shaped the geophysical environment, and how this has in turn shaped the ‘outback’ imaginary. Overall, the article purports that by examining how screen production is co-produced by humans and non-humans, new screen histories are illuminated. [ABSTRACT FROM AUTHOR]

Migration-induced land degradation is a challenging environmental issue in Sub-Saharan Africa. The need for expansion due to urban development has raised the question of effective sustainable measures. Understanding migration and land degradation links is paramount for sustainable urban development and resource use. This is particularly true in Nigeria, where elevated migration levels frequently result in accelerated land degradation due to urban expansion. Given the need to understand the impact of migration on land degradation in the Savannah Region of Nigeria (SRN), this study introduces a novel approach by integrating remote sensing data (NDVI, NDBI) with local community perceptions (mixed-methods approach) to assess the impact of migration on land degradation in four migration destination communities located in two local government areas (LGAs) (Sabon Gari East and Sabon Gari West of Fagge LGA; Zuba and Tungamaje of Gwagwalada LGA). We conducted focus group discussions and a semi-structured survey with 360 household heads to obtain a comprehensive view of perceptions. Our findings revealed that 41.1% and 29.5% of the respondents agreed and strongly agreed that migration significantly contributes to land degradation. We analysed the spatiotemporal patterns of the Normalised Difference Vegetation Index (NDVI) and the Normalised Difference Built-Up Index (NDBI) acquired from Landsat 8 datasets for 2014 to 2023. While increasing NDBI values were observed in all communities, a slight decrease in NDVI was noted in Sabon Gari East and Tungamaje. Our analyses highlighted activities leading to land degradation such as land pressure due to built-up expansion at Sabon Gari East, Sabon Gari West, and Tungamaje, and deforestation at Zuba. Based on the varying challenges of migration-induced land degradation, we recommend adequate community participation in suggesting targeted interventions and policies to foster various adaptive capacities and sustainable environments within SRN communities and Sub-Saharan Africa. [ABSTRACT FROM AUTHOR]

Land degradation is a significant global environmental issue, and its prevention has become a serious concern of the twenty-first century, particularly in the context of anthropogenic impact and climate change. It is crucial to map and assess the grade of land degradation to determine vulnerable areas. The Indian Himalayan region faces heightened risks with its steep terrain, active tectonics, heavy precipitation, and human interventions. This study focuses on the Nandakini Watershed. Employing AHP technique, the study calculates the Land Degradation Vulnerability Index (LDVI) using slope, terrain ruggedness, rainfall, temperature, LULC, soil depth, and organic carbon content. The results indicate that the upper region is highly vulnerable, and a higher slope influences the runoff in the area, followed by factors like NDVI and rainfall, collectively contributing to 62% of the overall index. In this context, the upstream regions of the watershed display a high LDVI, while most of the area falls within the low LDVI category. This indicates that approximately 2.10% of the study area is highly susceptible to soil erosion. RUSLE-based estimates have been used to further validate the LDVI result. The integrated LDVI offers a valuable tool for prioritising soil conservation and disaster mitigation. [ABSTRACT FROM AUTHOR]

Under perpetual growth-geared economic, governance and sociocultural systems, continued increases in agricultural output are necessary to feed an ever-expanding human population, as well as neoliberal appetites for financial profitability. These translate to intensifying and expanding agri landscapes. Yet agribusiness industries routinely seek to obfuscate visual tangibility of their production practices and impacts from public view. A gap exists in public availability of high-resolution imagery depicting Australian agriculture's industrial scales, degraded lands and landscape impacts. This visualisation endeavour is situated between the blurry and pixelated resolution of freely available agricultural satellite imagery, and agri- marketings' frequently glossy, colour-saturated and romanticised depictions from on-ground photography and video. Positioned between these two purviews, the drone-eye-view provides sharp and incisive imagery contributing new insights into agri- landscapes and practices. This visual essay draws from drone imagery captured during continental-scale field research spanning all Australian states and territories, all commodities and major industries, and all scales of commercial farming. As Australian agribusiness is landscape and resource extractive in its geometric pattern arrays, transmuted images are extricated from aerial stills and videos into compositional strips. Together with the poetic and interpretative text, the work reveals industrial and degraded landscapes at nested scales, links foods with their production contexts, and is suggestive of the state of Australia's agricultural environment. [ABSTRACT FROM AUTHOR]

This study carries out a comprehensive bibliometric analysis of scientific production on wildfires, soil erosion and land degradation, with the aim of understanding trends, critical gaps in scientific knowledge and research patterns. A total of 1400 articles published between 2001 and 2023 were analyzed with bibliometric tools (Bibliometrix and VOSviewer), revealing a steady growth in the number of publications over time. International collaboration between countries such as the United States, Spain, China and Portugal is evident, highlighting the global approach to tackling these issues, as well as the mobility and collaboration between scientists. Analyzing the conceptual structure through the co-occurrence of keywords reveals central themes such as "soil erosion" and "wildfire", indicating areas of primary focus in research. This study highlights the continuing importance of these themes and the need for global collaboration to tackle the environmental challenges affecting forest ecosystems, and particularly the soil layer, caused by wildfires, which affect wildlands all over the world. [ABSTRACT FROM AUTHOR]

Caatinga is a typical Brazilian biome facing severe threats despite its ecological and socio-economic importance. Conservation strategies are essential in protecting ecosystems and ensuring natural resource sustainability. Mata da Pimenteira State Park (PEMP), launched in 2012, is an example of such a strategy. The current study aims to use orbital remote sensing techniques to assess human impacts on changes in land use and land cover (LULC) after the establishment of PEMP in the semi-arid region known as Caatinga, in Pernambuco State. The effects of this unit on vegetation preservation were specifically analyzed based on using data from the MapBiomas Brasil project to assess trends in LULC, both in and around PEMP, from 2002 to 2020. Man–Kendall and Pettitt statistical tests were applied to identify significant changes, such as converting forest areas into pastures and agricultural plantations. Trends of the loss and gain of LULC were observed over the years, such as forest areas' conversion into pasture and vice versa, mainly before and after PEMP implementation. These findings highlight the importance of developing conservation measures and planning to help protecting the Caatinga, which is a vital biome in Brazil. [ABSTRACT FROM AUTHOR]

Cultivated land degradation has seriously threatened to the national food security and sustainable land use. Among them, the sustainability of cultivated land can decrease or even completely lose, when it is subjected to the external disturbance. This temporal and spatial evolution can represent the cultivated land quality and ecological degradation. Significant mutual feedback between them can also impact the cultivated land degradation. It is crucial to clarify the mechanisms of cultivated land degradation and governance strategies, in order to ensure the national food security and sustainable utilization of cultivated land. Most existing studies have been focused on the evaluation and monitoring of cultivated land degradation. However, it is still lacking to consider the "comprehensive" interaction between the quality and ecological degradation of cultivated land. Furthermore, it is a high demand to clarify the influencing factors and mechanism of cultivated land degradation for the effective countermeasures. In this study, a novel system was constructed to measure the cultivated land degradation from the mutual feedback perspective of quality and ecology. Shenyang City in the typical Liaoning Plain area was also selected as the research area. The spatiotemporal characteristics, influence mechanisms and governance strategies of cultivated land degradation were explored using principal component analysis, objective weighting, exploratory regression, geographical weighted regression, quantile regression, and fuzzy data set comparison. The results show: 1) The proportion of cultivated land quality degradation was 35.31% in the study area, indicating a "strong east, weak west" spatiotemporal pattern; The proportion of cultivated land ecological degradation was 79.10%, with the spatiotemporal pattern of "strong north, weak south"; According to the quality and ecological mutual feedback, the proportion of cultivated land degradation was 37.80%, indicating a “strong north and south, weak middle” spatiotemporal pattern. 2) The temperature, vegetation coverage, urbanization, irrigation capacity and environmental pollution were the key natural conditions and socio-economic factors, leading to the degradation of cultivated land in the study area. The spatial heterogeneity was found in the effects of these factors on cultivated land degradation in different regions. There were the non-stationarity effects of development stages on the cultivated land degradation. Different structural configurations were formed to synergistically affect the cultivated land degradation. There were the regional, periodical, and structural influence mechanisms of cultivated land degradation. 3) According to the intensity of cultivated land degradation in the different regions, the different influencing factors and the action path of multi-factor combination, the graded and zonal protection of cultivated land was established to utilize and control the multi-factor concurrent collaborative governance and security path. The impact mechanism of cultivates land degradation was obtained from the perspective of quality and ecological mutual requirements. The finding can provide the policy reference for the accurate, efficient and collaborative management of degraded cultivated land. The synchronous quality and ecological environment of cultivated land can be expected to resist external adverse factors. [ABSTRACT FROM AUTHOR]

Copyright of Journal of Resources & Ecology is the property of Journal of Resources & Ecology and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Arid Zone Research / Ganhanqu Yanjiu is the property of Arid Zone Research Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Arid Zone Research / Ganhanqu Yanjiu is the property of Arid Zone Research Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The study was aimed at identifying the potential of modern methods of rational land use in the Karasai district of the Almaty region of Kazakhstan, taking into account their intensive degradation. The research methodology was represented by the methods of statistical observation, comparison, analytical-structural grouping and forecasting. The priority goals of modernisation of agriculture of the Republic in the technological aspect have been analysed. It was established that innovative approaches to land use have the potential to increase the level of efficiency of the agrarian sector, improve the state of local and regional landscape. The concept of improving the state of degraded lands, including a system of management measures and practical activities, has been developed. It was proved that it should be based on the synergy of economic efficiency and environmental safety, with the mandatory introduction of modern innovative technological approaches. The effectiveness of methods of rational use of degraded lands as an effective tool for the transformation of the agrarian sector has been determined. It was proposed to intensify the development of organic agricultural production, which is positioned as the gentlest for degraded landscapes. It was proved that the implementation of sustainable management of landscape complexes in the innovative context implies the use of information monitoring technology, which anticipates the diagnosis, genesis and forecasting of the state of the studied ecosystems. Such measures will make it possible to develop programmes for the restoration of ecological functions of natural landscapes, which is an integral part of sustainable development programmes. Actualised the situation in the context of ecologisation of land use in Kazakhstan, predicted further destruction of ecosystems of agrarian landscapes in case of use of aggressive methods of soil cultivation. The necessity of introduction of improved methods of rational land use is substantiated, and the specificity of the introduction of organic and biological technologies of agricultural production is outlined, with an indication of tangential risks and challenges in the economic realities of Kazakhstan. The study substantiated that the application of integrated management and ecosystem approach have a synergistic potential to ensure the rational use of land in the Almaty region, the Karasai district in the conditions of their degradation. [ABSTRACT FROM AUTHOR]

1-Introduction Soil erosion is one of the most important environmental issues in the world; so that, soils that are affected by degradation processes such as compaction, loss of nutrients and water retention capacity lead to soil erosion and loss in fertile agricultural lands. Gully erosion is the most severe type of water erosion, which is one of the main factors of land degradation. Spatial forecasting of gully erosion using models that are based on land sensitivity to gully erosion and their output leads to the preparation of gully erosion risk maps in the form of gully erosion is the most suitable strategy for land management planning in watersheds to prevent gully erosion. If there is a zoning map of gully erosion in watersheds, economic and social damages could be controlled through appropriate measures and strategies in addition to preventing heavy costs to control gully erosion. According to the available models and relationships, it can be concluded that the most efforts in gully erosion modeling have been focused on the location of gullies as well as predicting the possibility or non-possibility of gully occurrence; So that, only a part of the effective factors have been investigated due to variability of factors affecting the gully. While the present research aims to determine the most important factors affecting the gully erosion and prioritize the factors and finally zoning the gully points and sensitivity to the gully in Maroon watershed. Maroon watershed is located in the southern and southwestern slopes of the Middle Zagros. The area of the watershed is 3837 km2, the maximum height from the sea level is 3420.3 m and the minimum is 372.8 m. The average annual rainfall is 815 mm, the long-term average annual temperature in te representative stations of the plains is and the stations located in the highlands are 19 and 16 ºC respectively. According to the Dumarten system, the climate type is Mediterranean to semi-arid. In summary, the present research was carried out as follows: 1) Selecting the area, preparation of the distribution map of gully occurrence (dependent variable) and its random division into two training or calibration (70 percent) and experimental or forecasting (30 percent) categories, 2) preparation of the maps of 23 effective factors (independent variables), 3) selecting the effective factors using alignment test between the effective factors and the occurrence of gullies, 4) running the model, 5) validation and evaluation of the model, and 6) preparation of a zoning map of susceptibility to gully erosion. In the present study, the location of gullies created in the Takht Daraz watershed was first recorded by field visit, and based on the recorded points, they were divided into two groups of training data (70%) and experimental data (30%) respectively in order to calibrate and validate the models. 23 factors affecting the occurrence of gully erosion were identified based on scientific references and watershed conditions, and their maps were prepared in ARCGIS environment. The weight of these factors was determined based on the frequency ratio, and then the correlation of the effective factors was investigated using the collinearity test. In the next step, the maximum entropy model was calibrated and validated using the weighted data of the effective factors and the spatial training and experimental data of the gully distribution. The Jackknife test and the receiver operating characteristic index were respectively used to determine the thresholds of effective factors in the occurrence of gully erosion as well as evaluating the efficiency of the studied models. 3-Results According to the collinearity analysis, the variance inflation rate of the investigated variables was less than 0.5, which indicates the non-collinearity between the investigated variables and all the variables were included in the modeling process. Based on the results of MaxEnt model (maximum entropy), a gully erosion sensitivity map was obtained, based on which the very high sensitivity class with 52 percent of gully occurrences has the highest density of gullies; So that the ratio of the frequency of gullies in this class was 6.73 and the Seed Cell Index area was 0.15. The very low sensitivity class has the lowest amount and frequency ratio of gully by 0.02 and nuclear cell surface index at the rate of 46.8. According to the information obtained from the map, the highest percentage of the area is related to very low sensitivity class (46%), which has eight pixels of gullies, and the lowest area of the watershed is related to the very high sensitivity class (8%) which has 420 pixels of gully. In general, based on the maximum entropy method, 34% of the watershed is in the medium to very high sensitivity class. Also, the validation results of the maximum entropy model based on the index of the area under the curve (AUC) showed that the area under the curve in this method was 0.85, which indicates the high accuracy of the maximum entropy model. 4-Discussion & Conclusions In the present study, the spatial distribution of gullies and its relationship with the effective environmental parameters of the Takht Daraz basin have been used in order to evaluate the sensitivity of gully erosion. For this purpose, different methods and models including witness weight, belief model and entropy method have been used to prepare a gully erosion sensitivity map. Google Earth image interpretation, past research and extensive field visits were used to prepare the gully distribution map, and 70% of the gullies were used for modeling and 30% for validation. In the field of effective parameters in gully erosion, 23 effective parameters were identified and prepared using research literature, access to data and environmental conditions of the study area. The results showed that the entropy model with the area under the curve (AUC) of 0.86 had high prediction accuracy. The results of the effective factors on gully erosion showed that according to the Jackknife test, the lithological factor had the greatest effect on the areas under the curve. The results of determining the parameters weight also showed that different parameters have different participation rates in the gully erosion occurrence; so that, the parameters of land-use and geology had the largest share of participation in the occurrence of gully erosion, with a contribution of 24% and 18% respectively. [ABSTRACT FROM AUTHOR]

Historical sheep farming in the Patagonian drylands has led to reduced grass cover, soil erosion, and shrub encroachment, compromising ecosystem function. Effective restoration requires managing shrub cover, bare soil, and patch connectivity through various strategies. This study evaluates rehabilitation interventions in a grass-steppe ecosystem, comparing grazed and ungrazed areas. Over three years, we tested the following: (a) mechanical shrub cutting with biomass redistribution, and (b) enhancing patch connectivity with Pinus spp. branch piles, alongside controls, in eighteen 5 m × 5 m plots invaded by Mulinum spinosum. Half of the plots were fenced to exclude grazing, resulting in six treatment combinations. We monitored soil properties, vegetation cover, and species composition. The treatments explained twice as much of the variation in community composition as the annual climatic variations (0.26 vs. 0.13). Livestock exclusion increased perennial grass cover more than the grazed plots did (2.14 vs. 1.42 times the initial measure). All treatments reduced the amount of bare soil except the grazed controls. Shrub cutting, especially with grazing, increased the lasting litter coverage by 5–10% and decreased the bare soil equivalently. Organic matter increased except in the non-intervened interpatches (0.95 times). The enclosures with cut shrubs trapped erodible particles, showing a 5% increase. Our study highlights that grazing destabilizes communities, while enclosures stabilize them, with interventions improving soil fertility and mitigating erosion. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The escalating rates of deforestation, compounded by land degradation arising from intensified mining operations, forest fires, encroachments, and road infrastructure, among other factors, are severely disrupting the botanical and soil ecology of tropical ecosystems. This research focused on the upper Narmada River catchment area in central India, employing geospatial methodologies to assess land use and land cover (LULC) changes. Landsat 5, 7, and 8 satellite data for 2000, 2010, and 2022 were digitally classified using the maximum likelihood algorithm within the ERDAS IMAGINE and ArcGIS platforms. LULC was delineated into five categories (i.e., water bodies, built-up land, agricultural areas, forested regions, and fallow land). A spatio-temporal analysis revealed substantial declines of approximately 156 km2 in fallow land and 148 km2 in forested areas, accounting for 3.21% of the total area, while built-up land, water bodies, and agriculture land expanded between 2000 and 2022. There was a notable negative correlation observed between the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) across all LULC categories, except water bodies. The Land Degradation Vulnerability Index indicated that fallow lands, followed by forests and agriculture areas, exhibited a high vulnerability, with 43.16% of the landscape being categorized as vulnerable over the past 22 years. This study underscores the imperative of effective ecological restoration to mitigate land degradation processes and foster resilient ecosystems. The findings emphasize the importance of integrating scientific data into policy-making frameworks to ensure the comprehensive and timely management of the Narmada River landscape. [ABSTRACT FROM AUTHOR]

Rangeland restoration in southern Africa faces complex challenges that require the involvement of diverse social groups to ensure both ecological and social sustainability. This systematic review focuses on the role of social inclusion in rangeland restoration across multiple countries in the region, specifically examining the engagement of marginalized groups such as women, youth, and indigenous communities. We conducted a comprehensive search using the PRISMA approach, utilizing Scopus and other literature sources. Initially, we found 853 articles published between 2000 and 2024, which were subsequently screened down to 20 studies that met stringent inclusion criteria. This review identifies key strategies and outcomes associated with social inclusion in restoration efforts. Our findings reveal that participatory planning, gender-inclusive strategies, indigenous engagement, and capacity building are crucial for gaining community support, promoting social equity, and enhancing ecological resilience. However, challenges such as power dynamics, cultural norms, and resource constraints often impede the full realization of these inclusive practices. Despite these barriers, integrating local and indigenous knowledge and empowering marginalized groups significantly strengthens governance structures and leads to more sustainable restoration outcomes. Our review highlights the necessity of adopting holistic and inclusive approaches in rangeland restoration where social inclusion is not just a component but a central pillar of successful ecological management. It emphasizes the importance of social inclusion in the restoration of communal rangelands in southern Africa and provides insights into the approaches used, challenges faced, and outcomes achieved in incorporating social inclusion in rangeland restoration efforts. Our findings underscore the significance of collaborative efforts and social inclusion among local communities, policymakers, and stakeholders to achieve the sustainable restoration of communal rangelands in southern Africa. [ABSTRACT FROM AUTHOR]

Land degradation is a major threat to sub-Saharan Africa rangelands, which are crucial for livestock farming and the livelihood of millions of people in the region. This systematic review aims to provide a comprehensive understanding of the causes and effects of land degradation, as well as to evaluate the effectiveness of different mitigation strategies. Following the PRISMA guidelines, we identified, screened, and analyzed 25 peer-reviewed articles published before 30 June 2024 using Scopus. The review highlights key factors that drive land degradation, such as soil erosion, drought, deforestation, and climate change, as well as socio-economic factors like poverty, land tenure issues, population pressure, and economic instability. These factors have serious implications, as land degradation can lead to poor quality of forage, an increased incidence of diseases, higher mortality rates among livestock, and a significant decline in livestock productivity. The socio-economic consequences of this degradation are significant, leading to reduced household income, increased poverty, and heightened food insecurity. Furthermore, the review assesses various mitigation strategies and concludes that practices such as rotational grazing and soil conservation techniques demonstrate high effectiveness, while agroforestry practices show only moderate success. An integrated approach that combines environmental, economic, and policy measures is crucial to addressing the complex challenge of land degradation in sub-Saharan Africa. Strengthening land tenure, improving economic stability, and promoting sustainable agricultural practices are essential steps toward improving the health of rangelands, increasing livestock productivity, and supporting the resilience and well-being of rural communities. [ABSTRACT FROM AUTHOR]

Land use and its change impact food security, carbon cycling, biodiversity, and, hence, the condition of ecosystems to mitigate and adapt to climate change, support economic prosperity, and human well-being. To support and guide policy actions between the economy and the environment, harmonized time series datasets, transparent methodologies, and easily interpretable statistics are needed. Therefore, monitoring of the function and condition of lands and their change, along with properly agreed methodologies and freely accessible data, are essential. The Copernicus Land Monitoring Service has produced over 20 years of Corine Land Cover datasets for 39 countries in Europe, which allows continental-wide harmonized and comparable monitoring and accounting of land cover and land use change at a high thematic resolution and in a long time series (2000–2018). With the upcoming 2024 update, the time series will reach a unique product worldwide in terms of time series length, spatial resolution, extent, and thematic detail, enabling policymakers and the scientific community to address the main anthropogenic drivers of land and ecosystem degradation. This paper describes a unified approach for producing continental-wide land accounts that aligns with internationally agreed-upon standards for measuring the environment and its relationship with the economy. Furthermore, the study provides a harmonized time series of geospatial data for deriving land accounts and provides statistics of land cover and land use status and changes for a twenty-year period. All geospatial data and statistics presented in this paper are freely accessible and downloadable to serve other studies. [ABSTRACT FROM AUTHOR]

Land degradation is a global issue with severe implications for local sustainability, regional development, and resilience of socio-environmental systems. Curbing land degradation has become a priority in international strategies and sustainable development goals. The present study examines land vulnerability to degradation and its influencing factors in Italian provinces over four decades (1970–2010). After a comprehensive scrutiny of the best regression strategy based on econometric tests, spatial effects were modelled with the Spatially Autoregressive model run cross-section (1970, 1990, 2010), comparing the results of different weighting matrices representative of short-haul, medium-haul, and long-haul spatial interactions. Multiple (socioeconomic) drivers of land degradation were identified and classified according to their spatial effects. The results highlight the role of spatial interactions in shaping territorial models of land vulnerability to degradation, distinguishing on-site and off-site impacts. These outcomes emphasize the importance of comprehensive approaches that address a place-specific ensemble of socioeconomic drivers in tackling land degradation. A combination of local, regional, and national actions revealed more appropriate to curb unsustainable land practices in Mediterranean economies. [ABSTRACT FROM AUTHOR]

Soil moisture (SM) plays a crucial role in land–atmosphere interaction systems, directly influencing evapotranspiration, photosynthesis, and the water dynamics of the soil surface. Invariably, SM is negatively impacted by disturbances such as fires, which are becoming more frequent across semi-arid ecosystems. Different ecological restoration activities have been implemented to mitigate the impacts of disturbance that, when left untreated, can worsen the effects of recurrent droughts and accelerate desertification and land degradation processes. To measure and monitor the dynamics of SM, advanced techniques and tools have been developed that integrate remote sensing and in situ measurement. This review encompasses various themes on the application of remote sensing for measuring and monitoring SM dynamics in semi-arid ecosystems at different scales. We focused our analysis on the western United States region and thus have developed a review on the following topics: (a) the different data sources (e.g., satellite, unmanned aerial vehicles), (b) approaches to measure field-based SM, and (c) algorithms and techniques to model SM at different scales. We summarize these topics by emphasizing repeatable approaches for the transparent estimation of this variable, identifying current data gaps, and highlighting future trends to fulfill the expanding demand for SM monitoring strategies. [ABSTRACT FROM AUTHOR]

The present study investigates territorial disparities in selected socioeconomic forces and environmental factors underlying soil degradation that may lead to early desertification processes in a dry Mediterranean region exposed to increasing human pressure. To verify if spatial disparities in land resources have increased over time, a standard approach based on the Environmentally Sensitive Area Index (ESAI) was adopted to evaluate sixty years of territorial transformations in Latium, Central Italy, a region prone to intense processes of land resource depletion. The ESAI provides a standard, holistic assessment of soil degradation based on the estimation of four different 'resource qualities' (climate, soil, vegetation, and land use) and their change over sufficiently long time windows; in this study, the procedure was run at three reference years (1960, 1990, and 2020). The observed divergence in soil degradation levels between coastal and inland districts arose during the study period, with a consequent reduction in the local-scale variability of the ESAI. Such differential processes observed along the elevation gradient in Central Italy are likely due to anthropogenic factors affecting land use and leveraging crop intensification in flat districts and farmland abandonment in steep areas. New findings to be achieved in the context of human impacts on land resource depletion are regarded as an original contribution to the study of early desertification processes in advanced economies. [ABSTRACT FROM AUTHOR]

In recent decades, watersheds in the middle Himalayan belt have witnessed land degradation, flood, and landslide disasters. Growing population pressure, intensified use of watershed resources, and development activities—often alleged injudicious, have brought resource productivity and availability to the edge of unsustainability. The threat to precarious ecological balance, sustainable livelihood, and disaster risk is underpinning issues of densely populated Himalayan watersheds. Hence, understanding the essential physical characteristics of watersheds vis-à-vis human dimensions is essential for assessing and prioritizing the watersheds intended for ecological restoration, landslide and erosion control, and disaster risk reduction in upstream and downstream zones. Following these issues, this study using a geographical approach examines watershed variables representing susceptibility, hydrological and geomorphic response, land use, and human pressure to assess sub-watershed conditions and prioritize sub-watersheds. The study used high-resolution satellite imageries, digital elevation model, topographic and geological maps, rainfall and socioeconomic data from government sources to obtain the watershed variables. These variables were analyzed in the GIS platform. The leading variables and their relative importance were identified for assessing the watershed conditions by analyzing the correlation matrix, and AHP supported the expert judgment. These variables are mean basin slope, lineament density, drainage density, landslides, population density, and non-forest-forest ratio. The sub-watersheds condition of the Syangja District was assessed. The calculated overall vulnerability of sub-watersheds is positively related to susceptibility, poor land management, and human pressure index. The present study provided a methodological basis for assessing and prioritizing the watershed condition. [ABSTRACT FROM AUTHOR]

Population pressure is the most important underlying cause of land degradation in Ethiopia. While large-scale investments have been made for landscape restoration over years and commendable results are achieved, implementation of the national population policy has been unsatisfactory and the population has continued to grow fast. This challenge needs to be addressed if Ethiopia is to achieve environmental sustainability and socioeconomic development. This opinion note argues that the ongoing landscape restoration initiatives can be used as an effective platform to integrate and promote voluntary use of family planning and reproductive health services, because it is community-based, well-funded, participatory, and inclusive. Women are already key actors in the landscape restoration activities including representation in community leadership positions. This will facilitate buy-in and ownership of family planning and reproductive health services by enhancing community awareness and women’s empowerment to exercise their reproductive health rights if delivered as a component of the already established participatory landscape restoration activities implemented by co-leadership of community institutions. [ABSTRACT FROM AUTHOR]

This study evaluates the impact of sub-daily bias correction of gridded rainfall products (RPs) on the estimation rainfall erosivity in Burkina Faso (West African Sahel). Selected RPs, offering half-hourly to hourly rainfall, are assessed against 10 synoptic stations over the period 2001–2020 to appraise their accuracy. The optimal product (the integrated multi-satellite retrievals for GPM, IMERG) is further used as a reference for bias correction, to adjust the rainfall distribution in the remaining RPs. RPs-derived rainfall erosivity is compared to the global rainfall erosivity database (GloREDa) estimates. The findings indicate that bias correction improves the rainfall accuracy estimation for all RPs, in terms of quantitative, categorial metrics and spatial patterns. It also improved the distributions of rainfall event intensities and duration across all products, which further significantly improved the annual rainfall erosivity estimates at various timescales along with spatial patterns across the country, as compared to raw RPs. The study also highlights that bias correction is effective at aligning annual trends in rainfall with those in rainfall erosivity derived from RPs. The study therefore underscores the added value of bias correction as a practice for improving the rainfall representation in high-resolution RPs before long-term rainfall erosivity assessment, particularly in data-scarce regions vulnerable to land degradation. [ABSTRACT FROM AUTHOR]

Despite the large number of different antierosion practices used in the country, the dynamics of the areas of eroded lands remains multidirectional and unstable. The goal of the work was to propose a methodological approach for semantic modeling of sustainable land management with a focus on antierosion measures, the methods for such modeling and land management in the areas prone to soil erosion in order to maintain and restore degraded lands. A variety of erosion control techniques, methods, approaches, technologies and activities described in different sources, including databases on best practices, educational and scientific literature serves as objects of the study. The study was based on the integration of several working hypotheses and approaches proposed by the authors in earlier publications. The methodological basis of these approaches is the concept of land degradation neutrality (LDN) and the principles for assessing the "sustainability" of environmental management based on it. Using the example of several sites, methods for semantic modeling of the sustainability of antierosion land management are considered. These methods are based on assessing the achievement of LDN using so-called "good" practices. For the assessment, the following parameters of the model were applied: "natural potential" (reflecting resource potential, adaptive potential and the ability to self-recovery of land), "expanded potential" (reflecting human improvements in natural potential and the sufficiency of socioeconomic conditions); "actual adverse impacts," including natural processes and phenomena and those caused by human impact; and "potential adverse impacts," including natural and anthropogenic risks. Model parameters can be combined in the required combination and reflect different modeling tasks in order to determine the adequacy of erosion control practices, including general approaches and techniques for regional models, methods and technologies for subregional and local ones, and specific activities and measures for local models implemented for individual land plots and farms. The proposed method for visualizing models, based on the construction of radar diagrams, is a flexible solution that provides opportunity to consider the sufficiency of practices, combine them into groups, and also generalize sustainability parameters depending on the goals of modeling. [ABSTRACT FROM AUTHOR]

Land degradation is a global environmental problem that affects the livelihoods of communities. Understanding the extent and causative factors of this phenomenon is important to design the cause-targeted strategies to cope with this problem. This study aimed to assess the effects of biophysical and socio-economic factors on the occurrence of land productivity degradation at the territorial level in Eastern DR Congo, using the Kalehe territory as a case study. The land productivity dynamics were determined based on the trend analysis of Landsat-based NDVI annual composites over the 1987-2020 period. Additionally, a binary logistic regression model was developed to identify the determinant factors and to map the susceptibility of this degradation at the territorial level. The results revealed that 31.25% (1303.175 km2) of the territory had experienced a decrease in land productivity, with 10.8% (453.83 km2) characterized by a significant decrease at the confidence level of 90%, representing the hotspots area of land productivity degradation where conservation actions should be prioritized. This decrease in land productivity is location-specific as it depends on the land cover types and health zones. It is likely to occur at high altitudes, in areas close to artisanal mining sites, rivers, and administrative centers. These results imply that policy interventions to cope with the problem of land productivity degradation should be developed following the heterogeneity of the landscape, and sustainable land management practices that take into account both the biophysical and socio-economic drivers of land degradation should be implemented in this region to achieve the land degradation neutrality by 2030.