Land Degradation Neutrality Research Articles

Integrated Modeling of Land Degradation Dynamics and Insights on the Possible Future Management Alternatives in the Gidabo River Basin, Ethiopian Rift Valley

Land degradation is a pivotal environmental concern, bearing substantial impacts in the Gidabo river basin (GRB) in Ethiopia, prompting a critical need for effective mitigation strategies. In this study, we aimed to assess the dynamics of land degradation pathways in the context of change in climate and land use. The identification of potential erosion hotspots and the appraisal of management strategies was also carried out. The Soil and Water Assessment Tool (SWAT) and the Good Practice Guidance (GPG) framework was employed. The results revealed a compelling synergy between land use dynamics and climate changes, asserting joint and individual prevalence in influencing surface runoff and sediment yield. The past simulation revealed 4–5.9% and 24–43% increments in mean annual runoff and sediment yield, respectively. While the near (2021–2040) and mid (2041–2060) future scenarios displayed varying trends under RCP4.5 and RCP8.5. Furthermore, sub-basins prone to soil erosion risk were identified, thereby enabling targeted conservation efforts. The assessment of trends in land degradation neutrality (LDN) unveiled the expansion of land degradation trajectories (by 26%) from 1985–2003 to 2003–2021. This might be attributed to the dynamic interplay between climate and land use land cover (LULC) change, with croplands and bare land emerging as high-risk degraded areas. Addressing these concerns, soil/stone bund, terracing, contour farming, and reforestation practice can significantly reduce the annual sediment yield in the future. The integration of soil erosion indicators with LDN sub-indicators can provide a more comprehensive approach that can lead to more effective land management and restoration strategies to achieve the LDN goal. The findings of this study could contribute crucial insights and substantial implications for policymakers, land managers, and conservationists. Moreover, future efforts should be directed to expand investigations into diverse land degradation pathways and mitigation measures.

Land degradation neutrality: Testing the indicator in a temperate agricultural landscape

Land degradation directly affects around 25% of land globally, undermining progress on most of the UN Sustainable Development Goals (SDG), particularly target 15.3. To assess land degradation, SDG indicator 15.3.1 combines sub-indicators of productivity, soil carbon and land cover. Over 100 countries have set Land Degradation Neutrality (LDN) targets. Here, we demonstrate application of the indicator for a well-established agricultural landscape using the case study of Great Britain. We explore detection of degradation in such landscapes by: 1) transparently evaluating land cover transitions; 2) comparing assessments using global and national data; 3) identifying misleading trends; and 4) including extra sub-indicators for additional forms of degradation. Our results demonstrate significant impacts on the indicator both from the land cover transition evaluation and choice or availability of data. Critically, we identify a misleading improvement trend due to a trade-off between improvement detected by the productivity sub-indicator, and 30-year soil carbon loss trends in croplands (11% from 1978 to 2007). This carbon loss trend would not be identified without additional data from Countryside Survey (CS). Thus, without incorporating field survey data we risk overlooking the degradation of regulating and supporting ecosystem services (linked to soil carbon), in favour of signals from improving provisioning services (productivity sub-indicator). Relative importance of these services will vary between socioeconomic contexts. Including extra sub-indicators for erosion or critical load exceedance, as additional forms of degradation, produced a switch from net area improving (9%) to net area degraded (58%). CS data also identified additional degradation for soil health, including 44% arable soils exceeding bulk density thresholds and 35% of CS squares exceeding contamination thresholds for metals.

Do adaptive policy adjustments deliver ecosystem-agriculture-economy co-benefits in land degradation neutrality efforts? Evidence from southeast coast of China.

Ecosystem restoration projects (ERPs) facilitate land degradation neutrality (LDN). However, the response dynamics and interactions of sectors within ecosystem-agriculture-economy nexus (EAEN) have not been sufficiently explored, which constrains the coordinated efficacy of LDN efforts. To bridge the knowledge gaps, the present study selected a land restoration hotspot in southeastern China as a case to investigate the simultaneous responses of the EAEN sectors to ERPs from a novel social-ecological system (SES)-based LDN perspective. Various biophysical models and Manne-Kendall trend test as well as multi-source spatially explicit data and socioeconomic statistics were applied to quantify the co-evolution of natural and socioeconomic indicators. ERPs converting cropland to woodland and grassland promoted vegetation restoration, reduced soil erosion, and enhanced carbon sequestration. However, cropland loss initially resulted in a decline in grain productivity. Policy adjustments and improvements in ecosystem restoration efforts and agricultural production conditions improved food security and increased agricultural production capacity. Effective policymaking and favorable resident engagement accelerated the transformation from a grain-production-based agriculture to diversified industries and, by extension, economic output, income, and population. The success of socioeconomic development under the SES framework for LDN demonstrated that this strategy could achieve the desired environmental, agricultural, and economic targets. EAEN under the SES conceptual framework provides an inclusive, comprehensive LDN perspective and improves ERP efficacy. The findings of the present work might be applicable to other land restoration areas challenged by the complex interactions among multidimensional factors. Comparably successful implementation of these ERPs could be realized if individual environmental and socioeconomic conditions are thoroughly considered during the formulation of coordinated development policies.

Sub-surface drainage: A win-win technology for achieving carbon neutrality and land amelioration in salt-affected Vertisols of India

This study aims to investigate the long-term impact of subsurface drainage (SSD) in restoring the soil quality and sugarcane productivity of waterlogged saline Vertisols. A combination of methodologies including analytical techniques, collection of soil and water samples and field survey with farmers was applied to collect the data, and drawing the inferences. The results indicated that successful long-term operation of SSD improved soil quality. A significant reduction in soil salinity (ECe) (Kavathesar site: 13.27 to 2.61, Shedshal site: 33.21 to 13.72 dS m−1) was observed. An appreciable improvement in soil bio-physico-chemical properties including organic carbon (OC%) (Kavathesar site: 0.48 to 0.63, Shedshal site: 0.22 to 0.44%) and dehydrogenase activity (DHA) (Kavathesar site:10.22 to 13.87, Shedshal site: 4.01 to 17.16 μg g−1 24 h−1), alkaline phosphatase (ALPA) (Kavathesar site:74.00 to 93.00, Shedshal site: 34.00 to 61.00 μg P-NP g−1 h−1), bulk density (BD) (Kavathesar site: 1.17 to 1.13, Shedshal site: 1.19 to 1.07 Mg m−3), saturated hydraulic conductivity (SHC) (Kavathesar site: 2.38 to 3.20, Shedshal site: 1.70 to 2.95 cm day−1) was found on surface (0–30 cm) layer comparing to their control sites (without SSD). The principal component analysis (PCA) showed that % OC, ECe, BD, and available K content were the most contributing factor for soil quality index (SQI). The improved soil quality has resulted in increasing the sugarcane yield by 226.8 and 585.5% at Kavathesar and Shedshal sites, respectively. The farmers' perception revealed that SSD technology (adopted on community scale) could play substantial role in improving the soil condition, and thereby enhancement in the yield of sugarcane crop. Thus, SSD technology was observed to have great potential in improving soil quality, crop (sugarcane) productivity, farmers' income and ensuring land degradation neutrality goal under saline Vertisols of India. Therefore, the large-scale adoption of SSD, managed with regional planning and strong cooperation among the stakeholders, may fulfil the promise of Sustainable Development Goals (SDGs) including Life on Land, No Poverty and Zero Hunger in degraded black saline soils.

Assessment of Land-Degradation Neutrality in Samara Oblast by Global and Regional Indicators

Assessment of Land-Degradation Neutrality in Samara Oblast by Global and Regional Indicators

Understanding the balance between soil conservation and soil water storage capacity during the process of vegetation restoration in semi‐arid watersheds in the Loess Plateau, China

AbstractIn the Loess Plateau, gaining insights into the water storage and soil retention functions of diverse vegetation types, especially, in the semi‐arid watersheds is crucial for identifying the key factors necessary to ensure sustainable development and achieve land degradation neutrality. In this study, five different land use types such as forest, shrub, artificial grass, and natural grasslands were surveyed from 2014 to 2020. Meanwhile, bare land was also used as a control plot. The trade‐off between erosion mitigation and water consumption indicator was quantified based on the ecosystem services perspective benefits. Our results showed that there are significant differences among different land use types (p < 0.05): natural grassland > shrubs > artificial grassland > forests. Vegetation restoration was able to change the soil particle size distribution, increasing clay and silt content, and decreasing sand particles. During the growing season, surface soil water storage decreased in all land use types coinciding with the higher decrease in the control plot. The change in surface water storage in the forest was the most stable, with a decrease of 0.13 mm. The trade‐off between erosion mitigation and water consumption indicator was less than 0 for all vegetation types, which indicates a synergistic effect on soil conservation and water storage benefit. Our results demonstrated that shrubs can register the most balanced benefit of water storage and soil preservation. This is a solid basis for the selection of specific vegetation types and the optimization of the watershed landscape in the middle reaches of the Yellow River, characterized by vulnerable areas due to aridification.

ASSESSMENT OF THE LAND DEGRADATION NEUTRALITY IN THE SAMARA REGION BY GLOBAL AND REGIONAL INDICATORS

The assessment of land degradation neutrality (LDN) is used to characterize the achievement of the UN Sustain-able Development Goal 15 (SDG), Target 15.3 — «to combat desertification, restore degraded lands and soils» by individual countries and regions. The article presents the calculation of land degradation neutrality for agricultural territories of the Samara region using global indicators (dynamics of land productivity, dynamics of land cover, dynamics of soil organic carbon) and regional ones, such as yield, erosion, content of mobile forms of potassium and phosphorus in the soil. The Trends.Earth tool presented on the Quantum GIS was used to calculate the first two global indicators platform. The evaluation of the remaining indicators was carried out using stock data and data from the agrochemical service. According to the results land degradation neutrality was not achieved in the agricultural territories of the Samara region. The indicator of SDG 15.3.1 («the proportion of land that is degraded over total land area») is 78,61%, and the LDN index is –57,22%. The main process leading to a negative LDN index is water erosion, which leads to a decrease in the levels of indicators such as land productivity and humus content.

An interactive system to map land degradation and inform decision‐making to achieve land degradation neutrality via convergence of evidence across scales: A case‐study in Ecuador

AbstractOne of the core challenges to achieve land degradation neutrality (LDN) is to spatially identify, and strategically prioritise, the areas to implement actions to avoid, reduce and reverse land degradation. To achieve this, a tool for a participatory and data‐driven assessment considering both the biophysical and socio‐economic dimensions of land degradation across scales was developed for Ecuador. In this paper, we present the methodology and results obtained, including the spatially explicit interactive tool developed to integrate indicators that support the scaling‐up of sustainable land management (SLM). The process involved specialists from various national and international institutions, as well as decision makers from the public sector and other relevant stakeholders. Cloud computing allowed the integration of five main sources of data: (1) the results of a participatory land degradation assessment based on an expert knowledge questionnaire following the land degradation assessment in drylands (LADA) and world overview of conservation approaches and technologies (WOCAT) methodology; (2) the Hand‐in‐Hand Initiative Ecuador typology maps based on poverty and estimated agricultural potential and efficiency scores from household surveys; (3) National datasets on land cover and land use, soil properties, and hydro climatic indicators; (4) global satellite‐derived LDN indicators, such as land productivity dynamics; and (5) documented SLM practices from WOCAT Global SLM Database. The tool is based on a Google Earth Engine application and allows decision makers to easily compare results and obtain statistics at different spatial scales and landscapes, including land use systems delimited by experts. It also includes a multi‐criteria module to identify areas with specific characteristics to prioritise different types of interventions to achieve the Country's LDN targets. Convergence of local and global evidence allowed the identification of hotspots of degradation as well as areas of false positives/negatives—if only global or remote sensing indicators were considered. The participatory process contributed to strengthening multi‐sector cooperation mechanisms and to guaranteeing ownership of the tool and the results. The system will support Ecuador's efforts to monitor and report progress towards LDN to the United Nations Convention to Combat Desertification. The system's code is shared as a repository at Earth Engine and can be adapted to and used by other countries and regions.

Effect of deficit saline irrigation, tillage and rice straw mulch in wheat‐sorghum cropping system on yield and nutritive value of rainfed forage sorghum in salt‐affected soils

AbstractSoil and groundwater salinity associated with limited rainfall are the challenges for checking salinity build‐up in semi‐arid regions. This field experiment was conducted to test the impact of deficit saline irrigation (DSI) (in winter) with mulching and tillage on salinity build‐up, yield and nutritive value of rainfed‐forage sorghum. Tillage (reduced, conventional and zero), saline water (8.0 dS m−1) irrigation (100%, 80% and 60% of water requirement [WR] in wheat) and mulch were allocated following split factorial layout. DSI with mulching produced at par wheat and sorghum yield compared with 100WR irrigation with harvested rainwater. Mulching improved wheat grain yield and the soil water content by ~13% throughout the cropping season. Forage sorghum yield was increased by DSI and mulching in the previous season compared with irrigation with 100WR saline water. Reduced tillage declined the neutral detergent fibre (NDF), acid detergent fibre (ADF) and acid detergent lignin (ADL) with an increase in cell soluble constituents. DSI and mulching also increased the digestible nutrient, crude protein (CP), ash and reduced ADF of sorghum. Soil salinity showed a negative correlation with CP, positive correlation with ADF, ADL and cellulose. Therefore, it is recommended that DSI and reduced tillage with mulching can be a reliable option for productive use of saline soils and water by cropping system intensification. These results also showed the potential for achieving 2030 agenda for sustainable development goals as well as targets of land degradation neutrality in salt‐affected soils by savings irrigation, doubling cropping intensity and preventing salinity build‐up.

Map-based soil crusting susceptibility assessment using pedotransfer Rules, CORINE and NDVI: A preliminary study in Greece

Map-based assessment of land degradation processes supports national monitoring and protection of the soil resources, in line with the Land Degradation Neutrality (LDN) and the Sustainable Development Goals (SDGs) initiatives. Soil crusting susceptibility, a complex expression of land degradation, with fundamental impact on soil functions, has not yet been estimated in Greek territory. To address this knowledge gap, current research uses well-known pedotransfer rules (PRLeB), partially adjusted to suit the local soil database format. The PRLeB, already applied at European scale, examine the soil crusting problem as a function of fundamental soil characteristics. From the first analysis a paradox emerged. Moderately and highly crusting prone soils were encountered in forested areas. This paradox indicated the need for a second formalization of the soil crusting problem (ePRLeB). The CORINE Land Cover (CLC) 2018 and a seasonal vegetation cover index (Normalized Difference Vegetation Index -NDVI) were used to divide the study area into categories and to capture the temporal variability of the problem, accordingly. Three land use categories emerged. The water bodies and the artificial areas were characterized as Non-evaluated areas (NE). Areas with considerable vegetation coverage (NDVI greater than 0.5) were characterized as Non-prone to crusting (NC), and the rest of the areas were characterized as Potentially prone to crusting (PC). The PRLeB approach was applied only to the PC areas. In both formalizations, the physicochemical and textural aspects of soil crusting adopted the same PRLeB. With the first formalization, 15% and 39% of the soils in Greece were characterized as very low and low susceptible to soil crusting respectively. With the second formalization 58 – 63% of the soils were characterized by no and 5 – 7% by very low crusting susceptibility. Current work explored two fundamentally different facets of the soil crusting problem. The first formalization, which can be expressed as the soil susceptibility to crusting, considers crusting as an inherent soil process. The second formalization, expressed as soil crusting susceptibility encounters crusting as a complex phenomenon involving natural but not anthropogenic factors. The study indicated that vegetation and seasonality are important factors in the map-based assessment of the observable soil crusting phenomenon. Also, it was highlighted that the unambiguous problem specification is a critical aspect for complex problem assessment and communication, particularly within an interdisciplinary context.

An approach to determine the neutrality of soil degradation in karst regions

Land as an open system is susceptible to any change in the environment, which makes it necessary to use it in a sustainable way, ensuring its availability for future generations, not only in terms of existence but also in terms of quality and productivity. This is how the concept of Land Degradation Neutrality (LDN) was born in 2012.The present work is developed based on this new concept with the objective of adjusting/updating the method for determining LDN proposed by Orr et al, (2017) to karstic environments. Based on a 1990 baseline compared to the year 2019 in the San José polje, Cuba, plus the adjustments introduced to the method, it shows that the LDN in karstic regions depends mainly on two indicators: edaphic and geological-geomorphological. The edaphic indicators, in general, show a tendency to recovery: increase of forest use (+27%) and increase of SOC content (+7105 t ha−1), being the main cause of this rehabilitation, the economic crisis that Cuba is going through and not totally an agro-environmental awareness.On the other hand, it was determined that the greatest challenge for the progress of agriculture in the polje is due to the geological-geomorphological conditions resulting from the unidirectional and irreversible advance of karst morphogenesis; that with the increase of SOC as a result of the change of paradigm from conventional to organic agriculture can accelerate the dissolution of CaCO3.

Application of the Concept of Land Degradation Neutrality for Remote Monitoring of Agricultural Sustainability of Irrigated Areas in Uzbekistan.

A scientific approach to the assessment of trends in land changes based on the novel concept of Land Degradation Neutrality (LDN) was applied to monitor the sustainability of irrigated farmlands in test areas in Uzbekistan (the Andijan, Namangan, Fergana, and Syrdarya regions). The tool "Trends.Earth", which was recommended by the UN Convention to Combat Desertification and developed as a special plugin for the Quantum GIS platform, was used to describe the dynamics of land degradation in the period 2001-2020. This study demonstrates the results of monitoring land productivity dynamics that reflect the investments in irrigation improvement during the last 10-15 years. A comparison between changes in land productivity measured via Normalized Difference Vegetation Index and its average value for the entire observation period is more informative than comparison with the initial 5-year period. More details could be noted through application of the "moving average" calculation method. The described trends demonstrate that the use of sustainable land management practices in the last decade led to a decreasing proportion of degraded lands compared to the average figure for the period 2001-2020 (from 25-40% to 10-20%). This trend is confirmed by reviewing state statistics and indicates the success of national policies and approaches to adaptation. However, the dynamics of land productivity in the study areas is diverse and includes "dry" and "humid" extremes, depending on climate fluctuations. Despite the generally positive trends identified across regions, the high dynamics of degraded hotspots and improved lands within certain areas confirm the instability of ongoing changes.

Achieving Land Degradation Neutrality Through Tea Plantation: Future Prospect for Combating Climate Change in the Northeast Himalayan Region of India

Achieving Land Degradation Neutrality Through Tea Plantation: Future Prospect for Combating Climate Change in the Northeast Himalayan Region of India

Characteristics and utilization of black soils in Indonesia

Black soils store a high amount of soil organic carbon (SOC) and play a crucial role in climate change, food security, and land degradation neutrality. However, data and information regarding black soils in tropical regions, including Indonesia, are limited. This study aimed to characterize and identify the utilization of black soils in Indonesia based on legacy soil survey data. We collated 142 soil pedon samples of Mollisols from articles, technical reports, and existing datasets. The site information (site position, elevation, land use type, parent material) and selected physicochemical properties were stored in a spreadsheet, from which exploratory data analysis was conducted. The result showed that the median SOC content was 1.53%, ranging from 0.6 to 8.2 %; cation exchange capacity was 30 cmol kg<sup>-1</sup>, ranging from 9 to 95 cmol kg<sup>-1</sup>; base saturation was 87%, ranging from 11 to 100 %; and bulk density was 1.21 g cm<sup>-3</sup>, ranging from 1.13 to 1.36 g cm<sup>-3</sup>. Other soil characteristics (particle size distribution, exchangeable bases, pH, pore, and water retention) varied with horizon type and land use/land cover. The black soils have been used for paddy fields, dryland farming, and gardens with low management intensity. Main cultivated crops include rice (<em>Oryza sativa</em>), corn (<em>Zea mays</em>), cassava (<em>Manihot esculenta</em>), sweet potato (<em>Ipomoea batatas</em>), and nutmeg (<em>Myristica fragrans</em>), clove (<em>Syzygium aromaticum</em>), coconut (<em>Cocos nucifera</em>), and cocoa (<em>Theobroma cocoa)</em>. Threats to black soil functions include soil erosion, carbon loss, and nutrient imbalance. Soil and water conservation measures, integrated soil nutrient management, and agroforestry are among the best land management practices for black soils.

A multi-data approach to evaluate progress towards land degradation neutrality in Central Asia

Central Asia hosts one of the largest continuous grassland areas on our planet, that is of vital importance for food security, biodiversity and carbon sequestration. However, this region is also subjected to some of the most intense land degradation processes, related to large scale land use change and climate change.To combat land degradation and pursue sustainable land management the concept of land degradation neutrality (LDN) has been proposed. LDN assessments are recommended to be based on global data in regions that lack sufficient regional data such as Central Asia. However, it remains unclear how the selection of datasets influences the estimated extent of land degradation. We followed the LDN framework and first calculated changes to three LDN indicators: land productivity, land cover, and Soil Organic Carbon (SOC). We then evaluated the impact of using different regional and global land cover data on the extent of land degradation in the region. Finally, we calculated a regionally specific integrated indicator on soil quality that we used to assess the “like-for-like” principle which enables counterbalancing losses and gains.Our results indicate that particularly the selection of land cover data has a significant impact on the overall assessment of degradation state. The extent of land between 2000 and 2019 varies considerably depending on the data and ranges between 15 and 34 % of the whole Central Asian region. Our findings reveal that the area of degraded land on high quality soils is twice as high as the area of high quality soils where the land condition has improved (12 % versus 6 %). In areas with low soil quality, 13 % was subject to degradation, and 10 % improved.Whilst the degradation extent varies according to the selected land cover datasets, our results demonstrates that Central Asia is undergoing land degradation affecting high quality soils. Sensitivity analysis of multiple datasets can reduce the risk of misjudgement in degradation extent assessments, especially in regions with mosaic ecosystems, such as grasslands.

Implementation of a multi‐layered land degradation monitoring and forecasting framework toward integrated countermeasure planning in drylands

AbstractVarious earth observation (EO) data and related spatial technologies are employed to monitor land degradation (LD) and its impacts on the drylands. However, a comprehensive framework that integrates multiple data sources and metrics to generate a consistent output still needs to be explored. Furthermore, the lack of consistency and the limited reliabilities of existing approaches make it challenging to identify proper countermeasures (avoid, reduce, reverse LD) and support decisions to combat LD in line with the Land Degradation Neutrality (LDN) Framework. The “Multi‐Layered Land Degradation Tracer (ML‐LDT)” is a framework that addresses the above research gaps. It is based on a comprehensive framework that integrates data extraction, LD monitoring, and forecasting capacities and consists of three functional layers, that is, a base data processor, monitoring/modeling components, and a forecasting layer employing machine learning (ML) algorithms. ML‐LDT has a state‐of‐art capacity to model wind erosion together with sand and dust storms (SDS), making it particularly suited to the arid lands most prone to these processes. It is implemented over cloud processors with open‐source components based on industry standards. Therefore, the routines are easily adaptable to user requirements in LDN planning. We evaluated the ML‐LDT framework in the Indian Thar Desert and Inner Mongolian drylands. The results showed the overall robustness of the procedures and that ML‐based models provide good insights to forecast future LD/SDS patterns that can be used to simulate LDN scenarios and targets. We validated the forecasting results against LD maps and remote sensing observations.

Soil Survey, the Profession I Embraced: a Few Pages from my Tour Diary

On 2022 World Soil Day (WSD), the author shares his experiences in soil surveys since his early days till date. Soil is the beginning of food, as mentioned in the year 2022 theme for WSD. Soil survey is the beginning of soil research regarding pedology, edaphology, and soil biology. The author delves into his experiences from different states, villages, and landscapes to identify varied soils. He argues about the grouping of soils and their utility in edaphology. Fieldwork, laboratory work, data generation, and dissemination are all critical; soil survey is the foundation of all such research activities. Fieldwork is strenuous, but in the long run, it's rewarding. The tour diary of the author describes the formation of spatially-associated Vertisols, Alfisols and Mollisols; besides, mention of Mollisols (brown forest soils) has been made the Histosols and their considerable capacity to be the hub of organic carbon which could be utilised as a model to combat climate change and global warming using artificial intelligence (AI). This soil database may serve as an essential engine for a negative emission strategy to combat global warming and assist land degradation neutrality (LDN). Starting his career in the Western Ghats, journeying through the tortuous paths of many terrains in the Satpura, Vindhyan, Himalayas, Northeastern regions and the southern Peninsula, the author returns to the same place at the end of his career, in the Western Ghats. He busy in research and continuing has been his quest for science.

Application of Basic and Modified Methods for Assessing the Land-Degradation Neutrality in the Context of Studying the Relationship between Degradation and Agricultural Production

Application of Basic and Modified Methods for Assessing the Land-Degradation Neutrality in the Context of Studying the Relationship between Degradation and Agricultural Production

Beyond "greening" and "browning": Trends in grassland ground cover fractions across Eurasia that account for spatial and temporal autocorrelation.

Grassland ecosystems cover up to 40% of the global land area and provide many ecosystem services directly supporting the livelihoods of over 1 billion people. Monitoring long-term changes in grasslands is crucial for food security, biodiversity conservation, achieving Land Degradation Neutrality goals, and modeling the global carbon budget. Although long-term grassland monitoring using remote sensing is extensive, it is typically based on a single vegetation index and does not account for temporal and spatial autocorrelation, which means that some trends are falsely identified while others are missed. Our goal was to analyze trends in grasslands in Eurasia, the largest continuous grassland ecosystems on Earth. To do so, we calculated Cumulative Endmember Fractions (annual sums of monthly ground cover fractions) derived from MODIS 2002-2020 time series, and applied a new statistical approach PARTS that explicitly accounts for temporal and spatial autocorrelation in trends. We examined trends in green vegetation, non-photosynthetic vegetation, and soil ground cover fractions considering their independent change trajectories and relations among fractions over time. We derived temporally uncorrelated pixel-based trend maps and statistically tested whether observed trends could be explained by elevation, land cover, SPEI3, climate, country, and their combinations, all while accounting for spatial autocorrelation. We found no statistical evidence for a decrease in vegetation cover in grasslands in Eurasia. Instead, there was a significant map-level increase in non-photosynthetic vegetation across the region and local increases in green vegetation with a concomitant decrease in soil fraction. Independent environmental variables affected trends significantly, but effects varied by region. Overall, our analyses show in a statistically robust manner that Eurasian grasslands have changed considerably over the past two decades. Our approach enhances remote sensing-based monitoring of trends in grasslands so that underlying processes can be discerned.

APPLICATION OF BASIC AND MODIFIED METHOD FOR ASSESSING THE LAND DEGRADATION NEUTRALITY IN THE CONTEXT OF STUDYING THE RELATIONSHIP BETWEEN DEGRADATION AND AGRICULTURAL PRODUCTION

The article is devoted to the theory and practice of applying the concept of land degradation neutrality (LDN) for the conditions of the Belgorod region of the Russian Federation. Its basic version is considered, based on the analysis of three sub-indicators, where the assessment of land degradation trends in the study area is based on the analysis of changes in the main indicator - the percentage of degraded land from the total area of the territory, and three sub-indicators of SDG 15.3.1: changes in land productivity, changes in land cover and dynamics of soil organic carbon reserves. As an adjustment to the basic approach of the LDN, it is proposed to supplement it with regional data on soil characteristics. The following soil properties can be recommended as necessary for considering in the evaluation model - the content of humus and nutrients, as well as pH, these characteristics, on the one hand, are largely related to soil fertility, and on the other hand, they are most at risk of degradation changes during human exploitation of soils. Modif cation of the LDN methodology allows not only to clarify the central (umbrella) indicator, but also to identify the relationship of the latter with indicators of agricultural production, in particular, gross crop yields. Analysis of the data using the modif ed LDN method showed that 64.8% of the region was degraded (which is almost 2 times higher than the values obtained by the basic LDN method), which leads to a signif cant loss of crop yield. The article proposes an algorithm for assessing the relationship between land degradation and gross crop yields based on correlation and regression analysis (spatial models).