Self-organization as a mechanism of resilience in dryland ecosystems.

Self-organized spatial patterns are a common feature of complex systems, ranging from microbial communities to mussel beds and drylands. While the theoretical implications of these patterns for ecosystem-level processes, such as functioning and resilience, have been extensively studied, empirical evidence remains scarce. To address this gap, we analyzed global drylands along an aridity gradient using remote sensing, field data, and modeling. We found that the spatial structure of the vegetation strengthens as aridity increases, which is associated with the maintenance of a high level of soil multifunctionality, even as aridity levels rise up to a certain threshold. The combination of these results with those of two individual-based models indicate that self-organized vegetation patterns not only form in response to stressful environmental conditions but also provide drylands with the ability to adapt to changing conditions while maintaining their functioning, an adaptive capacity which is lost in degraded ecosystems. Self-organization thereby plays a vital role in enhancing the resilience of drylands. Overall, our findings contribute to a deeper understanding of the relationship between spatial vegetation patterns and dryland resilience. They also represent a significant step forward in the development of indicators for ecosystem resilience, which are critical tools for managing and preserving these valuable ecosystems in a warmer and more arid world.

Integrating genomics and biogeography to unravel the origin of a mountain biota: The case of a reptile endemicity hotspot in Arabia.

Advances in genomics have greatly enhanced our understanding of mountain biodiversity, providing new insights into the complex and dynamic mechanisms that drive the formation of mountain biotas. These span from broad biogeographic patterns to population dynamics and adaptations to these environments. However, significant challenges remain in integrating large-scale and fine-scale findings to develop a comprehensive understanding of mountain biodiversity. One significant challenge is the lack of genomic data, particularly in historically understudied arid regions where reptiles are a particularly diverse vertebrate group. In the present study, we assembled a de novo genome-wide SNP dataset for the complete endemic reptile fauna of a mountain range (19 described species with more than 600 specimens sequenced), and integrated state-of-the-art biogeographic analyses at the population, species, and community level. Thus, we provide a holistic integration of how a whole endemic reptile community has originated, diversified and dispersed through a mountain system. Our results show that reptiles independently colonized the Hajar Mountains of southeastern Arabia 11 times. After colonization, species delimitation methods suggest high levels of within-mountain diversification, supporting up to 49 deep lineages. This diversity is strongly structured following local topography, with the highest peaks acting as a broad barrier to gene flow among the entire community. Interestingly, orogenic events do not seem key drivers of the biogeographic history of reptiles in this system. Instead, past climatic events seem to have had a major role in this community assemblage. We observe an increase of vicariant events from Late Pliocene onwards, coinciding with an unstable climatic period of rapid shifts between hyper-arid and semiarid conditions that led to the ongoing desertification of Arabia. We conclude that paleoclimate, and particularly extreme aridification, acted as a main driver of diversification in arid mountain systems which is tangled with the generation of highly adapted endemicity. Overall, our study does not only provide a valuable contribution to understanding the evolution of mountain biodiversity, but also offers a flexible and scalable approach that can be reproduced into any taxonomic group and at any discrete environment.

Plant root mechanisms and their effects on carbon and nutrient accumulation in desert ecosystems under changes in land use and climate.

Deserts represent key carbon reservoirs, yet as these systems are threatened this has implications for biodiversity and climate change. This review focuses on how these changes affect desert ecosystems, particularly plant root systems and their impact on carbon and mineral nutrient stocks. Desert plants have diverse root architectures shaped by water acquisition strategies, affecting plant biomass and overall carbon and nutrient stocks. Climate change can disrupt desert plant communities, with droughts impacting both shallow and deep-rooted plants as groundwater levels fluctuate. Vegetation management practices, like grazing, significantly influence plant communities, soil composition, root microorganisms, biomass, and nutrient stocks. Shallow-rooted plants are particularly susceptible to climate change and human interference. To safeguard desert ecosystems, understanding root architecture and deep soil layers is crucial. Implementing strategic management practices such as reducing grazing pressure, maintaining moderate harvesting levels, and adopting moderate fertilization can help preserve plant-soil systems. Employing socio-ecological approaches for community restoration enhances carbon and nutrient retention, limits desert expansion, and reduces CO2 emissions. This review underscores the importance of investigating belowground plant processes and their role in shaping desert landscapes, emphasizing the urgent need for a comprehensive understanding of desert ecosystems.

Dynamics of soil biota and nutrients at varied depths in a Tamarix ramosissima-dominated natural desert ecosystem: Implications for nutrient cycling and desertification management.

The underground community of soil organisms, known as soil biota, plays a critical role in terrestrial ecosystems. Different ecosystems exhibit varied responses of soil organisms to soil physical and chemical properties (SPCPs). However, our understanding of how soil biota react to different soil depths in naturally established population of salinity tolerant Tamarix ramosissima in desert ecosystems, remains limited. To address this, we employed High-Throughput Illumina HiSeq Sequencing to examine the population dynamics of soil bacteria, fungi, archaea, protists, and metazoa at six different soil depths (0-100 cm) in the naturally occurring T. ramosissima dominant zone within the Taklimakan desert of China. Our observations reveal that the alpha diversity of bacteria, fungi, metazoa, and protists displayed a linear decrease with the increase of soil depth, whereas archaea exhibited an inverse pattern. The beta diversity of soil biota, particularly metazoa, bacteria, and protists, demonstrated noteworthy associations with soil depths through Non-Metric Dimensional Scaling analysis. Among the most abundant classes of soil organisms, we observed Actinobacteria, Sordariomycetes, Halobacteria, Spirotrichea, and Nematoda for bacteria, fungi, archaea, protists, and metazoa, respectively. Additionally, we identified associations between the vertical distribution of dominant biotic communities and SPCPs. Bacterial changes were mainly influenced by total potassium, available phosphorus (AP), and soil water content (SWC), while fungi were impacted by nitrate (NO3-) and available potassium (AK). Archaea showed correlations with total carbon (TC) and AK thus suggesting their role in methanogenesis and methane oxidation, protists with AP and SWC, and metazoa with AP and pH. These correlations underscore potential connections to nutrient cycling and the production and consumption of greenhouse gases (GhGs). This insight establishes a solid foundation for devising strategies to mitigate nutrient cycling and GHG emissions in desert soils, thereby playing a pivotal role in the advancement of comprehensive approaches to sustainable desert ecosystem management.

Controlling desertification brings positive socioeconomic benefits beyond regional environmental improvement: Evidence from China's Gonghe Basin.

Large-scale desertification combatting programs (DCPs) are crucial tools for addressing climate change and improving the ecological environment. Despite existing research having predominantly focused on assessing the ecological benefits of DCPs, the understanding of their impacts on surrounding socioeconomic aspects remains limited, particularly at the household level. To comprehensively evaluate the returns of DCPs, this study chose the representative desertification control area of the Gonghe Basin on the Qinghai-Tibet Plateau as the research region and identified the dual benefits in terms of ecological environment and socioeconomic gains. Firstly, two essential ecosystem services, carbon sequestration (CS) and wind erosion prevention (WEP), were assessed using the MODIS NPP dataset and the RWEQ model from 2001 to 2021. Household surveys were conducted in 36 villages across 14 townships within the Gonghe Basin to gain a deeper understanding of the residents' socioeconomic conditions. Through regression analysis, the study assessed the impact of DCPs on the regional ecological environment and household socioeconomic status. The research findings revealed significant improvements in CS and WEP across a significant portion of the study area from 2001 to 2021. Upon analyzing data from 401 household questionnaires, it was generally perceived by residents in the Gonghe Basin that the implementation of DCPs led to environmental improvements and increased their income levels. Further regression analysis revealed a significant impact of both natural factors and the extent of resident participation in the projects on the ecological environment surrounding the villages and on household socioeconomic aspects. With increased resident engagement in the projects, the likelihood of increased household income and life satisfaction was higher. The diverse array of DCPs implemented in the Gonghe Basin not only improved the regional ecological environment but also stimulated socioeconomic development. In future projects, it is imperative to consider regional characteristics, align ecological effects, ensure the sustainability of livelihoods, and maximize the role of social capital.

Responses of soil dissolved organic carbon properties to the desertification of desert wetlands in the Mu Us Sandy Land.

In desert wetlands, the decline in ground water table results in desertification, triggering soil carbon and nutrient loss. However, the impacts of desertification on soil dissolved organic carbon (DOC) properties which determine the turnover of soil carbon and nutrients are unclear. Here, the desertification gradient was represented by the distance from the wetland center (0∼240 m) traversing reed marshes, desert shrubs and bare sandy land in the Hongjian Nur Basin, north China. Soil DOC properties were determined by ultraviolet and fluorescence spectroscopy coupled with parallel factor analysis (PARAFAC). Results showed that soil DOC content decreased significantly from 107.23 mg kg-1 to 8.44 mg kg-1 by desertification (p < 0.05). However, the proportion of DOC to soil organic carbon (SOC) was gradually significantly increased. According to spectral parameters, microbial-derived DOC decreased from 0 to 120 m (reed marshes to desert shrubs) but increased from 120 to 240 m (desert shrubs to bare sandy lands), with a reverse hump-shaped distribution pattern. The molecular weight and aromaticity of DOC increased from 0 to 120 m but decreased from 120 to 240 m, with a hump-shaped distribution pattern. For the DOC composition, although the relative abundances of humic-acid components remained stable (p > 0.05), they were ultimately decreased by serious desertification and the amino acids became the dominant component. A similar change pattern was also found for humification index. Additionally, MBC and C:N were the two most important variables in determining the content and spectral properties, respectively. Together, these findings relationships between the soil DOC properties and desertification degree, especially the increase in DOC proportion and the decrease in humification degree, which may reduce soil C stabilization in the Hongjian Nur Basin.

Multi-model assessment of potential natural vegetation to support ecological restoration.

Ecological restoration is imperative for controlling desertification. Potential natural vegetation (PNV), the theoretical vegetation succession state, can guides near-natural restoration. Although a rising transition from traditional statistical methods to advanced machine learning and deep learning is observed in PNV simulation, a comprehensive comparison of their performance is still unexplored. Therefore, we overview the performance of PNV mapping in terms of 12 commonly used methods with varying spatial scales and sample sizes. Our findings indicate that the methodology should be carefully selected due to the variation in performance of different model types, with Area Under the Curve (AUC) values ranging from 0.65 to 0.95 for models with sample sizes up to 80% of the total sample size. Specifically, semi-supervised learning performs best with small sample sizes (i.e., 10 to 200), while Random Forest, XGBoost, and artificial neural networks perform better with large sample sizes (i.e., over 500). Further, the performance of all models tends to improve significantly as the sample size increases and the grain size of the crystals becomes smaller. Take the downstream Tarim River Basin, a hyper-arid region undergoing ecological restoration, as a case study. We showed that its potential restored areas were overestimated by 2-3 fold as the spatial scale became coarser, revealing the caution needed while planning restoration projects at coarse resolution. These findings enhance the application of PNV in the design of restoration programs to prevent desertification.

The dominant influencing factors of desertification and ecological risk changes in Qinghai Area of Qilian Mountains National Park: Climate change or human activity?

Transitional features of desert environments partially determine the risks associated with ecosystems. Influenced by climate change and human activities, the variability and uncertainty of desertification levels and ecological risks in the Qinghai Area of Qilian Mountain National Park (QMNPQA) has become increasingly prominent. As a critical ecological barrier in northwest China, monitoring desertification dynamics and ecological risks is crucial for maintaining ecosystem stability. This study identifies the optimal monitoring model from four constructed desertification monitoring models and analyzes spatiotemporal changes in desertification. The spatial and temporal changes in ecological risks and their primary driving factors were analyzed using methods such as raster overlay calculation, geographic detector, cloud model, and trend analysis. The main conclusions are as follows: The desertification feature spatial model based on GNDVI-Albedo demonstrates better applicability in the study area, with an inversion accuracy of 81.24%. The levels of desertification and ecological risks in QMNPQA exhibit significant spatial heterogeneity, with a gradual decrease observed from northwest to southeast. From 2000 to 2020, there is an overall decreasing trend in desertification levels and ecological risks, with the decreasing trend area accounting for 89.82% and 85.71% respectively, mainly concentrated in the southeastern and northwestern parts of the study area. The proportion of areas with increasing trends is 4.49% and 7.05% respectively, scattered in patches in the central and southern edge areas. Surface temperature (ST), Digital Elevation Map (DEM), and Green normalized difference vegetation index (GNDVI) are the most influential factors determining the spatial distribution of ecological risks in QMNPQA. The effects of management and climatic factors on ecological risks demonstrate a significant antagonistic effect, highlighting the positive contributions of human activities in mitigating the driving effects of climate change on ecological risks. The research results can provide reference for desertification prevention and ecological quality improvement in QMNPQA.

Spatial and temporal-trend assessment of desertification-sensitive land using the desertification sensitivity index in the provincial Ninh Thuan, Vietnam.

Desertification is a specific land-degrading process, reducing soil productivity and potentially threatening global food security. Therefore, spatially and temporally identifying and mapping desertification-sensitive areas is essential for better management. The current study aimed to (1) assess spatial areas sensitive to desertification and (2) examine the changing tendency of the desertification-sensitive areas over the past 25 years in the provincial Ninh Thuan. The desertification sensitivity index (DSI) was computed based on the Medalus model using 10 quantitative parameters, grouped into the soil, climate, and vegetation quality indexes, computed for the years 1996, 2005, 2010, and 2016. GIS was used to map desertification-sensitive areas associated with five DSI classes. Results showed that classes II and III had the highest area percentage, followed by classes IV and V, and class I. The classes most sensitive to desertification (classes IV and V) covered around 13 to 17%, and classes II and III were 25 to 32% of the total study area, respectively. The coastal areas located in the southeastern parts were more sensitive to desertification than the other parts. Over the four examined periods, the areas of classes IV and V increased while those of classes II and I decreased. These indicated that the study province tended to increase in its desertification sensitivity with a severe increase in the coastal areas over the past 25 years. The key factors involved in these changes could be related the human activities and climate variation, which could be more serious in southeastern areas than in the other areas.

The role of invasive plant species in drought resilience in agriculture: the case of sweet briar (Rosa rubiginosa L.).

Sweet briar (Rosa rubiginosa) belongs to the group of wild roses. Under natural conditions it grows throughout Europe, and was introduced also into the southern hemisphere, where it has efficiently adapted to dry lands. This review focuses on the high adaptation potential of sweet briar to soil drought in the context of global climatic changes, especially considering steppe formation and desertification of agricultural, orchard, and horticultural areas. We provide a comprehensive overview of current knowledge on sweet briar traits associated with drought tolerance and particularly water use efficiency, sugar accumulation, accumulation of CO2 in intercellular spaces, stomatal conductance, gibberellin level, effective electron transport between photosystem II and photosystem I, and protein content. We discuss the genetics and potential applications in plant breeding and suggest future directions of study concerning invasive populations of R. rubiginosa. Finally, we point out that sweet briar can provide new genes for breeding in the context of depleting gene pools of the crop plants.

Satellite greenness and solar-induced chlorophyll fluorescence reveal reverse desertification in Gurbantunggut Desert.

The desertification reversal is a process of revegetation and natural restoration in fragile dryland areas due to human activities and climate change mediation. Understanding the impact of desertification reversion on terrestrial ecosystems, including vegetation greenness and photosynthetic capacity, is crucial for land policy-making and carbon-cycle model improvement. However, the phenomenon of desertification reversal is rarely mentioned in previous studies, which dramatically limits the understanding of vegetation dynamics in the arid area. Therefore, it is of great necessity to investigate the status of desertification reversal on the ecosystem in arid areas. In this study, we first reported the phenomenon of desertification reversion over the southern edge of the Gurbantunggut Desert through the Moderate-resolution Imaging Spectroradiometer classification map year by year. We discussed the consequences, ways, and causes of desertification reversion. Our results showed that the desertification reversal significantly increased vegetation greenness and photosynthetic capacity, which largely offset the negative impact of desertification on the ecosystem productivity; cropland expansion and grassland's natural restoration were the two main ways of desertification reversal; the improvement of soil-water condition was an essential environmental factor leading to the phenomenon of reverse desertification. This finding highlights the importance of desertification reversal in the carbon cycle of dryland ecosystems and prove that desertification reversal is an integral part of global and dryland vegetation greening.

South American Dry Chaco rangelands: Positive effects of cattle trampling and transit on ecohydrological functioning.

Livestock production in drylands requires consideration of the ecological applications of ecohydrological redistribution of water. Intensive cattle trampling and the associated increase of surface runoff are common concerns for rangeland productivity and sustainability. Here, we highlight a regional livestock production system in which cattle trails and trampling surrounding an artificial impoundment are purposely managed to enhance redistribution and availability of water for cattle drinking. Based on literature synthesis and field measurements, we first describe cattle production systems and surface water redistribution in the Dry Chaco rangelands of South America, and then develop a conceptual framework to synthesize the ecohydrological impacts of livestock production on these ecosystems. Critical to this framework is the pioshere-a degraded overgrazed and overtrampled area where vegetation has difficulties growing, usually close to the water points. The Dry Chaco rangelands have three key distinctive characteristics associated with the flat sedimentary environment lacking fresh groundwater and the very extensive ranching conditions: (1) cattle drinking water is provided by artificial impoundments filled by runoff, (2) heavy trampling around the impoundment and its adjacent areas generates a piosphere that favors runoff toward the impoundment, and (3) the impoundment, piosphere, and extensive forage areas are hydrologically connected with a network of cattle trails. We propose an ecohydrological framework where cattle transit and trampling alter the natural water circulation of these ecosystems, affecting small fractions of the landscape through increased runoff (compaction in piosphere and trails), surface connectivity (convergence of trails to piosphere to impoundment), and ponding (compaction of the impoundment floor) that operate together making water harvesting and storage possible. These effects have likely generated a positive water feedback on the expansion of livestock in the region with a relatively low impact on forage production. We highlight the role of livestock transit as a geomorphological agent capable of reshaping the hydrology of flat sedimentary rangelands in ways that can be managed positively for sustainable ranching systems. We suggest that the Dry Chaco offers an alternative paradigm for rangelands in which cattle trampling may contribute to sustainable seminatural production systems with implications for other dry and flat rangelands of the world.

Retaining natural vegetation to safeguard biodiversity and humanity.

Global efforts to deliver internationally agreed goals to reduce carbon emissions, halt biodiversity loss, and retain essential ecosystem services have been poorly integrated. These goals rely in part on preserving natural (e.g., native, largely unmodified) and seminatural (e.g., low intensity or sustainable human use) forests, woodlands, and grasslands. To show how to unify these goals, we empirically derived spatially explicit, quantitative, area-based targets for the retention of natural and seminatural (e.g., native) terrestrial vegetation worldwide. We used a 250-m-resolution map of natural and seminatural vegetation cover and, from this, selected areas identified under different international agreements as being important for achieving global biodiversity, carbon, soil, and water targets. At least 67 million km2 of Earth's terrestrial vegetation (∼79% of the area of vegetation remaining) required retention to contribute to biodiversity, climate, soil, and freshwater conservation objectives under 4 United Nations' resolutions. This equates to retaining natural and seminatural vegetation across at least 50% of the total terrestrial (excluding Antarctica) surface of Earth. Retention efforts could contribute to multiple goals simultaneously, especially where natural and seminatural vegetation can be managed to achieve cobenefits for biodiversity, carbon storage, and ecosystem service provision. Such management can and should co-occur and be driven by people who live in and rely on places where natural and sustainably managed vegetation remains in situ and must be complemented by restoration and appropriate management of more human-modified environments if global goals are to be realized.

Retención de la vegetación natural para salvaguardar la biodiversidad y la humanidad Resumen Hoy en día hay muy poca integración de los esfuerzos mundiales para alcanzar los objetivos internacionales de reducción de las emisiones de carbono, impedimento de la pérdida de biodiversidad y conservación de los servicios ambientales esenciales. Estos objetivos dependen parcialmente de la conservación de los bosques, selvas y praderas naturales (por ejemplo, nativos y en su mayoría sin alteraciones) y seminaturales (por ejemplo, de uso humano sostenible o de baja intensidad). Obtuvimos de manera empírica objetivos espacialmente explícitos, cuantitativos y basados en áreas para la conservación de la vegetación terrestre natural y seminatural (por ejemplo, nativa) en todo el mundo para mostrar cómo unificar los objetivos internacionales. Usamos un mapa de 250 m de resolución de la cubierta vegetal natural y seminatural y, a partir de él, seleccionamos las áreas identificadas como importantes en diferentes acuerdos internacionales para alcanzar los objetivos globales de biodiversidad, carbono, suelo y agua. Al menos 67 millones de km2 de la vegetación terrestre de la Tierra (∼79% de la superficie de vegetación restante) requieren ser conservados para contribuir a los objetivos de conservación de la biodiversidad, el clima, el suelo y el agua dulce en virtud de cuatro de las resoluciones de las Naciones Unidas. Esto equivale a conservar la vegetación natural y seminatural en al menos el 50% de la superficie terrestre total de la Tierra (sin contar a la Antártida). Los esfuerzos de retención podrían contribuir a alcanzar múltiples objetivos simultáneamente, especialmente en donde la vegetación natural y seminatural puede gestionarse para lograr beneficios colaterales para la biodiversidad, el almacenamiento de carbono y la provisión de servicios ambientales. Esta gestión puede y debe ser impulsada y llevada a cabo por las personas que viven en y dependen de los lugares donde la vegetación natural y gestionada de forma sostenible permanece in situ y debe complementarse con la restauración y la gestión adecuada de entornos modificados por el hombre si se quieren alcanzar los objetivos globales.

Remote sensing of desertification and study of temporal variability of aeolian deposits in parts of the Arabian Desert for sustainable development in an arid environment.

Aeolian deposit in part of the Arabian Desert is mapped using ASTER data to understand desertification, land encroachment, and degradation, and to assess agricultural development in arid regions. In this study, the interpretation of emissive spectra of sand deposits showed the presence of triplet absorptions in emissivity between 8 and 9.50 µm and studied with ASTER spectral bands to map the deposits. The ASTER quartz index (QI) images used to study the Abu Samra region, Qatar from 2000 to 2021 showed significant changes in desertification and land degradation. Analysis of temporal variability of deposits between 2000 and 2021 using ASTER band 12 by Parallelepiped image classification showed a decreasing trend from 9.70% to 2.94% in their distributions due to erosion and transportation. The changes are studied using FCC images (R:1; G:2; B:3) and hill-shaded images of 2000 and 2021. The results are confirmed from FCC (R:14; G:12; B:11) and Google Earth satellite images which showed the occurrence of sabkhas in 1985 and their disappearance from 2015, and the presence of agriculture in 2000 and their absence from 2005. The changes in desertification, land degradation, and agricultural development are verified in the field and evidenced. The grain size analysis of samples by ASTM method showed aeolian deposits have very fine to very coarse (63-2000 µm) sand types with silts of <3%. The samples analyzed by XRD and SEM-EDX methods showed the occurrence of dolomite, calcite, quartz, feldspar, and gypsum minerals with high sphericity and sub-angular to well-rounded characters and suggested transportations of grains from long distances. The geochemical elements analyses of samples reflected the chemistry of carbonates, aluminosilicates, and evaporites minerals which could have been derived from the carbonate, shale and sandstone formations, and sabkhas that occurred in Qatar and the Arabian Peninsula.

Framing socioecological complexity: The long-term evolution of multiple dimensions of desertification risk in Italy.

Desertification risk depends on the interplay of biophysical and socioeconomic drivers, among which climate change, soil depletion, landscape modifications, and biodiversity decline are key factors of change in Southern Europe. The present study introduces a diachronic analysis of desertification risk in Italy adopting a multidimensional approach based on four dimensions (ecological, economic, demographic, and administrative) assessed at three dates (1961, 1991, and 2011). These risk components were evaluated separately in Southern Italy, a formerly affected region (sensu United Nations Convention to Combat Desertification), and Northern/Central Italy, a nonaffected region in the country. All risk measures document how the divide between affected and nonaffected regions in Italy has gradually reduced. Because of local warming and rising human pressure, Northern Italy has recently displayed a level of desertification risk close to those observed in Southern Italy over the last 30 years. These results suggest a thorough revision of the national classification of risky areas, that may inform more specific mitigation and adaptation policies responding effectively to recent socioenvironmental trends and local (economic) dynamics. The intrinsic system's evolution observed at both regional and national level in Italy may be generalized to a broader European context. Our work finally documents the appropriateness of a multidimensional definition of desertification risk grounded on the joint analysis of ecological, demographic, economic, and administrative indicators. A comprehensive knowledge of socioeconomic patterns and processes of change contributes to more precise scenario modeling and design of integrated strategies mitigating desertification risk.

A High-Precision Remote Sensing Identification Method for Land Desertification Based on ENVINet5.

Land desertification is one of the serious ecological and environmental problems facing mankind today, which threatens the survival and development of human society. China is one of the countries with the most serious land desertification problems in the world. Therefore, it is of great theoretical value and practical significance to carry out accurate identification and monitoring of land desertification and its influencing factors in ecologically fragile areas of China. This is conducive to curbing land desertification and ensuring regional ecological security. Minqin County, Gansu Province, located in northwestern China, is one of the most serious areas of land desertification, which is also one of the four sandstorm sources in China. Based on ENVINet5, this paper constructs a high-precision land desertification identification method with an accuracy of 93.71%, which analyzes the trend and reasons of land desertification in this area, provides suggestions for disaster prevention in Minqin County. and provides a reference for other similar areas to make corresponding desertification control policies.

Monitoring Land Degradation Dynamics to Support Landscape Restoration Actions in Remote Areas of the Mediterranean Basin (Murcia Region, Spain).

This study aims to develop a workflow methodology for collecting substantial amounts of Earth Observation data to investigate the effectiveness of landscape restoration actions and support the implementation of the Above Ground Carbon Capture indicator of the Ecosystem Restoration Camps (ERC) Soil Framework. To achieve this objective, the study will utilize the Google Earth Engine API within R (rGEE) to monitor the Normalized Difference Vegetation Index (NDVI). The results of this study will provide a common scalable reference for ERC camps globally, with a specific focus on Camp Altiplano, the first European ERC located in Murcia, Southern Spain. The coding workflow has effectively acquired almost 12 TB of data for analyzing MODIS/006/MOD13Q1 NDVI over a 20-year span. Additionally, the average retrieval of image collections has yielded 120 GB of data for the COPERNICUS/S2_SR 2017 vegetation growing season and 350 GB of data for the COPERNICUS/S2_SR 2022 vegetation winter season. Based on these results, it is reasonable to asseverate that cloud computing platforms like GEE will enable the monitoring and documentation of regenerative techniques to achieve unprecedented levels. The findings will be shared on a predictive platform called Restor, which will contribute to the development of a global ecosystem restoration model.

Microplastic transport during desertification in drylands: Abundance and characterization of soil microplastics in the Amu Darya-Aral Sea basin, Central Asia.

Desertification and microplastic pollution are major environmental issues that impact the function of the ecosystem and human well-being of drylands. Land desertification may influence soil microplastics' abundance, transport, and distribution, but their distribution in the dryland deserts of Central Asia's Amu Darya-Aral Sea basin is unknown. Here, we investigated the abundance and distribution of microplastics in dryland desert soils from the Amu Darya River to the Aral Sea basin in Central Asia at a spatial scale of 1000 km and soil depths ranging from 0 to 50 cm. Microplastics were found in soils from all sample locations, with abundances ranging from 182 to 17841 items kg-1 and a median of 3369. Twenty-four polymers were identified, with polyurethane (PU, 37.3%), silicone resin (SR, 17.0%), and chlorinated polyethylene (CPE, 9.8%) accounting for 64.1% of all polymer types. The abundance of microplastics was significantly higher in deep (20-50 cm) soils than in surface (0-5, 5-20 cm) soils. The main morphological characteristics of the observed microplastics were small size (20-50 µm) and irregular particles with no round edges (mean eccentricity 0.65). The abundance was significantly and positively related to soil EC and TP. According to the findings, desertification processes increase the abundance of microplastic particles in soils and promote migration to deeper soil layers. Human activities, mainly grazing, may be the region's primary cause of desertification and microplastic pollution. Our findings provide new information on the diffusion of microplastics in drylands during desertification; these findings are critical for understanding and promoting dryland plastic pollution prevention and control.

Impacts of abandoned sloping farmland on soil aggregates and aggregate-associated organic carbon in karst rocky desertification areas.

Vegetation restoration after the abandonment of sloping farmland can effectively promote the sequestration of soil organic carbon (SOC), with soil aggregates playing a pivotal role. However, in abandoned farmlands in karst regions with varying degrees of rocky desertification, the relationship between soil aggregates, aggregate-associated organic carbon (AAOC), and total SOC content remains unclear. Taking abandoned sloping farmlands (5 years, 10 years, and 15 years) with different levels of rocky desertification (no rocky desertification, potential rocky desertification, slight rocky desertification, and moderate rocky desertification) in a typical karst area as research objects, this study investigated the dynamic characteristics of the particle size distribution of soil aggregates, total SOC, and AAOC. The results indicated that total SOC content in the 0-20 cm soil layer increased after abandonment in all levels of rocky desertification, peaking after 15 years. The abandoned sloping farmland with moderate desertification showed the best recovery effect. Post-abandonment vegetation restoration increased the content of 5-10 mm soil aggregates, but decreased those of 1-2 mm and < 0.25 mm aggregates. Particularly for 5-10 mm aggregates, the contribution of AAOC to total SOC significantly increased over time. Moreover, a strong correlation was observed between >1 mm aggregates and total SOC (p < 0.05). The increase in total SOC was primarily driven by the growth of AAOC in 5-10 mm aggregates. In general, vegetation restoration is an effective approach for enhancing total SOC content in abandoned sloping farmland with varying degrees of rocky desertification.

Environmental sensitivity assessment and land degradation in southeastern Serbia: application of modified MEDALUS model.

This paper aims to improve the methodology and results accuracy of MEDALUS model for assessing land degradation sensitivity through the application of different data detail levels and by introducing the application of Ellenberg indices in metrics related to vegetation drought sensitivity assessment. For that purpose, the MEDALUS model was applied at 2 levels of detail. Level I (municipality level) implied the use of available large-scale databases and level II (watershed) contains more detailed information about vegetation used in the calculation of the VQI and MQI factors (Fig. S6). The comparison was made using data based on CORINE Land Cover (2012) and forest inventory data, complemented with object-based classification. Results showed that data based on forest inventory data with the application of Ellenberg's indices and object-based classification have one class more, critical (C1 and C2) and that the percentage distribution of classes is different in both quantitative (area size of class sensitivity) and qualitative (aggregation and dispersion of sensitivity classes). The use of data from Forest Management Plans and the application of Ellenberg's indices affect the quality of the results and find its application in the model, especially if these results are used for monitoring and land area management on fine scales. Remote sensed data images (Sentinel-2B) were introduced into the methodology as a very important environmental monitoring tool and model results validation.