The sediment connectivity determined by hyrological processes, topography and ground cover regulates the soil redistribution, hence the sediment budget, and variation of soil properties on hillslopes. Exploring the coupling between sediment connectivity and the variation of soil properties will enhance the understanding of the role connectivity played in eco-geomorphological feedbacks. Sediment connectivity mediates the material supply and loss simultanously. There may be threshold of sediment connectivity for the soil material budget and thus the soil properties in the vegetation patches. However, scarce of quantitative linkage between the soil properties and connectivity hampered the idenfication of the threshold. This study aimed to linked the sedimentological connectivity with variation of soil orgainc carbon (SOC) and texture on hillslope in semi-arid region on the Loess Plateau in northern China. The Relative Connectivity Index (RCI_SS) integrating upslope connectivity (UC) indicating the probability of soil materials flow in and downslope connectivity (DC) describing the probability of soil resource flow out shrub patches was developed as comprehensive indicator of sedimentological connectivity. The coupling between sedimentological connectivity and the variation of SOC and soil texture was explored at the hillslope scale. Results showed that the sediment connectivity, SOC content and sand content increased from the summit to the foot slope, but the efficiency of shrub patches to retain sediment and SOC decreased. The enhanced connectivity led to the decreased efficiency of sediment and SOC retention, and the coarsening trend of soil texture. This study revealed that the sediment connectivity may contribute to the early warning of the degradation of planted shrub ecosystems from the perspective of soil properties. This study also suggested further exploration of the connectivity threshold for ecosystem state transition by adopting eco-geomorphological framework.

As a result of adaptation to the environment, the great environmental spatial heterogeneity leads to the high spatial heterogeneity of vegetation status. This coupling may be more apparent in water-limited drylands, where topography is the main determinant of small-scale variation in water availability and energy. Metrics describing this coupling may contribute to the detection of the extension of vegetation reshaped by human intervention and other driven forces. In this study, the heterogeneity index of coupling (HIC) was developed to indicate the coupling between spatial heterogeneity of vegetation status (H v) and the spatial heterogeneity of topography (H T) in the Loess Plateau in northern China. The 16-day composed MODIS normalized vegetation index (NDVI) with a resolution of 250 m and SRTM DEM were employed to quantify the heterogeneity of vegetation status and the topographical heterogeneity. The results show that HIC varies among geomorphic zones, land cover types, and land cover change categories. Among all land cover types, HIC of sandy areas was the largest, followed by the HIC of the forest, shrub, farmland, and grassland. Among geomorphic zones, the highest HIC value appeared in plains with dense residential areas, followed by sandy land that is frequently reshaped by wind, rocky mountainous areas, hilly and gully loess plateaus, and loess tableland. It was revealed that the alternation of vegetation by human activities and natural disturbances shaped greater HIC. Results of this study approved the effectiveness of the HIC in reflecting the coupling of the vegetation status with topography at regional scale.

The Sahel is facing a serious environmental crisis due to aeolian disaster that has seriously affected the local development and survival of residents. Thus, evaluating the aeolian disaster risk levels and their variation in the Sahel is important. This study established an optimal model by evaluating the applicability of different models in the aeolian disaster risk determination in the Sahel. Using this model, the spatiotemporal changes in the risk subsystem of aeolian disaster (hazard, sensitivity, vulnerability, and restorability) and the aeolian disaster risk in the Sahel from 2000 to 2020 were analyzed. Based on this analysis, the impact of climate change and human activities on the aeolian disaster risk in the Sahel was evaluated. Results revealed that the variable fuzzy recognition (VFR) based on the aeolian disaster risk index (ADRI) model had the highest accuracy, reaching 89.72 %. The middle of the Sahel, located in the desert-grassland transition zone, exhibited a high hazard, sensitivity, and vulnerability, rendering it highly susceptible to aeolian disaster. The proportion of areas with very low and very high aeolian disaster risk levels decreased from 2000 to 2020, while those with low and high levels increased, and the change in moderate risk level areas remained relatively stable. Areas of low, moderate, and high risk are more sensitive to climate change and human activities and are subjected to greater pressure for change. Human activities were the main factor for the change of ADRI in the Sahel, accounting for 69.74 and 58.19 % of the increased and decreased areas of ADRI, respectively. This study evaluated the level of aeolian disaster risk in the Sahel and identified the main driving factors, providing a reference for Sahel countries to better implement the Green Great Wall (GGW) program in Africa, thereby mitigating the adverse effects of aeolian disaster.

荒漠化被公认为是“地球的癌症”,沙漠化是荒漠化的主要表现形式之一。中国和非洲许多国家都深受荒漠化危害和威胁。2018 年中非合作论坛北京峰会上，习近_x000D_平指出：要在未来 3 年及今后一段时间重点实施“八大行动”,其中在“绿色发展行动”方面，强调要与非洲国家在应对气候变化、荒漠化防治等方面重点加强_x000D_交流合作。非洲“绿色长城”计划是 2005 年由非洲萨赫勒—撒哈拉国家共同体成员国发起建设的一条平均宽约 15 公里、长 7775 公里、穿越 11 个国家的防护林_x000D_带。2007 年该计划由非盟主导并正式启动确定为洲际旗舰计划。然而，非洲“绿色长城”建设因其覆盖面广、工程量大以及区域、技术等方面的差异性和复杂性而_x000D_面临众多挑战，特别是缺乏成套的技术模式与综合的系统方案来共同实现植树造林、生态适应、减贫和带动地区经济发展等目标，也更缺乏成熟的技术与模式具体_x000D_实施。本项目针对上述问题，开展了联合考察和研究，技术示范与推广能力建设与培养，形成了一系列成果与科学报告。该报告揭示了非洲绿色长城重点区域沙漠化时空格局与驱动机制；编制了非洲“绿色长城”重点区域土地沙化防治区划图；研发了机械—生物综合固沙技术体系，形成了尼日利亚防护林管护优化与经济功能提升、埃塞俄比亚退化草地生态修复与利用等关键技术；构建了综合防治方案，形成沙漠化防治技术与生计可持续管理的优化模式。本研究成果将提高非洲“绿色长城”建设国家土地沙化治理技术水平，改善区域生态环境质量，促进经济社会发展。The African"Great Green Wall"project,initiated in 2005 by member states of the African Community of Sahelo-Saharan States,entails the construction of a protective forest belt spanning approximately 15 kilometers wide and 7,775 kilometers long,traversing 11 countries.In 2007,under the leadership of the African Union,this initiative was officially launched and established as a flagship intercontinental program.Nevertheless,the construction of the"Great Green Wall"in Africa encounters numerous challenges due to its extensive coverage,significant workload,regional disparities,technical complexities,and,notably,the absence of comprehensive technical models and integrated system solutions required to achieve afforestation,ecological adaptation,poverty reduction,and regional economic development goals.Furthermore,mature technologies and specific implementation models are lacking._x000D__x000D_To address these challenges,this project conducted joint investigations and research,focusing on technology demonstrations,capacity building,and training.It has produced a range of findings and scientific reports.These reports delineate the spatiotemporal patterns and driving mechanisms of desertification in the key regions of the African Great Green Wall.The project has also developed a zoning map for land desertification prevention and control in these critical areas.Notably,it established a mechanical-biological integrated sand fixation technology system and key technologies,including the optimization of forest belt management and protection in Nigeria,as well as the enhancement of economic functions.Similarly,it explored ecological restoration and utilization of degraded grasslands in Ethiopia._x000D_The culmination of these efforts is the construction of a comprehensive prevention and control plan,encapsulating an optimized model for desertification control technology and sustainable livelihood management.The results of this study are poised to elevate the technical proficiency in land desertification control within the construction of Africa's"Great Green Wall,"thereby improving the quality of the regional ecological environment and stimulating economic and social development.

Accurate estimation of vegetation Net Primary Productivity (NPP) has important theoretical and practical significance for ecological environment governance, carbon cycle research, and the rational development and utilization of natural resources. In this study, the spatial characteristics, temporal changes, and driving factors of NPP in the Conventional Lake Chad Basin (CLCB) were based on MODIS data by constructing a Carnegie Ames Stanford Approach (CASA) model and using a combination of Residual trends (RESTREND) and correlation analysis. The results showed that from 2001 to 2020, the NPP of the CLCB decreased annually (1.14 g C/m2), mainly because of overgrazing, deforestation, and large-scale irrigation. We conducted a driving factor analysis and found that the main influencing factor of the NPP of the CLCB is high-intensity human activities, including farmland reclamation and animal husbandry. Although the impact of climate change on NPP is not obvious in the short term, climate change may help recover NPP in the long term. The continued reduction in NPP has greatly increased the difficulty of regreening the Sahel; the increase in population density and rapid urbanization have led are major contributing factors to this. Our findings have important implications for the continued implementation of stringent revegetation policies. However, owing to limited data and methods, only the overall change trend of NPP was obtained, and comprehensive follow-up studies are needed. © 2023 by the authors.

Climate factors like precipitation and temperature fulfil a significant role in assessing the status of the vegetation. Vegetation prediction in terms of climatic conditions represents a critical issue because it helps monitor and maintain the ecosystem's well-being by maintaining track of changes in vegetation disturbance. It is challenging to locate large-scale current vegetation data for use in a variety of applications. In this study, temperature and precipitation were applied to develop a simple linear regression model that predict Normalized Difference Vegetation Index (NDVI) over the African continent. For training data, the third-general Normalized Difference Vegetation Index (NDVI3g) generated from Global Inventory Modeling and Mapping Studies (GIMMS) at a 1/12 degrees resolution was the main input for simulation from 1982 to 2005. From 2006 to 2015, the third-general Normalized Difference Vegetation Index was used to validate the model outputs. The model's accuracy in the arid climate zone (poor vegetation areas) is stronger than in the other four climate zones of Africa, with an R2 of 74%, the lowest p-value of 0.001, the lowest root mean square error (RMSE) of 0.027 and the lowest mean absolute error (MAE) of 0.022. Based on future vegetation condition projections, this approach will assist a more effective management of the future food reservations for the battle against hunger. It will also help with the design, management, and execution of ecological restoration initiatives, research data availability as well as understanding the relationship between vegetation variation and climate variability.

Hydrological connectivity affects the carbon capture and redistribution over landscapes. However, the contribution of hydrological connectivity to the spatial heterogeneity of carbon sequestration, particularly the spatial variation of carbon retention, is not well covered in carbon inventory and estimation. This study addressed the contribution of hydrological connectivity to the soil carbon retention on a hillslope with a mosaic of shrub patches and inter-shrub area covered by grass, biological crust and bare soil on the Loess Plateau, China. The variation of the efficiency of the shrub patches to retain SOC and the SOC difference between shrub patch and inter-shrub area among slope positions were revealed in the context of varied hydrological connectivity indicated by the contributing area. The results illustrate that the efficiency of shrub patches to retain sediment and SOC transported from upslope areas decreased from the hillslope top to the slope foot, though the morphological traits of the shrub patches did not significantly varied. The mean SOC in shrub patches declined, and increased in intershrub areas from hillslope top to slope foot. Consequently, the SOC difference between shrub patch and intershrub area declined from the top to the foot of the hillslope. These results imply that the size of contributing areas is the dominant contributor to the spatial variation of the efficiency of shrub patches to retain SOC, and the pattern of SOC difference between shrub patches and inter-shrub areas. The results highlight the necessity to incorporate the spatial heterogeneity of hydrological connectivity into evaluating the carbon retention efficiency of vegetation, especially in the dryland landscape. This study also revealed that the lack of hydrological connectivity may lead to great uncertainty in assessing SOC sequestration in terrestrial landscapes.

The transitional characteristics of desert grasslands in the Sahel determine the ecosystem's fragility, which is extremely susceptible to the expansion and reversal of land desertification under the influence of climate change and anthropogenic activities. Accordingly, monitoring desertification dynamics is essential to combat this process. Based on Moderate Resolution Imaging Spectroradiometer (MODIS) data, this study analysed the applicability of different feature space models to monitor desertification levels in the Sahel from 2000 to 2020, revealing the optimal monitoring model, analysing the spatiotemporal changes and primary driving factors. The results were as follows: In the Sahel, the albedo-modified soil adjusted vegetation index (MSAVI) based on the point-to-point model is the best for desertification monitoring, with an overall accuracy of 86.78%. Generally, the level of desertification was reduced from 2000 to 2020, the area of extremely severe desertification decreased by retreating northward; and the areas of light, moderate, and severe desertification increased slowly by expanding northward. Light, moderate, and severe desertification lands were more sensitive to climate change and anthropogenic activities, undergoing greater change intensity. Precipitation was the most influential factor determining the spatial distribution of desertification in the Sahel, with anthropogenic activities also having a significant effect on the desertification level. This study comprehensively analysed desertification patterns in the Sahel and identified the primary driving factors, which are essential to inform Sahelian desertification control mechanisms in the future.

Long-term monitoring of the ecological environment changes is helpful for the protection of the ecological environment. Based on the ecological environment of the Sahel region in Africa, we established a remote sensing ecological index (RSEI) model for this region by combining dryness, moisture, greenness, and desertification indicators. Using the Moderate-resolution Imaging Spectroradiometer (MODIS) data in Google Earth Engine (GEE) platform, this study analyzed the ecological environment quality of the Sahel region during the period of 2001-2020. We used liner regression and fluctuation analysis methods to study the trend and fluctuation of RSEI, and utilized the stepwise regression approach to analyze the contribution of each indicator to the RSEI. Further, the correlation analysis was used to analyze the correlation between RSEI and precipitation, and Hurst index was applied to evaluate the change trend of RSEI in the future. The results show that RSEI of the Sahel region exhibited spatial heterogeneity. Specifically, it exhibited a decrease in gradient from south to north of the Sahel region. Moreover, RSEI in parts of the Sahel region presented non-zonal features. Different land-cover types demonstrated different RSEI values and changing trends. We found that RSEI and precipitation were positively correlated, suggesting that precipitation is the controlling factor of RSEI. The areas where RSEI values presented an increasing trend were slightly less than the areas where RSEI values presented a decreasing trend. In the Sahel region, the areas with the ecological environment characterized by continuous deterioration and continuous improvement accounted for 44.02% and 28.29% of the total study area, respectively, and the areas in which the ecological environment was changing from improvement to deterioration and from deterioration to improvement accounted for 12.42% and 15.26% of the whole area, respectively. In the face of the current ecological environment and future change trends of RSEI in the Sahel region, the research results provide a reference for the construction of the "Green Great Wall" (GGW) ecological environment project in Africa.

The world's rapid population growth is also fueling the high demand for food. Cropland intensification and expansion as the primary source of increasing food production thrives everywhere, yet hinders natural vegetation. This study aims to examine the extent to which the development of Cropland intensity affects natural vegetation and scrutinizes its relationship with Gross Domestic Product (GDP) on the African continent from 1992 to 2015. The ratio of total Crop area harvested and Cropland extent (CE) datasets used to compute the cropping intensity CI (yr(-1)) for each year over 24 years. The correlation coefficient and comparison method were applied for cropland intensity and natural vegetation to reveal the rate at which cropland intensity affects natural vegetation. The same method was applied between CI, CE and GDP percentage from Agriculture to know their relationship. The results revealed that Cropland extended at a rate of about 9130.17 km(2) yr(-1), leading to a rise of 219,123.99 km(2) of increase. Shrubland was the most devastated natural vegetation at a rate of -9461.96 km(2) and cleared about 227,087.1 km(2). The CI and GDP percentage from agriculture showed a strong negative correlation in most of the countries, especially in developing countries. The CI is low and the CE is high, which means the degradation of existing natural vegetation and the eradication of potential environment health. Ethiopia and Tanzania have been the only two countries which experienced cropland decrease among the top 10 African countries with a large cropland area, while Nigeria and Sudan have increased the most. Further Malawi witnessed the highest percentage growth for cropland. South Sudan has identified strong trends in GDP percent from agriculture, while Libya has seen substantial decline. On the other hand, Liberia, Sierra Leone, Guinea-Bissau, Ethiopia, and Chad identified to have the biggest % of agriculture to GDP during the study period.