Against the backdrop of accelerating global production network restructuring and the rapid ascent of the renewable energy sector, understanding how firms embedded in differing institutional environments integrate across local and global scales is crucial for interpreting the spatial logic of the energy transition. Drawing on 2023 headquarters - subsidiary data for Chinese and US renewable energy firms, this study constructs city-based integration networks to comparatively analyse the structural dynamics of production networks under distinct political-economic systems. Our analysis reveals three key findings. First, despite institutional divergence, localised networks in both countries exhibit strong territorial embeddedness, with electricity supply and manufacturing constituting the core sectors. Second, the state remains a pivotal actor; rather than serving merely as an institutional backdrop, it functions as an active network participant that reshapes firms' modes of embeddedness, intercity linkages and spatial organisation. This finding reinforces the imperative of placing the state at the centre of analytical frameworks regarding renewable energy systems. Third, while globalisation levels remain relatively limited, integration pathways differ markedly: China displays a springboard pattern mediated heavily by Hong Kong, whereas the US exhibits a more polycentric, multi-nodal configuration. The pronounced regionalisation observed in both contexts highlights the strategic necessity of fostering autonomous regional supply chains and leveraging key gateway nodes to navigate an increasingly fragmented global energy landscape.

Continuous monitoring of tidal currents with high spatiotemporal resolution is essential for navigation safety and marine environmental forecasting in strait regions. This study proposes a novel method for estimating diurnal tidal currents by combining Scharr operator-enhanced sea surface temperature (SST) imagery with the wavelet-based optical flow velocimetry (wOFV) algorithm. Using hourly 1-km resolution JCOPE-T 1 ks SST reanalysis data over the Western Channel of the Korea Strait, we retrieved continuous surface currents across four representative months in 2024. The Scharr operator significantly improved retrieval accuracy by enhancing thermal front features, increasing the U component correlation coefficient from 0.379 to 0.446 relative to raw SST, with improvements most pronounced in weak-gradient regions. Compared with the TPXO tidal model, the proposed method showed better agreement with high-frequency radar observations, reducing mean absolute errors (MAE) values for the U and V components by 12.2% and 20.9%, respectively. Harmonic analysis of the retrieved currents confirmed the M2-dominated mixed tidal regime. The tidal ellipse parameters showed good agreement with radar observations (M2 semimajor axis MAE of 0.069 m/s, inclination MAE of 8.98 degrees). The pronounced rectilinear flow characteristics reflect strong topographic constraints on tidal wave propagation. After removing tidal signals, the residual current clearly revealed the northeastward transport of the Tsushima Warm Current. In addition, a cyclonic eddy (similar to 20-30 km diameter) was successfully identified during tidal transitions, demonstrating the method's potential for detecting fine-scale dynamical processes. This approach provides a new pathway for all-weather, high-resolution tidal current monitoring in strait regions, serving as a valuable complement to existing observation systems and numerical models.

Climate change affects all components of terrestrial ecosystems, including animal migration that is often ignored. Understanding how migratory rhythm responds to climate factors will provide new insights into the protection of the Earth’s ecosystem and environment. The Serengeti-Masai Mara Ecosystem is sustained by the world’s largest terrestrial large-herbivore migrations and is essential to the earth environment. While rainfall has long been recognized as its driver, the synergistic and multiple paths of precipitation-temperature-vegetation in synchronizing migration phenology remain poorly understood. The migration rhythm is being insufficiently explained why migratory animals track resources in specific regions, as the values of climate variables fluctuate greatly. The monitoring of the interior migratory path and absolute climatic values limits the explanations, and there still lack periodic models to monitor the migration rhythm. Here, we derive a novel geospatial model for periodic migration based on composite trigonometric functions, and implement a concave hull optimization to delineate migration corridors while minimizing spatial sampling errors. Interior-exterior contrasts of the migratory region are applied to explain the periodic rhythm. The statistical dependencies of migration on environmental factors are detected through multiple paths of influence, revealing the different roles by granger causality model, structural equation model and multivariate linear regression. The results showed that the migration features are well captured by the proposed periodic model, indicating two longitudinal migration cycles and one latitudinal cycle per year. The climatic factors directly affect migration with different roles of precipitation and temperature played in latitude and longitude directions, and also indirectly impact migration through vegetation. The interior-exterior contrasts of concave hulls are proven to be superior with higher correlations and lower error variances, presenting stronger causal relationship and influence, and can better explain why animals migrate during specific seasons, rather than absolute climatic values that fluctuate dramatically. The illustrated abstract displays the theories, models, and results of how climatic factors impact animal migration. The top panel illustrates the research area and datasets including climate data (precipitation and temperature), vegetation data, and calculated centroid data of migratory animals from the Serengeti-Masai Mara Ecosystem in East Africa. The middle section outlines the methods for establishing periodic models and detecting multiple pathways and synergistic synchrony, including the conceptualization of interior-exterior contrasts through geographic concave hulls, theoretical construction of periodic models, and monitoring methods for correlations, causal relationships, and pathways for impacts detection. Finally, the main findings of the study are introduced at the bottom panel, including the novel geographic spatial models that reveal the migration rhythm and diverse influences. The geographic abstract not only provides a universal geographic model, but also reveals insights into deeper reasons for animal migration. This provides a basis for protecting migration and better understanding the geospatial responses of terrestrial ecosystem to climate. A novel geospatial model for monitoring periodic migration was developed, and it well captured the migration rhythm. The synergistic synchrony of precipitation-temperature-vegetation with migration revealed the direct and indirect impacts of climatic factors. Stronger climatic influences were detected through the interior-exterior contrasts of concave hulls. Precipitation dominated the latitudinal movement, while temperature affected the longitudinal movement strongly.

Given the combined pressures of climate change and intensive coastal development, the coastal setback line (CSL) has become a critical instrument for reconciling disaster risk reduction, ecological conservation, and waterfront development. Thus, its scientific delineation and effective implementation are essential for sustainable coastal development. China's CSL governance remains nascent, with studies lacking systematic international analyses to support effective cross-referencing and localized optimization. Utilizing the Technology-Institution-Society (TIS) three-dimensional framework, this paper systematically reviews the practical status and prominent challenges of the CSL system in China; analyzes CSL delineation and regulatory practices across 15 typical countries and regions to extract key governance elements and general patterns; identifies transferable elements adaptable to the Chinese context; and formulates multi-dimensional optimization pathways for China's CSL system. The results show China has established a three-tier governance system, yet static delineation techniques, ambiguous access lists, formalistic public participation, and weak adaptive assessment persist. International trends signal risk-adaptive dynamic management, refined use control, and institutionalized participation, although widespread challenges remain. Drawing upon these insights and a qualitative transferability analysis, pathways are proposed for optimizing China's CSL system. In technical terms, this means transitioning from static delineation to monitoring-supported zoning setback regimes, with dynamic adjustments for priority coastal segments. Institutionally, an adaptive regulatory system should be established, grounded in baseline classification, scenario adjustment and tiered decision-making. From the societal dimension, information disclosure, public participation, and third-party evaluation should be strengthened to foster a learning-oriented comprehensive governance mechanism. Theoretical and policy support facilitates the enhancement of China's CSL toward coastal spatial governance.

Rural areas in Zambia continue to grapple with critical electricity shortages, positioning rooftop solar energy as a viable pathway for enhancing rural electrification. This study investigates the rooftop photovoltaic (PV) potential in rural areas with limited electricity access by quantifying usable rooftop surfaces, solar radiation levels, and the theoretical electricity generation. Additionally, the economic feasibility of household-scale PV systems is assessed. The results indicate that: (1) The total usable rooftop area is estimated at 26.93 km 2 , with average daily solar radiation ranging from 225.6 to 254.3 W/m 2 . (2) The corresponding annual electricity generation potential is approximately 1.63 TWh, exhibiting stable interannual variation but distinct seasonality, with peak outputs during the hot-dry and reduced yields during hot-wet periods. (3) The average life-cycle investment cost for a household PV system is USD 1166.8. In the absence of subsidies, the payback period is approximately 17.7 years; however, a 40%-50% government subsidy could shorten this to 9-11 years, extending the profitable timeframe beyond 13 years. These findings offer technical and economic benchmarks to facilitate the large-scale deployment of rooftop PV systems in low-electrified rural areas of Zambia.

Drought is posing a severe threat to agroecosystems, especially in Africa suffering from both frequent droughts and food crisis. Improving water use efficiency (WUE) is beneficial to competitiveness of rain-fed agroecosystems under drought stress. The agroecosystem WUE responses to drought tend to be asymmetric with time-lag effect. However, it remains unclear whether the time-lag effect varies with diverse droughts and how various droughts affect agroecosystem WUE in a dissimilar manner. Here, this study aimed to incorporate non-negligible time-lag relationship to disentangle the effects of droughts - meteorological drought caused by precipitation deficit and agricultural drought owing to soil moisture depletion - on agroecosystem WUE from the perspective of contribution and threshold. The time-lag effects of meteorological and agricultural drought on agroecosystem WUE were evaluated by applying partial correlation and time-lag analysis, which were taken into account to identify contributions of different droughts to WUE variation using elastic based method as well as drought thresholds driving abrupt shifts in WUE based on R package chngpt. The results revealed the contrasting effects of meteorological and agricultural drought on growing-season WUE. Agricultural drought had a more significant timelag effect with WUE lagging 3-6 months, while the response of WUE lagged only 2-3 months behind meteorological drought. Meanwhile, agricultural drought was the predominant contributor to nearly 90 % of agroecosystem WUE variation, with deep soil moisture at a depth of 40-100 cm in particular responsible for the most. Drought threshold, representing abrupt shift in the ability of WUE to tackle drought stress from adaptability to vulnerability, was higher in tropical semi-arid climate zone during agricultural drought, whereas the value of meteorological drought was larger in savannah climate zone. The results underscore fragile agroecosystems responding differently to droughts and provide support for maintaining water use efficiency by determining crucial water-limited process.

Dissolved inorganic nitrogen(DIN)and dissolved inorganic phosphorus(DIP)are the two dominant nutrients influencing seawater quality.Due to the non-optically active nature of nutrients and their regional variability,relying solely on optical data is inadequate for achieving high-precision remote sensing retrieval in complex marine environments.We developed a novel remote sensing algorithm for DIN and DIP using MODIS remote sensing reflectance(Rrs)products and the XGBoost machine learning framework.Beyond optical inputs,our model integrates sea surface temperature(SST)and spatiotemporal information,including a shoreline-based pixel location descriptor,which significantly enhances model performance.We generated monthly average distributions of DIN and DIP concentrations across China's coastal waters from 2012 to 2022.The findings highlight extensive high-nutrient zones in the Bohai Bay and Changjiang River(Yangtze River)Estuary-Hangzhou Bay regions,with a notable declining trend in nutrient concentrations.The Zhujiang River(Pearl River)Estuary also exhibits elevated nutrient levels,albeit with minimal changes.This study pioneers the incorporation of dual-coordinate information in nutrient retrieval for complex marine environments,significantly improving model accuracy and addressing stripping artifacts associated with single-coordinate systems.Moreover,the results provide unprecedented spatiotemporal insights into nutrient distributions in China's coastal waters,offering valuable support for marine environmental management and policy-making.

Rapid urbanization has spurred numerous urbanization-environmental assessments, including vegetation dynamics, phenology, urban heat islands, and natural disasters. However, the most fundamental issue—the delineation of non-urban references—remains overlooked, despite its direct impact on environment assessment accuracy. We reveal widespread overestimation and substantial deviations in buffer distances and areas induced by existing strategies, and assess their impacts on vegetation dynamics. Distance-based buffers generate excessively large and unstable reference areas—up to 50 times the urban area for a 25 km buffer. Radius-based buffers, while improved, introduce significant biases due to the unrealistic assumption of urban circularity. These deviations are primarily driven by urban shape complexity rather than urban size. We propose and generate area-based buffers using Global Urban Boundaries data to obtain accurate and stable non-urban references. Existing buffers are often so large that undermining environment assessment accuracy and is confirmed through the average values of vegetation index and its dynamics with buffers expand. The area-based buffers eliminate systematic biases driven by urban shapes, ensuring accuracy and comparability in urbanization-environmental assessments.

Investigating the spatiotemporal coupling and coordinated evolution of economic and ecological resilience in Africa provides theoretical support and scientific foundation for the continent’s green and high-quality development. From the perspective of evolutionary resilience, this study constructs an evaluation model for Africa’s economic resilience and ecological resilience. Using kernel density models, namely the “economic-ecological” resilience zoning method, the coupling coordination degree model, and the Haken model, this study explores the spatiotemporal alignment, coupling, and synergistic evolution of economic and ecological resilience in Africa in a step-by-step manner. The results show that (1) the overall level of economic resilience in Africa is relatively low, with increasing regional disparities. Spatially, economic resilience exhibits a distribution pattern of “low values widely spread, high values concentrated”; the level of ecological resilience, in contrast, shows a more pronounced dispersion, with a spatial distribution of “low values concentrated, high values dispersed”; (2) based on the “economic-ecological” resilience zoning method, most African countries and regions fall into the low economic resilience category, with weak economic resilience and prominent issues related to economic instability. The seven major high economic resilience zones largely overlap with the high economic resilience-high ecological resilience areas, demonstrating good spatiotemporal alignment between economic and ecological resilience; (3) in terms of the spatiotemporal coupling relationship between economic resilience and ecological resilience, most of Africa falls into the disordered category, with an increasingly obvious polarization trend in the coupling coordination degree; (4) from the perspective of the synergistic relationship between economic resilience and ecological resilience, ecological resilience dominates the symbiotic system formed by economic resilience and ecological resilience. The development of ecological resilience and economic resilience is mutually inhibitive, with prominent contradictions between the economy and the environment. Ecological and economic resilience have formed an internal mechanism of positive feedback in the synergistic system. The regional differences in the synergistic value have expanded, while the differences within regions have narrowed, indicating an emerging trend of spatial differentiation.

Drought is a major challenge for the Tibetan Plateau (TP), severely affecting ecosystem services (ESs). Quantifying the impacts of drought on vital ESs, such as soil retention and water conservation, is essential for understanding and addressing extreme weather events. This study evaluated the ESs by the Revised Universal Soil Loss Equation and water balance method, and assessed the drought using the probability distribution method. The impacts of drought on ESs at multi-time scales within the TP ecosystem are investigated by examining the relationship between the Standardized Precipitation Evapotranspiration Index (SPEI) and the Z-scored soil retention (SRz) and water conservation (WCz) services. The results indicated that the transition from wet to dry conditions reduced the ESs, with SRz and WCz decreasing by an average of 1.45 and 1.37 standard deviations, respectively. Hydrological drought (represented by SPEI6) had stronger impacts on soil retention services, while meteorological drought (represented by SPEI1) more significantly affected water conservation services. Trend analysis revealed strong correlations between ESs and drought conditions across the TP. ESs in the eastern and western humid regions remained relatively stable, whereas those in the central and southern regions underwent continuous degradation. Overall, drought not only diminished ESs but also destabilized the TP ecosystem. Therefore, it is vital to strengthen the restoration and protection of the ecosystem in this region to mitigate the adverse effects of drought.

Drought has been putting enormous pressure on agriculture and food security, especially for African countries with inadequate monitoring. However, there is still a lack of standardization in the synthesized drought index, which could better monitor drought than normalized indices, as well as insufficient attention to the geographical backgrounds of weights. We aim to develop a standardized optimal synthesized drought index (SOSDI) that will improve drought monitoring and reflect dominant factors. The standardization transforms the input variable distribution functions, with the constraint optimization to compute the weight. Weight matrices are suggested to examine the geospatial heterogeneity of the input variable. The assessment of SOSDI from several dimensions was implemented. SOSDI was applied to monitor the periodic drought in East Africa, where rain-fed agriculture was susceptible to seasonal alternation. The results confirmed that standardization was more effective than normalization in the synthesized drought index, and the average correlation between SOSDI with the existing indices, soil moisture, and crop yield reached about 0.6, 0.7, and 0.7, respectively. The cyclical drought is well captured on the seasonal and annual scales, mostly during the long-dry season. SOSDI could capture drought evolution and had good resistance to disturbances. Overall, SOSDI demonstrated a strong capability in drought monitoring and enhanced the drought expression derived from vegetation and temperature more effectively, rather than just precipitation.

Rain-fed agriculture in East Africa faces growing threats from climate change and food insecurity. Exploring the sensitivity of major crop yields (maize, potato, sorghum, cassava) in Kenya, Tanzania, and Uganda to CO2 fertilization and its driving factors under global warming is crucial for ensuring food security. Using a CO2 time series dataset constructed from remote sensing and ground-based measurements, along with solar radiation, temperature, and NDVI data, the C-FIX model is applied to estimate gross primary productivity (GPP) from 2000 to 2021. Geographic detector is applied to analyze the driving mechanisms during the sowing, growing, and harvesting periods. The results show: (1) From 2000 to 2021, CO2 fertilization negatively impacted yields, primarily in northern Kenya and Tanzania-Uganda border regions, with the strongest effects during the growing period, particularly on potato yields (27.4 gC & sdot;m- 2 & sdot;month- 1). (2) Potato yield is negatively affected by CO2 fertilization across all periods. Sorghum and cassava yields are negatively affected by CO2 fertilization only during harvesting period, while maize yield benefits only during the growing period. (3) Soil moisture is the primary driver of yield changes (except for cassava), with its interaction with vapor pressure deficit exerting the most significant impact across all crops. These findings highlight the critical need for effective soil moisture management and atmospheric humidity control to ensure East Africa's food security under global warming.

With the rapid growth of the world's urban population, urban land expansion has become an inevitable trend, with Africa being one of the primary locations for both global urban population growth and urban land expansion. Small and medium-sized cities are gradually recognized as playing an important role in the urbanization process in Africa. However, there is relatively little attention has been paid to small and medium-sized cities. This study focused on urban clusters in Kenya, Tanzania, Uganda, Rwanda, and Burundi, five countries in East Africa. Urban land and urban centers of 59 cities were identified using multi-source data. Then, the growth law of cities of different sizes (large, medium, and small) was analyzed through the urban land density function and urban attractiveness index. Results indicate that large cities are more developed, with obvious core areas and high attractiveness, which may lead to further excessive urbanization and pose challenges to urban sustainable development. Small cities are still in the early stages of urban development and are experiencing rapid and disorderly expansion. By reviewing the history of urban development and policy implementation, we believe that promoting the development of small and medium-sized cities is a significant measure to slow down the excessive urbanization of large cities. Increasing employment opportunities and infrastructure is an effective way to enhance the attractiveness of small and medium-sized cities and promote their development. At the same time, it is necessary to carry out urban plans for small and medium-sized cities to avoid phenomena such as informal settlements that affect the sustainable development of large cities.

Forests play a vital role in the global carbon cycle; however, the carbon sink capacity of African forests is increasingly threatened by wildfires, rising temperatures, and ecological degradation. This study analyzes the spatiotemporal dynamics of forest carbon fluxes across Africa from 2001 to 2023, based on multi-source remote sensing and climate datasets. The results show that wildfires have significantly disrupted Africa’s carbon balance over the past two decades. From 2001 to 2023, fire activity was most intense in the woodland–savanna transition zones of Central and Southern Africa. In countries such as the Democratic Republic of the Congo, Angola, Mozambique, and Zambia, each recorded burned areas exceeding 500,000 km2, along with high recurrence rates (e.g., up to 0.7584 fires per year in South Sudan). These fire-affected regions often exhibited high ecological sensitivity and carbon density, which led to pronounced disturbances in carbon fluxes. Nevertheless, the Democratic Republic of the Congo maintained an average annual net carbon sink of 74.2 MtC, indicating a high potential for ecological recovery. In contrast, Liberia and Eswatini exhibited net carbon emissions in fire-affected areas, suggesting weaker ecosystem resilience. These findings underscore the urgent need to incorporate wildfire disturbances into forest carbon management and climate mitigation strategies. In addition, climate variables such as temperature and soil moisture also influence carbon fluxes, although their effects display substantial spatial heterogeneity. On average, a 1 °C increase in temperature leads to an additional 0.347 (±1.243) Mt CO2 in emissions, while a 1% increase in soil moisture enhances CO2 removal by 1.417 (±8.789) Mt. However, compared to wildfires, the impacts of these climate drivers are slower and more spatially variable.

The average global temperature has risen and is expected to continue increasing due to the emission of greenhouse gases. South Asia (SA) has seen a notable rise in both hot days and nights over the past few decades, leading to numerous fatalities. This research investigates historical and future extreme high temperature (EHT) occurrences in SA, identifying their causal connections among geophysical drivers (GD) using causal discovery (CD). An Ensemble Machine Learning (EML) model was created to merge bias-corrected CMIP6 GCMs, enhancing the precision of future EHT event projections. The findings show that the EML algorithm performed exceptionally well (CC = 0.98) compared to conventional ensemble models, accurately capturing EHT events in SA. The intensity of hot days and nights (TXx and TNx) increased during the first (1991–2000) and second (2001–2010) decades examined, with warmer climate conditions (0.01–0.6 °C). Future projections suggest that the intensity of hot days and nights will rise by up to 10 °C by the end of the twenty-first century, with the frequency of hot days and nights (TX90p and TN90p) increasing by approximately 50

This study investigates disparities in dietary water footprints (DWF) across Africa from a consumption-based perspective, focusing on urban-rural, inter-country, and food category dimensions. Using DWF data from 2010 to 2022 for urban and rural populations across 48 African countries and applying integrated assessment models, we analyze dietary consumption and DWF across 11 food types. The findings reveal significant structural differences in consumption patterns between urban and rural populations, across countries, and among dietary categories, as well as the current status and projected trends of DWF. Between 2010 and 2022, food consumption among urban residents in Africa increased by 10.3 %, while rural residents saw a decline of 5.4 %. Compared to urban residents, rural populations had higher grain intake but lower consumption of meat, fruits, and vegetables. The DWF for animal-based foods was notably higher than for plant-based foods, with beef showing the highest DWF at approximately 109.86 m3 in 2022, compared to fruits at 4.82 m3. Additionally, the analysis indicates notable inequalities in DWF among African countries, with widening disparities between the highest and lowest DWF-consuming countries, driven mainly by differences in poultry, beef, and grain consumption. Economic development also plays a key role, with higher-income countries experiencing greater increases in per capita DWF due to dietary shifts toward more water-intensive animal-based foods. The differences in DWF between urban and rural residents, as well as among countries, are projected to continue expanding. By 2030 and 2050, Africa's average DWF of African residents is expected to rise by 75.96 % and 534.51 %, respectively, relative to 2022. The DWF gap between the top and bottom five countries, recorded at 5026.13 m3 in 2022, is anticipated to increase to 7027.19 m3 by 2030 and 29,097.42 m3 by 2050. Scenario analysis shows that SSP3-RCP2.6, characterized by rapid population growth and resource-intensive diets, leads to the highest increase in DWF, while SSP1-RCP2.6, which assumes sustainable development and dietary shifts, results in the slowest growth. These findings support the potential for improving dietary structures in underserved areas by increasing access to nutrient-rich, plant-based foods, which may alleviate future water resource pressures.

The satellite precipitation products provide a reliable alternative data source for real-time drought monitoring in developing countries. Therefore, it is important to quantify the excellent satellite precipitation products for drought estimation. This study evaluated two long-term satellite precipitation products and their capability for monitoring meteorological drought events over East Africa. The Climate Hazard Group Infra-Red Precipitation with Station (CHIRPS) and the Precipitation Estimation from Remotely Sensed Information using Artificial Neural Network-Climate Data Record (PERSIANN-CDR) products have been selected from 1985 to 2019 and compared these datasets from observation data retrieved from Climate Research Unit over the studied region. The four statistical metrics were used to evaluate the performance of these satellite precipitation products. The Standardized Precipitation Index was estimated from these two satellite precipitation datasets and compared with observation data to identify the drought detection capacity of these products over East Africa. The findings of these studies revealed that the CHIRPS datasets showed excellent performance (CC = 0.95) with observation and significantly captured the drought events over the studied region. The PERSIANN-CDR products show overestimation/ underestimation of drought events (RMSE = 0.65) in both spatial and temporal scales over East Africa during the studied period. In addition, this study estimates the Hurst Exponent (H) to predict the magnitude of drought events capacity of these two satellite precipitation data. The H-exponent results show that the CHIRPS data performed well in predicting drought events in the future, and these drought events could decrease in most of the East Africa region in the future.

Urbanization in African countries entails substantial growth in the urban population and economic development. The interdependent progress of the population and economy significantly impacts the sustainable development of these nations. By constructing an evaluation framework, this paper assesses the urban population growth and economic development systems in African countries. Building upon the coupling coordination model, it quantitatively investigates the relationship between the two and utilizes a geographical detector model to analyze the driving factors of the coordination of evolution. The findings reveal a continuous improvement in the quality of urban population growth and economic development between 2001 and 2020. Nevertheless, their overall quality remains relatively low, exhibiting considerable variation across different countries. Many African countries struggle with a low level of development coordination, with economic progress often trailing behind the pace of urban population growth. The average coupling coordination degree increased from 0.464 to 0.526 over 20 years, with 48.08% of countries still in uncoordinated development by 2020. Factors such as industrialization, foreign trade dependence, government spending, international aid, and political stability are all influential factors affecting the degree of coordination. The absence of industrialization in conjunction with urbanization poses a major impediment to effectively harnessing urban population growth for economic development. Ultimately, this study provides a targeted framework for integrating urban population growth and economic development to address low coupling coordination.

As an important part of the terrestrial ecosystem, vegetation dynamics are subject to impacts from both climate change and human activities. Clarifying the driving mechanisms of vegetation variation is of great significance for regional ecological protection and achieving sustainable development goals. Here, net primary productivity (NPP) was used to investigate the spatiotemporal variability of vegetation dynamics from 2000 to 2020 in East Africa, and its correlations with climate factors. Furthermore, we utilized partial derivatives analysis and set up different scenarios to distinguish the relative contributions of climatic and human factors to NPP changes. The results revealed that NPP exhibited a significant increase with 4.16 g C/m2/a from 2000 to 2020 in East Africa, and an upward trend was detected across 71.06% of the study area. The average contributions of precipitation, temperature, and solar radiation to the NPP inter-annual variations in East Africa were 2.02, −1.09, and 0.31 gC⋅m–2⋅a–1, respectively. Precipitation made the greatest positive contribution among all of the climatic factors, while temperature made strong negative contributions. The contributions of climate change and human activities to NPP changes were 1.24 and 2.34 gC⋅m–2⋅a–1, respectively. Moreover, the contribution rate of human activities to NPP increase was larger than that of climate change, while the role of climate change in NPP decrease was larger than that of human activities. The findings of the study can provide new evidence for a deeper understanding of ecosystem stability and carbon cycling in East Africa, as well as a reference for decision-making and scientific support for ecological environmental protection.

Northern Africa has become the first region in the world to exhaust its water resources, with a 40 % decrease in per capita water availability south of the Sahara over the past decade. While adjusting production structures and consumption can regulate the supply-demand dynamics of water resources, the extent of the impact of virtual water-induced pressure on both the regional and national levels in Africa remains largely understudied. Applying the standard Penman formula, this research calculates the water footprint of eight cereal crops in 54 African countries from 1990 to 2021. By integrating corresponding data on cereal trade, the study analyzes changes in virtual water stress. The findings indicate a decline in the per-unit production and consumption water footprints for African cereals. However, the continuous expansion of cultivation areas contributes to a rising water stress. In comparison to 1990, the water stress for soybeans, sorghum, rice, maize, and cassava increased by 149.72 %, 146.88 %, 133.89 %, 123.30 %, and 90.8 %, respectively, in 2021. Only barley showed a reduction in water stress by 23.22 %. The study underscores the growing interconnectedness of virtual water trade (VWT) among African nations from 1990 to 2021, leading to a more balanced trade distribution. VWT has reduced water stress by 7.65 %, 2.08 %, and 1.8 % in Western, Central, and Northern Africa, respectively, while increasing pressure in Southern and Eastern Africa by 10.51 % and 1.01 %. The flow of virtual water in Africa is most influenced by spatial proximity, primarily occurring between adjacent countries or regions. Forecasts for water stress under the five scenarios of SSPs-RCP8.5 have been conducted, revealing a continuous increase in water stress across Africa. Furthermore, analysis of the SSP2-RCP8.5 scenario indicates that by 2030 and 2040, African cereal crops are projected to face virtual water resource stress increases of 7 % and 18.76 %, respectively, compared to 2020 levels. During the same period, Sierra Leone is anticipated to experience a growth rate in virtual water stress of approximately 1903.38 %. Consequently, altering crop cultivation structures and enhancing VWT are poised to alleviate water resource pressure, promoting the scientific management of agricultural water resources in Africa.