Search Results (305)

Quantifying vegetation ecological quality and ecological water requirement is essential for understanding ecosystem sustainability in arid regions. However, large-scale assessments of vegetation ecological quality and ecological water requirement thresholds remain limited in Central Asia. In this study, we developed a Vegetation Ecological Quality Index (VEQI) for Central Asia based on fractional vegetation cover (FVC) and net primary productivity (NPP) and estimated vegetation ecological water requirement quota (VEWRq) and total vegetation ecological water requirement (VEWR) using the Penman–Monteith method, the soil moisture limitation coefficient (SMLC), and GIS-based spatial analysis. We further examined the spatiotemporal variations in VEQI and VEWR during 2001–2020 and identified VEWRq thresholds corresponding to different VEQI levels. The results showed that (1) the multi-year mean VEQI in Central Asia was 28.46 and exhibited a slight increasing trend during 2001–2020; (2) the annual mean minimum, maximum, and optimal VEWRq were 147.53, 179.71, and 162.52 mm, respectively, corresponding to mean annual VEWR values of 146.98 × 10⁹ m³, 179.04 × 10⁹ m³ and 161.91 × 10⁹ m³, respectively; and (3) VEQI was positively correlated with VEWRq in 89.48% of the vegetation area. The VEWRq threshold increased with vegetation ecological quality. The five VEQI levels in Central Asia, namely very poor, poor, moderate, good, and very good, corresponded to VEWRq thresholds of 28.62–35.96, 88.33–107.81, 190.69–233.32, 362.86–432.81, and 678.59–838.31 mm, respectively. This study provides a remote sensing-based framework for evaluating vegetation ecological quality and quantifying ecological water requirement thresholds in arid regions and offers scientific support for regional ecological management and water resource allocation. Full article

Cropland and rural settlements are core components of rural human–environment systems, and their coordinated development is crucial for regional sustainability, particularly in China’s major agricultural production regions. Taking the Huang-Huai-Hai region as the study area, this study systematically investigates the spatiotemporal evolution of cropland and its coupling relationship with rural settlements using land use data from 1990 to 2020. Grid-based analysis and multiple spatial modeling methods were employed. The results show that: (1) From 1990 to 2020, the cropland in the region decreased by a net total of 21,021.94 km², with annual dynamic degrees ranging from −0.13% to −0.28%. Cropland conversion to other land uses far exceeded conversion from others, with construction land being the primary destination. Among these, rural settlements and urban construction land accounted for 43.75% and 55.58% of the total cropland loss, respectively. (2) The spatial distribution of cropland exhibited a distinct pattern of “hot in the center and south, cold in the periphery and north” (Moran’s I = 0.232, p < 0.001), indicating significant positive spatial autocorrelation. Hot spot areas clustered in the North China Plain and the Huang-Huai Plain, while cold spot areas were distributed in the Yanshan–Taihang mountains and the hilly regions of the Shandong Peninsula, clearly controlled by topography. (3) Cropland change exhibited stage-specific characteristics. The pattern was relatively stable during 1990–2000. During 2000–2010, cropland conversion to other uses intensified, with high-value conversion areas concentrated around urban agglomerations. In the 2010–2020 period, these high-value conversion areas diffused from the core plain areas to urban fringe zones. (4) The spatial coupling between cropland and rural settlements was predominantly characterized by the Moderately Coordinated Type (MCT), accounting for 48.38–58.44% of the area. However, the proportion of Rural Settlement-Dominant Type (RC) increased from 15.51% to 21.58%, indicating a trend toward intensifying human–environment conflicts. Overall, the Huang-Huai-Hai region experienced significant cropland changes. While its spatial pattern remains relatively stable, the coupling relationship between cropland and rural settlements is deteriorating, posing challenges to regional food security and rural sustainable development. Full article

Phytoplankton primary production (PP) underpins marine ecosystems. In winter marginal seas, the magnitude and size structure of PP not only sustain overwintering zooplankton but also shape larval fish survival and fishery resources in the following year. We conducted two cruises in the fish overwintering grounds of the East China Sea shelf to investigate the spatial distribution, size structure, and environmental controls of net primary production (NPP). Winter NPP was generally low relative to the annual range. Nutrient concentrations at most stations exceeded potential limitation thresholds, whereas the mixed-layer mean light exposure (LE) fell below the light-saturation threshold at most stations, indicating that insufficient light availability was primarily associated with sub-saturating light conditions of low winter productivity. Among size classes, the nano-sized fraction dominated NPP, followed by the pico-sized fraction, while the micro-sized fraction contributed least; however, the relative contribution of the micro-sized fraction increased in February. Measured values of two key parameters widely used in satellite-based NPP models—PBopt (optimal chlorophyll-specific carbon fixation rate) and F (a dimensionless light-related factor for the vertical distribution of primary production)—were both lower than model predictions, and the magnitude of deviation varied with water depth and mixing conditions. These findings refine our understanding of biogeochemical processes in overwintering grounds of winter marginal seas. Full article

Net primary productivity (NPP) is an important indicator for assessing ecosystem productivity and carbon cycling. The Yellow River Basin (YRB), as an important ecological conservation zone and economic region in China, is highly sensitive to climate change, land use change, and ecological restoration. Understanding the spatiotemporal variation in NPP and its relationships with environmental factors is therefore important for regional ecological management. In this study, MODIS NPP data, ERA5-Land environmental variables, land use data, machine learning algorithms, and SHAP-based model interpretation were used to analyze the spatiotemporal patterns of NPP and the nonlinear responses of NPP to environmental factors in the YRB from 2001 to 2020. The results showed the following: (1) NPP exhibited a spatial pattern of higher values in the south and lower values in the north. The annual average NPP showed a fluctuating upward trend, and most pixels showed varying degrees of increase during the study period. (2) Moisture-related variables contributed more strongly to model-predicted NPP variations in the entire basin than thermal variables. (3) For different ecosystem types, surface solar radiation downwards (SSRD) made the largest contribution to model-predicted NPP variations in cropland and forest ecosystems and showed a negative relationship with NPP, whereas evapotranspiration (E) contributed most strongly to model-predicted NPP in grassland ecosystems and showed a positive relationship with NPP. (4) Most environmental factors showed nonlinear associations with model-predicted NPP, and SHAP-derived response thresholds differed among ecosystem types. These thresholds should be interpreted as model-based nonlinear response points rather than confirmed ecological tipping points or ecological regime shifts. This study provides a reference for understanding the heterogeneous responses of vegetation productivity to environmental factors in the YRB. Full article

Organic matter production, recycling, and burial processes temporally fluctuate across the Clarion-Clipperton Zone (CCZ) in the Eastern Tropical Pacific. Between 2019 and 2022, we conducted pelagic and benthic surveys in Nauru Ocean Research Inc. contract area D (NORI-D) in the southeast CCZ to establish environmental baseline conditions. Here, we synthetise the natural ranges of variability in physicochemical and biogeochemical processes in NORI-D across multiple surveys and years. We present interannual water column physicochemical characteristics from five metocean and pelagic campaigns, annual satellite-derived net primary productivity and export production, time-integrated sediment trap annual particulate organic carbon flux, and seafloor biogeochemical and sediment physical characteristics from three benthic campaigns. Temperature and salinity seasonally varied at the sea surface. Strong thermohaline and oxygen stratification developed over 0–100 m. Mean net primary productivity, export production, and seafloor particulate organic carbon flux amounted to 634.1, 15.7, and 2.1 mg C m⁻² d⁻¹, respectively. These rates fluctuated nearly four-fold seasonally and interannually. An oxygen minimum zone (100–700 m) dampened organic carbon flux attenuation (b = −0.538) to the abyss. Abyssal seafloor organic matter dynamics showed more homogenous conditions in 2020–2021 (TOC = 0.57 ± 0.05%) than in 2022 (TOC = 0.42 ± 0.19%). Bioturbation rate and mixed-layer depth decreased from 2020 to 2022, while oxygen consumption increased at 0–1 cm bsf. Lipid consumption and compositional alteration in 2022 surpassed 2020–2021. Our findings provide critical baseline data to inform environmental impact assessments and monitoring programmes for deep-sea mining of polymetallic nodules in NORI-D. Full article

Wildfires are an increasingly recurrent disturbance in Mediterranean forest landscapes, yet fire severity assessment remains limited in data-scarce regions such as Lebanon. This study aims to assess wildfire severity patterns and identify the main environmental drivers influencing fire severity across the forests of Akkar, northern Lebanon, within a Digital Landscapes framework. Fire severity was mapped using the Differenced Normalized Burn Ratio (dNBR) derived from multi-temporal Landsat-8 imagery (2013–2024) processed in Google Earth Engine. Vegetation productivity was assessed through annual Net Primary Productivity (NPP), while topographic variables (elevation, slope, and aspect) were derived from a Digital Elevation Model. The results reveal heterogeneous fire severity patterns over the study period and pronounced spatial variability in NPP, with no consistent linear relationship between productivity and fire severity. Principal Component Analysis (PCA) was applied to explore multivariate relationships between fire severity, productivity, and terrain. PCA results show that the first two components explain 77.4% of the total variance, indicating that fire severity is primarily structured by topographic factors, particularly elevation and solar exposure, while vegetation productivity plays a secondary role. These findings highlight the dominant influence of terrain on wildfire severity in Mediterranean mountainous landscapes, and demonstrate the value of integrating remote sensing, cloud-based platforms, and multivariate analysis for fire assessment in data-scarce regions. The study contributes to the advancement of Digital Landscapes approaches by providing a scalable and data-driven framework for understanding fire dynamics and supporting future landscape management and risk assessment strategies. Full article

Soil total nitrogen (TN) and soil total phosphorus (TP) are key soil quality indicators and provide critical ecological functions in the grasslands. This study analyzed the driving factors of TN/TP in the grasslands of Qinghai Province based on Shapley additive interpretation (SHAP) analysis. Four machine learning methods, namely random forest (RF), XGBoost 3.2.0, support vector machine, and Cubist, were used to establish spatial prediction models for TN/TP. Vegetation factors (Net Primary Production and Normalized Difference Vegetation Index) and precipitation-related factors (Aridity Index and Mean Annual Precipitation) were the most important variables for TN, indicating plant productivity and precipitation are strongly associated with TN accumulation. Elevation and temperature-related factors (Mean Annual Temperature and evapotranspiration) were the most important variables for TP, demonstrating that elevation-mediated temperature was the major factor affecting the TP accumulation. XGBoost and RF were the optimal models for TN and TP, respectively. TN exhibited a decreasing spatial trend from east to west, while the northwestern and southwestern areas showed relatively higher and lower TP, respectively. Total TN and TP stocks were estimated to be 3.57 × 10⁸ t and 0.88 × 10⁸ t, respectively. This study provides data support and suggestions for sustainable soil nutrient management in the grasslands on the Qinghai-Tibet Plateau. Full article

The surface disturbance caused by coal mining and the ecological restoration have changed the vegetation coverage and ecosystem functions of the Shengli mining area. This disturbance has affected the carbon and water cycles, resulting in complex response characteristics of water use effectiveness (WUE). To reveal these response characteristics, this paper uses multi-source remote sensing data from 2001 to 2024 and applies random forests to scale down MODIS 500 m net primary productivity (NPP) and MODIS 1 km evapotranspiration (ET) to 30 m resolution. Then, it calculates the WUE of the Shengli mining area to reveal the temporal and spatial variation patterns and characteristics of WUE in the mining area and the spoil dump. It also uses the Pearson correlation coefficient to analyze the driving factors of WUE. The results show that the determination coefficients R² of the NPP and ET scaling models are 0.961 and 0.7142 respectively. The WUE in the study area and four spoil dumps from 2001 to 2024 all follow the pattern of “decrease due to disturbance—recovery and rise—gradual stabilization”, with the peak WUE in the mining area reaching 1.123 g·C·m⁻²mm⁻¹ in 2002, a fluctuation decline from 2002 to 2011 with a valley value of 0.398 g·C·m⁻²mm⁻¹ in 2010, an annual increase trend from 2011 to 2013, and a basic stabilization from 2013 to 2024, with an average value of 1.001 g·C·m⁻²mm⁻¹ during this period. Compared to the average value of 1.061 g·C·m⁻²mm⁻¹ from 2001 to 2022, WUE has not yet returned to the initial level. The Pearson correlation coefficients ranked from high to low are: NDVI (0.59, +) > | deformation (−0.39, −) | > temperature (0.27, +) > rainfall (0.26, +) > mining area (0.072, +), indicating that NDVI and deformation are important factors affecting WUE. Further analysis of the relationship between NDVI disturbance and WUE reveals that the mean NDVI disturbance and recovery in the study area from 2001 to 2024 are 0.438 and 0.392 respectively. WUE shows a “first decline—then rise—then stabilization” phased evolution pattern during the “disturbance—recovery—stability” process of vegetation, and the disturbance intensity and recovery intensity are positively correlated with the rate of WUE decrease and increase. The combination analysis of deformation and WUE indicates that the deformation areas in the mining area and the inner spoil dump show a trend of WUE reduction due to the increase in deformation volume. The study shows that the continuous mining of open-pit coal mines continues to affect the water usage function of vegetation in the mining area. Subsequent restoration should prioritize strengthening surface stability, soil water retention, and vegetation reconstruction in the mining area, inner spoil dump, and areas with large deformation to improve the stability and water usage efficiency of ecological restoration. Full article

This study evaluates the techno-economic feasibility of producing a functional baked snack formulated with sweet potato flour, cereals, and upcycled brewer’s spent grain (BSG). The analysis, developed in SuperPro Designer^®, integrates experimentally derived parameters from literature, justifying the transition from laboratory-scale data to an industrial production model. The analysis identified refrigerated storage (48 h) and tray drying as the primary bottlenecks limiting throughput. By synchronizing equipment cycles and increasing the number of units, the production capacity was adjusted from 154.32 to 1077.21 metric tons per year, capturing approximately 0.8% of the estimated annual demand for sweet potato snacks in Mexico. Economic evaluation for this scale demonstrated a capital investment of USD 24.6 million and annual operating costs of USD 8.49 million. The inclusion of a sedimentation-based water treatment, while increasing costs, enables a significant reduction in freshwater intake. The project yielded a payback period of 3.62 years and a Net Present Value (NPV) of USD 23.908 million. Sensitivity analysis revealed that profitability is strongly influenced by production volume and sweet potato costs. These findings provide a realistic framework for assessing the commercial viability of functional food formulations when scaled for industrial production. Full article

Net primary productivity (NPP) is a critical indicator of carbon sequestration and biomass accumulation in terrestrial ecosystems, directly reflecting ecosystem carbon sink capacity. Existing NPP studies have primarily emphasized climate-driven interannual variability. Spatially explicit analyses that jointly quantify multi-factor driving mechanisms, thresholds, and land-use transition risks remain limited. Here, we develop an integrated multi-method analytical workflow (DRIBS) that integrates Distributional Response, Informative Boundary constraints, and Spatial Interpretability Optimization, and apply it to the Jiziwan region in the Yellow River Basin, one of China’s major ecological restoration hotspot regions. From 2000 to 2020, the annual increasing rate of NPP was 5.80 gC·m⁻²·yr⁻¹, and 78% of the area showed a significant increasing trend. Among them, grasslands and croplands in the eastern and western parts exhibited strong fluctuations and low long-term stability. Evapotranspiration (ET) and fractional vegetation cover (FVC) were the dominant drivers of NPP spatial heterogeneity, and precipitation around ~220 mm marked a critical water-stress threshold. Population density and nighttime lights showed a non-linear “ecological adaptation window”, implying both disturbance and management potential. Land-use transitions exhibited divergent risk signatures: grassland/cropland-to-forest transitions produced stable enhancement (priority restoration zones), whereas cropland/unused-to-urban transitions were associated with degradation risk (urgent management). Overall, DRIBS provides an interpretable “change-mechanism-threshold-risk” assessment to support carbon-sink regulation and restoration prioritization in arid and semi-arid regions. Full article

Net primary productivity (NPP) and its response to global climate change are one of the hot topics in global change research. Based on Net primary productivity remote sensing data and meteorological data, this study analyzed the spatiotemporal variation in vegetation NPP in Maowusu sandy land by using Sen trend analysis, Mann–Kendall significance test, coefficient of variation stability analysis, partial correlation and complex correlation analysis, and quantitatively analyzed the response of vegetation NPP to climate factors. The results showed that from 2001 to 2023, the overall vegetation NPP showed a significant upward trend, and the annual average increased from 124.28 g·(m⁻²·a)⁻¹ to 221.41 g·(m⁻²·a)⁻¹. The Theil–Sen median slope of NPP was +3.87 g·(m⁻²·a)⁻¹ with a coefficient of variation (CV) of 0.19, suggesting a robust but spatially variable greening trend. In total, 98.53% of the area showed an upward trend, with a very significant and significant increase area. The overall stability of vegetation NPP was strong, with an average coefficient of variation (CV) of 0.19 and a CV< of 0.30 in 97.96% of the regions, but the local area from southwest to east was highly volatile and there was a risk of secondary desertification. The influence of climate factors on vegetation NPP had significant spatial heterogeneity: precipitation was the key driving factor, and most areas were positively correlated. Potential evapotranspiration was positively correlated in the central and northern regions, and negatively correlated in some southern areas. The overall temperature has a negative effect, and only the local area has a weak promoting effect. Multi-correlation analysis shows that vegetation NPP is the result of the synergy of multiple climatic factors, and the hydrothermal coupling mechanism plays a decisive role in its spatial pattern. This study can provide a scientific basis for the restoration of vegetation ecosystems, environmental protection policy formulation, ecological protection and high-quality development of the Yellow River Basin in Maowusu Sandy Land. Full article

Vanadium (V) is a strategically important metal commonly recovered from titaniferous magnetite ores. Its principal application is in steel production, where it enhances mechanical properties, while smaller quantities are utilized in chemical processing, catalysis, and emerging energy storage technologies. It is expected that the demand for vanadium in the steel industry will increase by a compound annual growth rate of approximately 2.7% by 2029, and demand in energy storage will increase by an additional 6%. The growing demand for V has triggered global concerns regarding the supply risks of this critical metal. Industrial recovery of vanadium from magnetite deposits is carried out either through dedicated primary vanadium extraction routes or integrated processes that co-produce vanadium alongside steel. The latter accounted for approximately 73% of global vanadium output in 2021. These co-production operations generate significant volumes of by-product slag, often referred to as titaniferous slag, which can still contain notable concentrations of vanadium. In this study, a modified primary vanadium extraction route is proposed to recover V from such slag, using material containing approximately 0.9% V₂O₅ sourced from the former Evraz Highveld Steel and Vanadium Corporation in South Africa as a representative case. The work focuses on assessing the economic feasibility of the proposed process through a Discounted Cash Flow (DCF) analysis. Key financial metrics including net present value (NPV), internal rate of return (IRR), and payback period were calculated to evaluate viability and to identify process stages requiring further optimization. Full article

Against the background of global climate change and intensified human activities, the Black Soil Region of Northeast China (BSRNC)—an ecologically fragile zone and critical grain-producing area—faces mounting pressures on ecosystem stability, productivity sustainability, and black soil conservation. Clarifying the spatiotemporal evolution characteristics of vegetation net primary productivity (NPP) and its associative patterns is crucial for ecological protection and sustainable land management in this region. Based on remote sensing, meteorological, topographic, soil and human activity data, this study employed the improved Carnegie–Ames–Stanford Approach (CASA) model to quantify vegetation NPP—an analytical approach that integrates the CASA model with tree-based machine learning and SHapley Additive exPlanations (SHAP) interpretation. By further combining multiple spatial analysis methods, it characterizes the spatiotemporal dynamics of NPP in the black soil region and innovatively compares seven machine learning algorithms to select the optimal Light Gradient Boosting Machine (LightGBM) model for quantifying the contributions of drivers in this region with high spatial heterogeneity. The results showed that the average annual vegetation NPP in the BSRNC was 301.18 g C·m⁻², exhibiting a fluctuating upward trend at a rate of 1.55 g C·m⁻²·a⁻¹ over the 24-year period. Spatially, NPP displayed significant heterogeneity, climbing gradually from the region’s southwest to its northeast quadrant, with over 90% of the territory showing an upward trajectory. Overall NPP reached a high stability level, though the western and southern regions faced higher degradation risks, and the entire region presented a weak anti-persistent trend. Precipitation was the dominant factor associated with NPP variations, followed by soil moisture, while soil pH had the smallest correlative contribution (0.38). Land-use changes were positively associated with NPP growth, and the interaction of multiple factors showed a significant associative pattern with NPP variations. This study clarifies the spatiotemporal patterns and associative patterns of vegetation NPP in the BSRNC with a 24-year-long time series, and its incremental findings on the coupling of land-use change and multi-factor interaction provide a targeted scientific basis for ecological protection, restoration policies and sustainable management of black soil resources. Full article

As the net gain of carbon by plants after accounting for respiration, vegetation net primary productivity (NPP) plays a central role in the terrestrial carbon cycle. However, a systematic and quantitative analysis of the spatiotemporal evolution and driving mechanisms of vegetation NPP on Hainan Island, a tropical region, is still lacking. Focusing on Hainan Island, this study employs an integrated approach—including the coefficient of variation, Mann–Kendall test, Hurst exponent, geographical detector, and PLS-SEM—to investigate the spatiotemporal dynamics of vegetation NPP and its underlying drivers from 2001 to 2022. The main conclusions as follows: (1) Vegetation NPP on Hainan Island showed a fluctuating upward trend from 2001 to 2022, with a mean annual increase of 3.6 g C·m⁻²·yr⁻¹, and displayed a spatial pattern of decrease from the central-southern mountainous areas toward the coastal regions. (2) NPP changes were generally stable; historically, areas showing an increasing trend exceeded those with a decreasing trend by 30.55%. In the future, the predominant projected trends are “persistent decrease” and “increase to decrease,” which together account for over 80% of the total area. (3) Topography and climate were the dominant drivers of NPP spatial heterogeneity. Elevation had the strongest explanatory power, followed by evapotranspiration and temperature. A significant, nonlinear enhancement effect was observed in the interaction between any two factors. (4) Topographic, climatic, anthropogenic, and vegetation factors all exerted direct positive effects on vegetation NPP. Anthropogenic activities also indirectly promoted NPP by influencing pathways such as vegetation growth. The conclusions of this research provide support for the implementation and evaluation of land-use planning, afforestation projects, and ecological protection and restoration measures on Hainan Island. Full article

Vegetation Net Primary Productivity (NPP) is vital for assessing carbon cycles, particularly in arid regions where dynamics rely on water availability. This study investigates the mechanisms by which ecological water conveyance impacts NPP in the Aiding Lake Basin. Integrating Remote Sensing Hydrological Station technology with the Google Earth Engine platform and the CASA model, we analyzed the spatiotemporal feedback between water conveyance and NPP from 2016 to 2023. Results showed increasing runoff and significant variation in conveyance volumes, with the Baiyang River exhibiting the highest efficiency. Mean annual NPP displayed a significant declining trend, characterized by higher values upstream than downstream and in the west compared to the east. Ecological water conveyance positively enhanced regional vegetation productivity, demonstrating a significant positive correlation with NPP that was stronger at the annual scale. These findings provide a new framework for evaluating the benefits of ecological water conveyance, offering a theoretical basis for ecological conservation in Northwest China. Full article