Search Results (244)

The Canadian Prairies are a region of critical importance to continental hydroclimate and agriculture, exhibiting high sensitivity to variability in atmospheric moisture transport. This study investigates the seasonal and interannual variability of integrated moisture flux over the Canadian Prairie region (96° W–114° W, 49° N–53° N) using the National Centers for Environmental Prediction (NCEP) Reanalysis dataset from 1979 to 2023. We employ a combination of composite analysis and Empirical Orthogonal Function (EOF) analysis to identify the dominant modes of variability and their associated large-scale synoptic drivers. Our results confirm a strong seasonal reversal: winter moisture flux is predominantly zonal (westerly), contributing an average of 90% to total inbound flux, while summer flux is primarily meridional (southerly), contributing a dominant 72.6%. Composite analysis of extreme moisture years reveals that anomalously high-moisture winters are associated with an intensified Aleutian Low and a strengthened pressure gradient off the North American west coast, facilitating enhanced westerly flow. Conversely, a strengthened continental high-pressure system characterizes anomalously low-moisture winters. During summer, high-moisture years are driven by an enhanced southerly component of the flow, likely linked to a strengthened Great Plains Low-Level Jet (GPLLJ). The first EOF mode for winter explains 43% of the variance in eastward flux and is characterized by a pattern consistent with the El Niño Southern Oscillation (ENSO) teleconnection pattern. These findings underscore the control of Pacific-centric circulation patterns on Prairie hydroclimate in winter and have significant implications for predicting seasonal water availability. Full article

The ancient city of Gela (built in the 7th century BCE) is located in the southern sector of the Sicily Island (Southern Italy) on a Pleistocene marine terrace near the mouth of the Gela River. Gela was one of the most important Greek colonies in the Mediterranean Sea, strategically positioned at the crossroads of the major maritime trade routes and with a rich production of cereals thanks to the fertile Gela River alluvial plain. To reconstruct the coastal and environmental configuration during the Greek period and to improve the understanding of the location of the harbour basin, a multidisciplinary approach was applied to a sector of the Gela River alluvial–coastal plain. This area, located very close to the ancient city, is known as Conca (Italian for “Basin”) and was identified through the analysis of historical and modern maps as well as aerial photographs. The multidisciplinary approach includes geomorphology (derived from maps and aerial photos), stratigraphy (boreholes and archeological trench), paleoecology (ostracoda, foraminifera and fossil contents of selected layers), geochronology (¹⁴C dating of selected organic materials) and archeology (historical sources and maps, pottery fragments extracted from boreholes and trench layers). The main results show that this area was occupied by lower shoreface environments in the time intervals between 4.4 and 2.8 ka, which progressively transitioned to upper shoreface environments until the Greek age. During the Roman period, these environments were significantly reduced due to repeated alluvial sedimentation of the Gela River transforming the area into fluvial–marshy environments. A time interval of aeolian sand deposition was recorded in the upper part of the coastal stratigraphical succession, which can be related to climatic conditions with high aridity. Available data show that marine environments persisted in the Conca sector during the Greek age, allowing hypothesizing the presence of an ancient harbour in this area. The depth of the Greek age marine environments is estimated to be between 4.5 and 7 m below the current ground level. Further investigation, mainly based on geophysical and stratigraphical methods, will be planned aimed at identifying the presence of buried archeological targets. Full article

The precise identification of territorial space conflicts (TSCs) and their driving mechanisms is key to enhancing spatial security governance. Taking Jinan City as a case study, this research evaluates territorial space suitability across production, living, and ecological dimensions, proposes an empirical TSC identification model, and employs GeoDetector to analyze spatiotemporal evolution patterns and driving mechanisms. The results indicated that (1) from 2000 to 2020, significant spatial heterogeneity characterized the suitability of production–living–ecological spaces in Jinan City. High suitability zones of production and living space expanded in the northern plain along the Yellow River and central piedmont plain, respectively, while those of ecological space contracted in the southern mountainous and hilly areas. (2) Significant spatiotemporal variations in territorial space conflicts (TSCs) were observed in Jinan City over the past two decades. Intense conflicts dominated production–living and production–ecological space interactions, while moderate conflicts were prevalent in living–ecological and production–living–ecological space interactions. Production–living space conflict zones expanded, living–ecological space conflict zones contracted, and production–ecological and production–living–ecological space conflict zones showed consistent expansion trends. (3) The spatiotemporal evolution of territorial space conflicts is jointly driven by the natural environment, geographical location, social economy, and regional policies. The interaction of driving factors exhibited significant dual-factor and nonlineal enhancement effects. Finally, this study provides some scientific references for the comprehensive management and pattern optimization of territorial space in Jinan City. Full article

Intensified water consumption has driven rapid groundwater depletion globally, threatening economic and environmental sustainability. Understanding large-scale groundwater dynamics has been constrained by the scarcity of long-term, high-resolution records. This study uses multi-decadal, high-density groundwater level monitoring data from the Southern Hebei Plain (SHP) to analyze the evolution of the groundwater flow field and depression cones from 1959 to 2020. We quantitatively characterize trends over six decades and assess the impact of the South-to-North Water Diversion Project (SNWD). The regional flow field shifted from a natural topographic-driven pattern (foothills to coast) in the 1960s to localized systems centered on depression cones by the 1980s. Subsequent management policies and the SNWD have progressively reduced the extent of these cones, facilitating a partial recovery of the regional flow pattern towards its original direction. Shallow aquifer levels declined steeply from the 1980s until 2016, particularly along the Taihang Mountains’ alluvial fan margins, with cumulative drawdown of 20–60 m. After SNWD implementation, levels stabilized and began recovering in piedmont urban areas. Deep aquifer levels generally declined from the 1980s to 2016, with the most significant drawdown (40–90 m) occurring in the central–eastern plain. The recovery of deep aquifers lagged behind shallow ones. These results provide critical insights for supporting sustainable groundwater management and depression cone recovery in the Hebei Plain. Full article

Under concurrent global warming and multi-scale climate anomalies, regional precipitation has become more uneven and less stable, and extreme events occur more frequently, amplifying water scarcity and ecological risk. Focusing on mainland China, we analyze nearly 70 years of monthly station precipitation records together with eight climate drivers—the Pacific Decadal Oscillation (PDO), Atlantic Multidecadal Oscillation (AMO), Multivariate ENSO Index (MEI), Arctic Oscillation (AO), surface air pressure (AP), wind speed (WS), relative humidity (RH), and surface solar radiation (SR)—and precipitation outputs from eight CMIP6 models. Using wavelet analysis and partial redundancy analysis, we systematically evaluate the qualitative relationships between climate drivers and precipitation and quantify the contribution of each driver. The results show that seasonal precipitation decreases stepwise from the southeast toward the northwest, and that stability is markedly lower in the northern arid and semi-arid regions than in the humid south, with widespread declines near the boundary between the second and third topographic steps of China. During the cold season, and in the northern arid and semi-arid zones and along the margins of the Tibetan Plateau, precipitation varies mainly with interdecadal swings of North Atlantic sea surface temperature and with the strength of polar and midlatitude circulation, and it is further amplified by variability in near-surface winds; the combined contribution reaches about 32% across the Northeast Plain, the Junggar Basin, and areas north of the Loess Plateau. During the warm season, and in the eastern and southern monsoon regions, precipitation is modulated primarily by tropical Pacific sea surface temperature and convection anomalies and by related changes in the position and strength of the subtropical high, moisture transport pathways, and relative humidity; the combined contribution is about 22% south of the Yangtze River and in adjacent areas. Our findings reveal the spatiotemporal variability of precipitation in China and its responses to multiple climate drivers and their relative contributions, providing a quantitative basis for water allocation and disaster risk management under climate change. Full article

Hunan Province from 2000 to 2023 is the study area. Based on NOAA precipitation data and county-level rice yield statistics in Hunan Province, the Mann–Kendall test, extreme precipitation indices, and wavelet analysis examine the spatial and temporal evolution characteristics of extreme precipitation and its multi-scale impact on rice yield. The results show that the extreme precipitation in Hunan Province showed a stable pattern of fluctuation, and the main extreme precipitation indexes had no significant change trend. The spatial distribution showed a pattern of “high value in central-northern Hunan and stable in southern Hunan”, and the precipitation was concentrated in June–August. The rice yield showed the characteristics of “stable increase in the core area, intensified fluctuation in the transition area, and continuous shrinkage in the marginal area”, and the Dongting Lake Plain was a high-yield and stable area. Multi-scale analysis shows significant coupling between extreme precipitation and yield: in the 4–8-year cycle, the peak value of precipitation lags behind the response of 1–2 years, and changes synchronously in a short period. The response of rice to extreme precipitation showed a threshold-type nonlinear characteristic. Moderate wetting was beneficial to stable yield, while the yield decreased significantly when the intensity or continuous precipitation exceeded the threshold. Hunan’s rice system has strong climate resilience but requires a multi-scale climate-adaptive agricultural system via engineering, technology, and policy for long-term stability and sustainable grain production. Full article

Intersectoral labour mobility is a key driver of economic resilience and innovation in Europe. The redistribution of workers across sectors and regions enables economies to adapt to shocks, create flexibility and increase the rate of structural change. However, the dynamics of mobility have not been adequately investigated across varying scales of sectoral granularity and spatio-temporal dimensions. This paper applies the Intersectoral Mobility Index (MI) to all European NUTS-2 areas from 2008 to 2020, utilising Eurostat Structural Business Statistics. Two levels of sectoral aggregation (NACE Rev. 2, 1-digit and 2-digit) are employed to compute MI, capturing both broad and fine-grained reallocations. Classical indices of structural change (NAV, Krugman, Shorrocks) are combined with spatio-temporal modelling in ArcGIS Pro, employing Space–Time Cubes, time-series exponential smoothing forecasts, time-series clustering and emerging hot spot analysis. Results indicate that MI distributions are positively skewed and heavy-tailed, with peaks coinciding with systemic crises (2009–2011, 2020). At the 2-digit level, MI values are significantly higher, revealing intra-sectoral changes obscured in aggregated data. A statistically significant downward trend in mobility suggests an increasing structural rigidity following the global financial crisis. Regional clustering highlights heterogeneity: a small number of regions, such as Bremen, Madeira and the Southern Great Plain, have sustained high or unstable mobility, while most exhibit convergent mobility and low reallocation. This paper contributes to the conceptualisation of MI as a dual measure of resilience and innovation preparedness. It underscores the importance of multi-scalar and spatio-temporal methods in monitoring labour market flexibility. The findings have policy implications, including the design of targeted reskilling programmes, proactive labour market policies and just transition plans to maintain regional resilience during the EU’s green and digital transitions. Full article

Proactive management of groundwater resources is hindered by the static nature of conventional vulnerability assessments, which provide only a single temporal snapshot and lack predictive capability. To address this limitation, we developed a coupled dynamic–spatial modeling framework to forecast the spatio-temporal evolution of groundwater vulnerability. The framework integrates a βSARMA time-series model for precipitation forecasting with an enhanced M-DRASTIC-LAaRd model, which incorporates Land use, Anthropogenic activity, and River network density, weighted via the Analytical Hierarchy Process (AHP) to better capture hydrogeological complexity. The βSARMA model consistently outperformed conventional SARIMA models across the five subregions of Beijing, achieving the lowest RMSE values (0.0832–0.1617) and MAE values (0.0922–0.1372), with an average RMSE reduction of 15.3% relative to the best SARIMA baseline. These results ensure highly reliable dynamic precipitation inputs for the time-varying Net Recharge (R) parameter. Model validation against historical observations yielded a coefficient of determination (R²) of 0.87, confirming the framework’s robustness and predictive accuracy. Applied to the Beijing metropolitan area (1980–2027), the model projects a marked spatial restructuring of groundwater vulnerability: high-vulnerability zones are expected to expand from 38.65% to 46.18%, while low-vulnerability areas will decline from 42.53% to 34.63%. Emerging “hotspots” are concentrated in the southern urban plains, where urbanization and reduced recharge converge. Overall, 27.9% of the region is predicted to experience intensified vulnerability, whereas only 11.5% will show improvement. This study advances groundwater vulnerability assessment from static mapping toward dynamic forecasting, providing a quantitatively validated and spatially explicit framework that supports more informed groundwater management under future environmental change. Full article

The severe degradation of thin-layer black soil in the Southern Songnen Plain threatens both regional agricultural sustainability and national food security. While various fertile topsoil restoration technologies have been proposed, a systematic evaluation of their comprehensive benefits is lacking, hindering effective policy and technology promotion. This study addresses this gap by employing an entropy weight–fuzzy comprehensive evaluation method to assess the economic, social, and ecological performance of four predominant restoration models—no-tillage, strip-tillage, deep-tillage, and indirect return—using survey data from 263 farmers. Results identify strip-tillage as the optimal model, achieving the highest integrated benefit score (8.153) by successfully balancing superior economic profitability and social acceptance with robust ecological performance. Although no-tillage excels in ecological benefits like moisture conservation (8.901) and pesticide reduction (8.524), its economic potential is constrained by higher management costs. Deep-tillage rapidly enhances soil fertility (8.628) but is limited by high operational costs, whereas the indirect model, despite high ecological sustainability (7.781), faces adoption barriers due to technical complexity and cost. The findings underscore the necessity of moving beyond one-size-fits-all approaches. We propose a targeted promotion system based on “categorized guidance and precision adaptation”, offering a practical framework for optimizing technology deployment to support both black soil conservation and sustainable agricultural development. Full article

Atmospheric sulfur (S) deposition, a key component of acid deposition, poses risks to ecosystems, human health, and sustainable development. In China, decades of coal-dominated energy use caused severe S pollution, but recent emission-control policies and energy restructuring have sought to reverse this trend. However, the effectiveness and regional differences in these measures remain insufficiently quantified. Here, we combined continuous observations from 43 monitoring sites (2013–2023), satellite-derived SO₂ vertical column density, and multi-source environmental datasets to construct a high-resolution record of wet S deposition. A random forest model, validated with R² = 0.52 and RMSE = 1.2 kg ha⁻¹ yr⁻¹, was used to estimate fluxes and spatial patterns, while ridge regression and SHAP analysis quantified the relative contributions of emissions, precipitation, and socioeconomic factors. This framework allows us to assess both the environmental and health-related sustainability implications of sulfur deposition. Results show a nationwide decline of more than 50% in wet S deposition during 2013–2023, with two-thirds of sites and 95% of grids showing significant decreases. Historical hotspots such as the North China Plain and Sichuan Basin improved markedly, while some southern provinces (e.g., Guizhou, Hunan, Jiangxi) still exhibited high deposition (>20 kg ha⁻¹ yr⁻¹). Over 90% of the reduction was attributable to emission declines, confirming the dominant effect of sustained policy-driven measures. This study extends sulfur deposition records to 2023, demonstrates the value of integrating ground monitoring with remote sensing and machine learning, and provides robust evidence that China’s emission reduction policies have delivered significant environmental and sustainability benefits. The findings offer insights for region-specific governance and for developing countries balancing economic growth with ecological protection. Full article

The pepper weevil Anthonomus eugenii is a devastating pest native to Central America that can cause severe damage to over 35 pepper varieties. Global trade in peppers has significantly increased the risk of its spread and expansion. Moreover, future climate change may add more uncertainty to its distribution, resulting in considerable ecological and economic damage globally. Therefore, we employed an ensemble model combining Random Forests and CLIMEX to predict the potential global distribution of A. eugenii in historical and future climate scenarios. The results indicated that the maximum temperature of the warmest month is an important variable affecting global A. eugenii distribution. Under the historical climate scenario, the potential global distribution of A. eugenii is concentrated in the Midwestern and Southern United States, Central America, the La Plata Plain, parts of the Brazilian Plateau, the Mediterranean and Black Sea coasts, sub-Saharan Africa, Northern and Southern China, Southern India, Indochina Peninsula, and coastal area in Eastern Australia. Under future climate scenarios, suitable areas in the Northern Hemisphere, including North America, Europe, and China, are projected to expand toward higher latitudes. In China, the number of highly suitable areas is expected to increase significantly, mainly in the south and north. Contrastingly, suitable areas in Central America, northern South America, the Brazilian Plateau, India, and the Indochina Peninsula will become less suitable. The total land area suitable for A. eugenii under historical and future low- and high-emission climate scenarios accounted for 73.12, 66.82, and 75.97% of the global land area (except for Antarctica), respectively. The high-suitability areas identified by both models decreased by 19.05 and 35.02% under low- and high-emission scenarios, respectively. Building on these findings, we inferred the future expansion trends of A. eugenii globally. Furthermore, we provide early warning of A. eugenii invasion and a scientific basis for its spread and outbreak, facilitating the development of effective quarantine and control measures. Full article

Lotus corniculatus L. is a valuable fodder legume, recognized for its ecological adaptability and high potential for production and fodder quality. In this study, 18 genotypes collected from wild flora were analyzed to highlight genetic variability and facilitate the selection of genotypes with superior potential. The collection area was in the western part of Romania and featured a diverse topography, including parts of the Banat Plain, the Banat Hills, and the Southern and Western Carpathians. The genotypes selected from the wild flora were cultivated and evaluated for morpho-productive and forage quality traits, including pod weight, average number of seeds/pods, green mass production, and protein percentage. PCA highlighted the main components explaining the variability, and K-means clustering allowed for the identification of groups of genotypes with similar performances. ANOVA showed statistically significant differences (p < 0.001) for all traits analyzed. According to the results, genotypes LV-LC-3, LV-LC-4, LV-LC-6, and LV-LC-16 showed high productive potential and were highlighted as the most valuable for advancing in the breeding program. The moderate relationships between traits confirm the importance of integrated selection. The identified genetic variability and selected genotypes support the implementation of effective breeding strategies to obtain high-performance Lotus corniculatus L., adapted to local soil and climate conditions and with a superior forage yield. Full article

As China’s first systematic assessment of high-risk Amaranthaceae invaders, this study addresses a critical knowledge gap identified in the National Invasive Species Inventory, in which four invasive Amaranthaceae species (Dysphania ambrosioides, Celosia argentea, Amaranthus palmeri, and Amaranthus spinosus) are prioritized due to CNY 2.6 billion annual ecosystem damages in China. By coupling multi-species comparative analysis with a parameter-optimized Maximum Entropy (MaxEnt) model integrating climate, soil, and topographical variables in China under Shared Socioeconomic Pathways (SSP) 126/245/585 scenarios, we reveal divergent expansion mechanisms (e.g., 247 km faster northward shift in A. palmeri than D. ambrosioides) that redefine invasion corridors in the North China Plain. Under current conditions, the suitable habitats of these species span from 92° E to 129° E and 18° N to 49° N, with high-risk zones concentrated in central and southern China, including the Yunnan–Guizhou–Sichuan region and the North China Plain. Temperature variables (Bio: Bioclimatic Variables; Bio6, Bio11) were the primary contributors based on permutation importance (e.g., Bio11 explained 56.4% for C. argentea), while altitude (e.g., 27.3% for A. palmeri) and UV-B (e.g., 16.2% for A. palmeri) exerted lower influence. Model validation confirmed high accuracy (mean area under the curve (AUC) > 0.86 and true skill statistic (TSS) > 0.6). By the 2090s, all species showed net habitat expansion overall, although D. ambrosioides exhibited net total contractions during mid-century under the SSP126/245 scenarios, C. argentea experienced reduced total suitability during the 2050s–2070s despite high-suitability growth, and A. palmeri and A. spinosus expanded significantly in both total and highly suitable habitat. All species shifted their distribution centroids northward, aligning with warming trends. Overall, these findings highlight the critical role of temperature in driving range dynamics and underscore the need for latitude-specific monitoring strategies to mitigate invasion risks, providing a scientific basis for adaptive management under global climate change. Full article

Conventional tillage and monocropping are common practices employed for cotton production in the Southern Great Plains (SGP) region, but they can be detrimental to soil health, crop yield, and water resources when improperly managed. Regenerative practices such as cover crops and conservation tillage have been suggested as an alternative. The proposed shift in management practices originates from the need to make agriculture resilient to extreme weather events including intense rainfall and drought. The objective of this study is to test the effects of these regenerative practices in an environment with limited rainfall. Runoff volume, nutrient and sediment concentrations and loadings, and surface soil moisture levels were compared on twelve half-acre (0.2 hectare) cotton plots that employed different cotton seeding rates and variable winter wheat cover crop presence. A winter cover implemented on plots with a high cotton seeding rate significantly reduced runoff when compared to other treatments (p = 0.032). Cover cropped treatments did not show significant effects on nutrient or sediment loadings, although slight reductions were observed in the concentrations and loadings of total Kjeldahl nitrogen, total phosphorus, total solids, and Escherichia coli. The limitations of this study included a short timeframe, mechanical failures, and drought. These factors potentially reduced the statistical differences in several findings. More efficient methods of crop production must continue to be developed for agriculture in the SGP to conserve soil and water resources, improve soil health and crop yields, and enhance resiliency to climate change. Full article

This study examines a convergence event at the trailing end of a cold front observed in the United States’ Southern Great Plains region on 28 September 1997, using an array of in situ and remote sensing instruments. The event exhibited a structure with elevated divergence near 3 km AGL and moisture transport over both warm and cold sectors. Data from Raman lidar (RL), Atmospheric Emitted Radiance Interferometer (AERI), and Radar Wind Profilers (RWP) were used to characterize vertical profiles of the event, revealing the presence of a narrow moist updraft, horizontal moisture advection, and cloud development ahead of the front. Convection parameters, Convective Available Potential Energy (CAPE) and Convective Inhibition (CIN), were derived from collocated AERI and RL. Regions of high CAPE were aligned with areas of high moisture, indicating that convection was more favorable at moist elevated levels than near the surface. RWP observations revealed vorticity structures consistent with existing theories. This study highlights the value of high-resolution, continuous profiling from remote sensors to resolve mesoscale processes and evaluate convection potential. The event underscores the role of elevated moisture and wind shear in modulating convection initiation along a trailing-end cold front boundary where mesoscale and synoptic forces interact. Full article