Search Results (112)

Precision agriculture increasingly relies on high-resolution, long-term remote sensing to delineate sub-field management zones. However, traditional spatial zonation assumes temporal stationarity, utilizing seasonal aggregates that obscure transient, intra-annual stress signals. This study develops a data-driven framework to characterize both persistent and non-stationary crop water use dynamics by integrating monthly, 30-m evapotranspiration (ET) data from OpenET (2000–2025) with zero-shot temporal anomaly detection. A pre-trained time-series foundation model (Chronos-T5-Small) generated counterfactual expectations for sub-field ET, quantifying deviations using a mean absolute error-based anomaly score. Unsupervised clustering of these anomaly scores with longitudinal ET metrics partitioned the landscape into dynamic biophysical regimes. Cross-registered against legacy persistence mapping based on seasonal totals, the foundation model showed strong directional agreement (86.1%, Cohen’s Kappa = 0.716) in identifying chronically constrained zones across 869 shared active pixels. Crucially, the framework identified 966 historically persistent pixels undergoing stability decay, of which 95.3% were statistically verified via paired t-tests to have collapsed into the field’s baseline variance pool. Furthermore, counterfactual anomaly detection isolated zones of recent acute divergence, differentiating enduring edaphic constraints from sudden system disruptions. This approach demonstrates how foundation models can transition from purely predictive engines to diagnostic instruments, advancing operational precision agriculture. Full article

The Jabal Ali Marine Sanctuary, Dubai, is one of the most important marine protected areas (MPAs) in the UAE. The Arabian Gulf is characterised by extreme environmental conditions, including high temperatures and hypersaline waters. These conditions, combined with increasing anthropogenic pressures from coastal development projects such as desalination plants, energy plants and the Palm Jebel Ali development, may influence the pelagic ecosystems of MPAs. This study examined seasonal variability in phytoplankton communities and environmental conditions between summer (June 2017) and winter (December 2017), with particular emphasis on the interactions between temperature-driven stratification, hypersaline conditions, and phytoplankton community structure, abundance, and diversity. The AZTI (AZTI Tecnalia Marine Research Centre) Marine Biotic Index indicated predominantly “Good” to “High” ecological status of the pelagic ecosystem, indicating favourable environmental conditions. Potentially harmful algal bloom taxa, including Pseudo-nitzschia and Dinophysis, were detected at low abundances. Summer surveys recorded higher total species richness (44 vs. 34 species) and greater phytoplankton abundance (mean 68.6 vs. 49.8 cells/L) compared to those in winter. Diatoms dominated the assemblages in both seasons, accounting for 62–69% of the recorded species, while distinct spatial zonation patterns reflected habitat heterogeneity. The observed seasonal and spatial variability highlight the importance of incorporating temporal and spatial dimensions into management strategies. As the first pelagic phytoplankton assessment conducted in an MPA, this study provides important baseline data for understanding phytoplankton ecology in one of the world’s most environmentally extreme marine ecosystems. The findings contribute to evidence-based management under increasing climate change and anthropogenic pressures. However, because sampling was limited to the two principal climatic seasons, the study characterises inter-seasonal variability rather than a complete annual succession cycle. Additional surveys during spring and autumn are recommended to fully resolve seasonal succession dynamics. Overall, the findings support the continued protection of the sanctuary as an important biodiversity reservoir and a potential reference site for assessing marine ecosystem responses to environmental conditions. These findings are directly relevant to the environmental sustainability agenda of the Dubai 2040 Urban Master Plan, which prioritises the protection and expansion of the emirate’s nature reserves and the safeguarding of marine and coastal biodiversity. By establishing the first pelagic phytoplankton baseline for the sanctuary, this study provides an evidence base for monitoring and managing marine protected areas in line with this long-term framework. Full article

Precise classification of landslide types is essential for effective hazard mitigation; however, many existing landslide inventories lack type-specific information, limiting their applicability in risk management. This study presents a transferable machine learning framework to identify rainfall-induced cliff-type (shallow) landslides from unclassified inventories across seismic and non-seismic environments. Using the Forest-based and Boosted Classification and Regression (FBCR) tool in ArcGIS Pro 3.5, two models were developed using 25 landslide conditioning factors (LCFs) from Wakayama and Tokushima Prefectures, Japan. Both models achieved strong training performance, with accuracy and sensitivity exceeding 0.84, F1 scores of 0.84–0.85, and Matthews correlation coefficients (MCC) of 0.68–0.71. Transferability was assessed by applying both models to the Kegalle District, Sri Lanka, where the non-seismic model achieved approximately 80% spatial validation accuracy. Variable importance analysis revealed that rainfall consistently ranked as a high-influence LCF in both models—second in the seismic model and seventh in the non-seismic model—confirming its role as a primary conditioning factor for cliff-type shallow landslide susceptibility regardless of tectonic setting. The proposed framework provides a practical approach for complementing missing landslide type information in existing inventories, improving hazard zonation and supporting risk-informed planning in diverse geological and climatic settings. Full article

Chromium-related hazard in mine wastes depends strongly on oxidation state, with hexavalent chromium [Cr(VI)] representing the most mobile and toxicologically relevant chromium form. Abandoned tailings dumps can develop sharp pH and redox gradients that favour either Cr(VI) persistence or attenuation, yet field-based evidence from Eastern European post-mining sites remains limited. This study evaluates the Defor Petrila tailings dump, Jiu Valley, Romania, as a first-tier environmental hazard-screening case study based on repeated monitoring performed during 2022–2024 at twelve permanent sampling points and two local operational control samples. Field pH and redox potential (Eh), moisture, organic matter, acid-extractable Mn and Fe, pseudo-total Cr, and method-defined extractable Cr(VI) were determined. Here, pseudo-total Cr refers to chromium released by microwave-assisted acid digestion and does not represent complete decomposition of the silicate matrix, while extractable Cr(VI) refers to the operationally defined fraction obtained by alkaline extraction. In addition, a conservative redox-based prioritisation score (R_redox) was applied only as an internal ranking layer to identify sectors where Cr(VI) is more likely to persist. The upper dump sector (P1–P4) was alkaline (pH 7.5–8.2), strongly oxidising (+280 to +412 mV), and enriched in Mn and Fe, whereas the lower sector (P9–P12) was wetter, slightly acidic to near-neutral, and reducing (−59 to −10 mV). Extractable Cr(VI) reached 18.7 mg kg⁻¹ at P2 in 2024, while both control samples remained below the quantification limit. Exploratory repeated-site statistics, sector-based comparison, and correlation analysis supported a coherent association between Eh, Mn enrichment, and extractable Cr(VI), but these relationships are interpreted as spatially structured screening evidence rather than proof of a single mineralogical oxidation pathway. No direct exposure, leachability, bioaccessibility, ecotoxicity, airborne dust, water, vegetation, or biomonitoring measurements were included; therefore, the results identify priority zones for confirmatory toxicological and exposure-based assessment, not receptor-specific risk estimates. This study demonstrates that combining chromium speciation with field redox zonation can support conservative monitoring prioritisation at abandoned mine-waste sites where the toxic form of chromium may remain environmentally active. Full article

With the rapid growth of tourism in Dayi County over the past decade, this study develops a meteorological disaster risk assessment framework for major tourist attractions in this region. Drawing upon daily precipitation and temperature records from 25 meteorological stations (2014–2023) alongside multi-source geospatial data, we evaluate six primary attractions: Xiling Snow Mountain, Huashuiwan, Anren Ancient Town, Xinchang Ancient Town, Tianfu Huaxigu Valley, and Shujiu Cultural Park. The evaluation model integrates four core dimensions: hazard, environmental sensitivity, asset vulnerability, and disaster mitigation capacity. Indicator weights are determined through the Analytic Hierarchy Process, and GIS-based spatial analysis is employed for risk zonation. Additionally, the 45-year ChinaMet dataset provides independent validation for the long-term stability of the hazard assessment. Results reveal a distinct west-low, east-high composite risk gradient. High-altitude mountainous regions in the west exhibit a lower overall risk. Despite frequent extreme weather events, extensive vegetation coverage and low visitor density effectively buffer the negative impacts of physical hazards. Conversely, tourist attractions on the eastern plains fall within high-risk zones. Concentrated visitor populations, dense built environments, and low-lying terrain collectively amplify exposure to severe rainstorms and extreme heatwaves. These findings demonstrate that meteorological disaster risk in tourism destinations fundamentally arises from the deep coupling of natural and human systems. Thus, this study provides a scientific basis for implementing differentiated disaster prevention, mitigation, and localized emergency management strategies. Full article

Precise assessment of commercial service facilities (CSFs) is a vital pillar for megacity governance. However, existing evaluations rely on static population and 2D metrics, overlooking behavioral heterogeneity and 3D spatial supply at the micro scale. This study constructs a “3D Supply–Group Demand–Matching” framework at the community level. On the supply side, a Building Coupling Entropy (BCE) model integrates 3D volume and morphology to characterize service capacity. On the demand side, a dynamic behavioral model measures multi-group needs. Mismatch patterns are identified using the Entropy-modified Spatial Disparity Ratio (ESDR). Using Guangzhou as a case, the results reveal three paradigms: (1) Core districts exhibit rigid path dependency, where first-tier sub-districts rose from 48 to 51, and elderly service shortages in old areas plummeted by nearly 80% via micro-regeneration; (2) Growth poles show spatial fragmentation, with core labor demand spilling over but infrastructure lagging, creating a fast production–slow urbanism mismatch; (3) Far-suburban areas reduced extreme-shortage sub-districts from 38 to 34, identifying resource islands besieged by residential demand. Overall, the framework elucidates the shape–flow mismatch mechanism and provides a transferable basis for precision zonation governance, supporting a shift from static quantity-based allocation to dynamic quality-oriented provision in high-density megacities. Full article

This study comprehensively analyzed the compounded effects of climatic factors and non-climatic factors on vegetation dynamics in the northern Shaanxi Loess Plateau region in China. The objective was to provide robust scientific insights and a solid theoretical framework to support the long-term stability and sustainable development of the local ecosystem. The temperature vegetation dryness index was used to improve the water stress factor of the CASA model, so as to estimate the NPP of vegetation on the Loess Plateau of northern Shaanxi from 2000 to 2020. The temporal and spatial change characteristics of vegetation NPP and its relationship with climatic factors were analyzed using the coefficient of variation, the Mann–Kendall test of significance, and second-order partial correlation analysis. The partial derivative residual trend method was used to isolate the specific impacts of climatic factors and non-climatic factors on vegetation NPP. The results indicate the following: (1) The vegetation NPP shows a notable upward trend, with an annual growth rate of 9.4195 gC·m⁻²·a⁻¹ and a long-term average of 269.71 gC·m⁻², with the spatial distribution showing markedly high south, low north, and latitudinal zonation characteristics. (2) Vegetation NPP exhibits positive correlations with temperature, precipitation, and solar radiation. Among these factors, precipitation shows the strongest correlation with variations in vegetation NPP. (3) Non-climatic factors are the main factor affecting vegetation NPP across most parts of the study area, which is greater than the effect of selected climatic factors, and human activities may be the key component within non-climatic factors. Full article

Orogenic gold deposits host a substantial proportion of global gold resources, yet their internal alteration architecture and mineral assemblage variability are commonly reconstructed from random samples, limiting our ability to resolve along-profile zonation and its linkage to gold enrichment. Here we evaluate hyperspectral drill-core spectroscopy, integrated with surface spectroscopy and petrographic validation, as a rapid and spatially continuous approach to delineate alteration zoning in the Liba orogenic gold deposit (West Qinling Orogen, China). We acquired hyperspectral spectra (0.35–2.50 μm) from 255 evenly spaced surface points across two orebodies and from nine representative drill cores scanned at 1 m intervals, and organized the spectral dataset according to Au-grade domains (<0.05 g/t, 0.05–0.5 g/t, and >0.5 g/t). Spectra were quality controlled and interpreted using ENVI-based spectral library matching and The Spectral Geologist (TSG) processing workflows. Petrographic observations from 76 polished thin sections provide independent mineralogical constraints. The hyperspectral results resolve a systematic alteration progression from barren chlorite-dominated assemblages (Au-grade < 0.05 g/t) (locally with minor carbonate) through a weakly mineralized transition (Au-grade 0.05–0.5 g/t) characterized by diminishing chlorite and emergent kaolinite–carbonate with intensified sericitization, to an ore-grade (Au-grade > 0.5 g/t) assemblage dominated by kaolinite–sericite–carbonate–pyrite where biotite persists in distal and proximal zones but was progressively replaced by chlorite during subsequent hydrothermal stages; its modal abundance exhibits a clear inverse correlation with mineralization intensity. These results demonstrate that hyperspectral core scanning, coupled with targeted validation, can rapidly reconstruct a three-dimensional alteration architecture and provide practical mineralogical vectors for exploration targeting and process-oriented studies in orogenic gold systems. Full article

The Fengcheng Formation in the Mahu Sag of the Junggar Basin represents one of the oldest and most significant alkaline lacustrine systems, hosting abundant dolomite that serves as a key unconventional reservoir. However, the formation mechanism of dolomite remains unclear. This study integrates detailed petrography, geochemistry and cyclostratigraphy to elucidate the origin and distribution of dolomite. Petrographic characteristics indicate a penecontemporaneous origin for the dolomite, with no apparent hydrothermal influence. Mineralogical features exhibit a multi-zonation structure of dolomite, aligning with in situ Fe content, jointly indicating that a multi-stage formation process of dolomite from core to rim. Microbial methanogenesis likely played an important role in the dolomite formation. Spatially, dolomite is enriched in the transition zone but scarce in the depocenter zone, where sodium carbonate prevails. This distribution is primarily controlled by pH differentiation between the transition zone and the depocenter zone of the Mahu Sag. In the transition zone, orbitally driven wet–dry cycles regulated the lake-level change, which, in turn, controlled pH fluctuation, as revealed by the silica precipitation during humid phases and dissolution during arid intervals. In the depocenter zone, lake water remained at a high-pH state, which was unfavorable for dolomite formation. These findings highlight that pH dynamics, linked to orbital climate cycles, played a critical role in governing dolomite formation and distribution in this ancient alkaline lake, providing new insights for the formation of dolomite in alkaline lacustrine environments. Full article

Caves are fragile subterranean ecosystems whose conservation depends on accurate microclimatic zonation. Traditional fixed-distance sampling often overlooks non-linear thermodynamic transitions at geomorphological thresholds, hindering sustainable management of subterranean biodiversity. This study introduces the Adaptive Morpho-Statistical Protocol (AMSP), a novel, resource-efficient framework for functional cave profiling. The methodology integrates high-precision atmospheric monitoring with adaptive spatial positioning to identify three distinct sectors (S1–S3) based on thermodynamic homeostasis rather than linear distance. Validated across five diverse cave archetypes in the Vratsa Karst Region (Bulgaria), the AMSP demonstrated exceptional predictive power using second-order polynomial regressions (R² > 0.92). A key finding is the definition of a standardized reference threshold for deep-reach stability (Sector 3), consistently characterized by a Dew Point Standard Deviation (SD_DP < 0.40) and stabilized thermal coupling (∆T → 0). Furthermore, the adaptive strategy successfully captured extreme hygrometric jumps at morphological bottlenecks—critical inflection points for protecting sensitive biota. By providing a cost-effective and replicable standard, the AMSP bridges the gap between spatial resolution and logistical feasibility in challenging environments. These results confirm that morphological isolation is the primary driver of microclimatic inertia, offering a robust tool for sustainable subterranean heritage management and high-precision ecological monitoring in protected karst landscapes. Full article

Irrigation-driven greening is essential for northwest China’s dryland ecosystems, where vegetation growth depends on key hydrological factors, including precipitation (PRE), evapotranspiration (ET), soil moisture (SM), and irrigation water use (IWU), which affect water availability to a certain extent. To assess greening sustainability, a 1 km IWU dataset was created for 2001–2022 by combining remote sensing and ancillary data using machine learning, overcoming limited irrigation records. By linking IWU with the normalized difference vegetation index (NDVI) and analyzing trends in irrigated areas, we implemented a regional zonation approach to identify specific risk areas and evaluated both greening sustainability and vegetation responses using water balance (WB) and various hydrological variables. The results show that NDVI has increased widely over the past two decades, with sustained positive WB and stable irrigation, indicating improved water availability. However, spatial differences exist: 35.98% of irrigated areas have rising NDVI but falling IWU, especially in the east, where higher NDVI, IWU, WB, PRE, and ΔSM (soil moisture difference between growing season end and start) reflect favorable climate and hydrology; attention should also be directed toward potential deep percolation and saline sinks. In contrast, areas with high IWU often displayed elevated NDVI but declining water availability, suggesting unsustainable greening due to excessive irrigation. In addition, the SCD_IWU-SCD_NDVI class dominates among significant NDVI-IWU trends, indicating potential for sustainable irrigation under certain drought and climate conditions. Overall, the northwestern portion of the study area exhibits the lowest water availability; cities such as Urumqi warrant particular attention. These findings identify at-risk areas and those with better water resilience, supporting targeted water–vegetation management. Full article

Under the combined pressures of natural variability and human activities, the area of tidal flats has been gradually decreasing, with most muddy coasts experiencing varying degrees of erosion. The central coast of Jiangsu Province, a world-renowned region for extensive tidal flats, has witnessed intensifying erosion of its muddy coasts in recent years. To mitigate further coastal erosion, an ecological submerged breakwater (ESB) was constructed in the intertidal zone north of the Sheyang River estuary to reduce wave impact on the shoreline. This study evaluates the wave attenuation performance of the ESB based on wave observations conducted at stations deployed on the seaward and landward sides of the structure in May 2025. Results indicate that the breakwater effectively reduces wave height, but its performance exhibits significant dynamic characteristics. During the observation period, the maximum attenuation rate for significant wave height (H₁/₃) reached 76.3%, with an average rate of 33.8%. Wave dissipation efficiency was closely related to sea state: under calm conditions (H₁/₃ < 0.4 m), the average attenuation rate was only 18.4%, whereas under severe sea states (H₁/₃ ≥ 0.4 m), it increased markedly to 57.6%. The wave transmission coefficients (K_t) span a wide range from 0.20 to 0.99, indicating a significant dynamic variability in the wave attenuation performance of the ESB. The performance of the ESB was primarily controlled by two key factors: incident wave height and submergence depth of the structure. Compared to “zonated” natural ecosystems such as oyster reefs, coral reefs, salt marshes, and mangroves, the ESB, as a “linear” engineered structure, achieves comparable wave attenuation within a limited spatial footprint. A promising future strategy involves using the ESB as a frontline defense, integrated with landward ecological restoration measures like salt marsh rehabilitation, to establish a hybrid “grey-green” coastal protection system that synergistically enhances both coastal resilience and ecological function. This study provides a scientific basis for the design and performance evaluation of ecological engineering solutions for protecting eroding muddy coasts. Full article

Spatial analyses of built-up areas based on aggregated land cover data are inherently affected by the Modifiable Areal Unit Problem (MAUP). This study quantifies the influence of the data scale and the areal unit configuration on Lorenz-based measures of the concentration of the built area. Using Łódź Metropolitan Area (Poland) as a case study, harmonized land cover datasets at scales of 1:10,000 and 1:100,000 were analysed with regular square and hexagonal grids of varying sizes, as well as irregular cadastral units. Concentration was measured using a Lorenz curve-based coefficient and sensitivity to zonation was assessed using the coefficient of variation. The results show that the data scale is the primary determinant of the concentration values, with coarser-scale data consistently producing higher and more variable coefficients. Increasing the size of the areal unit leads to a systematic decrease in the concentration measured, while differences in unit geometry and location exert a comparatively minor influence. Irregular cadastral units improve spatial interpretability, but do not reduce susceptibility to MAUP. The findings confirm the strong scale dependency of concentration measures and highlight the necessity of multiscale approaches in quantitative analyses of built-up areas. Full article

Genetics strongly impacts the course of metabolic dysfunction-associated steatotic liver disease (MASLD), with the I148M Patatin like phospholipase domain containing 3 (PNPLA3) variant representing the main modifier. Fat accumulation in the hepatic lobule, strongly enhanced by this SNP, may be influenced by the liver’s zonation. Therefore, we applied spatial transcriptomics to investigate the metabolic processes across portal (PZ)-central (CZ) zones in I148M PNPLA3 carriers. Visium CytAssist technology was applied to liver biopsies from MASLD patients sharing similar disease severity, who were wild-type (WT) or homozygous for the I148M variant (Discovery cohort, n = 4). The distribution of steatosis, inflammation, and fibrosis was assessed in the liver biopsies of MASLD patients, stratified according to the I148M variant (validation cohort, n = 100). At the Visium-LOUPE browser, we spatially mapped PZ and CZ hepatocytes (HEPs), revealing higher lipid turnover, glucose signaling, and lower mitochondrial activity in I148M-PZ-HEPs compared to 148M-CZ-HEPs. Thus, the I148M variant could unbalance the physiological hepatic zonation boosting steatosis development in PZ, consequently inducing mitochondrial dysfunction. The unsupervised analysis confirmed the altered metabolic pattern among CZ and PZ in patients carrying the variant. Interestingly, PNPLA3 expression was higher in I148M-PZ, which also showed an enrichment of non-parenchymal cells, thus possibly explaining the more severe injury in this area. Finally, in the validation cohort, we observed a pronounced PZ distribution of steatosis, inflammation, and fibrosis in I148M PNPLA3 subjects compared to WT, confirming the spatial data. The I148M variant contributes to the metabolic switching across different hepatic zones and represents a new clinical perspective by defining a specific histological pattern of MASLD. Full article

Understanding the coupling mechanisms between vegetation phenology and carbon productivity is essential for assessing ecosystem responses to climate change and guiding sustainable grassland management. This study focuses on stable alpine grasslands on the southern slope of the Qilian Mountains from 2001 to 2020, a climatically sensitive but relatively under-investigated transition zone on the northeastern Tibetan Plateau. We utilized MODIS NDVI time-series (MOD13Q1) and the latest PML V2 gross primary productivity (GPP) product at 500 m resolution to quantify changes in the start (SOS), end (EOS), and length (LOS) of the growing season. A pixel-wise linear regression approach was applied to evaluate the sensitivity of GPP to phenological metrics, explicitly characterizing how much GPP changes in response to unit shifts in SOS, EOS and LOS. Compared with previous studies that mainly described large-scale correlations between phenology and GPP or relied on coarser GPP products, this study provides a pixel-level, sensitivity-based assessment of phenology–carbon coupling in alpine grasslands using a long-term, phenology–GPP dataset tailored to the Qilian alpine region. The results revealed trends of earlier SOS, delayed EOS, and extended LOS, accompanied by a gradual increase in GPP. However, phenology–GPP coupling exhibited notable spatial heterogeneity. In mid- and low-altitude areas, extended growing seasons enhanced GPP, whereas high-altitude zones showed limited or even negative responses, likely due to climatic constraints such as cold stress and thermal–moisture mismatches. To better understand these spatial differences, we constructed a three-dimensional phenology–GPP sensitivity space and applied k-means clustering to delineate three ecological functional zones: (1) high carbon sink potential, (2) ecologically fragile regions, and (3) neutral buffers. This sensitivity-based functional zonation moves beyond traditional correlation analyses and provides a process-oriented and spatially explicit framework for ecosystem service assessment, carbon sink enhancement and adaptive land-use strategies in sensitive mountain environments. Full article