Search Results (2,593)

Phosphorites are a vital source of phosphorus for agricultural and industrial applications and are increasingly recognized for their potential as secondary repositories of critical raw materials (CRMs) such as rare earth elements plus yttrium (REYs). This study investigates deep-sea phosphorites from the Galicia Bank, Madeira, and Canary Seamounts, in the NE Atlantic Ocean, which are spatially associated with ferromanganese (Fe-Mn) mineralization. Through integrated petrographic, geochemical, and in situ isotopic analyses (O and Sr), we assess the timing, processes, and paleoenvironmental conditions of phosphogenesis and its implications for CRM enrichment. Rare earth element patterns in apatite reflect a predominant seawater-derived signature with variable Ce anomalies. Nevertheless, variable Y/Ho ratios point to evolving fluid sources including a hydrogenous component (directly derived from seawater), modified porewaters and, locally, volcanic or possibly hydrothermal inputs. Oxygen and strontium isotope compositions constrain phosphogenesis to several episodes ranging from the Upper Cretaceous to the Middle Miocene, with distinct isotopic shifts identifying both primary formation and later overprinting processes mostly linked to Fe-Mn oxyhydroxide growth or volcanic–hydrothermal activity. These findings highlight the dynamic and multiphase nature of phosphorite formation in deep-marine settings. The integration of high-resolution geochemical and isotopic tools proves essential for reconstructing genetic histories, defining metallogenic context and evaluating CRM prospectivity in complex submarine systems. Full article

Introduction: Elasmobranchs play a vital role in marine food webs through top-down control and the structuring of ecosystem stability, yet more than one-third of species face extinction. The Maldives, a recognised Indian Ocean hotspot for shark and batoid diversity, designated its EEZ as a shark sanctuary in 2010, but multispecies elasmobranch occurrence patterns and environmental drivers remain poorly characterised in Lhaviyani Atoll in the central Maldives, which hosts two Important Shark and Ray Areas (ISRAs). Recreational SCUBA networks can turn routine dive activity into long-term conservation evidence, already informing nearly 10% of the western Indian Ocean ISRAs. Objective: To characterise spatiotemporal patterns of elasmobranch assemblages in Lhaviyani Atoll (2017–2024), quantify how environmental and geomorphic drivers shape relative abundance, diversity, and hotspots, and provide evidence for targeted elasmobranch conservation. Methodology: A seven-year opportunistic dive-log dataset of 12,732 SCUBA surveys and 142,994 elasmobranch records across 94 dive sites was analysed. Effort-standardised relative abundance and community metrics (Shannon diversity, Pielou’s evenness) were modelled against sea surface temperature (SST), salinity, dissolved oxygen, chlorophyll-a, zonal current velocity, substrate type, and reef geomorphology using generalised additive models (GAMs). Spatial analyses identified persistent northern-rim aggregation areas aligned with ISRAs. Results: Twenty-eight species (14 sharks, 14 batoids) were recorded, including 23 threatened on the IUCN Red List (4 Critically Endangered, 12 Endangered, 7 Vulnerable). Relative abundance and diversity peaked during the late southwest monsoon (August–September) and declined during the northeast monsoon (December–March). After 2021, diversity and evenness increased while overall abundance declined. Relative abundance was primarily driven by SST, salinity, and current velocity; for sharks, dissolved oxygen and chlorophyll-a were additionally significant, whereas batoid abundance was driven mainly by temperature, oxygen, and current velocity. Four persistent hotspots along the northern atoll rim were identified, with sharks concentrated along exposed slopes and channels, and batoids distributed broadly within lagoonal habitats. Conclusions: Long-term citizen science dive-log monitoring is cost-effective for elasmobranch conservation in remote tropical seascapes. These results show how dive-industry partnerships can inform conservation governance over a decade after sanctuary designation, supporting targeted, habitat-focused management as shark and batoid conservation frameworks continue to evolve. Full article

The rapid development of high-density cities has triggered severe ecological challenges, including habitat fragmentation, urban heat island (UHI) effects, and conflicting demands for public recreation. Traditional ecological networks (ENs) often focus only on “source” landscapes while neglecting degraded “sink” areas. This bias limits the ability of planners to resolve complex spatial conflicts. Therefore, the primary aim of this study is to develop a robust spatial planning framework that mitigates urban ecological conflicts and enhances regional resilience. To achieve this, we constructed a composite ecological network (CEN) for the high-density city of Guangzhou that harmonizes bird habitat conservation, thermal regulation, and cultural recreation. We combined the MaxEnt model, morphological spatial pattern analysis (MSPA), and circuit theory to identify functional “sources” and “sinks” across these three dimensions. Next, using complex network theory, we optimized the CEN and evaluated its structural robustness using low degree addition (LDA) and low betweenness addition (LBA) strategies. The results indicate the following: (1) The CEN effectively captured the complex mosaic landscape of the city. (2) Single-objective networks displayed distinct spatial differences—the recreational network formed a dispersed web of 242 corridors, while habitat and climate networks remained highly clustered. (3) The integrated CEN generated 1137 multi-layered corridors, creating a vital green skeleton to support species dispersal, mitigate UHI effects, and improve cultural access. (4) Optimization simulations verified that the LBA strategy provided the highest stability against targeted attacks by balancing network connectivity with local aggregation. Ultimately, this framework offers a highly adaptable planning tool for dense cities, providing precise spatial guidance to overcome ecological bottlenecks and harmonize urban growth with ecosystem resilience. Full article

In the context of urban regeneration, identifying the nonlinear and interactive effects of the built environment on commercial vitality is essential for targeted spatial improvement. Using Xi’an’s central urban area as a case study, this study integrated multi-source data, including POI, AOI, street-view imagery, and mobile phone signaling data, to delineate commercial spaces via kernel density analysis. With actual service population density as the vitality indicator, a built-environment framework was constructed using 14 indicators across four dimensions: transport accessibility, functional diversity, street quality, and environmental capacity. Random forest regression and SHAP-based interpretable machine learning were employed to examine factor importance, nonlinear thresholds, and interactions. Results show that environmental capacity and transport accessibility are the dominant dimensions, with building density, road network density, and employment density contributing most. Built-environment variables generally exhibit nonlinear threshold effects; key thresholds include road network density > 8 km/km², building density > 40%, functional mix > 4.5, and sky view factor around 40%. Interactions involving building density are most pronounced, and its positive effect is significantly amplified under higher accessibility or employment density. These findings suggest prioritizing road network optimization and building coverage, while balancing functional mix and spatial scale in commercial space regeneration. Full article

Disentangling the coupled, nonlinear impacts of climate change and anthropogenic activities on vegetation dynamics is critical yet challenging for global change research. The Qinghai–Tibetan Plateau (QTP), a highly climate-sensitive and ecologically strategic region, serves as a vital arena for examining such complex socio-ecological attributions. Based on multi-source environmental datasets from 2000 to 2020, this study developed an integrated, spatially explicit framework coupling residual trend analysis (RESTREND) and GeoDetector to quantify individual drivers and nonlinear climate–human interactions. The QTP exhibited a significant, widespread greening trend during 2000–2020, featuring prominent spatial clustering with “High–High” clusters in the southeast and “Low–Low” clusters in the northwest. Attribution modeling revealed that vegetation dynamics were governed not by isolated variables, but by multifaceted, nonlinear synergies among precipitation, temperature, topography, vegetation type, and land-use change. Key interactive pairs, particularly elevation–temperature and slope–precipitation, dramatically increased explanatory power over single-factor models. Crucially, climate–human synergies explained substantially more variance than climate variables alone, bounded by a distinct elevational threshold: human activities dominated vegetation dynamics at mid-elevations (2500–3500 m), while climate factors took over as the primary controller at high altitudes (above 3500 m). Quantitatively, human activities induced vegetation improvement across 38.6% of the plateau, maintained stability in 35.8%, and caused degradation in 25.6%. By successfully merging trend decomposition with spatial stratified heterogeneity analysis, this study provides a transferable approach to uncoupling complex environmental interactions. These insights highlight the intensifying human footprint on alpine ecosystems and advocate for zone-specific adaptive management: mitigating human disturbances at mid-elevations and fostering climate adaptation in higher zones to preserve plateau resilience. Full article

Building inclusive, high-density cities requires understanding vulnerable groups’ public space usage. While green exposure significantly impacts urban health, existing research frequently overlooks females’ specific needs regarding streetscape visual quality, green space structures, and daily travel experiences. To address this, the study investigates spatial disparities in Suzhou’s historic district. Utilizing multi-source data and mixed modeling strategies, including Partial Least Squares and Ordinary Least Squares (PLS-OLS) and eXtreme Gradient Boosting (XGBoost), the research analyzes how streetscape perceptions and green space characteristics affect female life satisfaction and expressed sentiment. Results indicate three main findings. (1) Streetscape visual features fundamentally drive subjective evaluations. Safe significantly enhances well-being, whereas boring and lively negatively impact life satisfaction, reflecting females’ acute sensitivity to environmental oppressiveness during daily travel. (2) Park diversity elevates expressed sentiment, while patch density positively influences life satisfaction, demonstrating the vital value of fragmented greenery for daily public space usage. (3) Boring precipitously diminishes life satisfaction after surpassing a specific threshold, while park diversity elevates expressed sentiment only after crossing a critical interval. The study establishes an integrated analytical framework linking visual perception, green space structure, emotional response, and satisfaction. These findings provide targeted strategies for enhancing inclusive urban design and optimizing green space allocation to improve streetscape safety and alleviate visual oppressiveness, thereby advancing gender social justice for vulnerable groups in historic districts. Full article

Urban vitality is regarded as a cornerstone of sustainable urban development. While land use mix (LUM) is widely acknowledged for fostering vitality, most empirical evidence relies on mean-effect models, neglecting the heterogeneous impacts across different vitality levels. This overlooks the complex, context-dependent nature of LUM and risks perpetuating one-size-fits-all planning. Based on a theoretical framework that links LUM analysis with contemporary urban revitalization, public governance, and smart city development discussions, this study leverages a Spatial Durbin Quantile Regression (SDQR) framework with multi-source geospatial data from 511 blocks in Ningbo, China, to systematically investigate the distributional heterogeneity of LUM’s effects on urban vitality. We decompose LUM into “diversity”, “proximity”, and “coordination” dimensions, revealing three distinct mechanisms across the vitality spectrum. Results show “coordination” acts as a fundamental “ignite” mechanism, consistently driving vitality across all quantiles, especially in new towns and low-vitality areas. “Diversity” primarily serves as a “boost” mechanism, enhancing vitality in medium-to-high vitality areas, demonstrating a non-linear, conditional effect. Crucially, “proximity” exhibits a novel “cap & siphon” mechanism: its direct effect is often insignificant or negative in low-vitality areas (suggesting structural mismatch), while its significant negative spatial spillover effect (siphon effect) across all quantiles, particularly in low-vitality zones, highlights intense inter-area competition. Furthermore, LUM’s direct effects tend to diminish in high-vitality areas, indicating a saturation or “cap” effect. By revealing these heterogeneous impacts and spatial spillover dynamics, this research refines the boundary conditions of classic mixed-use propositions and provides a differentiated planning paradigm, moving from universal zoning to context-specific, stage-calibrated interventions that address areas based on their current vitality levels, spatial interactions and governance contexts. Full article

The seamless integration of real-time operational technology (OT) with big data architectures remains a critical bottleneck in developing robust robotic Digital Twins. Furthermore, evaluating stochastic motion planners strictly within pristine simulations obscures vital real-world challenges such as sensor noise, communication latency, and mechanical stress. This study presents a high-throughput, real-time Hardware-in-the-Loop (HIL) pipeline integrating ROS 2, Apache Kafka, and Functional Mock-up Units (FMUs). Using a UR10e manipulator in a constrained industrial environment, we conducted extensive physical benchmarking of 11 Open Motion Planning Library (OMPL) algorithms across 10 repetitions, generating a comprehensive dataset of 785,192 samples. The proposed IT/OT architecture achieved deterministic millisecond-level synchronization, bounding end-to-end communication latency between 0.09 and 15.51 ms. Physical executions revealed a macroscopic “topological divergence” between simulation and reality, with spatial deviations peaking at 457.65 mm due to real-world point-cloud noise. While algorithms like EST and KPIECE demonstrated optimal geometric efficiency (e.g., a mean path length of 14.57 m) and hardware-friendly dynamics, traditional planners like RRT generated severe inertial spikes of up to 100 N, demonstrating substantial unsuitability for continuous industrial deployment. The primary contribution is a methodologically novel, rigorously validated big data pipeline and the release of an open-source, 50 Hz multimodal dataset (spatial, temporal, and dynamic forces), bridging the sim-to-real gap and providing a foundational benchmark for future data-driven robotic applications. Full article

This study evaluates the multi-year taxonomic diversity and functional structure of beetle assemblages (Coleoptera) within Sub Arini Park, a historic urban green space in Sibiu, Romania. Following a preliminary baseline and methodological calibration phase in 2023, systematic monitoring was conducted during the 2024 and 2025 seasonal cycles utilizing standardized pitfall trapping across diverse park zones. We explicitly tested two hypotheses: (H1) that long-standing historic park management preserves a resilient and functional insect community structure, and (H2) that local spatial heterogeneity and microhabitat variations significantly drive species distribution. A total of 14,843 individuals belonging to 39 species were analyzed. While total abundance exhibited a slight decrease from 2024 (N = 7112) to 2025 (N = 6551), true diversity metrics (Hill numbers) revealed a significant increase in raw species richness (q = 0) from 30 to 39 species, alongside an enhanced equity of frequent species (Shannon diversity, q = 1, increased from 4.26 to 5.12). Functional guild analysis and multivariate PCA demonstrated a highly structured biocenotic distribution; specialist and hygrophilous species (e.g., Carabus variolosus Fabricius, 1787) were strictly constrained to high-humidity riparian corridors, whereas thermophilous generalists dominated open lawns under high anthropogenic stress. Our spatial analysis identified critical degradation within these heavily managed zones, specifically driven by intensive mowing, soil compaction, and organic debris removal. These findings confirm both hypotheses, revealing that the park operates as a heterogeneous mosaic of ecological refugia rather than a uniform habitat block. Crucially, this study provides a concrete, quantitative basis—derived from empirical thresholds of species richness, abundance shifts, and mapped microhabitat preferences—for implementing nature-based management strategies (such as establishing buffer zones with reduced mowing frequencies, limiting trampling, and retaining coarse woody debris) aimed at mitigating urban biodiversity loss and maintaining vital biological pest control services in Central–Eastern Europe. Full article

Bacterial communities play vital roles in coastal biogeochemical cycling and ecological stability. Despite their importance, a significant knowledge gap exists regarding their spatiotemporal dynamics and assembly mechanisms in the tropical coastal waters of the Leizhou Peninsula, China. To investigate the bacterial community structure, co-occurrence networks, and assembly processes, we conducted 16S rRNA gene amplicon sequencing on water samples collected seasonally from August 2022 to June 2023. The bacterial communities were dominated by Proteobacteria and Cyanobacteria, and were characterized by a distinct warm-season peak in the relative of Cyanobium. Alpha diversity indices exhibited significant seasonal fluctuations, reaching a minimum in August (autumn) and a maximum in December (winter). These variations were strongly regulated by water temperature and phosphate availability. Redundancy analysis (RDA) identified salinity as the primary deterministic factor shaping community composition. Seasonal environmental heterogeneity, rather than spatial variation, primarily governed bacterial community dynamics. We also observed a seasonal succession in community assembly mechanisms with deterministic filtering dominated in autumn, whereas stochastic processes prevailed in other seasons. Predicted functional profiles indicated a stable core metabolism, although local anthropogenic inputs stimulated specific metabolic adaptations in industrial and aquaculture zones. Our findings reveal that seasonal environmental filtering (especially temperature and salinity) and a shifting balance between stochastic and deterministic assembly processes govern bacterial dynamics in this tropical coastal ecosystem, with anthropogenic inputs modulating local metabolic functions. This study provides fundamental insights into the mechanisms maintaining microbial diversity and stability in tropical coastal waters facing seasonal and human pressures. Full article

Introduction: The Cananéia–Iguape Lagoon Complex, part of the Lagamar Mosaic of Conservation Units, comprises interconnected ecosystems that facilitate the dispersal and exchange of larvae, juveniles, and adults across habitats. This connectivity is a vital ecological process, driving the demographic linkage of local populations. Due to its commercial importance and abundance, the fat snook (Centropomus parallelus) serves as an ideal model for connectivity studies in this region. This study evaluated the otolith fingerprints of fat snook nursery areas within an estuarine complex using elemental chemical signatures. Methodology: Otoliths from 24 juveniles (n = 6 per site) were sampled across four nurseries: Ariri (AR), Itapanhapima (IT), Subauma (SU), and Iguape (IG). Multi-elemental signatures (Na, Mg, P, K, Ca, Mn, Sr, Ba, and Pb) at the otolith edge were measured via Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS). Results: Multivariate analysis (PERMANOVA, p < 0.05) revealed significant chemical differences between nurseries, corroborated by pairwise tests. Canonical Analysis of Principal Coordinates (CAP) with leave-one-out cross-validation successfully assigned individuals to their collection sites with accuracies of 55% (AR), 72% (IT), 94% (SU), and 88% (IG), achieving a 78% global reclassification rate. CAP results distinguished two primary groups: the southern nurseries (AR/IT) and northern nurseries (SU/IG). This spatial separation was primarily driven by Sr:Ca and Ba:Ca ratios, reflecting the higher marine influence in the south versus freshwater input from the Ribeira de Iguape River in the north. Conclusions: These findings provide critical data to support public policies for the conservation of coastal ecosystems and the management of associated fish stocks. Full article

Utilizing underwater vehicles for hydropower infrastructure inspection is increasingly vital. However, these GNSS-denied and confined environments pose significant navigation challenges: Inertial Navigation Systems (INSs) suffer cumulative drift, Doppler Velocity Logs (DVLs) face acoustic blind zones near walls, and visual navigation frequently fails in highly turbid waters. To address these issues, this paper proposes a tightly coupled multi-source (INS/acoustic/optical/vision) navigation algorithm leveraging prior wall geometry constraints. Developed within an Error-State Kalman Filter (ESKF) framework, the model seamlessly accommodates sensor spatiotemporal heterogeneity. To overcome optical failures, a structural surface constraint model is innovatively constructed using single-beam sonar ranging. The core contribution involves transforming sonar ranging data into 6-DOF spatial pose constraints based on the dam’s planar characteristics, effectively bounding the localization drift perpendicular to the surface. Field experiments at the hydropower station dam demonstrate that under extreme conditions with total visual failure, the proposed algorithm effectively constrains critical motion degrees of freedom. By maintaining the wall-tracking error within 0.08 m (Root Mean Square Error, RMSE)—which effectively represents the relative localization error given the known absolute position of the structural wall—this method significantly enhances the operational robustness and precision of close-wall inspections in extreme underwater environments. Full article

Exploring the interaction relationship among multiple ecosystem services is vital for maintaining ecosystem function. However, traditional approaches are limited in their ability to: (i) characterize complex interactions and (ii) visualize the spatial connectivity of various ecosystem services delivered by social–ecological systems. To address these challenges, a framework for constructing spatial networks of multiple ecosystem services was proposed. The framework is implemented by: (i) estimating the spatial distribution of multiple ecosystem services using the InVEST model, and (ii) generating network nodes and edges with geographical attributes based on the minimum cumulative resistance model and a multiresolution segmentation method. We conducted a case study in the Guangdong–Hong Kong–Macao Greater Bay Area and examined the topological features of the spatial networks using complex network indicators. For each network, winding and multiple edges connected adjacent nodes and formed continuous linkages across the entire study area, indicating that the proposed framework is feasible for capturing the spatial connectivity of multiple ecosystem services. The different ecosystem service networks exhibited conspicuous spatial heterogeneity and generally maintained relatively high connectivity, as evidenced by their tree-like structure with winding pathways and the distribution of multi-edge nodes, indicating that each ES was predominantly connected with multiple other ecosystem services. Meanwhile, nodes with high values of degree centrality and clustering coefficient were mainly concentrated in coastal and mountainous regions. This study advances the representation of complex interactions among multiple ecosystem services from a spatial perspective, thereby facilitating a deeper understanding of the interaction mechanisms underlying ecosystem functioning. Full article

Worldwide, flash floods are among the most unpredictable and hazardous hydrological phenomena, particularly in arid and semi-arid regions such as the Kingdom of Saudi Arabia, where sudden heavy rainfall follows prolonged periods of drought. This work presents an effective integrated model for flood hazard evaluation in the Hanefah Catchment, a socioeconomically vital area in the central part of Saudi Arabia that includes the capital city, Riyadh. Using high-resolution ALOS PALSAR 12.5 m Digital Elevation Model spatial data, we extracted and investigated indicative linear, areal, and relief morphometric keys of 64 sub-catchments. This paper employs a dual-method concept that integrates a multi-criteria ranking method and the El-Shamy approach in conjunction with morphotectonic analysis to model flood-susceptibility zones. Furthermore, this paper suggests a comparative assessment of low-cost morphometric models under data-scarce conditions, assessing the multi-criteria ranking method against El-Shamy’s approach, using the topographic position index (TPI) as an internal terrain scale benchmark. The ranking method successfully assigned 85.7% of the historically recorded flood locations to the high-hazard zone that covers ~24.22% of the Hanefah catchment. In contrast, the El-Shamy approach systematically underestimated flood susceptibility because regional tectonic activity increases bifurcation ratios, resulting in just ~42.9% of the historical floods being assigned to the high-hazard zone. The final results highlight the northern and northwestern parts of the catchment as high-hazard zones, characterized by high drainage density and steep relief. This study provides a refined, cost-effective model that aligns with the strategic objectives of Saudi Vision 2030 for sustainable water resources management and significant urban development. Full article

Urban ethnic enclaves are historically layered cultural landscapes whose public signage encodes community vitality, power relations, and cultural identity in ways that conventional land-use inventories cannot capture. Addressing the absence of scalable, longitudinal computational methods for monitoring such at-risk landscapes, this study develops a reproducible digital-mapping pipeline that operationalises linguistic-landscape analysis as a cultural-heritage monitoring tool for heritage-sensitive land-use planning. Taking Daerim-dong—Seoul’s primary Joseonjok (Korean Chinese) enclave—as a case, we process 38,640 Kakao Map Road View images across 17 annual cross-sections (2008–2024). The pipeline integrates four methodological components: a bounded Spatial Weighting Correction that adjusts for uneven historical coverage; zero-shot semantic sign-function classification using the Qwen2-7B-Instruct model; an exploratory Difference-in-Differences design probing the 2016–2017 THAAD geopolitical disruption; and a Boundary Permeability Ratio (BPR) for tracking enclave edge dynamics. The results document a three-phase trajectory—rapid bilingual expansion (2008–2016), stabilisation (2016–2019), and a COVID-period contraction (2019–2024)—and show that raw sign-count metrics can systematically overstate minority-language decline during economic crises once crisis-period signage is isolated. The BPR is presented as a candidate leading indicator of enclave contraction whose operational thresholds remain to be calibrated through multi-enclave validation. As a methodological proof-of-concept, the study illustrates how computational street-view analysis can support cultural-landscape governance, offering urban planners and heritage managers an actionable, transparent baseline for monitoring at-risk multicultural urban landscapes. Full article