Search Results (1,444)

Accurate and spatially detailed soil information is essential for supporting sustainable land use planning, particularly in data-scarce regions such as Cyprus, where soil degradation risks are intensified by land fragmentation, water scarcity, and climate change pressure. This study aimed to generate national-scale predictive maps of key soil health descriptors by integrating satellite-based indicators with a recently released geo-referenced soil dataset. A machine learning model was applied to estimate a suite of soil properties, including organic carbon, pH, texture fractions, macronutrients, and electrical conductivity. The resulting maps reflect spatial patterns consistent with previous studies focused on Cyprus and provide high resolution insights into degradation processes, such as organic carbon loss, and salinization risk. These outputs provide added value for identifying priority zones for soil conservation and evidence-based land management planning. While predictive uncertainty is greater in areas lacking ground reference data, particularly in the northeastern part of the island, the modeling framework demonstrates strong potential for a national-scale soil health assessment. The outcomes are directly relevant to ongoing soil policy developments, including the forthcoming Soil Monitoring Law, and provide spatial prediction models and indicator maps that support the assessment and mitigation of soil degradation. Full article

Background: Cervicogenic headache (CGH) is a prevalent secondary headache disorder associated with upper cervical spine dysfunction, often involving nociceptive convergence at the trigeminocervical complex. While manual therapy and exercise have demonstrated benefit, autonomic dysregulation may contribute to persistent symptoms. This case report explores the integration of external vagus nerve stimulation (eVNS) into a multimodal physical therapy approach targeting both mechanical and neurophysiological contributors to CGH. Case Description: A 63-year-old female presented with chronic CGH characterized by right-sided suboccipital and supraorbital pain, impaired sleep, and postural dysfunction. Examination revealed a right rotational atlas positional fault, restricted left atlantoaxial (AA) mobility, suboccipital hypertonicity, and reduced deep neck flexor endurance. Initial treatment emphasized manual therapy to restore AA mobility and atlas symmetry, combined with postural correction and neuromuscular training. Intervention: After initial symptom improvement plateaued, eVNS targeting the auricular branch of the vagus nerve was introduced to modulate autonomic tone. The patient used a handheld eVNS device nightly over three weeks. Outcomes: Substantial improvements were observed in the Neck Disability Index (↓77%), Headache Disability Inventory (↓72%), and pain scores (↓100%). Cervical mobility, atlas symmetry, and deep neck flexor endurance improved markedly. The patient reported reduced anxiety, improved sleep, and sustained headache relief at one-month follow-up. Conclusions: This case highlights the potential synergistic benefits of integrating eVNS within a physiotherapy-led CGH management plan. Further research is warranted to explore its role in targeting autonomic imbalance and enhancing conservative treatment outcomes. Full article

Landslides pose persistent threats to mountainous regions in Taiwan, particularly in areas such as Nanfeng Village, Nantou County, where steep terrain and concentrated rainfall contribute to chronic slope instability. This study investigates spatiotemporal patterns of vegetation change as a proxy for identifying potential landslide-prone zones, with a focus on the Tung-An tribal settlement in the eastern part of the village. Using high-resolution satellite imagery from SPOT 6/7 (2013–2023) and Pléiades (2019–2023), we derived annual NDVI layers to monitor vegetation dynamics across the landscape. Long-term vegetation trends were evaluated using the Mann–Kendall test, while spatiotemporal clustering was assessed through Emerging Hot Spot Analysis (EHSA) based on the Getis-Ord Gi* statistic within a space-time cube framework. The results revealed statistically significant NDVI increases in many valley-bottom and mid-slope regions, particularly where natural regeneration or reduced disturbance occurred. However, other valley-bottom zones—especially those affected by recurring debris flows—still exhibited declining or persistently low vegetation. In contrast, persistent low or declining NDVI values were observed along steep slopes and debris-flow-prone channels, such as the Nanshan and Mei Creeks. These zones consistently overlapped with known landslide paths and cold spot clusters, confirming their ecological vulnerability and geomorphic risk. This study demonstrates that integrating NDVI trend analysis with spatiotemporal hot spot classification provides a robust, scalable approach for identifying slope hazard areas in data-scarce mountainous regions. The methodology offers practical insights for ecological monitoring, early warning systems, and disaster risk management in Taiwan and other typhoon-affected environments. By highlighting specific locations where vegetation decline aligns with landslide risk, the findings can guide local authorities in prioritizing slope stabilization, habitat conservation, and land-use planning. Such targeted actions support the Sustainable Development Goals, particularly SDG 11 (Sustainable Cities and Communities), SDG 13 (Climate Action), and SDG 15 (Life on Land), by reducing disaster risk, enhancing community resilience, and promoting the long-term sustainability of mountain ecosystems. Full article

Urban landscapes have given rise to novel ecosystems (e.g., green areas), which differ in design and ecological quality depending on local planning strategies. Europe has the goal to increase conservation through increasing greenspace; however, urban wildlife health impacts, particularly on birds, are poorly studied. This study investigates associations between haemosporidians and intestinal coccidia in the Eurasian Tree Sparrow (Passer montanus), as well as their body condition and immunological status, from five urban green areas in Madrid, Spain, from 2019 to 2022. These green areas differ in green infrastructure, and because these birds are adapted to urban environments, they are a good model to evaluate how green area infrastructure may affect the birds’ health. We detected a 29% prevalence of haemosporidians (Haemoproteus being the most common, followed by Leucocytozoon and Plasmodium) and a 4% prevalence of intestinal coccidia. We found that haemosporidian prevalence was significantly higher in green areas with untreated stagnant water surrounded by muddy areas, ideal conditions for vector reproduction. Therefore, effective management strategies, especially related to water treatment, are essential for protecting urban wildlife and human health. This study provides valuable information for researchers and urban wildlife managers to incorporate appropriate management strategies into urban green area planning to preserve urban biodiversity and protect public health. Full article

Establishing a sustainable framework for remediating environmental degradation caused by historical mining operations in the Sierra Minera of Cartagena-La Unión, southeastern Spain, is a critical imperative. When the reclamation requirements of the post-mining district are considered in the context of its critical location, nested among conflicting land uses, the development of practical solutions to restore ecological and cultural functions emerge as a landscape planning challenge. The greenway approach emphasizes the primary ecological and functional corridors that sustain the vitality of the region; therefore, it is essential to preserve and enhance these critical lifelines. This study aimed to design a localized greenway network to support the conservation of key ecological, agricultural, and cultural resources within the area, while simultaneously promoting reclamation activities in degraded zones. The greenway corridor is built upon key elements: conservation areas, post-mining cultural resources, dry riverbeds, and agricultural zones. In the light of greenway approach, planners and land managers can make their decisions more judiciously by considering the priority zones. The protection, leveraging, and reclamation of significant resources can be provided through a multifunctional greenway approach as seen in the case of Cartagena-La Unión Post-Mining District. Full article

The rapid expansion of urbanization and inadequate planning have triggered a water balance crisis in many cities, manifesting as both the need for artificial lake supplementation and frequent urban flooding. Using the Xuanwu Lake watershed in Nanjing as a case study, this research aims to optimize the Blue–Green Infrastructure (BGI) network to maximize rainfall utilization within the watershed. The ultimate goal is to restore natural water balance processes and reduce reliance on artificial supplementation while mitigating urban flood risks. First, the Soil Conservation Service Curve Number (SCS–CN) model is employed to estimate the maximum potential of natural convergent flow within the watershed. Second, drawing on landscape connectivity theory, a multi-level BGI network optimization model is developed by integrating the Minimum Cumulative Resistance (MCR) model and the gravity model, incorporating both hydrological connectivity and flood safety considerations. Third, a water balance model based on the Storm Water Management Model (SWMM) framework and empirical formulas is constructed and coupled with the network optimization model to simulate and evaluate water budget performance under optimized scenarios. The results indicate that the optimized scheme can reduce artificial supplementation to Xuanwu Lake by 62.2% in June, while also ensuring effective supplementation throughout the year. Annual runoff entering the lake reaches 13.25 million cubic meters, meeting approximately 13% of the current annual supplementation demand. Moreover, under a 100-year return period flood scenario, the optimized network reduces total watershed flood volume by 35% compared to pre-optimization conditions, with flood-prone units experiencing reductions exceeding 50%. These findings underscore the optimized BGI network scheme’s capacity to reallocate rainwater resources efficiently, promoting a transition in urban water governance from an “engineering-dominated” approach to an “ecology-oriented and self-regulating” paradigm. Full article

The Nahuelbuta Mountain Range in the south-central zone of Chile is a biodiversity hotspot that has undergone intense land use/cover transformation. This study analyses two decades of land use change (1999–2018) in the watersheds of the Lebu and Leiva rivers. The magnitude and spatial configuration of these changes were assessed using detailed spatial information, transition matrices, and landscape metrics. The results show that between 1999 and 2018, temperate native forest decreased by 30.3% in Lebu and 22.8% in Leiva, being replaced mainly by exotic forest plantations, which increased by 20.2% and 13.5%, respectively. The spatiotemporal analysis revealed losses concentrated in the lowland and middle zones of both watersheds, with persistence of temperate native forest in higher elevations. Landscape metrics showed an increase in diversity (SIDI: Lebu 0.41–0.65; Leiva 0.29–0.57) and a decrease in aggregation (AI: 92–86%; 95–90%). At the class level, the temperate native forest presented greater fragmentation, with a reduction in size and proximity, an increase in density, and more irregular shapes. In contrast, exotic forest plantations increased in size and proximity, with a slight decrease in density and greater complexity of form, consolidating their expansion and spatial continuity in both watersheds. These findings emphasise the need to implement territorial planning and conservation strategies adapted to the Nahuelbuta context, through native forest management plans that promote ecological conservation, the recovery of degraded landscapes, and the strengthening of ecosystem services, thus contributing to the well-being of local communities and long-term environmental sustainability. Full article

The Ecological Green Heart Area of the Chang–Zhu–Tan Urban Agglomeration in Central China faces increasing forest health threats due to rapid urbanization and land use change. This study assessed the spatiotemporal dynamics and drivers of forest health from 2005 to 2023 using a multi-dimensional framework based on vitality, organizational structure, and anti-interference capacity. A forest health index (FHI) was constructed using multi-source data, and the optimal parameter geographic detector (OPGD) model was applied to identify dominant and interacting factors. The results show the following: (1) FHI declined from 0.62 (2005) to 0.55 (2015) and rebounded to 0.60 (2023). (2) Healthier forests were concentrated in the east and center, with degradation in the west and south; (3) Topography was the leading driver (q = 0.17), followed by climate, while socioeconomic factors gained influence over time. (4) Interactions among factors showed strong nonlinear enhancement. This research demonstrates the effectiveness of the OPGD model in capturing spatial heterogeneity and interaction effects, underscoring the need for differentiated, spatially informed conservation and land management strategies. This research provides scientific support for integrating ecological protection with urban planning, contributing to the broader goals of ecosystem resilience, sustainable land use, and regional sustainability. Full article

Drone power management poses ongoing challenges that significantly impact operational effectiveness across various applications. This research examines path planning optimization, particularly focusing on distance minimization to enhance efficiency and performance. When drones must visit static ground stations, analyzing the constituent elements of flight paths reveals that segments connecting the launch pad to initial and final stations emerge as a distinct area for further path optimization. Given scenarios where launch pad relocation remains feasible, this study proposes several alternative methodologies for adjusting launch positions to minimize total flight distances across multiple drone operations. The investigation employed extensive experimentation involving diverse configurations with varying station counts and available drone units. Results demonstrate that repositioning the launch pad to serve as an optimal center point for all drone routes yields substantial improvements in total distance minimization, ranging from 4% to 22% across different operational scenarios. The geometric median approach consistently outperformed alternative positioning strategies, achieving these improvements while maintaining computational efficiency. These findings contribute to sustainable drone operations by reducing energy consumption through optimized flight planning. The methodology proves particularly valuable for applications requiring flexible launch point positioning, offering practical solutions for enhancing operational efficiency in environmental monitoring, precision agriculture, and infrastructure inspection tasks where energy conservation directly impacts mission success and operational viability. Full article

Background: Pelvic fractures are complex injuries often associated with significant morbidity and mortality, requiring multidisciplinary management. This case series highlights the presentation, management strategies, and outcomes of patients with pelvic fractures treated at our institution. Methods: The medical records of 13 patients diagnosed with pelvic fractures from 1 January 2020 through 31 December 2023 were retrospectively reviewed. Demographic data, mechanism of injury, fracture pattern, associated injuries, treatment modalities, and outcomes were analyzed. Results: A total of 13 patients were included in the study, with ages ranging from 18–95 years. Six of the patients were male and seven were female. The most common mechanisms of injury were falls and pedestrians struck by vehicles. Associated injuries included traumatic brain injury (TBI), fractures including extremities, ribs, and vertebrae, visceral injury, and spinal cord injury. Treatment strategies ranged from conservative, non-surgical management to operative intervention, including interventional radiology embolization, external traction, open reduction and internal fixation (ORIF), and percutaneous screw stabilization. Additional interventions included chest tube placement, exploratory laparotomy, and craniectomy. Two patients died while in the hospital, one was discharged to a shelter, and the remaining 10 were discharged to various inpatient rehab facilities. Conclusions: Pelvic fractures pose significant clinical challenges due to their complexity and associated injuries. This case series underscores the importance of multidisciplinary intervention and treatment strategies in optimizing outcomes. Further studies should focus on the effectiveness of interventions, utilization of new technology, and multidisciplinary team planning. Full article

This study highlights the spatial, seasonal, and climatic variations in bird species richness across Türkiye, a country with rich avian richness situated at the intersection of major migratory routes. Bird species richness was calculated for each province. Differences between regions, Köppen–Geiger climate classes, and seasons were analyzed using the Kruskal–Wallis method. Non-parametric analysis of longitudinal data in factorial experiments was also employed to determine seasonal differences within regions and climate classes. The results revealed significant spatial variations in species richness, particularly between temperate and cold climate regions. While seasonal differences were generally less pronounced, they were critical for both migratory and resident bird species. Wetlands, coastal areas, and transitional habitats were identified as biodiversity hotspots for both resident and migratory birds. This study underscores the need to integrate regional, climatic, and seasonal variations into ecosystem-based management plans. Protecting critical habitats, enhancing connectivity through ecological corridors, and adopting adaptive conservation strategies are essential for sustaining Türkiye’s rich avian diversity. These results provide valuable insights for conservation planning and emphasize the importance of addressing spatial and seasonal dynamics to ensure long-term biodiversity preservation. Full article

Groundwater plays a crucial role in sustaining agriculture and livelihoods in the arid Middle Draa Valley (MDV) of southeastern Morocco. However, increasing groundwater extraction, declining rainfall, and the absence of effective floodwater harvesting systems have led to severe aquifer depletion. This study applies and compares six machine learning (ML) algorithms—decision trees (CART), ensemble methods (random forest, LightGBM, XGBoost), distance-based learning (k-nearest neighbors), and support vector machines—integrating GIS, satellite data, and field observations to delineate zones suitable for groundwater recharge. The results indicate that ensemble tree-based methods yielded the highest predictive accuracy, with LightGBM outperforming the others by achieving an overall accuracy of 0.90. Random forest and XGBoost also demonstrated strong performance, effectively identifying priority areas for artificial recharge, particularly near ephemeral streams. A feature importance analysis revealed that soil permeability, elevation, and stream proximity were the most influential variables in recharge zone delineation. The generated maps provide valuable support for irrigation planning, aquifer conservation, and floodwater management. Overall, the proposed machine learning–geospatial framework offers a robust and transferable approach for mapping groundwater recharge zones (GWRZ) in arid and semi-arid regions, contributing to the achievement of Sustainable Development Goals (SDGs))—notably SDG 6 (Clean Water and Sanitation), by enhancing water-use efficiency and groundwater recharge (Target 6.4), and SDG 13 (Climate Action), by supporting climate-resilient aquifer management. Full article

The Tibetan-Himalayan region, recognized as a global biodiversity hotspot, is increasingly threatened by the dual pressures of climate change and human activities. Understanding the vulnerability of plant species to these forces is crucial for effective ecological conservation in this region. This study employed an improved Climate Niche Factor Analysis (CNFA) framework to assess the vulnerability of six representative alpine endemic herbaceous plants in this ecologically sensitive region under future climate changes. Our results show distinct spatial vulnerability patterns for the six species, with higher vulnerability in the western regions of the Tibetan-Himalayan region and lower vulnerability in the eastern areas. Particularly under high-emission scenarios (SSP5-8.5), climate change is projected to substantially intensify threats to these plant species, reinforcing the imperative for targeted conservation strategies. Additionally, we found that the current coverage of protected areas (PAs) within the species’ habitats was severely insufficient, with less than 25% coverage overall, and it was even lower (<7%) in highly vulnerable regions. Human activity hotspots, such as the regions around Lhasa and Chengdu, further exacerbate species vulnerability. Notably, some species currently classified as least concern (e.g., Stipa purpurea (S. purpurea)) according to the IUCN Red List exhibit higher vulnerability than species listed as near threatened (e.g., Cyananthus microphyllus (C. microphylla)) under future climate change. These findings suggest that existing biodiversity assessments, such as the IUCN Red List, may not adequately account for future climate risks, highlighting the importance of incorporating climate change projections into conservation planning. Our study calls for expanding and optimizing PAs, improving management, and enhancing climate resilience to mitigate biodiversity loss in the face of climate change and human pressures. Full article

We studied Galápagos barn owls on Santa Cruz Island in the Galápagos Archipelago. We collected and analyzed pellets to determine diet composition. Barn-owl diet consisted—in terms of biomass—of ~89% rodents and ~10% insects. Bird remains occurred in 1% of the pellets. Foraging was studied with data loggers, a method not previously applied to the study of Galápagos barn owls. Owls rested during the day in natural and human-built roosts such as lava holes, trees, or huts. Night-time foraging was characterized by periods during which the bird moved and periods during which the bird stayed within one place, with the latter amounting to ~56% of the time away from the day roost. Birds began foraging shortly after sunset and returned to their day roost before sunrise. The duration of foraging was approximately 11 h per night. Foraging areas were small (median value: 0.28 km²). Although our data demonstrate a continued presence of the subspecies, we regard the situation for this subspecies as labile, as multiple threats, such as road kills, poisoning, and intentional killing by farmers, have increased recently, and suggest the development of a management plan to improve its conservation. Full article

Background: Midportion Achilles tendinopathy (Mid-AT) is a complex condition that may be exacerbated by anatomical variations of the plantaris tendon. Recent anatomical studies, particularly the classification proposed by Olewnik et al., have enhanced the understanding of plantaris–Achilles interactions and their clinical implications. Objective: This review aims to assess the anatomical types of the plantaris tendon, their imaging correlates, and the impact of the Olewnik classification on diagnosis, treatment planning, and surgical outcomes in patients with Mid-AT. Methods: We present an evidence-based analysis of the six anatomical types of the plantaris tendon and their relevance to Achilles tendinopathy, with emphasis on MRI and ultrasound (USG) evaluation. A diagnostic and therapeutic algorithm is proposed, and clinical outcomes of both conservative and operative management are compared across tendon types. Results: Types I and V were most strongly associated with symptomatic conflict and showed the highest benefit from surgical resection. Endoscopic approaches were effective in Types II and III, while Type IV typically responded to conservative treatment. Type VI, often misdiagnosed as tarsal tunnel syndrome, required combined neurolysis. The classification significantly improves surgical decision-making, reduces overtreatment, and enhances diagnostic precision. Conclusions: The Olewnik classification provides a reproducible, clinically relevant framework for individualized management of Mid-AT. Its integration into imaging protocols and treatment algorithms may improve therapeutic outcomes and guide future research in orthopaedic tendon pathology. Full article