Search Results (236)

It is important to understand the ecological information of Metapenaeopsis dalei to better conserve and manage the stocks in Asia. In this study, we employed research vessels to collect the field data including biomass and number of M. dalei in each survey stations along with environmental data including depth, water temperature, and salinity from November 2018 to September 2019 in the region of 26.50–35.00° N and 120.00–127.00° E in the southern Yellow and East China Seas of China. We found that the annual mean catch per unit effort of weight and number (CPUE_w and CPUE_n) was 15,235.89 g∙h⁻¹ and 17,319.13 ind∙h⁻¹, respectively. Metapenaeopsis dalei was found in 10–130 m. The greatest biomass occurred at 10–20 m in spring, 30–40 m in summer, 10–100 m in autumn, and 10–40 m in winter. The greatest abundance occurred at sea bottom temperature (SBT) 14–15 °C in spring, 19 °C in summer, 15–20 °C in autumn, and 10–12 °C in winter. The greatest abundance occurred at sea bottom salinity (SBS) 32–33 in spring, 32 in summer, 32–35 in autumn, and 31–32 in winter. We found the lowest SBT of M. dalei at 10–11 °C in spring and summer. The juveniles were found at SBT 21 °C and SBS 34 in autumn. The total CPUE_w and CPUE_n rankings were winter > spring > autumn > summer, and the mean average individual weight (AIW) ranking was summer > spring > winter > autumn. Fishing grounds of Haizhou Bay–Lvsi and Zhoushan–Yushan may be the spawning grounds for M. dalei. These findings can benefit fishery management action and planning in the future. Full article

Coastal environments are fragile ecosystems threatened by various factors, both natural and anthropogenic. The preservation and protection of these environments, and in particular, the sand dune systems, which contribute significantly to the defense of the inland from flooding, require continuous monitoring. To this end, high-resolution and high-precision multitemporal data acquired with various techniques can be used, such as, among other things, the global navigation satellite system (GNSS) using the network real-time kinematic (NRTK) approach to acquire 3D points, UAS-based structure-from-motion photogrammetry (SfM), terrestrial laser scanning (TLS), and handheld mobile laser scanning (HMLS)-based light detection and ranging (LiDAR). These techniques were used in this work for the 3D survey of a portion of vegetated sand dunes in the Caleri area (Po River Delta, northern Italy) to assess their applicability in complex environments such as coastal vegetated dune systems. Aerial-based and ground-based acquisitions allowed us to produce point clouds, georeferenced using common ground control points (GCPs), measured both with the GNSS NRTK method and the total station technique. The 3D data were compared to each other to evaluate the accuracy and performance of the different techniques. The results provided good agreement between the different point clouds, as the standard deviations of the differences were lower than 9.3 cm. The GNSS NRTK technique, used with the kinematic approach, allowed for the acquisition of the bare-ground surface but at a cost of lower resolution. On the other hand, the HMLS represented the poorest ability in the penetration of vegetation, providing 3D points with the highest elevation value. UAS-based and TLS-based point clouds provided similar average values, with significant differences only in dense vegetation caused by a very different platform of acquisition and point of view. Full article

Rapid adoption of digital surveying technologies in construction has highlighted the need for engineering education to equip students with technological competency as well as higher-order problem-solving skills. This experiment explores undergraduate students’ acceptance of emerging surveying technologies and their perceived learning results within a constructivist framework of experiential learning. Thirty-six students in a required construction surveying class interacted with traditional and advanced technologies such as total stations, terrestrial laser scanning, drones, and mobile LiDAR through structured, semi-structured, and unstructured lab activities. Data were gathered based on two post-course surveys: a technology acceptance survey grounded in Unified Theory of Acceptance and Use of Technology (UTAUT) and a self-perceived cognitive learning outcome survey through Bloom’s Taxonomy. Qualitative analysis along with quantitative analysis indicated a gap between technology acceptance and perceived learning gains. Laser scanner had the greatest acceptance scores followed by other advanced tools. Total station (widespread in hands-on lab activities) was perceived to have been most influential in terms of enhancing learning. Lower-order skills were strengthened in structured labs, while higher-order thinking emerged more unevenly in open-ended labs. These findings underscore that the mode of student engagement with technology matters more for learning than the sophistication of the tools themselves. By embedding UTAUT and Bloom’s Taxonomy in an authentic learning environment, this experiment provides engineering educators a mechanism to assess technology-enhanced learning and identifies strategies to facilitate higher-order skills aligned with industry needs. Full article

To investigate the seasonal dynamics of phytoplankton community structure and its relationship with environmental factors in the coastal waters of the Leizhou Peninsula, China, surveys were conducted at 21 stations during four seasonal cruises: autumn (August 2022), winter (December 2022), spring (March 2023), and summer (June 2023). A total of 174 phytoplankton species from 7 phyla were identified. Species richness peaked in summer (93 species, 5 phyla), followed by winter (80 species, 3 phyla), spring (79 species, 5 phyla), and autumn (75 species, 5 phyla). Bacillariophyta dominated throughout the year, with Skeletonema costatum (Greville) Cleve 1878 and Chaetoceros lorenzianus Grunow 1863 being consistently dominant across all seasons. Phytoplankton cell density showed a distinct seasonal pattern, highest in autumn, followed by summer, and lower in spring and winter. Diversity indices (H, J, D) indicated moderately to heavily polluted waters. Redundancy analysis identified salinity, dissolved inorganic nitrogen, chlorophyll a (Chl a), pH, water temperature, chemical oxygen demand, and dissolved silicon as key environmental drivers, with their influence varying seasonally: salinity was strongest in summer, Chl a in winter, and multiple factors jointly shaped the community in spring and autumn. This study provides a comprehensive assessment of phytoplankton biodiversity and clarifies the environmental drivers of their distribution in the coastal waters of the Leizhou Peninsula, China. Full article

Knowledge of Algeria’s orchid flora has increased considerably over the past two decades; however, certain regions, such as Guelma Province in northeastern Algeria, remain poorly studied. Between 2013 and 2024, survey work was conducted in this region using a subjective sampling approach. A total of 40 stations were inventoried, and ecological variables such as altitude, exposure, and vegetation cover were recorded to interpret the distribution patterns of orchid taxa. In total, 37 taxa including 16 species, 19 subspecies and 2 hybrids were identified, with a predominance of the genus Ophrys (19 taxa). Among these, ten taxa exhibit a close endemic relationship with neighboring North African territories, and 22 are classified as rare in Algeria. Several taxa also appear as widespread and abundant, enriching the known orchid flora of the study area. Multivariate analyses revealed site typologies and environmental variables influencing the distribution of the recorded species. Cluster analysis identified five distinct Operational Biogeographical Units (OBUs), corresponding to specific environmental characteristics and orchid physiognomies. Furthermore, correlations between the studied taxa and environmental factors suggest that their occurrence is strongly influenced by these variables. Given the high vulnerability of the surveyed sites and the increasing anthropogenic pressures they face, the implementation of urgent conservation measures to protect these habitats and their components is strongly recommended. Full article

The first extensive Bus Rapid Transit (BRT) system in the Philippines, the EDSA Busway, was put into place as a result of Metro Manila’s ongoing traffic congestion. This study uses an integrated framework that combines cost–benefit analysis (CBA), commuter perception survey, and traffic simulation to assess its economic, social, and environmental implications. The operational viability and traffic impact of the planned Magallanes BRT station were evaluated through simulation using PTV VISSIM. A total of 385 commuters participated in a survey measuring their impressions of safety, accessibility, and satisfaction using a four-point Likert scale. The Busway’s excellent economic feasibility was confirmed by the CBA results, which showed a Benefit–Cost Ratio (BCR) of 15.38 and a Net Present Value (NPV) of ₱778.64 billion. Results from the simulation showed a 24% decrease in PM₂ emissions, a 75% increase in throughput, and a 64% reduction in bus trip time. According to survey results, 61% of commuters said accessibility had improved and 62% said travel satisfaction had increased. The study supports the EDSA Busway’s status as a feasible model for future BRT expansion in Metro Manila and other emerging metropolitan regions by showing how it greatly improves environmental sustainability and mobility efficiency. Full article

In forest resource plot surveys, tree relative positioning is a crucial task with profound silvicultural and ecological significance. However, traditional methods such as compasses and total stations suffer from low efficiency, high costs, or poor environmental adaptability, while single-sensor technologies (e.g., UWB or IMU) struggle to balance accuracy and stability in complex forest environments. To address these challenges, this study designed a multi-sensor fusion-based tree positioning device. By integrating the high-precision ranging capability of Ultra-Wideband (UWB) with the dynamic motion perception advantages of an Inertial Measurement Unit (IMU), a dynamic weight fusion algorithm was proposed, effectively mitigating UWB static errors and IMU cumulative errors. Experimental results demonstrate that the device achieves system biases of −1.54 cm (X-axis) and 1.27 cm (Y-axis), with root mean square errors (RMSE) of 21.34 cm and 23.93 cm, respectively, across eight test plots. The average linear distance error was 26.23 cm. Furthermore, in single-operator mode, the average measurement time per tree was only 20.89 s, approximately three times faster than traditional tape measurements. This study confirms that the proposed device offers high positioning accuracy and practical utility in complex forest environments, providing efficient and reliable technical support for forest resource surveys. Full article

To investigate the impact of PV power station construction on insect community diversity in the desert steppe of Ningxia and its response to environmental factors, insect communities were surveyed in different areas within the PV station (both under and between PV panels) and outside the station. The species composition, diversity differences, and responses to environmental factors of insect communities in these areas were analyzed. The results showed that a total of 19,833 insect specimens, belonging to 68 species and 23 families, were collected across different areas of the PV station. The dominant species within the PV station (both under and between PV panels) were Labidura riparia japonica (Dermaptera: Labiduridae), Harpalus sinicus (Coleoptera: Carabidae) and Harpalus calceatus (Coleoptera: Carabidae), while outside the station, the dominant species were L. r. japonica, H. sinicus, H. calceatus and Harpalus pallidipennis (Coleoptera: Carabidae). The number of species by feeding habit ranked as follows: phytophagous insects > predatory insects, whereas the abundance of individuals followed the order: predatory insects > phytophagous insects. The species richness, abundance, Margalef richness index, Shannon–Wiener index and Pielou evenness index of phytophagous insects were significantly higher outside the PV power station than inside (both under and between PV panels). In contrast, Simpson dominance index was significantly lower outside the PV power station compared to inside (both under and between PV panels). For predatory insects, no significant differences were observed in species richness, Margalef richness index, Shannon–Wiener diversity index, Simpson dominance index, or Pielou evenness index among different PV panel areas. However, the abundance of predatory insects was significantly higher outside the PV power station than inside (both under and between PV panels); phytophagous insects in the PV station were primarily positively driven by soil nutrients (total nitrogen, available potassium), whereas predatory insect diversity was more responsive to soil organic matter and nitrogen levels. Both predatory and phytophagous insects showed a significant negative correlation with vegetation height. This study holds significant importance for exploring biodiversity conservation within PV power stations, providing a scientific basis for the planning, design, and implementation of ecological protection measures during the operation of PV station in Ningxia’s desert steppe. Full article

Numerous studies have been conducted on the benthic stages of Medusozoa in Reunion Island, but none on the pelagic stages. This study is the first to investigate the shallow waters of the island for the diversity, abundance, and spatio-temporal distribution of jellyfish. During a one-year survey, samples were collected with a plankton net weekly or biweekly at four sites (two reef/two non-reef) and two depths (10/50 m). Of the 267 samples, 3450 medusae were sorted and 56 species identified. The meroplanktonic Hydroidolina (Antho- and Leptomedusae) were the most diverse (38 species), while the holoplanktonic Trachylinae (13 species) were the most abundant. Hydromedusa species richness was higher at coastal stations than offshore, but similar between reef and non-reef sites. There was no significant variation in species richness or abundance between months or seasons. Including some other catches, the total number of species reached 62. Eight species are new records for the Indian Ocean (all Anthomedusae). Indian Ocean literature references are given in the species list, and some photographs are provided. This initial study, which greatly expands the local hydrozoan fauna knowledge, will serve as a reference for future research, especially regarding climate change and coastal management in Reunion Island. Full article

Accurate mapping of small water structures and streambeds is essential for hydrological modeling, erosion control, and landscape management. While traditional geodetic methods such as GNSS and total stations provide high precision, they are time-consuming and require specialized equipment. Recent advances in mobile technology, particularly smartphones equipped with LiDAR sensors, offer a potential alternative for rapid and cost-effective field data collection. This study assesses the accuracy of the iPhone 14 Pro’s built-in LiDAR sensor for mapping streambeds and retention structures in challenging terrain. The test site was the Dílský stream in the Oslavany cadastral area, characterized by steep slopes, rocky surfaces, and dense vegetation. The stream channel and water structures were first surveyed using GNSS and a total station and subsequently re-measured with the iPhone. Several scanning workflows were tested to evaluate field applicability. Results show that the iPhone LiDAR sensor can capture landscape features with useful accuracy when supported by reference points spaced every 20 m, achieving a vertical RMSE of 0.16 m. Retention structures were mapped with an average positional error of 7%, with deviations of up to 0.20 m in complex or vegetated areas. The findings highlight the potential of smartphone LiDAR for rapid, small-scale mapping, while acknowledging its limitations in rugged environments. Full article

This study evaluates the positional accuracy of Global Navigation Satellite Systems (GNSS) and Unmanned Aerial vehicle (UAV)-based LiDAR systems in terrain modeling, using a total station as a reference. The research was conducted over 17 Ground Control Points (GCPs), with measurements obtained using a CHCNAV i50 GNSS receiver and a DJI Zenmuse L1 Light Detection and Ranging (LiDAR) sensor mounted on a UAV. Accuracy was assessed for horizontal (X, Y) and vertical (Z) components by comparing the results against total station data. Errors were quantified using statistical metrics such as Mean Absolute Error (MAE), Root Mean Square Error (RMSE), and RMS at 1σ. GNSS exhibited superior horizontal accuracy with an RMS 1σ of 1.1 cm, while LiDAR achieved 1.7 cm. In contrast, GNSS outperformed LiDAR in vertical precision, achieving a 1σ RMS of 6.4 cm compared to 6.6 cm for LiDAR. These findings align with manufacturer specifications and international standards such as those of the American Society for Photogrammetry and Remote Sensing (ASPRS). The results highlight that GNSS is preferable for applications requiring high horizontal precision, while LiDAR is better suited for vertical modeling and terrain analysis. The combination of both systems may offer enhanced results for comprehensive geospatial surveys. Overall, both technologies demonstrated sub-decimetric accuracy suitable for precision agriculture, civil engineering, and environmental monitoring. Full article

Fish stocks and their management are paramount for sustainable fisheries under the ongoing changes in atmosphere–sea interactions. The Aegean Sea, one of the composite seas influenced by different water masses, is characterized by a diverse ecosystem. Small pelagic fish are abundant and tend to form schools that vary in size. One of the most efficient and rapid techniques for sampling fish schools over a large area is the use of acoustic methods. Therefore, an acoustic survey was conducted in the coastal areas along the entire Turkish Aegean waters between June and August 2024, using a scientific quantitative echosounder equipped with a split-beam transducer operating at 206 kHz. During the survey, environmental parameters, including water physics, optics, and bathymetry, were measured at 321 stations. Additionally, satellite data were used to obtain water primary production levels for each sampling month across the entire study area. Using a custom computer algorithm written during the present study in MATLAB (2021a), fish schools were automatically detected to measure various morphological and acoustic features. Through a series of statistical analyses, three optimal clusters, validated with the total silhouette sum of distances (1317.38), were identified, each characterized by specific morphological, acoustic, and environmental variables associated with different areas of the study. School morphology and acoustic properties also varied with bottom depth. Cluster 1 was mostly found in open and relatively deep waters. Cluster 2 appeared in areas impacted by anthropogenic sources. Principal Component Analysis (PCA) revealed that the first component (PCA1) was correlated with school height from the bottom (HFB) and overall school height (SH), followed by minimum depth (MnD), maximum depth (MxD), and volume backscattering strength at the school edge (SvE). The second component (PCA2) was associated with school width (SW) and area (A). Cluster 1 was characterized by schools with large SW and A, and relatively high HFB and SH. Cluster 2 showed low HFB and SH, while Cluster 3 had high MnD and MxD and low SvE. Based on the descriptors for these clusters, each cluster could be attributed to fish species at different life stages inferred based on target strength (TS), namely sardine, horse mackerel, and chub mackerel, distributed along the entire Turkish Aegean coast. Full article

This study examines the impact of recent climatic trends on the preservation of submerged wooden structures at the Gran Carro archaeological site in Lake Bolsena, Italy. Climatic data from the Bolsena Meteorological Station were analysed alongside in situ water quality measurements collected near the archaeological remains at a depth of 4 m. The key parameters included water temperature (Tw), redox potential (Eh), dissolved oxygen (DO), and total dissolved solids (TDS). Trend analyses using the Mann–Kendall test and Sen’s slope revealed significant increases in air and water temperatures, which were strongly correlated. Although precipitation exhibited an upward trend, its negative correlation with temperature suggests greater variability rather than a stable water supply. Despite increased rainfall, lake levels showed a significant decline, likely due to intensified evaporation and water extraction for irrigation. UAV surveys confirmed recent lowering of the lake’s water surface during drought periods. Among the limnological parameters, dissolved oxygen saturation declined significantly, while redox potential increased, indicating shifts toward more anaerobic conditions. These environmental changes could promote the activity of erosive bacteria that degrade submerged wood. Conversely, increased evaporation might also enhance oxygen penetration at depth, potentially activating decay agents such as soft rot fungi and wood-boring bacteria. Overall, the findings suggest that ongoing climatic changes are adversely affecting the preservation of submerged wooden structures, highlighting the need for adaptive management strategies to protect both the lake ecosystem and its archaeological heritage. Full article

Accurate stockpile volume estimation is essential for industries that manage bulk materials across various stages of production. Conventional ground-based methods such as walking wheels, total stations, Global Navigation Satellite Systems (GNSSs), and Terrestrial Laser Scanners (TLSs) have been widely used, but often involve significant safety risks, particularly when accessing hard-to-reach or hazardous areas. Unmanned Aerial Systems (UASs) provide a safer and more efficient alternative for surveying irregularly shaped stockpiles. This study evaluates UAS-based methods for estimating the volume of coal stockpiles at a storage facility near Cadiz, Ohio. Two sensor platforms were deployed: a Freefly Alta X quadcopter equipped with a Real-Time Kinematic (RTK) Light Detection and Ranging (LiDAR, active sensor) and a WingtraOne UAS with Post-Processed Kinematic (PPK) multispectral imaging (optical, passive sensor). Three approaches were compared: (1) LiDAR; (2) Structure-from-Motion (SfM) photogrammetry with a Digital Surface Model (DSM) and Digital Terrain Model (DTM) (SfM–DTM); and (3) an SfM-derived DSM combined with a kriging-interpolated DTM (SfM–intDTM). An automated boundary detection workflow was developed, integrating slope thresholding, Near-Infrared (NIR) spectral filtering, and Canny edge detection. Volume estimates from SfM–DTM and SfM–intDTM closely matched LiDAR-based reference estimates, with Root Mean Square Error (RMSE) values of 147.51 m³ and 146.18 m³, respectively. The SfM–intDTM approach achieved a Mean Absolute Percentage Error (MAPE) of ~2%, indicating strong agreement with LiDAR and improved accuracy compared to prior studies. A sensitivity analysis further highlighted the role of spatial resolution in volume estimation. While RMSE values remained consistent (141–162 m³) and the MAPE below 2.5% for resolutions between 0.06 m and 5 m, accuracy declined at coarser resolutions, with the MAPE rising to 11.76% at 10 m. This emphasizes the need to balance the resolution with the study objectives, geographic extent, and computational costs when selecting elevation data for volume estimation. Overall, UAS-based SfM photogrammetry combined with interpolated DTMs and automated boundary extraction offers a scalable, cost-effective, and accurate approach for stockpile volume estimation. The methodology is well-suited for both the high-precision monitoring of individual stockpiles and broader regional-scale assessments and can be readily adapted to other domains such as quarrying, agricultural storage, and forestry operations. Full article

This study investigates the economic viability of a new composting station dedicated to the recycling of date palm by-products. A field experiential analysis was performed in the Figuig Oasis (Morocco), providing the first evidence on the agronomic quality of the compost. The compost produced from date palm by-product was compared to cattle manure and unamended soil and can be considered as a good-quality amendment, demonstrating its ability to enhance soil fertility. Second, a socio-economic survey was conducted to explore farmers’ perceptions and adoption of sustainable agricultural practices. A total of 201 farmers out of 450 farmers registered in Figuig’s municipal administration were surveyed. In terms of fertilisation, farmers preferred locally produced organic fertiliser when available in order to improve soil organic matter content and reduce dependence on chemical inputs. The selling price for the compost was set at 0.14 EUR/kg to reflect the current market price for compost and the willingness of about 38% of the farmers surveyed to buy it. Third, a detailed cost/benefit analysis was performed, with a breakdown of the station’s operational and investment expenses. This illustrates the minimum scale needed to generate a viable business model. Financial projections show that increasing production capacity from 350 tonnes/year to 3500 tonnes/year reduces unit production costs while increasing profits. As illustrated by the application of the Ecocanvas framework, the socio-economic analysis reveals the potential to generate positive environmental, economic, and social impacts, as the circular approach could be replicable and scalable in similar oases agro ecosystems. Full article