Search Results (455)

Wildfires have become increasingly frequent and destructive environmental hazards, especially in boreal ecosystems facing prolonged droughts and temperature extremes. This study presents an integrated spatio-temporal framework that combines Spatio-Temporal Density-Based Spatial Clustering of Applications with Noise (ST-DBSCAN), Fire Radiative Power (FRP), and the differenced Normalized Burn Ratio (ΔNBR) to characterize the dynamics and ecological impacts of large-scale wildfires, using the extreme 2023 Quebec fire season as a case study. The analysis of 80,228 VIIRS fire detections resulted in 19 distinct clusters across four fire zones. Validation against the National Burned Area Composite (NBAC) showed high spatial agreement in densely burned areas, with Intersection over Union (IoU) scores reaching 62.6%. Gaussian Process Regression (GPR) revealed significant non-linear relationships between FRP and key fire behavior metrics. Higher mean FRP was associated with both longer durations and greater burn severity. While FRP was also linked to faster spread rates, this relationship varied by zone. Notably, Fire Zone 2 exhibited the most severe ecological impact, with 83.8% of the area classified as high-severity burn. These findings demonstrate the value of integrating spatial clustering, radiative intensity, and post-fire vegetation damage into a unified analytical framework. Unlike traditional methods, this approach enables scalable, hypothesis-driven assessment of fire behavior, supporting improved fire management, ecosystem recovery planning, and climate resilience efforts in fire-prone regions. Full article

Insects exhibit diverse ecological characteristics, but species identification is challenging due to high morphological similarity. Traditional methods require genitalia dissection, which damages specimens and flattens three-dimensional structures, potentially losing key morphological details. In this study, we evaluate the utility of Micro-CT (Computed Tomography) as a non-destructive alternative for species identification by comparing genitalia structures obtained through Micro-CT with those obtained through traditional dissection. Micro-CT enabled three-dimensional reconstructions of male genitalia and aedeagus, providing detailed views from multiple angles without physical damage. The aedeagus was also virtually separated in a digital environment, further enhancing morphological analysis. Using this approach, we identified three new species, Casmara fulvacorona sp. nov. from Sumatra, C. falcatussica sp. nov. and C. fuscatulipa sp. nov. from Taiwan, based on genitalia characteristics. In addition, we provide a checklist of all Casmara Walker, 1863 species reported to date, including these newly described species, to confirm and clarify the distribution of this genus. Our results demonstrate that the additional use of Micro-CT in insect species identification can provide a scientific basis for reviewing and increasing confidence in species identification based on genital dissection. Full article

In recent years, agricultural crops have increasingly been attacked by more destructive insect pests, forcing modern farming to depend mainly on chemical insecticides. Although valuable, their widespread and intensive misuse has raised serious concerns about environmental and public health impacts. RNAi has been proposed as a safer alternative due to its high specificity, adaptability, and low ecological footprint. So far, dsRNA has proven effective in controlling various pest species, either through topical application or via genetically modified plants. Despite advances, large-scale implementation of RNAi remains challenging due to technical and biological hurdles that contribute to inconsistent performance. Key aspects such as dsRNA design, delivery techniques, and cellular uptake mechanisms still require refinement. Additionally, ensuring environmental stability, addressing biosafety concerns, and developing cost-effective production methods are essential for its practical application. In this review, we explore recent advances in the design and implementation of dsRNA, as well as the strategies that could support the successful integration of RNAi technology into pest management programs. Full article

The South Caspian Basin of Iran (SCBI), a vital ecosystem for unique and valuable fish species, is under severe threats due to anthropogenic activities that are rapidly deteriorating its fish biodiversity. The initial step to effectively combat or mitigate threats to biodiversity is to precisely identify these threats. While such threats are often categorized qualitatively, there is a lack of a comparative quantitative assessment of their severity. This means that although we may have a general understanding of the threats, we do not have a clear picture of how serious they are relative to one another. This study aimed to quantify and prioritize these threats using a modified quantitative “SWOT” (Strengths, Weaknesses, Opportunities, Threats) analysis. Twenty multidisciplinary experts identified and evaluated 26 threats, and we used multivariate cluster analysis to categorize them as “High”, “Medium”, and “Low” based on their quantitative contributions to overall threat. Invasive non-native species and global warming emerged as the most significant threats, followed by resource exploitation, habitat destruction, and pollution. We then used this information to develop a “Situation Model” and “Results Chains” to guide responses to the threats. According to the Situation Model, these threats are interconnected, driven by factors such as population growth, unsustainable resource use, and climate change. To address these challenges, we propose the Results Chains, including two strategies focused on scientific research, land-use planning, public awareness, and community engagement. Prioritizing these actions is crucial for conserving the Caspian Sea’s unique fish fauna and ensuring the region’s ecological and economic sustainability. Full article

Coastal wetlands are critical ecosystems that require effective monitoring to support conservation and restoration efforts. This study evaluates the use of small unmanned aerial systems (sUAS) and multispectral imagery to estimate aboveground biomass (AGB) in tidal marshes, comparing models calibrated with destructive versus non-destructive in situ sampling methods. Imagery was collected over South Carolina’s North Inlet-Winyah Bay National Estuarine Research Reserve, and vegetation indices (VIs) were derived from sUAS imagery to model biomass. Stepwise linear regression was used to develop and validate models based on both sampling approaches. Destructive sampling models, particularly those using the Normalized Difference Vegetation Index (NDVI) and Difference Vegetation Index (DVI), achieved the lowest root mean square error (RMSE) values (as low as 70.91 g/m²), indicating higher predictive accuracy. Non-destructive models, while less accurate (minimum RMSE of 214.86 g/m²), demonstrated higher R² values (0.44 and 0.61), suggesting the potential for broader application with further refinement. These findings highlight the trade-offs between ecological impact and model performance, and support the viability of non-destructive methods for biomass estimation in sensitive wetland environments. Future work should explore machine learning approaches and improved temporal alignment of data collection to enhance model robustness. Full article

Pine wilt disease (PWD), a destructive pine forest disease caused by pine wood nematode (PWN), Bursaphelenchus xylophilus, has led to huge economic losses and ecological environment damage. Thaumatin-like proteins (TLPs) are the products of a complex gene family involved in host defense and a wide range of developmental processes in fungi, plants, and animals. In this study, a tlp gene of B. xylophilus (Bxtlp) (GenBank: OQ863020.1) was amplified via PCR and cloned into the expression vector pET-15b to construct the recombinant vector PET-15b-Bxtlp, which was then transformed into Escherichia coli BL-21(DE3). The recombinant protein was successfully purified using Ni-NTA affinity chromatography. The effect of the Bxtlp gene on the vitality and pathogenicity of PWNs was elucidated through RNA interference (RNAi) and overexpression. Bxtlp dsRNA significantly reduced the feeding, motility, spawning, and reproduction abilities of PWN; shortened its lifespan; and increased the female–male ratio. In contrast, the recombinant BxTLP markedly enhanced the reproductive ability of PWN. In addition, Bxtlp dsRNA increased reactive oxygen species (ROS) content in nematodes, while the recombinant BxTLP was confirmed to have antioxidant capacity in vitro. Furthermore, the bioassays on Pinus thunbergii saplings demonstrated that Bxtlp could significantly influence PWN pathogenicity. Overall, we speculate that Bxtlp affects the pathogenicity of PWNs mainly via regulating ROS levels, the motility, and hatching of PWN. Full article

Unmanned Aerial Vehicles (UAVs) have become powerful tools for high-resolution, quantitative remote sensing in ecological and environmental studies. In this study, we present a novel approach to accurately mapping and estimating the biomass of Suaeda salsa using UAV-based visible-light imagery combined with hue angle inversion modeling. By integrating diffuse reflectance standard plates into the flight protocol, we converted RGB pixel values into reflectance and derived hue angle metrics with enhanced radiometric accuracy. A hue angle cutoff threshold of 249.01° was identified as the optimal cutoff to distinguish Suaeda salsa from the surrounding land cover types with high confidence. To estimate biomass, we developed an exponential inversion model based on hue angle data calibrated through extensive field measurements. The resulting model—Biomass = 3.57639 × 10⁻¹⁵ × e^0.12201×α—achieved exceptional performance (R² = 0.99696; MAPE = 3.616%; RMSE = 0.02183 kg/m²), indicating strong predictive accuracy and robustness. This study highlights a cost-effective, non-destructive, and scalable method for the real-time monitoring of coastal vegetation, offering a significant advancement in remote sensing applications for wetland ecosystem management. Full article

Phytopythium vexans is a plant pathogen responsible for a variety of destructive diseases in crops worldwide. This includes patch canker, damping-off, root, and crown rots in economically important crops, such as apple, pear, grapevine, citrus, avocado, and kiwi. The pathogen has a global distribution, and a recent report confirmed its presence in southern Ontario, Canada. This study presents the first genome sequencing, assembly, and annotation of the Canadian P. vexans strain SS21. To explore how variation in secreted protein repertoires may relate to infection strategies and host adaptation, we compared the predicted secretome of SS21 with reference strains from Iran (CBS 119.80) and China (HF1). The analysis revealed that HF1 harbors a larger set of CAZymes, sterol-binding proteins, and predicted effectors, which may suggest broader adaptive potential. In contrast, strain SS21 appears to have adapted to a niche-specific strategy, with fewer necrosis-inducing proteins, glucanase inhibitors, and effectors, possibly indicating adaptation to specific hosts or ecological conditions. Comparative genome data highlight distinct evolutionary trajectories that may have shaped each strain’s infection strategy, with SS21 potentially serving as a robust additional reference for future studies on P. vexans biology and host interactions. While this analysis identifies key candidate effectors, gene expression studies are required to validate their functional roles in infection and host manipulation. Full article

The Tigris-Euphrates basin hosts a diverse assemblage of native aquatic plants vital to the region’s ecological and cultural heritage. However, decades of hydrological alterations, pollution, salinity intrusion, habitat destruction, and climate change have caused significant declines in aquatic plant species diversity. This review compiles historical and contemporary information on key native aquatic plant species, assesses their current conservation status, identifies major threats, and provides recommendations for their protection. Sensitive submerged and floating species, including Vallisneria spiralis, Najas marina, and Potamogeton spp., have been particularly affected, with many now being rare or locally extinct. Although restoration efforts in the Mesopotamian Marshes have partially restored some wetlands, aquatic plant conservation remains largely overlooked. We propose targeted recovery plans, integration of aquatic plants into wetland management, enhancement of water quality measures, and increased cross-border hydrological cooperation. Protecting native aquatic flora is essential for maintaining the ecological integrity and resilience of the Tigris-Euphrates basin. Full article

The mining of shallow coal seam groups triggers mine water inrush and ecological environment destruction. Effective groundwater prevention and control requires controlling the compaction and seepage characteristics (CSCs) of broken rock in goaf. In this study, the CSCs of roof lithology and goaf broken rock combinations are experimentally investigated. The results indicate that, for samples with identical gradation, the percentage of void (PV) is minimized in sandstone–mudstone combinations, while PV increases with higher coal content. Initial compaction of composite samples is primarily governed by soft rock re-crushing, whereas the stable compaction stage is determined by the initial PV. Under low axial stress, the CSCs of lithological combination samples exhibit instability, with the mudstone layer reducing flow velocity by approximately 36% under equivalent compaction and seepage conditions. Particle migration, leading to the blockage of the seepage section, is an important cause of the decrease in permeability. Based on experimental findings, a stress–void–seepage coupling model is established to describe the compaction–seepage behavior of lithologic combination broken rock in shallow goafs. Full article

In the wake of intensifying global Extreme Climate Incidents (ECIs), which have particularly noticeable effects on indigenous populations, integrating value-driven education has become a global imperative. While Education for Sustainable Development (ESD) for SDG 13 climate action has been widely adopted in science and engineering curricula, language and culture programs remain underexplored as venues for transformative sustainability learning in Global Competence (GC). Learners in these fields often demonstrate critical literacy and global awareness, but lack the interdisciplinary tools and strategies to translate values into climate-conscious behavior. This study responds to this gap by incorporating virtual reality (VR) into a modified Global Competence Framework (GCF) in an experiment study within intercultural communication courses (N = 303, VR explorative group = 152, control group = 151). A mixed methodological approach was adopted by evaluating pretest–posttest quantitative data of ESD knowledge, attitudes, behaviors, and qualitative data of critical online reflection. The results demonstrate increase localized ESD knowledge in terms of climate, attitudes, and ecological behaviors in both groups in the lived experience of GCF, yet the VR explorative group showed a greater improvement in knowledge and behavior because of their visualization of the 3D rotation of rarely acquired scientific knowledge in monsoonal movement and the local indigenous village reconstruction after destruction. By localizing the Typhoon Morakot tragedy that devastated Shiaolin Village, the intervention provided a culturally specific and interactive context for ESD concepts, enabling interdisciplinary learners to experience climate injustice firsthand with value-based strategies while critically reflecting on global responsibility and sustainable action. Full article

Dredging is essential for the maintenance of ports, waterways, lakes, and lagoons to ensure their operability and economic value. Over the last few decades, scientists have focused on the significant environmental challenges associated with dredging, including habitat destruction, loss of biodiversity, sediment suspension, and contamination with heavy metals and organic pollutants. The huge loss of sediment in coastal areas and the associated erosion processes are now forcing stakeholders to look ahead and turn potential problems into an opportunity to develop new sediment management strategies, beyond environmental protection, toward ecosystem restoration and coastal resilience. Moreover, the European and Italian strategies, such as the European Green Deal (EGD) and the Italian Ecological Transition Plan (PTE), highlight the need to reuse dredge sediment in circular economy strategies, transforming them into valuable resources for construction, agriculture, and environmental restoration projects. European legislation on dredging is fundamental to the issue of management and priorities of dredged materials, but the implementation rules are deferred to individual member states. In Italy, the Ministerial Decree 173/2016 covers the main aspects of dredge activities and dredge sediment management. Moreover, it encourages the remediation and reuse of the dredge sediment. This study starts with a comprehensive analysis of the innovative remediation techniques that minimize impacts and promote sustainable, beneficial sediment management. Different remediation methods, such as electrochemical treatments, chemical stabilization, emerging nanotechnologies, bioremediation, and phytoremediation, will be evaluated for their effectiveness in reducing pollution. Finally, we highlight new perspectives, integrated strategies, and multidisciplinary approaches that combine various technological innovations, including artificial intelligence, to enhance sediment reuse with the aim of promoting economic growth and environmental protection. Full article

Freshwater mussels play a vital ecological role in aquatic ecosystems, serving as effective natural filters that enhance water quality by removing suspended particles and excess nutrients, thereby preventing eutrophication. Their filtration activity supports overall ecosystem stability and promotes biodiversity by providing habitat structure for various aquatic species. Additionally, mussels are valuable bioindicators of environmental health, reflecting water quality changes and accumulating pollutants, including pharmaceuticals and heavy metals, which can offer insights into pollution trends. Freshwater mussels offer considerable economic potential through sustainable aquaculture, particularly in pearl production and jewelry applications, while also contributing nutritionally in controlled and culturally appropriate contexts. Despite these benefits, freshwater mussels face significant threats, including habitat destruction, pollution, invasive species, and overexploitation. These pressures have resulted in drastic population declines and extinctions across various species. Effective conservation and management strategies are essential to protect freshwater mussels, focusing on habitat protection and restoration, ongoing research, and stakeholder engagement to ensure the sustainability of these crucial organisms. This review highlights the multifaceted ecological and economic values of freshwater mussels, the challenges they face, and the importance of comprehensive conservation efforts to maintain their populations and the health of aquatic ecosystems. Full article

The Hainan gibbon (Nomascus hainanus) is one of the most endangered primates globally, threatened by habitat destruction, genetic diversity loss, and ecological competition. In this study, given the critical role of the gut microbiota in host immune regulation and nutrient metabolism, we investigated the composition of and age-related variations in the gut microbiota in Hainan gibbons. Using 16S rRNA sequencing, we systematically investigated the gut microbial diversity of Hainan gibbons. We collected 41 fecal samples from Hainan Tropical Rainforest National Park, covering three age groups: juveniles (4–6 years), subadults (7–10 years), and elderly animals (≥13 years). This study found that microbiota composition changed significantly with age. Juveniles had higher microbial diversity and complexity, while subadults showed an increased abundance of Fibrobacter and Prevotella in their microbial communities, along with a Tax4Fun-predicted enrichment of functional genes related to energy metabolism, cell motility, and nervous system functions. LEfSe analysis identified statistically significant microbial taxa among different age groups, with Bacteroidota and Firmicutes being the dominant phyla across all groups with varying proportions. These results highlight the critical role of the gut microbiota in the health and adaptability of Hainan gibbons, offering insights for conservation strategies. The findings of this study are significant for understanding the changes in gut microbiota and their ecological functions across different life stages of endangered primates. Full article

Surface mining activities cause severe disruption to ecosystems, resulting in the substantial destruction of surface vegetation, the loss of soil organic carbon stocks, and a decrease in the ecosystem’s ability to sequester carbon. The ecological restoration of mining areas has been found to significantly enhance the carbon storage capacity of ecosystems. This study evaluated ecological restoration strategies in Chongqing’s Tongluo Mountain mining area by integrating GF-6 satellite multispectral data (2 m panchromatic/8 m multispectral resolution) with ground surveys across 45 quadrats to develop a quadratic regression model based on vegetation indices and the field-measured biomass. The methodology quantified carbon storage variations among engineered restoration (ER), natural recovery (NR), and unmanaged sites (CWR) while identifying optimal vegetation configurations for karst ecosystems. The methodology combined the high-spatial-resolution satellite imagery for large-scale vegetation mapping with field-measured biomass calibration to enhance the quantitative accuracy, enabling an efficient carbon storage assessment across heterogeneous landscapes. This hybrid approach overcame the limitations of traditional plot-based methods by providing spatially explicit, cost-effective monitoring solutions for mining ecosystems. The results demonstrate that engineered restoration significantly enhances carbon sequestration, with the aboveground vegetation biomass reaching 5.07 ± 1.05 tC/ha, a value 21% higher than in natural recovery areas (4.18 ± 0.23 tC/ha) and 189% greater than at unmanaged sites (1.75 ± 1.03 tC/ha). In areas subjected to engineered restoration, both the vegetation and soil carbon storage showed an upward trend, with soil carbon sequestration being the primary form, contributing to 81% of the total carbon storage, and with engineered restoration areas exceeding natural recovery and unmanaged zones by 17.6% and 106%, respectively, in terms of their soil carbon density (40.41 ± 9.99 tC/ha). Significant variations in the carbon sequestration capacity were observed across vegetation types. Bamboo forests exhibited the highest carbon density (25.8 tC/ha), followed by tree forests (2.54 ± 0.53 tC/ha), while grasslands showed the lowest values (0.88 ± 0.52 tC/ha). For future restoration initiatives, it is advisable to select suitable vegetation types based on the local dominant species for a comprehensive approach. Full article