Abstract: Wind farms are known to trigger avoidance behaviour leading to habitat loss in some raptors. The recovery of the Spanish imperial eagle, Aquila adalberti, in Cadiz, a Spanish province with a high density of wind farms, is of concern. Macro-displacement was studied by comparing juvenile density between wind farms and control areas. Meso-displacement was studied comparing actual density in each 200 m interval of distance around turbines against a random distribution, assuming no-avoidance, controlling for the influence of other environmental factors. We found no evidence of avoidance at macro scale. At meso scale, using density method, we did not find any evidence supporting eagle avoidance behaviour. The study of avoidance behaviours is an ongoing topic that can help to improve conservation and management decisions, especially for species sensitive to the presence of wind farms and other threatening infrastructures in their habitats.

Abstract: Turbidity, a key indicator of water quality, arises from suspended and colloidal particles that reduce clarity, hinder disinfection, disrupt aquatic ecosystems, and undermine consumer confidence. With increasing pressures from global water pollution, effective turbidity control is critical for protecting public health, supporting industrial operations, and maintaining environmental sustainability. It is also essential for the stable performance of water treatment processes, including biologically mediated systems such as slow sand filtration. A wide range of treatment techniques, spanning conventional approaches to advanced emerging technologies, are available for turbidity removal; however, existing reviews often consider these methods in isolation, limiting comparative insight. This review presents a mechanism-based classification framework that integrates both traditional and modern approaches. Treatment methods are classified according to their underlying mechanisms, including particle destabilization, aggregation, and separation; adsorptive and transformation processes; and hybrid or assisted systems that combine multiple mechanisms. For each category, the review examines fundamental principles, operational mechanisms, turbidity removal efficiencies, advantages, and limitations, supported by relevant case studies. A comparative discussion highlights the strengths and constraints of different methods, providing a comprehensive reference to guide the selection and optimization of turbidity control strategies across diverse water matrices and treatment objectives.

Abstract: Carbon losses from decomposition and erosion threaten intensive crop production systems. While conservation tillage enhances soil organic carbon (SOC), soil tex-ture-dependent responses and time-scales of soil quality change remain poorly understood. We addressed this gap using a dual time-scale design: 11 years of minimum tillage (MT) versus conventional ploughing (CT), followed by 5-year transitions to no-till (NT) in contrasting textures (loamy vs. silty clay) in NE Slovenia. In loamy soils, reduced tillage significantly increased SOC, dissolved organic carbon (DOC), permanganate oxidizable carbon (POX-C), particulate organic carbon (POC), and mineral-associated organic carbon (MAOC < 50 μm) in the 0-10 cm layer. In silty clay soils, high clay content provided baseline protection that masked tillage effects on bulk SOC, though POX-C and POC showed vertical stratification. MAOC in the fine fraction (< 20 μm) remained consistent (2.0-2.5%) across treatments and textures, except under CT in loamy soil (1.73%), indicating accelerated decomposition. Tillage intensity drove aggregate distribution: CT fragmented soil structure (fewer macroaggregates, higher Dm), while MT and NT promoted macroaggregate formation. Structural indices (MWD, GMD, Dm) correlated strongly with C fractions, confirming physical protection mechanisms. Our dual time-scale approach reveals labile C pools and aggregate recovery respond within 5 years of NT, while texture modulates response magnitude and detectability. Reducing tillage intensity consistently supports C preservation across textures, though lighter soils show faster, more pronounced responses.

Abstract: Deep and middle-layer tight sandstone reservoirs represent an emerging frontier in oil and gas exploration and development. Significant breakthroughs have recently been achieved in the northern deepwater region of the Qiongdongnan Basin, particularly within the Oligocene Lingshui Formation in the Baodao Depression. However, the petrophysical characteristics of these tight sandstone reservoirs and the controlling factors influencing sweet spot development remain poorly understood. This study integrates comprehensive datasets—including thin section petrography, cathodoluminescence, scanning electron microscopy (SEM), X-ray diffraction (XRD), and conventional reservoir property analyses—to systematically investigate the reservoir characteristics and key controls on sweet spot formation in the third member of the Lingshui Formation along the northern slope of the Baodao Depression. A pore evolution model for sweet spot reservoir development is subsequently proposed. The results indicate that: 1) The tight sandstones are predominantly lithic feldspathic quartzarenite, feldspathic quartzarenite, and feldspathic litharenite, with primary pore types including feldspar dissolution pores, moldic pores, and residual intergranular pores. 2) Among these, feldspathic quartzarenite and lithic feldspathic quartzarenite exhibit superior reservoir quality and constitute the main sweet spots; high quartz and feldspar content coupled with low lithic fragment abundance are critical compositional controls on sweet spot formation in deep to middle-depth settings. 3) Grain size demonstrates a positive correlation with reservoir physical properties. Compaction has led to porosity reduction by 22.0%~28.0%, establishing the fundamental basis for reservoir tightness. 4) Dissolution processes play a pivotal role in enhancing reservoir quality. Secondary porosity zones developed at depths of 3800~3950 m and 4100~4400 m due to dissolution significantly improve porosity and permeability. Conversely, during the late stage of mesodiagenesis (Stage B), extensive carbonate cementation contributes to further reservoir compaction. This research provides a theoretical foundation for the evaluation and prediction of sweet spot reservoirs in deepwater tight sandstone systems in the South China Sea, offering guidance for hydrocarbon exploration, field development planning, and the selection of favorable drilling targets. Furthermore, it advances the understanding of the formation mechanisms and evolutionary pathways of different types of sweet spots in deep and middle-layer tight sandstone reservoirs.

Abstract: A retrospective ozone simulation was conducted with the Microscale Forward and Adjoint Chemical Transport (MicroFACT) model for an industrialized area of Detroit, Michigan, USA using a 24 km × 24 km horizontal × 1.5 km vertical grid. The domain encompassed a regulatory monitoring station at East 7 Mile Rd at the northern edge of the grid. The episode day was 30 June 2022, when the station-measured 8-hour ozone reached 76 ppb during predominantly southwesterly wind. The ozone impacts of mobile, point, nonpoint, and biogenic emissions were simulated at 400 m horizontal resolution. Simulation results were compared against station measurements of ozone, nitrogen oxides, and total reactive nitrogen. Local nitrogen oxide sources were found to titrate ozone, while ozone turbulently entrained to the surface from ~500 m aloft enhanced surface Ozone Production Efficiency and led to extended periods of high ozone concentrations very similar to observations. Volatile Organic Compound emission reductions produced only weak decreases in maximum 8-hour ozone, suggesting that radicals were enhanced mostly by photolysis of subsiding ozone. Entrainment of ozone layers aloft may thus be critical in explaining historical ozone exceedances of the United States National Ambient Air Quality Standard at the East 7 Mile Rd station.

Abstract: Remote sensing has become a cornerstone of data-driven decision-making for monitoring biodiversity and supporting the achievement of the Sustainable Development Goals (SDGs). By providing consistent, spatially explicit observations across scales, Earth observation (EO) technologies enable systematic assessment of environmental change and ecosystem dynamics. Within this context, the Essential Biodiversity Variables (EBV) framework offers a standardised approach to harmonising biodiversity observations from in-situ and remote sensing platforms, thereby enhancing interoperability and the effective use of biodiversity information for conservation and sustainable development. This paper focuses on two EBV classes of particular relevance to EO applications: Ecosystem structure and Species traits. We review recent advances in remote sensing techniques—particularly LiDAR, multispectral, hyperspectral, and radar data—and their capacity to monitor ecosystem vertical structure, ecosystem distribution, habitat suitability, and vegetation traits such as productivity, phenology, leaf area index, chlorophyll content, and functional traits. The integration of EO data with in-situ observations and machine learning approaches is highlighted as a key pathway for improving habitat modelling and biodiversity assessments at regional to continental scales, with direct relevance to SDG 15 (Life on Land). We further discuss current challenges, including data resolution limitations, standardisation, computational demands, and the translation of EO-derived indicators into policy-relevant metrics. Finally, we outline future perspectives, emphasising the role of emerging sensor technologies, artificial intelligence, FAIR data principles, and multi-source data integration in advancing EBV monitoring and strengthening the contribution of remote sensing to sustainable ecosystem management and global biodiversity targets.

Abstract: Robust radar object classification is a challenging task, primarily due to the aspect sensitivity limitation of one-dimensional High-Resolution Range Profile (HRRP) data. To address this, we propose Point-HRRP-Net. This multi-modal framework integrates HRRP with 3D LiDAR point clouds via a Bi-Directional Cross-Attention (Bi-CA) mechanism to enable deep feature interaction. Since paired real-world data is scarce, we constructed a high-fidelity simulation dataset to validate our approach. Experiments conducted under strict angular separation demonstrated that Point-HRRP-Net consistently outperformed single-modality baselines. Our results also verified the effectiveness of Dynamic Graph CNN (DGCNN) for feature extraction and highlighted the high inference speed and the potential of Mamba- based architectures for future efficient designs. Finally, this work validates the feasibility of the proposed approach in simulated environments, establishing a foundation for robust object classification in real-world scenarios.

Abstract: Collecting and analysing data after an earthquake is essential to determine its impact. In 2014, the European Mediterranean Seismological Centre (EMSC) launched the LastQuake system. This system collects intensity reports from users to help provide rapid situational awareness. However, text data collected through crowdsourcing platforms is unstructured. Therefore, natural language processing techniques such as sentiment analysis are necessary to extract meaningful information. On the 26th November 2019, following an earthquake in Albania, the LastQuake app recorded 28,220 reports with user comments. For the current analysis, we sampled comments posted on the exact day of the earthquake, in Albanian: 1678 comments (6%). The most frequent polarity detected in comments from LastQuake app users was negative (52%) followed by far by positive, neutral and unrelated comments. However, manual classification is time-consuming and not feasible during the emergency phase. Therefore, we tested the accuracy of two automatic classification models for sentiment analysis: ‘troberta’ and ‘txlm’. These models were fine-tuned using already classified text data from the 2020 Aegean earthquake. Using the manual classification as the reference to evaluate the accuracy of automatic classification models for sentiment analysis yields accuracies of 71% for the ‘troberta’ model and 56% for the ‘txlm’ model.

Abstract: Water shortage is a major problem that affects sustainability of agricultural sector in northeastern Thailand especially areas remote from a main river. This study aims at developing a system for water shortage risk assessment at sub-district level in Maha Sarakham Province. QSWAT model for sub-watershed streamflow simulation was integrated with WEAP model to analyze water balance and assess water shortage based on water demand from five sectors: non-irrigated agriculture, irrigated agriculture, consumption, services, and industry. The findings revealed that both models provided the results of calibration, and the validated results of streamflow analysis were at satisfactory to good level. From spatial analysis, distribution of provincial water resource was significantly different. Sub-districts located along the Chi River had high streamflow but low water shortage while those from central to southern part had limited streamflow although water demand was high especially for agricultural sector. According to temporal analysis, critical period of water shortage was found in the dry season and seasonal transition after post-harvest period. Integration of data on streamflow and water demand can be useful to divide subdistricts into three group: positive water balance, balance, and negative water balance. Most sub-districts were classified as negative water balance that needed urgent measures for water resource development. These findings have provided important data for planning water resource management locally and supporting development of drought mitigation measures for vulnerable areas in Maha Sarakham Province.

Abstract: Biogas has been identified as one of the viable options which can be used to reduce energy poverty, deforestation and overreliance on the use of biomass and fossil fuels. Despite being introduced in the country decades ago, its uptake has remained limited. To address this challenge, this research was conducted to identify ways to increase its adoption in Malawi and to reduce its dis-adoption. The study employed qualitative methods to gather experience from biogas adopters, disadopters, potential adopters, and energy experts across four districts. The research study was carried out in four districts namely Mchinji, Mzimba, Ntcheu, and Chikwawa. The data collected was an-alyzed through thematic analysis. Results of the study indicated that there are several obstacles that are hindering adoption of biogas technology in the country and these in-clude high investment costs, a lack of post-installation services, socio-cultural barriers, lack of technical support, and a lack of clear policy frameworks. To address these chal-lenges, respondents proposed several holistic strategies which can be used to improve biogas adoption. These involve increasing public awareness, provision of subsidies and soft loans, creating strong technical support systems, setting biogas standards, decen-tralizing demonstration sites, and encouraging cross-sector collaboration. The research observed that a combined approach, supported by policy and driven by community engagement, is essential for increasing biogas technology and guiding Malawi towards clean, affordable, and sustainable energy solutions.

Abstract: Remote sensing has revolutionized monitoring landscapes that are inaccessible or impractical to survey on the ground. Satellite platforms such as Sentinel-2 enable assessment of ecosystem changes over extensive areas with high temporal frequency, while Unmanned Aerial Systems (UAS) offer flexible, ultra-high-resolution observations ideal for site-specific analysis and sensitive environments. This study compares the performance of Sentinel-2 and Phantom 4 multispectral RTK data for monitoring vegetation dynamics in Mediterranean shrubland ecosystems, focusing on the Normalized Difference Vegetation Index (NDVI). Both platforms produced broadly consistent patterns in seasonal and interannual vegetation dynamics. However, UAS outperformed satellite data in capturing fine-scale heterogeneity, regeneration patches, and subtle disturbance responses, particularly in sparsely vegetated or heterogeneous terrain where satellite metrics may be insensitive. The comparison of NDVI across platforms accounted for standardized processing, harmonization, radiometric and atmospheric correction, and spatial resolution differences. Results show platform selection can be optimized according to monitoring objectives: satellite data are well suited for large-scale, long-term ecosystem monitoring and regional environmental modelling, while UAS data provide critical detail for localized management, early stress detection, and restoration prioritization. A combined approach enhances ecosystem disturbance assessments and resource management by binding the strengths of both wide-area coverage and precise spatial detail.

Abstract: (1) Background: Since its introduction to China, PWD has caused severe damage to coniferous forests in affected areas. Currently, the disease continues to expand towards the northwest regions, posing a serious threat to the ecological security of Xinjiang. (2) Methods: This study utilized MaxEnt model to predict the potential transmission areas of PWD and the potential suitable habitats of Monochamus saltuarius. After coupling the results of both, the potential occurrence areas of PWD in Xinjiang were ultimately determined. (3) Results: Human factors are the main driving forces behind the spread of PWD, with activities in scenic areas and human impact factors playing a key role in transmission. Altitude and Isothermality are the primary limiting factors for vector insects. Xinjiang has potential occurrence areas of PWD, covering 88% of the total coniferous forest area in Xinjiang. (4) Conclusions: Urumqi City, Ili Kazakh Autonomous Prefecture, and the Altay Prefecture are high-risk areas for PWD. This study clarifies the potential transmission routes of PWD and analyzes its high-risk areas, providing a scientific basis for forestry and relevant departments to implement prevention and control measures.

Abstract:

Selenium (Se) is an essential trace element for humans, but excessive intake can cause various diseases and dysfunction. Its level is very low in natural water and becomes a pollutant when it exceeds permissible limits, bringing serious risks and damage to human health. The distribution and pollution of selenium in water, the impact of selenium on health and the limit requirements for selenium in drinking water are introduced. The development of selenium detection techniques is presented, including atomic spectrometry, spectrofluorometry, ultraviolet-visible spectrophotometry, inductively coupled plasma mass spectrometry (ICP-MS), voltammetry, and so on. Different detection methods for selenium have their own characteristics and different applicability. It is necessary to establish a safety monitoring mechanism with large-scale instrument analysis as the main body and on-site rapid screening detection methods as a supplement, providing effective technical support for the detection of selenium in the environment.

Abstract: Invasive alien species such as Lantana camara L. have ecological impacts that affect native species and soil conditions in different areas. The context specific ecological effects of L. camara on native woody species and communities remain poorly understood, yet such understandings are essential to maintain biodiversity. Therefore, we assessed the ecological impacts of L. camara on native woody species and soil nutrients in protected and communal areas in the Kavango Zambezi Transfrontier Conservation Area (KAZA TFCA) in Zimbabwe. Stratified random sampling was used to sample 60 plots in invaded and uninvaded sites in the separate Communal and Park of the KAZA TFCA. In each plot, woody vegetation was assessed with respect to species composition and richness, stem density, canopy diameter, height and diameter at breast height. Soil samples were collected and analysed for nitrogen, organic carbon, phosphorus, potassium, and pH. The results showed that L. camara negatively affected the native species, with a significant decrease in species richness, density, height, and canopy cover in invaded plots relative uninvaded plots. However, invaded plots had lowest pH (6.1) and soil nutrients such as phosphorus and organic carbon than uninvaded plots. However, some vegetation and soils changes were likely the result of land uses and land use intensities which promote the invasion of L. camara. We conclude that L. camara invasion negatively affected native vegetation diversity and growth, which necessitates the implementation of appropriate control and the management strategies for L. camara in this species rich transfrontier conservation area. Such strategies need to be suitable for the area based on current land uses in the area.

Abstract: Against the background of dramatic climate change, resource constraints and industrial upgrading, optimising the coupling and coordination of the water-energy-food (WEF) system in the northeast region is crucial to ensuring regional security and sustainable development. Existing research lacks long-term continuity and inter-provincial analysis. This article uses data from 2005 to 2023 to evaluate the development of the three northeastern provinces through 24 index frameworks covering safety, coordination and resilience. The methods include entropy weight method, coupling coordination model and constraint model. The result shows: (1) The overall development level fluctuates and has an upward trend, reaching a medium-coordinated level, and there are significant differences between provinces. (2) Coordination initially differentiated, and then gradually converged. From close to the improvement of the disorder to the level of moderate coordination, Liaoning Province declined under the impact of policies. (3) Systemic obstacles are structural and cross-regional, with energy self-sufficiency and water efficiency as key limiting factors. In order to achieve a high level of coordination between water, energy and food systems, it is necessary to formulate tailor-made subsystem governance policies, enhance the technological empowerment of water and energy conservation and efficiency improvement, and promote the development of resilient infrastructure. This integrated approach will systematically resolve resource competition conflicts, thus enhancing the overall resilience and sustainability of regional development.

Abstract: Climate change has caused tremendous concerns in many societies on all continents. However, the decline in biodiversity, which is at least as serious a crisis, is mostly ignored. An increasing number of technological approaches for carbon dioxide reduction (CDR), which are in fact geoengineering, are being studied, partially at the pilot scale. The Intergovernmental Panel on Climate Change (IPCC) supports technologies such as direct air capture (DAC), carbon capture and storage (CCS) and the use of captured CO2 (CCU). A new concept for objectively judging “sustainability” is described: entropy as a generally applicable criterion for sustainability, followed by an analysis of whether CDR technologies are sustainable. It becomes clear that such technologies are seriously unsustainable. Therefore, after the CDR potential of natural ecosystems is explored, the contributions of bioagriculture to CO2 capture and long-term storage (deeply in soil) are shown, as well as their impact on biodiversity recovery via fully integrated bioagriculture – which proves to be sustainable according to the entropy criterion. Practical examples are taken from the German Kattendorf biofarm (450 hectares leased pastures and fields). Their experience with solar and bioenergy will be reported, bird/plant species diversity will be detailed for selected areas, and CO2eq emissions vs. storage figures will be given for milk production, cheese manufacturing and for the whole farm. CDR by natural/renaturalized ecosystems, including bioagriculture, is not only sustainable but also much more capable than CDR technologies and contributes to biodiversity recovery, in contrast to technological approaches. We must address species decline and climate change without mitigating one crisis with approaches that exacerbate the other.

Abstract: Soil heavy metal (HM) pollution poses a severe threat to ecological security and human health. Selenium (Se) is an essential trace element for the human body and can regulate crop growth and development as well as HM uptake in HM-contaminated soils. The regulatory mechanisms of Se on HMs are mainly reflected in four aspects: Geochemical immobilization promotes the formation of metal selenide precipitates and the adsorption of HMs by soil colloids by regulating the rhizosphere redox potential (Eh) and pH value. Rhizosphere microbial remodeling drives the enrichment of functional microorganisms such as Se redox bacteria, plant growth-promoting rhizobacteria (PGPR) and arbuscular mycorrhizal fungi (AMF) through the dual selective pressure of Se toxicity and root exudates, so as to synergistically realize Se speciation transformation and HM adsorption/chelation. Root barrier reinforcement constructs physical and chemical dual defense barriers by inducing the formation of iron plaques on the root surface, remodeling root morphology and strengthening cell wall components such as lignin and polysaccharides. Intracellular transport regulation down-regulates the genes encoding HM uptake transporters, up-regulates the genes encoding HM efflux proteins, and promotes the synthesis of phytochelatins (PCs) to form HM complexes and finally realizes vacuolar sequestration. Finally, we summarize current research gaps in the interaction mechanisms of different Se species, precise application strategies, and long-term environmental risk assessment, providing a theoretical basis and technical outlook for the green remediation of HM-contaminated farmlands and Se biofortification of crops.

Abstract: Papua New Guinea is one of the least studied regions in the Southwest Pacific, and large areas of the country, such as the Fly Plat-form, remain poorly understood due to limited exposure and access constraints. This study presents the first documentation of basaltic volcanism on the Fly Platform, based on new field discoveries at Mea-hill and Yemsigi, two areas located approximately 25 km apart. Inte-grated field observations, petrography, mineral chemistry, and whole-rock geochemistry show that both basalt suites were derived from a similar magma source but record contrasting emplacement histories. Meahill basalts, which include welded tuffs and highly ve-sicular basalt units, reflect rapid magma ascent, vigorous degassing, and locally explosive activity. In contrast, the massive, less vesicular porphyritic basalts at Yemsigi preserve a quieter emplacement history, but with more extensive post-magmatic alteration. Geochemical sig-natures from least altered rocks of both suites support an intraplate origin with similarities to Pliocene-Pleistocene lava fields of Northeast Queensland. The origin of the intra-plate basaltic magmatism is enig-matic, but both young volcanic provinces correlate spatially with a lower mantle anomaly that may represent residual slab material and a seated-seated magma source. These findings provide further insight into the tectono-magmatic evolution of the Fly Platform region and highlight the need for continued geological investigation in this underexplored district.

Abstract: This study explores how demystifying Earth Observation (EO) through co-creation path-16 ways and local language can enhance flood resilience and environmental governance in 17 African informal cities. Using case studies from Maiduguri and Hadejia, Nigeria, the re-18 search employed a transdisciplinary mixed-methods design combining rapid evidence as-19 sessment, surveys, participatory workshops (n = 50 stakeholders) integrating simplified 20 Sentinel-1/2 demonstrations, indigenous knowledge mapping, and pre-/post-engagement 21 surveys. Participants (non-experts) were trained to interpret satellite data in both Hausa 22 and English, linking distant teleconnections with local flood experiences. Findings re-23 vealed significant gains in EO literacy and improvements in interpretive confidence, gen-24 der-inclusive participation, and policy engagement. The use of local learning process en-25 abled participants to translate technical EO concepts into locally meaningful narratives, 26 fostering cognitive empowerment and practical application in flood preparedness and ad-27 vocacy. The study demonstrates that data democratization is not only a matter of open 28 access but also of open understanding. It advances a conceptual model linking Demysti-29 fication, Literacy, Empowerment, Co-Production and Resilience, positioning EO as a so-30 cial technology that bridges scientific and indigenous knowledge systems. The findings 31 contribute to debates on decolonizing environmental science and propose a participatory 32 framework for integrating EO into community-based adaptation, legal accountability, and 33 policy reform across Africa’s rapidly urbanizing landscapes.

Abstract: Taiwan faces significant water resource challenges driven by pronounced seasonal variability, regional hydrological contrasts, and growing anthropogenic pressures. To mitigate shortages and uneven distribution, this article emphasizes the urgent need for integrated water resource management that jointly considers surface water and groundwater. Building on principles of sustainability and resilience, we synthesize recent advances in hydrological modeling, sediment transport analysis, and infrastructure optimization—including reservoir desiltation, seawater desalination, rainwater harvesting, and assessments of land subsidence from groundwater extraction. Particular attention is given to spatial sediment dynamics across river reaches and their implications for enhancing storage capacity. We further evaluate the feasibility of single-unit seawater desalination facilities in Taiwan’s coastal zones, analyzing energy demand and unit water costs under varying scenarios. Design guidelines for rainwater harvesting systems are proposed to reflect the distinct hydrological characteristics of northern and southern Taiwan, while integrating ecological resilience and cultural narratives. By bridging technical rigor with socio-cultural perspectives, this article offers a holistic framework for sustainable water resource planning in Taiwan and comparable island contexts. Finally, we outline preliminary guidelines for incorporating artificial intelligence into future management strategies. This research proposes reasonable cost reflection, differentiated water pricing, recycling goals, and a social equity perspective. These measures all have positive indicator benefits for the implementation of carbon budget management, global energy conservation, carbon reduction, and zero-carbon emission goals, and the achievement of carbon reduction targets of 40% reduction by 2030 and 50% reduction by 2050 for Taiwan.