Search Results (1,969)

Microorganisms exhibit metabolic versatility, which enables their multifaceted application, including in pollutant detoxification, waste recycling, and environmental restoration. Agricultural processing generates substantial byproducts rich in carbon, nitrogen, and sulfur, which require proper handling to mitigate ecological challenges and reduce carbon footprints. The generation of recalcitrant keratinous biomass and its slow degradation in the environment have prompted technological interventions for sustainable solutions. Fundamentally, chemical, thermal and mechanical processing methods have been utilized in managing keratinous waste. These approaches are not only energy-intensive but also yield low-quality products and exacerbate environmental challenges. Multidimensional research on the microbial-assisted conversion of keratinous waste into valuable products, which aligns with circular economy principles, is underway. The biodegradation of keratinous resources has predominantly employed culturable single microbial strains; however, few studies have recently investigated microbial consortia as a promising strategy. The use of microbial consortia leverages the high cultural stability and complementary metabolic pathways of microbes to achieve excellent keratin biodegradation. Therefore, this study examined the latest advancements in transforming keratinous waste into high-quality protein hydrolysates using microbial strains. It detailed various types of microbial consortia and their roles in the valorization of keratinous biomass, while highlighting some knowledge gaps for future studies. The study also explored the role of ancillary microbial enzymes in facilitating the conversion of keratinous biomass into value-added products. Full article

The Larimichthys crocea represents a critically important economic marine species in China’s East Yellow Sea. However, its populations have experienced significant decline due to overexploitation. Despite implemented conservation measures—including stock enhancement, spawning ground protection, and seasonal fishing moratoria—the recovery of yellow croaker resources remains markedly slow. To address this, our study employed the Maximum Entropy (MaxEnt) model to evaluate and characterize the habitat selection patterns of Larimichthys crocea, thereby providing a theoretical foundation for scientifically informed stock enhancement and resource recovery strategies. Species occurrence data were compiled from field surveys conducted during April and November (2019–2023), supplemented with records from the GBIF database and peer-reviewed literature. Concurrent environmental variables, including primary productivity, current velocity, depth, temperature, salinity, silicate, nitrate, phosphate, and pH, were obtained from the Copernicus and NOAA databases. After rigorous screening, 136 distribution points (April) and 369 points (November) were retained for analysis. The model performance was robust, with an AUC (Area Under the Curve) value of 0.935 for April (2019–2023) and 0.905 for November (2019–2023), indicating excellent predictive accuracy (AUC > 0.9). April (2019–2023): Nitrate, salinity, phosphate, and silicate were identified as the primary environmental factors influencing habitat suitability. November (2019–2023): Silicate, salinity, nitrate, and primary productivity emerged as the dominant drivers. Spatially, Larimichthys crocea exhibited high-density distributions in offshore regions of Zhejiang and Jiangsu, particularly near the Yangtze River estuary. Populations were also associated with island-reef systems, forming continuous distributions along Zhejiang’s offshore waters. In Jiangsu, aggregations were concentrated between Nantong and Yancheng. This study delineates habitat suitability zones for Larimichthys crocea, offering a scientific basis for optimizing stock enhancement programs, designing targeted conservation measures, and establishing marine protected areas. Our findings enable policymakers to develop sustainable fisheries management strategies, ensuring the long-term viability of this ecologically and economically vital species. Full article

Livestock and poultry genetic resources form the cornerstone of elite population breeding, new breed development, and global food security. The yak (Bos mutus), endemic to the Qinghai–Tibet Plateau, is indispensable for maintaining regional biodiversity and ecological stability. The Datong yak—China’s first nationally recognized cultivated yak breed and the world’s inaugural domesticated yak variety—plays a pivotal role in enhancing yak production performance, mitigating grassland–livestock conflicts, and restoring degraded grasslands. This study aimed to provide a scientific basis for the conservation and sustainable utilization of yak genetic resources by comprehensively evaluating the genetic resource value of Datong yaks. We employed the market price method, opportunity cost method, and shadow engineering method to assess four value dimensions—aligned with the Food and Agriculture Organization (FAO) livestock genetic resource value framework and adapted to China’s yak production context: direct use value (DUV), indirect use value (IUV), potential use value (PUV), and conservation value (CV). Data were collected through expert consultations, semi-structured interviews, and questionnaire surveys in Datong County (Qinghai Province, the core production area of Datong yaks) between August and September 2024, with the widely distributed Qinghai Plateau yak serving as the control breed. Based on a recent market survey, the total genetic resource value of Datong yaks in China was estimated at CNY 2.505 billion in 2024, highlighting the increasing economic and strategic significance of yak genetic resources. Among the four value dimensions, PUV accounted for the largest share (65.67%), driven by superior production performance, market price premiums, and reduced feeding costs. DUV contributed 20.72%, reflecting the value of biological assets and beef products; IUV represented 7.10%, primarily associated with grassland conservation benefits; and CV constituted 6.51%, encompassing costs for genetic resource preservation and cultural heritage contributions. These results underscore the substantial potential of Datong yak genetic resources, particularly given their unique adaptation to high-altitude environments and their critical role in supporting local livelihoods and ecological stability. Future research should focus on expanding breeding programs and genetic conservation, optimizing industrial and value chains, and strengthening genetic improvement initiatives to promote ecological security and sustainable development of the yak industry on the Qinghai–Tibet Plateau. Full article

Droughts are increasingly threatening ecological balance, agricultural productivity, and socio-economic resilience—especially in semi-arid regions like the Inner Mongolia segment of China’s Yellow River Basin. This study presents a hybrid drought forecasting framework integrating machine learning (ML) and deep learning (DL) models with high-resolution historical and downscaled future climate data. TerraClimate observations (1985–2014) and bias-corrected CMIP6 projections (2030–2050) under SSP2-4.5 and SSP5-8.5 scenarios were utilized to develop and evaluate the models. Among the tested ML algorithms, Random Forest (RF) demonstrated the best trade-off between accuracy and interpretability and was selected for feature importance analysis. The top-ranked predictors—precipitation, solar radiation, and maximum temperature—were used to train a Long Short-Term Memory (LSTM) network. The LSTM outperformed all ML models, achieving high predictive skill (R² = 0.766, CC = 0.880, RMSE = 0.885). Scenario-based projections revealed increasing drought severity and variability under SSP5-8.5, with mean PDSI values dropping below −3 after 2040 and deepening toward −4 by 2049. The high-emission scenario also exhibited broader uncertainty bands and amplified interannual anomalies. These findings highlight the value of hybrid AI–climate modeling approaches in capturing complex drought dynamics and supporting anticipatory water resource planning in vulnerable dryland environments. Full article

The conversion of ecological product value is vital for reconciling economic growth with environmental sustainability. As a financial innovation that combines digital technology with inclusive finance, digital finance has emerged as a key driver of this process. Drawing on Chinese provincial panel data from 2011 to 2020, this study shows that digital finance significantly enhances the conversion efficiency of ecological product value (CEEPV), and the results remain robust after addressing endogeneity and sensitivity concerns. The analysis reveals that the depth of use and the level of digitalization of digital finance strongly promote CEEPV, while coverage breadth has no significant effect. Mechanism tests indicate that digital finance improves CEEPV mainly through alleviating rural financing constraints, fostering entrepreneurship, encouraging green innovation, enhancing agricultural social services, and supporting rural e-commerce. In addition, traditional finance and financial regulation complement digital finance in strengthening CEEPV. Heterogeneity analysis further shows that the positive effect of digital finance is concentrated in provinces with higher levels of marketization and urbanization. Overall, the findings underscore the importance of accelerating digital finance development and implementing region-specific policies to maximize its potential in advancing ecological product value realization. Full article

In the context of increasing climate variability and flood risk, this study explores how long-standing agricultural practices in the Hunter Valley, New South Wales, Australia, have fostered flood resilience through the integration of local agro-environmental knowledge and geomorphologic conditions. Employing a morpho-typological framework, the research identifies three flood adaptation landscape types (FALTs)—rolling hills, foot slopes, and flood plains—each reflecting distinct interactions between landform, soil, biodiversity, hydrology, and viticultural management. Through geospatial analysis, field surveys, and interviews with local farmers, the study reveals how adaptive strategies—ranging from flood avoidance to attenuation and acceptance—have evolved in response to site-specific hydrological and ecologic dynamics. These strategies demonstrate a form of ‘sponge landscape’ design, where agricultural systems are co-shaped with natural processes to enhance systemic resilience and long-term productivity. The findings underscore the value of preserving biocultural legacies and suggest that spatially explicit, context-based approaches to flood adaptation can inform sustainable landscape planning and climate resilience strategies in other rural regions. The FALT framework offers a replicable methodology for identifying flood adaptation patterns across diverse agricultural systems in Australia, supporting proactive land use planning and nature-based solutions. This research contributes to the discourse on climate adaptation by bridging traditional environmental knowledge with contemporary planning frameworks, offering practical insights for policy, landscape management, and rural development. Full article

Xylella fastidiosa was first detected in Portugal in 2019 in Lavandula dentata. In response, the national plant health authorities promptly established a Demarcated Zone in the affected area and implemented a series of eradication and control measures, including the systematic removal and destruction of infected and host plants. This study analyzes the economic and operational impacts of these eradication efforts in the northern region of Portugal, with a focus on Demarcated Zones such as the Porto Metropolitan Area, Sabrosa, Alijó, Baião, Mirandela, Mirandela II, and Bougado between 2019 and June 2023. During this period, about 412,500 plants were uprooted. The majority were Pteridium aquilinum (bracken fern), with 360,324 individuals (87.3%), reflecting its wide distribution and the large area affected. Olea europaea (olive tree) was the second most common species removed, with 7024 plants (1.7%), highlighting its economic relevance. Other notable species included Quercus robur (3511; 0.85%), Pelargonium graveolens (3509; 0.85%), and Rosa spp. (1106; 0.27%). Overall, destruction costs were estimated at about EUR 1.04 million, with replanting costs of roughly EUR 6.81 million. In parallel, prospection activities—conducted to detect early signs of infection and monitor disease spread—generated expenses of roughly EUR 5.94 million. While prospecting represents a significant financial investment, the results show that it is considerably more cost-effective than large-scale eradication. Prospection enables early detection and containment, preventing the widespread destruction of vegetation and minimizing disruption to agricultural production, biodiversity, and local communities. Importantly, our findings reveal a sharp decline in confirmed cases in the initial outbreak area—the Porto Demarcated Zone—from 124 cases in 2019 to just 5 in 2023, indicating the effectiveness of the eradication and monitoring measures implemented. However, the presence of 20 active Demarcated Zones across the country as of 2023 highlights the continued risk of spread and the need for sustained vigilance. The complexity of managing Xylella fastidiosa across ecologically and logistically diverse territories justifies the high costs associated with surveillance and targeted interventions. This study reinforces the strategic value of prospection as a proactive and sustainable tool for plant health management. Effective surveillance requires the integration of advanced methodologies aligned with the phenological stages of host plants and the biological cycle of vectors. Targeting high-risk locations, optimizing sample numbers, ensuring diagnostic accuracy, and maintaining continuous training for field teams are critical for improving efficiency and reducing costs. Ultimately, the findings underscore the need to refine and adapt monitoring and eradication strategies to contain the pathogen, safeguard agricultural systems, and prevent Xylella fastidiosa from becoming endemic in Portugal. Full article

Larix gmelinii is the fourth most important tree species in China and a typical zonal climax species in the cold temperate region, with high ecological and resource value. However, intensive logging, high-density afforestation, and insufficient scientific management have led to overly dense, homogeneous, and unstable plantations, severely limiting productivity. To clarify the mechanisms by which structural dynamics regulate productivity, we established a space-for-time sequence (T1–T3, T2-D, CK) under a consistent early-tending background. Using the “1 + 4” nearest-neighbor framework and six spatial structural parameters, we developed tree and forest spatial structure indices (TSSI and FSSI) and integrated nine structural–functional indicators for multivariate analysis. The results showed that TSSI and FSSI effectively characterized multi-level stability and supported stability classification. Along the stand-age gradient, structural stability and spatial use efficiency improved significantly, with FSSI and biomass per hectare (BPH) increasing by 91% and 18% from T1 to T3, though a “structural improvement–functional lag” occurred at T2. Moderate thinning markedly optimized stand configuration, reducing low-stability individuals from 86.45% in T1 to 42.65% in T2-D, while DBH, crown width, FSSI, and BPH (229.87 t·hm⁻²) increased to near natural-forest levels. At the tree scale, DBH, tree height, crown width, and TSSI were positive drivers, whereas a high height–diameter ratio (HDR) constrained growth. At the stand scale, canopy density, species richness, and mean DBH promoted FSSI and BPH, while mean HDR and stand density imposed major constraints. A critical management window was identified when DBH < 25 cm, HDR > 10, and TSSI < 0.25 (approximately 10–30 years post-planting). We propose a stepwise, moderate, and targeted thinning strategy with necessary underplanting to reduce density and slenderness, increase diameter and canopy structure, and enhance diversity, thereby accelerating the synergy between stability and productivity. This framework provides a practical pathway for the scientific management and high-quality development of L. gmelinii plantations. Full article

Urban community gardens are valued for promoting sustainable food production, yet the accumulation of toxic heavy metals in city soils can present both ecological and public health risks. Therefore, this study was aimed at assessing the environmental and health risks of toxic heavy metals in community gardens soil contaminated by an industrial fire hazard in New Brunswick, Canada. Both top and subsoil soil samples were collected at Carleton community garden. The collected samples were examined for toxic heavy metals using inductively coupled plasma optical emission spectrometry and inductively coupled plasma mass spectrometry. Ecological risks were evaluated through the ecological risk factor and the potential ecological risk index, while human health risks were determined using a standard human health risk assessment approach. The mean concentration of Pb, Zn, Cu, and Sn exceeded permissible limits when compared to the Canadian soil quality guidelines and upper continental crust values. Findings from the ecological risk assessment showed that all metals were associated with low risk, except for nickel, which posed a high ecological risk across both soil layers. PERI results revealed a low overall ecological threat. The human health risk analysis indicated that children could face non-carcinogenic and carcinogenic risks from As exposure, while adults were not at risk from any of the studied metals. These findings identify arsenic as the primary contaminant of concern, with children representing the most vulnerable population, emphasizing the necessity for targeted mitigation strategies and protective measures to reduce their exposure. The results of this study can inform interventions aimed at safeguarding both environmental and public health, while also raising awareness about the presence and risks of toxic heavy metals, ultimately contributing to the protection of human health and the broader ecosystem. Full article

As a fundamental metric for assessing carbon sequestration, Net Primary Productivity (NPP) and the mechanisms driving its spatiotemporal dynamics constitute a critical research domain within global change science. This research centered on the Huang–Huai–Hai Plain (HHHP), combining 2001–2023 MODIS-NPP data with natural (landform, temperature, precipitation, soil) and socio-economic (population density, GDP density, land use) drivers. Trend analysis, coefficient of variation, and Hurst index were applied to clarify the spatiotemporal evolution of NPP and its future trends, while geographic detectors and structural equation models were used to quantify the contribution of drivers. Key findings: (1) Across the HHHP, the multi-year average NPP ranged between 30.05 and 1019.76 gC·m⁻²·a⁻¹, with higher values found in Shandong and Henan provinces, and lower values concentrated in the northwestern dam-top plateau and central plain regions; 44.11% of the entire region showed a statistically highly significant increasing trend. (2) The overall fluctuation of NPP was low-amplitude, with a stable center of gravity and the standard deviation ellipse retaining a southwest-to-northeast direction. (3) Future changes in NPP exhibited persistence and anti-persistence, with 44.98% of the region being confronted with vegetation degradation risk. (4) NPP variations originated from the synergistic impacts of multiple elements: among individual elements, precipitation, soil type, and elevation had the highest explanatory capacity, while synergistic interactions between two elements notably enhanced the explanatory capacity. (5) Climate variation exerted the strongest influence on NPP (direct coefficient of 0.743), followed by the basic natural environment (0.734), whereas human-related activities had the weakest direct impact (−0.098). This research offers scientific backing for regional carbon sink evaluation, ecological security early warning, and sustainable development policies. Full article

Trichilia emetica and T. dregeana butter oils are gaining recognition in the cosmeceutical industry, yet comparative data on their yields and bioactive composition remain scarce. This study assessed oil yields, fatty acid profiles, and tocol compositions of kernel and aril oils extracted by screw press from seeds collected in KwaZulu-Natal, South Africa. T. emetica produced smaller but more numerous seeds (603 per 200 g) than T. dregeana (159). Kernel oil yields were slightly higher in T. emetica (52.86%) than in T. dregeana (50.81%), while aril oils averaged 48.61% and 45.22%, respectively. Kernel oils of both species showed strong oxidative stability, with low peroxide and anisidine values and lower free fatty acid content compared to aril oils. T. emetica kernel oil was dominated by saturated fatty acids (SFAs), particularly palmitic acid (51.8%), and contained high γ-tocopherol (202 mg/kg), supporting applications in soaps, bio-lubricants, and industrial formulations. In contrast, T. dregeana kernel oil was richer in oleic acid (47.6%) and α-tocotrienol, favouring nutraceutical and cosmetic uses. Aril oils were dominated by linoleic acid (24–25%), with T. dregeana aril oil distinguished by elevated α-tocopherol (91.8 mg/kg) and a more diverse tocotrienol profile, making it suitable for antioxidant-rich cosmetics and dietary products. The dual-oil system offers complementary value: kernel oils provide structural stability for industrial applications, while aril oils supply bioactive-rich lipids for health and cosmetic formulations. Seed cakes present additional potential as biofertilizers or feedstock. This study provides the first comparative analysis of kernel and aril oils from T. emetica and T. dregeana, revealing interspecific differences in yield, fatty acid composition, and tocol profiles, and linking these to ecological adaptation and differentiated industrial potential. Full article

Against the backdrop of the rapid proliferation of electric vehicles (EVs), gender-oriented behavioral mechanisms remain underexplored, particularly the unique pathways of female users in usage experience, value assessment, and purchase decision-making. This study constructs an integrated framework based on the Stimulus–Organism–Response (SOR) model, leveraging social media big data to analyze in depth how gender differences influence EV users’ purchase intentions. By integrating natural language processing techniques, grounded theory coding, and structural equation modeling (SEM), this study models and analyzes 272,083 pieces of user-generated content (UGC) from Chinese social media platforms, identifying key functional and emotional factors shaping female users’ perceptions and attitudes. The results reveal that esthetic value, safety, and intelligent features more strongly drive emotional responses among female users’ decisions through functional cognition, with gender significantly moderating the pathways from perceived attributes to emotional resonance and cognitive evaluation. This study further confirms the dual mediating roles of functional cognition and emotional experience and identifies a masking (suppression) effect for the ‘intelligent perception’ variable. Methodologically, it develops a novel hybrid paradigm that integrates data-driven semantic mining with psychological behavioral modeling, enhancing the ecological validity of consumer behavior research. Practically, the findings provide empirical support for gender-sensitive EV product design, personalized marketing strategies, and community-based service innovations, while also discussing research limitations and proposing future directions for cross-cultural validation and multimodal analysis. Full article

The green macroalgae Ulva Linnaeus, 1753, also known as sea lettuce, is one of the most ecologically and economically significant algal genera. Its representatives occur in marine, brackish, and freshwater environments worldwide and show high adaptability, rapid growth, and marked biochemical diversity. These traits support their ecological roles in nutrient cycling, primary productivity, and habitat provision, and they also explain their growing relevance to the blue bioeconomy. This review summarizes current knowledge of Ulva biodiversity, taxonomy, and physiology, and evaluates applications in food, feed, bioremediation, biofuel, pharmaceuticals, and biomaterials. Particular attention is given to molecular approaches that resolve taxonomic difficulties and to biochemical profiles that determine nutritional value and industrial potential. This review also considers risks and limitations. Ulva species can act as hyperaccumulators of heavy metals, microplastics, and organic pollutants, which creates safety concerns for food and feed uses and highlights the necessity of strict monitoring and quality control. Technical and economic barriers restrict large-scale use in energy and material production. By presenting both opportunities and constraints, this review stresses the dual role of Ulva as a promising bioresource and a potential ecological risk. Future research must integrate molecular genetics, physiology, and applied studies to support sustainable utilization and ensure safe contributions of Ulva to biodiversity assessment, environmental management, and bioeconomic development. Full article

Intestinal microbiota populations are constantly shaped by both intrinsic and extrinsic factors, including diet, environment, and host genetics. As a result, understanding how to assess, monitor, and exploit microbiome–host interplay remains an active area of investigation, especially in aquaculture. In this study, we analyzed the taxonomic structure and functional potential of the intestinal microbiota of European sea bass and rainbow trout, incorporating gilthead sea bream as a final reference. The results showed that the identified core microbiota (40 taxa for sea bass and 20 for trout) held a central role in community organization, despite taxonomic variability, and exhibited a predominant number of positive connections (>60% for both species) with the rest of the microbial community in a Bayesian network. From a functional perspective, core-associated bacterial clusters (75% for sea bass and 81% for sea bream) accounted for the majority of predicted metabolic pathways (core contribution: >75% in sea bass and >87% in trout), particularly those involved in carbohydrate, amino acid, and vitamin metabolism. Comparative analysis across ecological phenotypes highlighted distinct microbial biomarkers, with genera such as Vibrio, Pseudoalteromonas, and Paracoccus enriched in saltwater species (Dicentrarchus labrax and Sparus aurata) and Mycoplasma and Clostridium in freshwater (Oncorhynchus mykiss). Overall, this study underscores the value of integrating taxonomic, functional, and network-based approaches as practical tools to monitor intestinal health status, assess welfare, and guide the development of more sustainable production strategies in aquaculture. Full article

The rapid growth of the human population and industrialization has intensified anthropogenic activities, leading to the release of various toxic chemicals into the environment, triggering significant risks to human health and ecosystem stability. One sustainable solution to remove toxic chemicals from various environmental matrices, such as water, air, and soil, is bioremediation, an approach utilizing biological agents. Microalgae, as the primary producers of the aquatic environment, offer a versatile bioremediation platform, where their metabolic processes break down and convert pollutants into less harmful substances, thereby mitigating the negative ecological impact. Besides the CO₂ sequestration potential, microalgae are a source of renewable energy and numerous high-value biomolecules. Additionally, microalgae can mitigate various toxic chemicals through biosorption, bioaccumulation, and biodegradation. These remediation strategies propose a sustainable and eco-friendly approach to address environmental pollution. This review evaluates the microalgal mitigation of major environmental contaminants—heavy metals, pharmaceuticals and personal care products (PPCPs), persistent organic pollutants (POPs), flue gases, microplastics, and nanoplastics—linking specific microalgae removal mechanisms to pollutant-induced cellular responses. Each section explicitly addresses the effects of these pollutants on microalgae, microalgal bioremediation potential, bioaccumulation process, the risks of trophic transfer, and biomagnification in the food web. Herein, we highlight the current status of the microalgae-based bioremediation prospects, pollutant-induced microalgal toxicity, bioaccumulation, and consequential biomagnification. The novelty of this review lies in integrating biomagnification risks with the bioremediation potential of microalgae, providing a comprehensive perspective not yet addressed in the existing literature. Finally, we identify major research gaps and outline prospective strategies to optimize microalgal bioremediation while minimizing the unintended trophic transfer risks. Full article