Search Results (2,586)

This study evaluated the long-term effects of organo-mineral fertilization on floristic diversity, species diversity, and vegetation structure in an HNV grasslands of the Apuseni Mountains. The experiment included five fertilization variants (control, organic, organo-mineral, mineral, and intensive organo-mineral), applied over a period of more than 15 years. Floristic diversity was assessed using a modified Braun–Blanquet method and multivariate methods—cluster analysis, principal coordinate analysis (PCoA), MRPP procedure, and indicator species analysis (ISA). Our analysis showed a trophic gradient, from oligotrophic Festuca rubra grasslands to mesotrophic (Agrostis capillaris–Trisetum flavescens) and eutrophic (Agrostis capillaris–Centaurea pseudophrygia) communities, depending on the intensity of organo-mineral fertilization applied. Moderate organo-mineral fertilization maintained a balanced floristic diversity and higher Shannon and Simpson indices compared to variants fertilized only with mineral inputs. Organo-mineral inputs improved soil fertility and ecosystem resilience, supporting soil microbiota activity and reducing nutrient losses. Intensive mineral fertilization led to a reduction in floristic richness and the dominance of nitrophilic species. This study demonstrates that moderate organo-mineral fertilization (≤10 t ha⁻¹ manure combined with N₅₀P₂₅K₂₅) provides an optimal balance between grassland productivity and biodiversity conservation, offering practical guidance for the sustainable management of High Nature Value mountain grasslands. Full article

Urban Water Systems (UWS) are complex infrastructures that interact with energy, food, ecosystems and socio-political systems, and are under growing pressure from climate change and resource depletion. Planning circular interventions in this context requires system-level analysis to avoid fragmented, siloed decisions. This paper develops the Hydrosocial Resource Urban Nexus (HRUN) framework that integrates hydrosocial thinking with the Water–Energy–Food–Ecosystems (WEFE) nexus to guide UWS design. We conduct a structured literature review and analyse different configurations of circular interventions, mapping their synergies and trade-offs across socioeconomic and environmental functions of hydrosocial systems. The framework is operationalised through a typology of circular interventions based on their circularity purpose (water reuse, resource recovery and reuse, or water-cycle restoration) and management scale (from on-site to centralised), while greening degree (from grey to green infrastructure) and digitalisation (integration of sensors and control systems) are treated as transversal strategies that shape their operational profile. Building on this typology, we construct cause–effect matrices for each intervention type, linking recurring operational patterns to hydrosocial functionalities and revealing associated synergies and trade-offs. Overall, the study advances understanding of how circular interventions with different configurations can strengthen or weaken system resilience and sustainability outcomes. The framework provides a basis for integrated planning and for quantitative and participatory tools that can assess trade-offs and governance effects of different circular design choices, thereby supporting the transition to more resilient and just water systems. Full article

Climate change and land-use intensification are speeding up the loss of ecosystem services that support human health, food security, and environmental stability. Vegetative interventions—such as urban forests in cities and cover crops in farming systems—are increasingly seen as nature-based solutions for climate adaptation. However, their benefits are often viewed separately. This review combines 20 years of research to explore how these strategies, together, improve provisioning, regulating, supporting, and cultural ecosystem services across various landscapes. Urban forests help reduce urban heat islands, improve air quality, manage stormwater, and offer cultural and health benefits. Cover crops increase soil fertility, regulate water, support nutrient cycling, and enhance crop yields, with potential for carbon sequestration and biofuel production. We identify opportunities and challenges, highlight barriers to adopting these strategies, and suggest integrated frameworks—including spatial decision-support tools, incentive programs, and education—to encourage broader use. By connecting urban and rural systems, this review underscores vegetation as a versatile tool for resilience, essential for reaching global sustainability goals. Full article

Accurate mapping of wetland vegetation is essential for ecosystem monitoring and conservation planning. Traditional workflows combining Sentinel-1 SAR, Sentinel-2 optical imagery, and topographic data have advanced vegetation classification but require extensive preprocessing and often yield fragmented boundaries and “salt-and-pepper” noise. In this study, we compare a conventional multi-sensor classification framework with a novel embedding-based approach derived from the AlphaEarth foundation model, using a cluster-guided Random Forest classifier applied to the dynamic wetland system of Narran Lake, New South Wales. Both approaches achieved high accuracy ac with test performance typically in the ranges: OA = 0.985–0.991, Cohen’s κ = 0.977–0.990, weighted F1 = 0.986–0.991, and MCC = 0.977–0.990. Embedding based maps showed markedly improved spatial coherence (lower edge density, local entropy, and patch fragmentation), producing smoother, ecologically consistent boundaries while requiring minimal preprocessing. Differences in class delineation were most evident in fire-affected and agricultural areas, where embeddings demonstrated greater resilience to spectral disturbance and post-fire variability. Although overall accuracies exceeded 0.98, these high values reflect the use of spectrally pure, homogeneous training samples rather than overfitting. The results highlight that embedding-driven methods can deliver cleaner, more interpretable vegetation maps with far less data preparation, underscoring their potential to streamline large-scale ecological monitoring and enhance the spatial realism of wetland mapping. Full article

Mesozooplankton play a pivotal role in marine pelagic food webs, mediating energy and matter transfer between primary producers and higher trophic levels. Daya Bay, a semi-enclosed bay located in the northern South China Sea, has undergone significant environmental changes due to anthropogenic activities, such as thermal discharge from nuclear power plants and eutrophication. This study examined the mesozooplankton community structure, feeding preferences, and food web organization through four seasonal cruises (May 2022, February 2023, August 2023, and November 2023), employing stable isotope analysis and a Bayesian Isotopic Mixing Model. Results indicate that mesozooplankton abundance and diversity were lower in regions affected by thermal discharge, suggesting a suppressive effect of elevated temperatures. Seasonal shifts in dominant species were observed: Penilia avirostris and Dolioletta gegenbauri dominated the community in spring, while Noctiluca scintillans blooms occurred in summer and winter. Isotopic analysis revealed distinct trophic strategies: copepods exhibited omnivorous habits, whereas cladocerans and tunicates showed stronger herbivorous tendencies. N. scintillans functioned as a high-trophic omnivore, preying on copepod larvae and competing for food resources. Overall, the mesozooplankton community was characterized by an omnivory-dominated trophic network, which enhanced resilience yet remains sensitive to anthropogenic disturbances. This study clarifies how human-induced environmental changes reshape trophic pathways in subtropical coastal waters, providing a valuable reference for long-term monitoring and ecosystem management in Daya Bay. Full article

This study examines how inclusive finance organisations are adapting to the European Union (EU)’s digital–green twin transition and how regulatory design can reinforce this alignment. Drawing on qualitative insights from 26 institutions—including microfinance organisations, small and medium-sized enterprise finance providers and socially oriented fintechs—across the EU and neighbouring countries, the analysis identifies how digitalisation, financial inclusion and environmental sustainability are being integrated into organisational strategies. The findings show that hybrid models, built on partnerships between nationally rooted microfinance institutions and cross-border fintech platforms, enable scalable, high-tech, high-touch ecosystems that align closely with sustainability objectives. The study argues that a coordinated EU-wide regulatory sandbox would advance inclusive, green financial innovation and build resilience across the inclusive finance ecosystem. Full article

This paper reviews Artificial Intelligence techniques for distributed energy management, focusing on integrating machine learning, reinforcement learning, and multi-agent systems within IoT-Edge-Cloud architectures. As energy infrastructures become increasingly decentralized and heterogeneous, AI must operate under strict latency, privacy, and resource constraints while remaining transparent and auditable. The study examines predictive models ranging from statistical time series approaches to machine learning regressors and deep neural architectures, assessing their suitability for embedded deployment and federated learning. Optimization methods—including heuristic strategies, metaheuristics, model predictive control, and reinforcement learning—are analyzed in terms of computational feasibility and real-time responsiveness. Explainability is treated as a fundamental requirement, supported by model-agnostic techniques that enable trust, regulatory compliance, and interpretable coordination in multi-agent environments. The review synthesizes advances in MARL for decentralized control, communication protocols enabling interoperability, and hardware-aware design for low-power edge devices. Benchmarking guidelines and key performance indicators are introduced to evaluate accuracy, latency, robustness, and transparency across distributed deployments. Key challenges remain in stabilizing explanations for RL policies, balancing model complexity with latency budgets, and ensuring scalable, privacy-preserving learning under non-stationary conditions. The paper concludes by outlining a conceptual framework for explainable, distributed energy intelligence and identifying research opportunities to build resilient, transparent smart energy ecosystems. Full article

The rapid economic and urban development in the Yellow River Delta Efficient Ecological Economic Zone (YRDEEZ) has intensified land use changes and aggravated ecological patch fragmentation. Constructing ecological networks (ENs) can reconnect fragmented patches and enhance ecosystem services. This study simulated land use patterns for 2040 under three scenarios: Natural Development (NDS), Ecological Protection (EPS), and Urban Development (UDS). Results indicated a consistent decline in agricultural land and an expansion of urban land across all scenarios, with the most pronounced urban growth under UDS (6.79%) and the largest ecological land area under EPS (5178.96 km²). Since 2000, the number of EN sources and corridors had decreased, with sources mainly concentrated along coastal areas. The source and corridor under UDS exhibited the highest area ratio (20.08%), while NDS showed the lowest (18.72%), with UDS demonstrating the strongest resilience. Through community detection, the UDS EN was divided into five ecological clusters, encompassing 127 intra-cluster corridors (2285.95 km) and 34 inter-cluster corridors (1171.32 km), among which the cluster near the Yellow River estuary was determined to be the most critical (Level 1). These findings will provide valuable insights for managing landscape fragmentation and biological habitat protection in YRDEEZ. Meanwhile, the multi-scenario simulations of ENs could play an important role in constructing ecological security patterns and protecting ecosystems. Full article

Heavy metal pollution poses a serious threat to soil ecosystems worldwide, as long-term exposure can alter microbial community functioning and reduce overall ecosystem resilience. This study investigated the impact of heavy metal contamination in technogenic industrial areas of the East Kazakhstan Region on soil microbial communities. Soil samples were collected for chemical and metagenomic analyses. Concentrations of Zn, Pb, Cu, and Cd were quantified by flame atomic absorption spectrometry (FAAS). Using long-read whole-metagenome nanopore sequencing, we conducted strain-level profiling of soils with different levels of metal contamination. This approach provided high-resolution taxonomic data, enabling detailed characterization of microbial community structure. Heavy metal exposure did not significantly reduce microbial diversity or richness but influences the quality of community composition. Metal-resistant taxa dominated contaminated soils. Overall, the results highlight the value of long-read sequencing for resolving strain-level responses to environmental contamination. Full article

The convergence of Artificial Intelligence (AI) and the Internet of Things (IoT), known as Artificial Intelligence of Things (AIoT), has emerged as a transformative paradigm for enabling intelligent, data-driven, and context-aware decision-making in urban environments to reduce the carbon footprint of mobility and industry. This review examines the conceptual foundations, and state-of-the-art developments of AIoT, with a particular emphasis on its applications in smart cities and its relevance to climate change management. AIoT integrates sensing, connectivity, and intelligent analytics to provide optimized solutions in transportation systems, energy management, waste collection, and environmental monitoring, directly influencing urban sustainability. Beyond urban efficiency, AIoT can play a critical role in addressing the global challenges and management of climate change by (a) precise measurements and autonomously remote monitoring; (b) real-time optimization in renewable energy distribution; and (c) developing prediction models for early warning of climate disasters. This paper performs a literature review and bibliometric analysis to identify the current landscape of AIoT research in smart city contexts. Over 1885 articles from Web of Sciences and over 1854 from Scopus databases, published between 1993 and January 2026, were analyzed. The results reveal a strong and accelerating growth in research activity, with publication output doubling in the most recent two years compared to 2023. Waste management and air quality monitoring have emerged as leading application domains, where AIoT-based optimization and predictive models demonstrate measurable improvements in operational efficiency and environmental impact. Altogether, these support faster and more effective decisions for reducing greenhouse gas emissions and ensuring the sustainable use of resources. The reviewed studies reveal rapid advancements in edge intelligence, federated learning, and secure data sharing through the integration of AIoT with blockchain technologies. However, significant challenges remain regarding scalability, interoperability, privacy, ethical governance, and the effective translation of research outcomes into policy and citizen-oriented tools such as climate applications, insurance models, and disaster alert systems. By synthesizing current research trends, this article highlights the potential of AIoT to support sustainable, resilient, and citizen-centric smart city ecosystems while identifying both critical gaps and promising directions for future investigations. Full article

Sustainable food production for a growing population requires farming practices that reduce chemical inputs while maintaining soil as a living, renewable foundation for productivity. This review synthesizes current advances in understanding how endophytic fungi (EFs) interact with the soil microbiome and contribute to the physicochemical and biological dimensions of soil health in arable ecosystems. We examine evidence showing that EFs enhance plant nutrition through phosphate solubilization, siderophore-mediated micronutrient acquisition, and improved nitrogen use efficiency while also modulating plant hormones and stress-responsive pathways. EFs further increase crop resilience to drought, salinity, and heat; suppress pathogens; and influence key soil properties including aggregation, organic matter turnover, and microbial network stability. Recent integration of multi-omics, metabolomics, and community-level analyses has shifted the field from descriptive surveys toward mechanistic insight, revealing how EFs regulate nutrient cycling and remodel rhizosphere communities toward disease-suppressive and nutrient-efficient states. A central contribution of this review is the linkage of EF-mediated plant functions with soil microbiome dynamics and soil structural processes framed within a translational pipeline encompassing strain selection, formulation, delivery, and field scale monitoring. We also highlight current challenges, including context-dependent performance, competition with native microbiota, and formulation and deployment constraints that limit consistent outcomes under field conditions. By bridging microbial ecology with agronomy, this review positions EFs as biocontrol agents, biofertilizers, and ecosystem engineers with strong potential for resilient, low-input, and climate-adaptive cropping systems. Full article

This follow-up study investigates the long-term environmental sustainability and remediation outcomes of the UPPER (‘Urban Productive Parks for Sustainable Urban Regeneration’-UIA04-252) project in Latina, Italy, focusing on Nature-Based Solutions (NbS) applied to urban green infrastructure. By integrating proximal and satellite-based remote sensing methodologies, the research evaluates persistent improvements in vegetation health, soil moisture dynamics, and overall environmental quality over multiple years. Building upon the initial monitoring framework, this case study incorporates updated data and refined techniques to quantify temporal changes and assess the ecological performance of NbS interventions. In more detail, ground-based data from meteo-climatic, air quality stations and remote satellite data from the Sentinel-2 mission are adopted. Ground-based measurements such as temperature, humidity, radiation, rainfall intensity, PM10 and PM2.5 are carried out to monitor the overall environmental quality. Updated satellite imagery from Sentinel-2 is analyzed using advanced band ratio indices, including the Normalized Difference Vegetation Index (NDVI), the Normalized Difference Water Index (NDWI) and the Normalized Difference Moisture Index (NDMI). Comparative temporal analysis revealed consistent enhancements in vegetation health, with NDVI values significantly exceeding baseline levels (NDVI 2022–2024: +0.096, p = 0.024), demonstrating successful vegetation establishment with larger gains in green areas (+27.0%) than parking retrofits (+11.4%, p = 0.041). However, concurrent NDWI decline (−0.066, p = 0.063) indicates increased vegetation water stress despite irrigation infrastructure. NDMI improvements (+0.098, p = 0.016) suggest physiological adaptation through stomatal regulation. Principal Component Analysis (PCA) of meteo-climatic variables reveals temperature as the dominant environmental driver (PC2 loadings > 0.8), with municipality-wide NDVI-temperature correlations of r = −0.87. These multi-scale findings validate sustained NbS effectiveness in enhancing vegetation density and ecosystem services, yet simultaneously expose critical water-limitation trade-offs in Mediterranean semi-arid contexts, necessitating adaptive irrigation management and continued monitoring for long-term urban climate resilience. The integrated monitoring approach underscores the critical role of continuous, multi-scale assessment in ensuring long-term success and adaptive management of NbS-based interventions. Full article

Root exudates are key mediators of plant–soil–microbe interactions, shaping rhizosphere dynamics and influencing agroecosystem resilience. Comprising diverse primary and secondary metabolites, these compounds are actively secreted through specific transport pathways and are modulated by intrinsic plant traits and environmental conditions. Root exudates serve as chemical signals that recruit and structure microbial communities, facilitating nutrient mobilization, microbial feedbacks, and the regulation of plant growth and stress responses. By modulating soil chemical, physical, and biological properties, exudates contribute to carbon cycling, soil health, and the maintenance of ecosystem services. Moreover, they play multifunctional roles in enhancing plant tolerance to abiotic and biotic stresses, while also mediating interactions with neighboring plants. This review provides a holistic perspective on root exudation, encompassing their mechanisms and drivers, roles in rhizosphere ecology and plant stress adaptation, and methodological advances, while highlighting opportunities to harness these processes for resilient, productive, and sustainable agroecosystems. Full article

Wildfire is a dominant ecological force in Mediterranean pine forests, and post-fire silvicultural practices can substantially alter their recovery trajectories. In this study, we examined how natural regeneration and artificial plantations influence the composition, structure, and functional roles of medium and large-sized mammal communities in burned Pinus brutia forests of southwestern Türkiye. Camera trap data were combined with linear mixed-effects models, functional diversity metrics, and indicator species analysis to assess community responses. Mammalian assemblages showed marked shifts across treatments: generalist carnivores such as Vulpes vulpes and Canis aureus dominated burned areas, whereas higher-trophic specialists like Caracal caracal were restricted to unburned forests. Functional richness was consistently higher in unburned stands, while artificial plantations reduced both richness and evenness. Natural regeneration partly mitigated these declines by sustaining more balanced community structures. Indicator species analysis confirmed these patterns, with Lepus europaeus strongly associated with burned sites and C. caracal with unburned forests. Overall, findings demonstrate that post-fire silvicultural practices strongly shape mammalian community assembly and functional diversity. Natural regeneration preserves structural heterogeneity and supports functionally diverse assemblages, whereas artificial plantations promote homogenization. Effective restoration strategies should therefore integrate wildlife responses with vegetation recovery to strengthen ecosystem resilience and maintain the ecological roles of mammals. Full article

Small and medium-sized enterprises (SMEs) play a central role in employment and regional economic development, yet they are highly vulnerable to shocks such as pandemics, energy price spikes, and supply chain disruptions. Scenario modelling, stress testing, and digital twins are used to assess resilience, yet most applications focus on large firms in single-country settings. This article develops a model to stress test the resilience of Slovenian SMEs, calibrated with parameters and mechanisms derived from South African SME resilience studies. A system dynamics model with stocks for cash, inventory, and productive capacity is specified and subjected to demand, supply, financial, and compound shock scenarios, with and without resilience measures such as liquidity buffers, customer and supplier diversification, and basic digital planning capabilities. Results indicate non-linear tipping points where small reductions in liquidity sharply increase the likelihood of distress, and show that combinations of liquidity, diversification, and collaborative supply chain practices reduce the depth and duration of output losses. The study demonstrates how evidence from an African context can inform resilience strategies in a small European economy and provides a transparent, portable modelling architecture that can be adapted to other settings. Implications are discussed for SME managers and for policies supporting sustainable, resilient enterprise ecosystems. Full article