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Cultural ecosystem services (CES) provide non-material benefits that support human well-being and motivate ecosystem conservation, yet their subjectivity and spatial ambiguity complicate quantitative assessment and management. Taking the Changbai Mountain tourism area as a case, we adopted the ecosystem service matrix method to assess the CES supply score based on the natural system and human system. The service coverage density was obtained through accessibility, thereby quantifying the available supply index for each tourist source area. In addition, we quantified CES demand using a questionnaire survey. Demand for 10 CES types was measured via preference ranking and integrated with the entropy weight method; statistical analysis and GIS mapping were used to examine spatial patterns and influencing factors. Results show that: (1) The overall CES demand in the Changbai Mountain tourism area exhibits clear spatial differentiation, with higher demand in the central and eastern regions and lower demand in the northwest. High-demand areas are mainly concentrated in cities relatively close to the Changbai Mountain tourism area. (2) Among individual CES, recreation (r = 6.58), natural landscapes (r = 6.35), and aesthetic value (r = 6.19) receive the highest demand, and demand structure is significantly associated with occupation, education level, consumption level, and spatial distance. The results indicate that cultural services dominated by knowledge-based services are significantly positively correlated with educational level (r = 0.549, p < 0.001). (3) CES supply capacity shows strong seasonal fluctuations, and is frequently overloaded during peak seasons, leading to prominent supply–demand conflicts; with the exception of Shenyang, Dalian, Jilin and Anshan, the other 17 cities exhibit supply–demand imbalance. By integrating multiple CES types and multiple drivers, this study reveals spatial matching patterns of CES supply and demand in a complex mountain ecotourism region and provides evidence to support ecotourism management, service capacity improvement, and sustainable development. Full article

Climate change threatens crop yields and farming profitability, especially in drought-prone regions, requiring a transition to climate-resilient farming systems. Concurrently, growing demand for health-promoting and bio-based materials is creating new market opportunities for farmers. Sulla (Sulla coronaria Medik; syn. Hedysarum coronarium L.), a Mediterranean forage crop, may represent a strategic resource for sustainable intensification by simultaneously providing high-value commodities and a wide range of ecosystem services. This review explores the multifunctional potential of sulla following a holistic approach and is structured in thematic chapters, exploring: i. agronomy, ii. ecosystem services and agroecological value, iii. plant biochemical profile, iv. emerging applications for the bio-based industry, v. genetic diversity (including rhizobia diversity) and breeding perspectives for target environments and end-use. A SWOT analysis synthesizes strengths, research gaps and bottlenecks hindering large-scale adoption and valorization. The review proposes a strategic framework matching research priority with specific, actionable goals. The review aims to increase awareness of the multifaceted value of sulla as a promising model legume to increase sustainability in agriculture, promote product diversification and farming profitability, while assuring important ecosystem benefits. Full article

This paper presents a comprehensive review of existing research on the integration of blockchain technologies with the trust service ecosystem governed by the Electronic Identification, Authentication and Trust Services (eIDAS) Regulation of the European Union (EU). While Public Key Infrastructure (PKI) and electronic signature (ES) systems deployed under eIDAS provide strong cryptographic guarantees, standardized protocols, and cross-border legal recognition, their operational model remains largely centralized, concentrating trust in supervised authorities and service providers. This centralization raises concerns related to transparency, auditability, and resilience that blockchain, with its decentralized consensus and immutable distributed ledgers, has been increasingly explored to address. This review covers the most relevant application domains in which blockchain has been proposed as a complementary layer for Trust Service Providers (TSPs): certificate lifecycle management, remote signature services, signature preservation, signature validation, timestamping, content provenance and authenticity, and the European digital identity (EUDI) Wallet ecosystem. For each domain, this paper analyzes how blockchain can strengthen auditability and distributed trust while preserving the interoperability, legal assurance, and standards compliance required by eIDAS and ETSI (European Telecommunications Standards Institute) frameworks. A quantitative comparison of latency, throughput, and operational costs between blockchain-augmented and traditional architectures is provided, together with a technology maturity classification for each application domain. Finally, the paper identifies current limitations, including scalability, regulatory alignment, privacy constraints, and the absence of production-scale pilot data, and outlines open research challenges for the adoption of blockchain in regulated digital trust services. Full article

Biodiversity is declining globally principally because of land degradation and more because of climate change. Its effective conservation is vital for species and habitats, but also to maintain the related ecosystem services they provide for human well-being. In this context, evaluating the ability of Protected Areas (PAs) to cover species distribution under current and future environmental conditions is highly valuable. Considering the distributions of 1692 species of plants in the cross-border region of Grand Genève, located between France and Switzerland, the effectiveness of existing PAs in preserving plant diversity through local hotspots and priority areas for rare and vulnerable species was evaluated. The results show that PAs are moderately effective in conserving plant diversity, but are not expected to lose effectiveness in future conditions because important areas for plant diversity conservation will remain at similar locations. To address this gap, a spatial conservation network combining hotspots and priority areas was identified to cover 30% of the study area. It captures a significantly higher proportion of species distributions under both current and future conditions, and covers a greater representation of rare and ecologically important habitats, such as subalpine meadows and wetlands. The proposed solution aims to inform local stakeholders about areas of high ecological value that could be used to identify the Blue-Green Infrastructure, supporting the expansion of PAs and the improvement of conservation strategies in the face of environmental change. Full article

Recreation is a key ecosystem service provided by mountainous areas. The European Alps are a main attraction for tourists due to their natural landscapes. Nature-based recreation and ecotourism are an opportunity for local communities in alpine valleys. However, tourism may also represent a threat to fragile mountain environments when large numbers of tourists are involved in touristic models based on heavy use of resources. This study aims to provide insights into how local communities in an alpine valley, the Comelico Valley, see the current tourism demand and its future changes. Comelico shares similar environmental and landscape characteristics with the surrounding valleys but is less developed from the touristic point of view. We used the Delphi method on a panel of nine local tourism experts from different areas of operations. The results about the forecast of future activities to be prioritized highlight the importance of diversification of tourism offer towards sustainable activities closer to the concept of nature-based tourism and ecotourism. Activities to be prioritized for development were hiking and thematic hiking, forest well-being initiatives and experience laboratories. These results suggest a potential need to change the present model of mountain tourism towards a more diversified and soft approach to mountain recreation. Full article

Arid region ecosystems are among the most fragile ecological types worldwide. They depend heavily on limited water resources and are strongly influenced by intensive human activities, leading their ecosystem services to exhibit nonlinear and threshold responses to driving factors. Identifying the thresholds of ecosystem services under the combined influence of natural and socio-economic interactive drivers is of great significance for regional ecological risk warning and differentiated management. Taking the Tarim River Basin as a case study, this research establishes an integrated analytical framework that combines causal inference, interaction term construction, interpretable machine learning (XGBoost-SHAP), and piecewise linear regression. The framework is used to evaluate the variations in four types of ecosystem services in 2000, 2010, and 2023, to analyze the interactive effects of driving factors, and to identify their thresholds influencing ecosystem service functions. The results indicate that (1) different types of ecosystem service functions exhibited distinct trends from 2000 to 2023, with habitat quality and water yield showing declining tendencies, while soil conservation and Windbreak and sand fixation demonstrated gradual increases; (2) Causal Screening and interaction modeling revealed that the interaction between precipitation and population density (Pre × Pop) served as the key synergistic driver of changes in the four ecosystem service functions. Both the ecosystem services and the coupled natural–social driving processes exhibited pronounced nonlinear characteristics, with evident trend shifts occurring within specific threshold intervals. (3) The precise coupling thresholds of different ecosystem services under natural–social drivers were identified, intuitively revealing the coupling threshold characteristics of various ecosystem services; (4) The integration of causal inference with interpretable machine learning enhances the reliability of threshold identification, revealing the heterogeneous response mechanisms of different services and providing a quantitative basis for the zoning regulation and differentiated management of regional ecosystems. The findings offer a transferable methodological framework to support ecological governance in arid regions. Full article

Urban lake scenic areas serve as crucial ecological barriers but face acute conflicts between expansion and conservation. Existing research has often overlooked microscale landscape fragmentation and its associated ecological effects. Focusing on the Wuhan East Lake ecotourism scenic area (Wuhan East Lake), this study investigated the spatiotemporal impacts of micro-scale land-use transitions on ecosystem service value (ESV). To evaluate the historical evolution of ESV from 2010 to 2024, an improved equivalent factor method was coupled with a patch-generating land-use simulation (PLUS) model. Spatial autocorrelation and landscape pattern metrics were then incorporated to diagnose structural degradation and establish a foundation for simulating the four development scenarios for 2035. Results demonstrate that sporadic construction expansion led to a decline in total ESV from 2.445 to 2.216 billion CNY, driving a pronounced “core-hot vs. edge-cold” spatial disparity. Among future projections, the Sustainable Development pathway emerges as optimal, effectively balancing economic demands with the need to minimize ecological fragmentation. Ultimately, this study contributes to the literature by integrating microscale landscape fragmentation analysis with a PLUS-based multi-scenario simulation to provide a refined understanding of ecosystem service dynamics in urban lake systems, thereby offering a scientific reference for resilient spatial planning and policymaking. Full article

Creative expression is no longer separate from monetization. It is increasingly structured by the business models that platforms provide. Content monetization has evolved rapidly: early models focused on advertising revenue, followed by brand partnerships, and most recently, the integration of commerce-oriented features at the platform level. YouTube, for example, launched its YouTube Shopping service in South Korea in June 2024, enabling creators to sell products directly through their content. This development demonstrates that commerciality has become intrinsic to the creator economy. While prior research has emphasized factors such as authenticity, less focus has been placed on commerciality itself. This study addresses this gap by analyzing how varying levels of content commerciality affect performance, using real-world data from a Korean YouTube beauty creator agency (N = 286 short-form videos). The analysis tests the effects of three revenue models (organic, sponsored, and content-driven commerce) and two content types (context-focused and product-focused) through multiple regression. Results reveal a trade-off between engagement and revenue, as while content-driven commerce generates significantly higher engagement than sponsored content, it yields lower immediate revenue. Regarding content strategy, contrary to expectations, product-focused content consistently outperforms context-focused content in driving engagement, except within sponsored videos where a context-focused approach effectively mitigates the negative impact of overt commercial intent. These findings demonstrate the divergent efficacy of monetization models and content strategies in the short-form ecosystem. By empirically validating the relationship between commerciality and performance, this study advances theoretical discussions on the platform-driven creator economy and offers practical insights for creators, brands, and platforms navigating this evolving environment. Full article

Airborne particulate matter (PM) poses a major health risk, yet species selection for vertical greening systems (VGS) is poorly quantified. We evaluated PM retention by seven commercially available shade-tolerant species grown in a modular living wall system (LWS) on a north-facing façade at Sapienza University of Rome. After 3 months of in situ exposure, leaves were analyzed via SEM (1000×), collecting 210 images, 30 per species. An automated FIJI/ImageJ pipeline segmented particles, computed equivalent circular diameters, and classified them into (PM < 0.5, PM [0.5, 1), PM [1, 2.5), PM [2.5, 10), and PM ≥ 10 µm). Across species, ultrafine and fine fractions dominated deposits, with the <0.5 µm class typically comprising 60–70% of counts. Vinca minor cv. albomarginata exhibited the highest densities in ultrafine and fine classes, closely followed by Fatsia japonica; Hedera helix captured more coarse particles (2.5–10 µm and >10 µm). Heuchera sanguinea consistently displayed the lowest densities across all size classes. Performance patterns aligned with leaf surface traits: wax-coated, moderately rough or gently structured cuticles favored adhesion, whereas highly irregular microrelief did not consistently enhance retention. Methodological considerations include thresholding sensitivity, use of equivalent circular diameter for irregular particles, and an upper area filter that may undercount large aggregates. The findings identify Vinca minor cv. albomarginata and Fatsia japonica as priority species for PM mitigation in shaded VGS, with Hedera helix complementing coarse PM capture. The results provide trait-based, design-oriented guidance for living wall species selection in Mediterranean urban and indoor contexts. Full article

Mediterranean cork oak forests provide essential ecosystem services but face increasing threats from climate change, ecosystem simplification, and oak decline. Ensuring their long-term sustainability requires governance approaches that integrate regional planning frameworks with international certification standards. This study presents a pioneering case of public cork oak forest management in Alà dei Sardi, Sardinia (Italy), where municipal forest planning was aligned with national and regional regulations and further enhanced through Forest Stewardship Council^® (FSC^®) certification. The FSC system offers internationally recognized standards and the Ecosystem Services Procedure (FSC-PRO-30-006 v2-1) to verify responsible forest management and quantify key ecosystem benefits. The Alà dei Sardi forest is the first publicly owned municipal cork oak forest to achieve FSC Forest Management certification, with demonstrated positive impacts of its management activities on biodiversity conservation, carbon sequestration and storage, water protection, soil conservation, and recreational services. The certification process integrated management planning, stakeholder engagement, monitoring, and adaptive interventions, showing that public institutions can combine legal frameworks with voluntary standards to enhance ecological performance, accountability, and socio-economic value. This case illustrates a potentially scalable and replicable model for sustainable forest governance, linking territorial planning with market-based mechanisms, and provides a practical example of governance for resilient and multifunctional forest systems. Full article

The pervasive adoption of Internet of Things (IoT) devices has profoundly reshaped digital connectivity by enabling real-time data exchange and autonomous interactions on a global scale. While this transformation presents substantial operational benefits, it simultaneously introduces significant security challenges, especially in terms of Identity and Access Management (IAM) for non-human entities, such as sensors, devices, machine agents, and service accounts. Historically, traditional perimeter-based security models, which depend on static trust boundaries and implicit trust for internal actors, have been applied to human identities. However, these models prove inadequate for managing non-human identities. This inadequacy has spurred interest in Zero Trust Architecture (ZTA), an advanced security paradigm based on the principle of “never trust, always verify.” This paper examines the application of ZTA in safeguarding IoT ecosystems, with a particular emphasis on managing non-human identities. The study delves into ZTA’s fundamental principles, such as least privilege, micro-segmentation, continuous monitoring, and identity-centric access control, and evaluates their effective implementation in resource-constrained IoT settings. The research identifies critical implementation challenges and considerations for applying identity-based ZTA within IoT contexts. The findings of this paper underscore that ZTA, when meticulously implemented, provides a robust framework for mitigating the cyber risks inherent in IoT ecosystems. Furthermore, the paper delineates prospective research avenues aimed at integrating ZTA into IoT environments. Ultimately, this study contributes to the expanding body of scholarly knowledge by endorsing Zero Trust as a foundational strategy for contemporary IoT security. Full article

Career assessment instruments for children with special needs are not fully inclusive and precise. This study uses both quantitative and qualitative methods to identify the key problems students face, refine the career matching stages, and assess the desirability, feasibility, and viability of the services developed. This study found that co-design in the preparation and validation of the career matching platform has integrated several aspects, namely people with disabilities’ behavior, interests, and career paths, and has been adjusted to national competency standards, according to the group. The development of this platform uses the Double Diamond approach, including focus group discussions with several extraordinary school teachers across two activities. The existing analysis shows that the fifteen-stage career development model has prepared students for career paths, making it a potential reference for career services for people with disabilities. In addition, implementing a career development model integrated with the platform can make it easier for students to find a job profile that best suits the world of work. The results of this research can be the basis for disability career development policies, programs that bridge students to the world of work, and the formation of an industrial ecosystem that cares more about children with special needs. Full article

Suspended sediment concentration (SSC) and sediment flux (SF) are critical indicators of sediment delivery in the Lower Mekong and underpin deltaic geomorphic stability and ecosystem services. With recent evidence of declining sediment supply caused by upstream regulation and intensive in-channel extraction, there is a pressing need for data-efficient tools to reproduce non-linear sediment dynamics and assist management in the Vietnamese Mekong Delta (VMD). This study evaluates three machine-learning algorithms—Random Forest (RF), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost)—for data-driven prediction of SSC (2009–2023) and SF (2009–2021) at Tan Chau (Viet Nam). The predictive models were developed using daily discharge inputs from Kratie (Cambodia) and local hydrological data, including water levels and discharge, from the Tan Chau station. Across the held-out testing dataset, all models captured substantial variability in both targets, with consistently higher performance for SF than for SSC. RF achieved the highest skill (SSC: R² = 0.783; SF: R² = 0.867), followed by XGBoost and then SVM. Variable-importance analysis indicates that upstream discharge at Kratie is the most influential predictor for both SSC and SF, consistent with basin-scale hydrological forcing governing downstream sediment transport capacity. The observed record at Tan Chau further suggests an attenuation of wet-season SSC peaks during 2018–2022 relative to earlier years, signalling potential sediment-starvation dynamics that warrant continued monitoring. Overall, the results demonstrate the utility of ML-based sediment prediction models as a complement to conventional monitoring and as an evidence base to inform sediment-aware river–delta management and risk mitigation in the Lower Mekong. Full article

Mountainous Mediterranean rivers provide essential ecosystem services but are increasingly affected by land-use change, hydraulic works, and inadequate wastewater management. This study investigates the links between geomorphological transformation and river water quality in the Central Eurytania drainage basin (Greece) over the past two decades, within the institutional framework of European and Greek environmental legislation, with emphasis on the protection and restoration of aquatic ecosystems. Georeferenced satellite imagery from 2003/2010 and 2023, Google Earth Engine (GEE, Python Earth Engine API: 1.7.20)-based spatial analysis, high-resolution UAV orthomosaics, and seasonal spectrophotometric analyses were integrated to assess spatial and temporal dynamics. Results indicate that land-use changes, including the construction of solar parks, expansion of tourism infrastructure, and partial agricultural abandonment, reflect ongoing socio-economic shifts influencing fluvial processes. Water-quality analyses further showed that channel alteration and wastewater inputs jointly degrade ecological conditions. The findings highlight the need for integrated watershed management focused on riparian buffer restoration, improved wastewater control, and systematic monitoring of hydromorphological change. The proposed interdisciplinary framework contributes to the assessment of environmental resilience in Mediterranean mountainous watersheds, which are increasingly vulnerable to climatic and socio-economic pressures. Full article

Coral reefs are among the most biodiverse marine ecosystems, playing irreplaceable roles in maintaining marine ecological balance and coastal services. Under dual pressures of global climate change and human activities, coral bleaching and degradation have become increasingly frequent, creating an urgent need for large-scale, long-term, and highly automated monitoring technologies. In recent years, advances in underwater imaging and deep learning have made visual recognition a core approach for coral classification and health assessment. However, most studies only focus on isolated model accuracy optimization, lacking systematic full-chain analysis integrating datasets, model evolution, cross-domain generalization, engineering constraints, and ecological adaptation, which severely hinders large-scale cross-regional and long-term application. This paper systematically reviews coral visual recognition technologies. It summarizes underwater image acquisition, public dataset characteristics, and annotation system evolution, then compares traditional feature engineering and deep learning in key tasks, highlighting their differences in feature representation and generalization. Four core challenges are identified: class imbalance, poor underwater image quality, weak cross-device/region generalization, and mismatched algorithm metrics with ecological needs. Finally, feasible solutions based on self-supervised pre-training, domain adaptation, and multimodal fusion are discussed to enhance model robustness and ecological interpretability, providing methodological support for intelligent coral reef monitoring systems. Full article