Search Results (5,362)

The red fox (Vulpes vulpes) is a widely distributed and highly adaptive small carnivore known by its generalist diet, which includes small mammals, invertebrates, and fruits. Despite its ecological relevance, how habitat heterogeneity affects its diet across the Mediterranean, a biodiversity hotspot shaped by long-term human disturbance, remains insufficiently synthesized. In this review, we synthesized and analyzed published studies that reported habitat-specific data on the red fox diet in the Mediterranean. Only 12 studies met the selection criteria, and no study directly compared two different habitats. The studied areas covered three dominant habitats: forests, scrublands (garrigue), and agroecosystems, and diet items were grouped in 7 categories: birds, carcasses, fruits, invertebrates, lagomorphs, small mammals, and reptiles. Overall diet composition varied significantly, with invertebrates and fruits being the most frequent diet items. In turn, lagomorphs and reptiles were the least frequent. In turn, diet composition varied little across habitats, indicating that diet variation follows specific local resource abundance regardless of habitat type. Despite the analytical limitations associated with the limited availability of habitat-explicit studies. The results highlight the pronounced dietary plasticity of the red fox and its capacity to integrate resource availability across heterogeneous Mediterranean landscape mosaics. This trophic adaptability and top predator role support various ecosystem functions such as controlling invertebrate and small mammal populations, dispersing seeds, and cycling nutrients, reinforcing the potential of the red fox as functional bioindicator in the Mediterranean. Therefore, sustainable land management, especially in agricultural areas, and restoration efforts for degraded areas should consider the beneficial roles of generalist carnivores like the red fox. Full article

The sustainability of the beef and dairy industry requires a systems approach that integrates environmental stewardship, social responsibility, and economic viability. Over the past two decades, global genetics consortia have advanced data-driven germplasm programs (breeding and conservation programs focusing on genetic resources) to enhance sustainability across cattle systems. These initiatives employ multi-trait selection indices aligned with consumer demands and supply chain trends, targeting production, longevity, health, and reproduction, with outcomes including greenhouse gas mitigation, improved resource efficiency and operational safety, and optimized animal welfare. This study analyzes strategic initiatives, germplasm portfolios, and data platforms from leading genetics companies in the USA, Europe, and Brazil. US programs combine genomic selection with reproductive technologies such as sexed semen and in vitro fertilization to accelerate genetic progress. European efforts emphasize resource efficiency, welfare, and environmental impacts, while Brazilian strategies focus on adaptability to tropical conditions, heat tolerance, and disease resistance. Furthermore, mathematical models and decision support tools are increasingly used to balance profitability with environmental goals, reducing sustainability trade-offs through data-driven resource allocation. Industry-wide collaboration among stakeholders and regulatory bodies underscores a rapid shift toward sustainability-oriented cattle management strategies, positioning genetics and technology as key drivers of genetically resilient and sustainable breeding systems. Full article

Sloping cropland on the Loess Plateau faces severe challenges from soil organic carbon (SOC) depletion and structural instability due to erosion and intensive tillage. Although mulching can enhance SOC sequestration, its long-term effects on the spatial distribution of SOC and aggregates across slopes remain unclear. A 15-year field experiment evaluated five practices—conventional tillage (T), no tillage (NT), straw mulching (SM), plastic film mulching (PM), and ridge–furrow plastic film mulching (RPM)—on SOC storage, aggregate stability, and their variation with different slope positions. Compared to T, all mulching treatments significantly increased SOC concentration by 4.19% to 83.48% in the 0–30 cm layer. SM and RPM notably increased macro-aggregates (>2 mm) and their associated SOC (24.04–56.49% higher than T) by adding organic matter and optimizing micro-topography. Different slope positions strongly influenced SOC redistribution: lower slopes accumulated more SOC than upper slopes due to erosion–deposition processes. Mulching reduced SOC spatial variability and minimized differences between slope positions. Although mulching increased cumulative SOC mineralization compared to T, the long-term net SOC gain was positive, driven by improved aggregate protection and reduced erosion. SM and RPM are recommended for sustainable slope farmland management due to their dual benefits in enhancing carbon sinks and soil stability. This study offers practical strategies for improving soil health and SOC sequestration in vulnerable sloping landscapes. Full article

This paper analyses the role of landscape as a fundamental dimension of post-earthquake recovery in the inland areas of Central Italy, arguing that reconstruction must be understood not only as the repair of damaged buildings but as a broader territorial process affecting identity, spatial organization, and long-term settlement trajectories. In this sense, post-earthquake recovery is also interpreted as a strategic opportunity to reinforce coast–inland relationships, acknowledging the structural interdependence between inland Apennine areas and coastal urban systems. Drawing on insights from applied research conducted in the L’Aquila 2009 crater and on the conceptual framework developed within the PRIN TRIALS project, the paper discusses how seismic events accelerate pre-existing territorial dynamics and produce enduring transformations, particularly in the proximity landscapes surrounding historic centres. Rather than presenting empirical findings, the contribution offers a theoretical and operational framework aimed at integrating landscape considerations into reconstruction processes. It outlines key concepts such as landscape quality, transformative resilience, and permanent temporariness; reviews critical normative aspects linked to emergency procedures; and proposes a set of landscape-oriented guidelines and criteria for the contextual integration of reconstruction projects. These include landscape quality objectives, multiscalar readings of identity values, and operational tools such as visual-impact assessment, Project Reference Context analysis, and principles for managing transformations in peri-urban and historic environments. Overall, the paper argues that adopting a landscape-based perspective can strengthen territorial cohesion, support the sustainable redevelopment of historic centres and their surroundings, and embed post-earthquake reconstruction within broader coast–inland territorial strategies aimed at long-term resilience and balanced regional development in Apennine communities. Full article

The sustainability of resources and ecological integrity are significantly influenced by land use and land cover change (LULCC) dynamics, particularly in ecotonal semi-arid regions where biome transitions are highly sensitive to anthropogenic disturbance and climatic variability. This study aims to assess historical LULCC dynamics and spatial reconfiguration across nine classes (grassland, shrubland, wetlands, forestland, waterbodies, farmed land, built-up land, bare land, and mines/quarries) in the C5 Secondary Drainage Region of South Africa over the three periods 1990–2014, 2014–2022, and 1990–2022. Using the South African National Land Cover datasets and the TerrSet liberaGIS v20.03 Land Change Modeller, this research applied post-classification comparison, transition matrices, asymmetric gain–loss metrics, and patch-based landscape analysis to quantify the magnitude, direction, source–sink dynamics, and spatial reconfiguration of LULCC. Results showed that between 1990 and 2014, Shrubland expanded markedly (+49.1%), primarily at the expense of Grassland, Wetlands, and Bare land, indicating bush encroachment and hydrological stress. From 2014 to 2022, the trend reversed as Grassland increased substantially (+261.2%) while Shrubland declined sharply (−99.3%). Forestland also regenerated extensively (+186%) along riparian corridors, and Waterbodies expanded more than fivefold (+384.6 km²). Over the long period between 1990 and 2022, Built-up land (+30.6%), Cultivated land (+16%), Forestland (+140%), Grassland (+94.4%), and Waterbodies (+25.6%) increased, while Bare land (−58.1%), Mines and Quarries (−56.1%), Shrubland (−98.9%), and Wetlands (−82.5%) decreased. Asymmetric analysis revealed strongly directional transitions, with early Grassland-to-Shrubland conversion likely driven by grazing pressure, fire suppression, and climate variability, followed by a later Shrubland-to-Grassland reversal consistent with fire, herbivory, and ecotonal climate sensitivity. LULC dynamics in the C5 catchment show class-specific spatial reconfiguration, declining landscape diversity (SHDI 1.3 → 0.9; SIDI 0.7 → 0.43), and patch metrics indicating urban and cultivated fragmentation, shrubland loss, and grassland consolidation. Based on these quantified trajectories, we recommend targeted catchment-scale land management, shrubland restoration, and monitoring of anthropogenic hotspots to support ecosystem services, hydrological stability, and sustainable land use in ecotonal regions. Full article

Cocoa production in West Africa supplies most of the global demand but is increasingly constrained by yield stagnation, soil degradation, disease pressure, and climate variability. This review examines how integrating regenerative agriculture (RA) with unmanned aerial systems (UAS) and artificial intelligence (AI) can support more precise and resilient cocoa management across heterogeneous smallholder landscapes. A PRISMA-guided systematic review of peer-reviewed literature published between 2000 and 2024 was conducted, yielding 49 core studies analyzed alongside supporting evidence. The synthesis evaluates regenerative agronomic outcomes, UAV-derived multispectral, thermal, and structural diagnostics, and AI-based analytical approaches for stress detection, yield estimation, and management zoning. Results indicate that regenerative practices consistently improve soil health and yield stability, while UAS data enhance spatial targeting of rehabilitation, shade management, and stress interventions. AI models further improve predictive capacity and decision relevance when aligned with data availability and institutional context, although performance varies across systems. Reported yield stabilization or improvement typically ranges from 12–30% under integrated approaches, with concurrent reductions in fertilizer and water inputs where spatial targeting is applied. The review concludes that effective scaling of RA–UAS–AI systems depends less on technical sophistication than on governance arrangements, extension integration, and cooperative service models, positioning these tools as enabling components rather than standalone solutions for sustainable cocoa intensification. Full article

Accurate estimation of above-ground biomass (AGB) is vital for carbon accounting, biodiversity conservation, and sustainable forest management, especially in tropical regions under strong anthropogenic pressure. This study estimated and mapped AGB in the Atacora Mountain Chain, Togo, using a multi-source remote sensing approach within Google Earth Engine (GEE). Field data from 421 plots of the 2021 National Forest Inventory were combined with Sentinel-1 Synthetic Aperture Radar, Sentinel-2 multispectral imagery, bioclimatic variables from WorldClim, and topographic data. A Random Forest regression model evaluated the predictive capacity of different variable combinations. The best model, integrating SAR, optical, and climatic variables (S1S2allBio), achieved R² = 0.90, MAE = 13.42 Mg/ha, and RMSE = 22.54 Mg/ha, outperforming models without climate data. Dense forests stored the highest biomass (124.2 Mg/ha), while tree/shrub savannas had the lowest (25.38 Mg/ha). Spatially, ~60% of the area had biomass ≤ 50 Mg/ha. Precipitation correlated positively with AGB (r = 0.55), whereas temperature showed negative correlations. This work demonstrates the effectiveness of integrating multi-sensor satellite data with climatic predictors for accurate biomass mapping in complex tropical landscapes. The approach supports national forest monitoring, REDD+ programs, and ecosystem restoration, contributing to SDGs 13, 15, and 12 and offering a scalable method for other tropical regions. Full article

Skyros Island, the largest island of the Sporades Complex (NW Aegean Sea, Greece), preserves a geologically diverse record spanning from the Upper Permian to the Quaternary, including crystalline and non-metamorphosed carbonate rocks, ophiolitic rocks and mélanges, medium-grade metamorphic units, rare Miocene volcanic rocks, and impressive fossil-bearing sediments and tufa deposits, together with historically significant quarry and mining landscapes. Through a comprehensive evaluation of the geological heritage of Skyros, this study proposes a transferable, results-based framework for geoconservation, geoeducation, and tourism space management within a geopark context. A systematic inventory of twenty (20) geosites, including six (6) flagship case studies, was established based on scientific value, dominant geodiversity type, risk of degradation, accessibility, educational and tourism potential. The assessment integrates the Scientific Value and Risk of Degradation criteria with complementary management and sustainability indicators. The results demonstrate consistently high scientific value across the selected geosites, with several reaching maximum or near-maximum scores due to their rarity, integrity, and reference character at a regional to international scale. Although some geosites exhibit elevated degradation risk, overall vulnerability is considered manageable through targeted conservation measures and spatially explicit visitor management. Based on the assessment results, a network of thematic georoutes was developed and evaluated using route-level indicators, including number of geosites, route length, educational potential, tourism suitability, accessibility, and contribution to responsible geotourism. The study demonstrates how integrated geosite and georoute assessment can support sustainable land management and confirms that Skyros Island meets key criteria for inclusion in the Hellenic Geoparks Network, providing a robust scientific basis for future UNESCO Global Geopark designation. Full article

Fungal diseases continue to limit global crop production and drive major economic losses. Conventional diagnostic and control approaches depend on time-consuming culture-based methods and broad-spectrum chemicals, which offer limited precision. Advances in molecular identification have changed this landscape. PCR, qPCR, LAMP, sequencing and portable platforms enable rapid and species-level detection directly from plant tissue. These tools feed into RNA-based control strategies, where knowledge of pathogen genomes and sRNA exchange enables targeted suppression of essential fungal genes. Host-induced and spray-induced gene silencing provide selective control without the long-term environmental costs associated with chemical use. CRISPR/Cas9 based tools now refine both diagnostics and resistance development, and bioinformatics improves target gene selection. Rising integration of artificial intelligence indicates a future in which disease detection, prediction and management connect in near real time. The major challenge lies in limited field validation and the narrow range of fungal species with complete molecular datasets, yet coordinated multi-site trials and expansion of annotated genomic resources can enable wider implementation. The combined use of molecular diagnostics and RNA-based strategies marks a shift from disease reaction to disease prevention and moves crop protection towards a precise, sustainable and responsive management system. This review synthesizes the information related to current molecular identification tools and RNA-based management strategies, and evaluates how their integration supports precise and sustainable approaches for fungal disease control under diverse environmental settings. Full article

The Arid Region of Northwest China (ARNC) functions as a critical ecological barrier for the Eurasian hinterland. To clarify the non-linear drivers of eco-environmental dynamics, a long-term (2000–2024) Remote Sensing Ecological Index (RSEI) time series was constructed and analyzed using an interpretable machine learning framework (XGBoost-SHAP). The analysis reveals pronounced spatial asymmetry in ecological evolution: improvements are concentrated in localized, human-managed areas, while degradation occurs as a diffuse process driven by geomorphological inertia. The ARNC exhibits low-level stability (mean RSEI 0.25–0.30) and marked unbalanced dynamics, with significant degradation (19.9%) affecting more than twice the area of improvement (6.5%). Attribution analysis identifies divergent driving mechanisms: ecological improvement (R² = 0.559) is primarily anthropogenic (58.3%), whereas degradation (R² = 0.692) is mainly governed by natural constraints (58.4%), particularly structural topographic factors, where intrinsic landscape vulnerability is exacerbated by human activities. SHAP analysis corroborates a “Greenness-Quality Paradox” in stable agroecosystems, where high vegetation cover coincides with reduced evaporative cooling and secondary salinization from irrigation, resulting in declining Eco-Environmental Quality (EEQ). A zero-threshold effect for grazing intensity is also identified, indicating that any increase beyond the baseline immediately initiates ecological decline. In response, a Resist-Accept-Direct (RAD) framework is proposed: direct salt-water balance regulation in oases, resist hydrological cutoff in ecotones, and accept natural dynamics in the desert matrix. These findings provide a scientific basis for reconciling artificial greening initiatives with hydrological sustainability in water-limited regions. Full article

Cloning large biosynthetic gene clusters (BGCs) is fundamental to unlocking microbial natural product potential for drug discovery and biotechnology. These clusters encode diverse bioactive compounds, but their size, high GC content, and complex architecture pose significant technical challenges. This review scrutinises recent advances in BGC cloning strategies, categorising them into three major groups: (1) direct release-and-capture methods, (2) genome-integrated preconditioning systems, and (3) CRISPR-assisted hybrid platforms. This review compares the strengths, limitations, and reported efficiencies of BGC cloning strategies, highlighting trade-offs in precision, scalability, and workflow complexity. Emerging trends, such as AI-driven genome mining, modular synthetic biology toolkits, and high-throughput automation, are reshaping the cloning landscape, enabling predictive design and streamlined assembly of clusters exceeding 100 kb. By integrating comparative analysis with future perspectives, this review provides outlines on how next-generation strategies will accelerate heterologous expression, natural product discovery, and sustainable biomanufacturing. Full article

Extreme wildfires are becoming increasingly frequent and severe across many regions worldwide, driven by climate change, land-use transitions, and long-standing fire-suppression legacies. In this context, Nature-based Solutions (NbS)—defined as actions that work with ecological processes to address societal challenges while providing biodiversity and socio-economic benefits—offer a promising yet underdeveloped pathway for enhancing wildfire resilience. This Special Issue brings together eleven contributions spanning empirical ecology, landscape configuration, simulation modelling, spatial optimisation, ecosystem service analysis, governance assessment, and community-based innovation. Collectively, these studies demonstrate that restoring ecological fire regimes, promoting multifunctional landscapes, and integrating advanced decision support tools can substantially reduce wildfire hazard while sustaining ecosystem functions. They also reveal significant governance barriers, including fragmented policies, limited investment in prevention, and challenges in incorporating social demands into territorial planning. By synthesising these insights, this editorial identifies several strategic priorities for advancing NbS in fire-prone landscapes: mainstreaming prevention within governance frameworks, strengthening the science–practice interface, investing in long-term socio-ecological monitoring, managing trade-offs transparently, and empowering local communities. Together, the findings highlight that effective NbS emerge from the alignment of ecological, technological, institutional, and social dimensions, offering a coherent pathway toward more resilient, biodiverse, and fire-adaptive landscapes. Full article

Landscape ecology is the study of how different land uses and natural areas are arranged across a region, and how these spatial patterns affect biodiversity, ecosystem health, and human impacts. To measure and track these patterns, ecologists are using a range of tools and metrics that capture features such as connectivity, fragmentation, and the balance between natural and developed land. One such method is the Landscape Mosaic (LM) approach which classifies land into categories based on the mix of agriculture, natural habitats, and developed areas (e.g., urban), providing an integrated view of how humans are influencing ecosystems. Until recently, LM was only available through a specialized software package (i.e., GuidosToolbox), which limits its flexibility, interaction with other tools, and integration in scientific workflows. To address this, we present PyLM, a Python-based implementation of the LM model, making it easier for researchers, planners, and conservationists to analyze land use/cover (LUC) maps, generate statistics, and embed results into broader environmental workflows. The applicability of PyLM is demonstrated through a use case based on a LUC dataset for Switzerland. This new implementation enhances accessibility, supports sustainability assessments, and strengthens the ability to monitor landscapes over time. Full article

Repeated sowing of winter cereals represents one of the adaptive dryland approaches to make more sustainable the rainfed agriculture activities in southern Kazakhstan. This study conducted a multi-year reconstruction of crop transitions using Sentinel-2 imagery for 2018–2025, based on the combined analysis of Normalized Difference Vegetation Index (NDVI) temporal profiles and the Plowed Land Index (PLI), enabling the creation of a field-level harmonized classification set. The transition “spring crop → winter crop” was used as a formal indicator of repeated winter sowing, from which annual repeat layers and an integrated metric, the R-index, were derived. The results revealed a pronounced spatial concentration of repeated sowing in foothill landscapes, where terrain heterogeneity and locally elevated moisture availability promote the recurrent return of winter cereals. Comparison of NDVI composites for the peak spring biomass period (1–20 May) showed a systematic decline in NDVI with increasing R-index, indicating the cumulative effect of repeated soil exploitation and the sensitivity of winter crops to climatic constraints. Precipitation analysis for 2017–2024 confirmed the strong influence of autumn moisture conditions on repetition phases, particularly in years with extreme rainfall anomalies. These findings demonstrate the importance of integrating multi-year satellite observations with climatic indicators for monitoring the resilience of agricultural systems. The identified patterns highlight the necessity of implementing nature-based solutions, including contour–strip land management and the development of protective shelterbelts, to enhance soil moisture retention and improve the stability of regional agricultural landscapes. Full article

The current landscape of Environmental, Social, and Governance (ESG) ratings is fragmented by methodological inconsistencies, lack of standardization, and substantial divergences among rating providers. These discrepancies hinder comparability, reduce transparency, and undermine the reliability of ESG assessments, limiting their effectiveness for both investors and corporate decision-makers. To address these issues, this study introduces a standardized approach to ESG rating construction, aimed at enhancing the objectivity and interpretability of corporate sustainability evaluations. The methodology integrates the Global Reporting Initiative standards with the United Nations Sustainable Development Goals, thereby identifying a coherent set of key performance indicators across the ESG pillars. By relying solely on publicly available data and incorporating mechanisms for managing missing information, the model provides a transparent and reproducible framework for sustainability assessment. Its validity is demonstrated through an empirical application to firms in the financial and manufacturing sectors across Europe and the United States, with benchmarking against established ratings from providers. Rather than replicating existing ESG scores, the model offers a transparent and reproducible alternative built on disclosed performance data, without relying on forward-looking statements, corporate promises, or commercial data providers. By penalizing non-disclosure and enabling sector-specific sensitivity analysis, the framework supports more accountable and customizable sustainability assessments, helping align ESG evaluations with strategic and regulatory priorities. Full article