Search Results (1,404)

As agricultural land continues to expand, the conversion of forests to farmland has intensified, significantly altering the structure and function of agroecosystems. However, the dynamic ecological responses and their interactions with economic outcomes remain insufficiently modeled. This study proposes an integrated framework that combines a dynamic food web model with the Eco-Economic Benefit and Sustainability (EEBS) model, utilizing empirical data from Brazil and Ghana. A system of ordinary differential equations solved using the fourth-order Runge–Kutta method was employed to simulate species interactions and energy flows under various land management strategies. Reintroducing key species (e.g., the seven-spot ladybird and ragweed) improved ecosystem stability to over 90%, with soil fertility recovery reaching 95%. In herbicide-free scenarios, introducing natural predators such as bats and birds mitigated disturbances and promoted ecological balance. Using XGBoost (Extreme Gradient Boosting) to analyze 200-day community dynamics, pest control, resource allocation, and chemical disturbance were identified as dominant drivers. EEBS-based multi-scenario optimization revealed that organic farming achieves the highest alignment between ecological restoration and economic benefits. The model demonstrated strong predictive power ($R^2$ = 0.9619, RMSE = 0.0330), offering a quantitative basis for green agricultural transitions and sustainable agroecosystem management. Full article

Amaranthus is appointed as a common weed associated with crops. The research was designed to survey the Amaranth existence pattern throughout the Fayoum Depression, Egypt, accompanied with a community vegetation analysis. The study was extended to collect and analyze associated soil samples. The obtained results figured out the prevalence of dicot families, herb growth forms, therophyte followed by phanerophyte life forms, the Pantropical monoregional chorotype, and the Mediterranean and Sudano-Zambezian followed by the Irano-Turanian pluri-regional chorotype. Multilevel pattern analysis stated that Gossypium barbadense, Corchorus olitorius, Sorghum bicolor, Sesamum indicum, and Zea mays are indicator species most related to Amaranth occurrence and prediction. NMDS analysis denoting that the Ibshaway, Youssef Al Seddik, Itsa, and Fayoum districts are the most representative districts for Amaranth existence on the basis of edaphic resources. Itsa and Youssef Al Seddik, in addition to Itsa and Fayoum, resemble each other in species composition. High pH and CaCO₃ percentages were discriminatory in Ibshaway, Itsa, and Youssef Al Seddik. Ni was the cornerstone for districts partitioning in pruned trees. Finally, Amaranth was flourishing in both comfortable and harsh habitats with cultivated crops and orchards, as well as on the outskirts. The findings are considered to be valorized by decision makers in arable land management. Full article

Microbial carbon use efficiency (CUE) is an important indicator of soil organic carbon accumulation and loss and a key parameter in biogeochemical cycling models. Its regulatory mechanism is highly dependent on microbial communities and their dynamic mediation of abiotic factors. Land-use change (e.g., agricultural expansion, deforestation, urbanization) profoundly alter carbon input patterns and soil physicochemical properties, further exacerbating the complexity and uncertainty of CUE. Existing carbon cycle models often neglect microbial ecological processes, resulting in an incomplete understanding of how microbial traits interact with environmental factors to regulate CUE. This paper provides a comprehensive review of the microbial regulation mechanisms of CUE under land-use change and systematically explores how microorganisms drive organic carbon allocation through community compositions, interspecies interactions, and environmental adaptability, with particular emphasis on the synergistic response between microbial communities and abiotic factors. We found that the buffering effect of microbial communities on abiotic factors during land-use change is a key factor determining CUE change patterns. This review not only provides a theoretical framework for clarifying the microbial-dominated carbon turnover mechanism but also lays a scientific foundation for the precise implementation of sustainable land management and carbon neutrality goals. Full article

Landslides are among the most hazardous natural phenomena affecting Greater Abidjan, causing significant economic and social damage. Strategic planning supported by geographic information systems (GIS) can help mitigate potential losses and enhance disaster resilience. This study evaluates landslide susceptibility using logistic regression and frequency ratio models. The analysis is based on a dataset comprising 54 mapped landslide scarps collected from June 2015 to July 2023, along with 16 thematic predictor variables, including altitude, slope, aspect, profile curvature, plan curvature, drainage area, distance to the drainage network, normalized difference vegetation index (NDVI), and an urban-related layer. A high-resolution (5-m) digital elevation model (DEM), derived from multiple data sources, supports the spatial analysis. The landslide inventory was randomly divided into two subsets: 80% for model calibration and 20% for validation. After optimization and statistical testing, the selected thematic layers were integrated to produce a susceptibility map. The results indicate that 6.3% (0.7 km²) of the study area is classified as very highly susceptible. The proportion of the sample (61.2%) in this class had a frequency ratio estimated to be 20.2. Among the predictive indicators, altitude, slope, SE, S, NW, and NDVI were found to have a positive impact on landslide occurrence. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), demonstrating strong predictive capability. These findings can support informed land-use planning and risk reduction strategies in urban areas. Furthermore, the prediction model should be communicated to and understood by local authorities to facilitate disaster management. The cost function was adopted as a novel approach to delineate hazardous zones. Considering the landslide inventory period, the increasing hazard due to climate change, and the intensification of human activities, a reasoned choice of sample size was made. This informed decision enabled the production of an updated prediction map. Optimal thresholds were then derived to classify areas into high- and low-susceptibility categories. The prediction map will be useful to planners in helping them make decisions and implement protective measures. Full article

Archaeological sites located on the edge of growing cities often struggle to reconcile heritage protection with rapid development. To understand this tension, we examined a 50.83 km² zone around the Western Han Imperial Mausoleums in the Qin-Han New District. Using Landsat images from 1992, 2002, 2012, and 2022, this study applied supervised classification, land-use transfer matrices, and dynamic-degree analysis to trace three decades of land-use change. From 1992 to 2022, built-up land expanded by 29.85 percentage points, largely replacing farmland, which shrank by 35.64 percentage points and became fragmented. Forest cover gained a modest 5.78 percentage points and migrated eastward toward the mausoleums. Overall, urban growth followed a “spread–integrate–connect” pattern along major roads. This study interprets these trends through five interrelated drivers, including policy, planning, economy, population, and heritage protection, and proposes an integrated management model. The model links archaeological pre-assessment with land-use compatibility zoning and active community participation. Together, these measures offer a practical roadmap for balancing conservation and sustainable land management at imperial burial complexes and similar urban fringe heritage sites. Full article

Traffic crashes represent a major challenge for road safety, public health, and mobility management in complex urban environments, particularly in metropolitan areas characterized by intense traffic flows, high population density, and strong commuter dynamics. The development of short-term traffic crash prediction models represents a fundamental line of analysis in road safety research within the scientific community. Among these efforts, macro-level modeling plays a key role by enabling the analysis of the spatiotemporal relationships between diverse factors at an aggregated zonal scale. However, in cities like Bogotá, predicting short-term traffic crashes remains challenging due to the complexity of these spatiotemporal dynamics, underscoring the need for models that more effectively integrate spatial and temporal data. This paper presents a strategy based on deep learning techniques to predict short-term spatiotemporal traffic crashes in Bogotá using 2019 data on socioeconomic, land use, mobility, weather, lighting, and crash records across TMAU and TAZ zones. The results showed that the strategy performed with a model called SpatioConvGru-Net with top performance at the TMAU level, achieving $R^2$ = 0.983, MSE = 0.017, and MAPE = 5.5%. Its hybrid design captured spatiotemporal patterns better than CNN, LSTM, and others. Performance improved at the TAZ level using transfer learning. Full article

As the cradle of Jiangnan culture, Suzhou is home to a dense concentration of historical architectural heritage that is currently facing existential threats from rapid urbanization. This study aims to develop a spatial heritage corridor network for conservation and sustainable utilization. Using kernel density estimation, this study identifies 15 kernel density groups, along with the Analytic Hierarchy Process (AHP), to pinpoint clusters of historical architectural heritage and assess the involved resistance factors. Current Effective Conductance (CEC) theory is further applied to model spatial flow relationships among heritage nodes, leading to the delineation of 27 heritage corridors and revealing a spatial structure characterized by one primary core, one secondary core, and multiple peripheral zones. Based on 15 source points, six cultural relics-themed routes are proposed—three land-based and three waterfront routes—connecting historical sites, towns, and ecological areas. The study further recommends a resource management strategy centered on departmental collaboration, digital integration, and community co-governance. By integrating historical architectural types, settlement forms, and ecological patterns, the research builds a multi-scale narrative and experience system that addresses fragmentation while improving coordination and sustainability. This framework delivers practical advice on heritage conservation and cultural tourism development in Suzhou and the broader Jiangnan region. Full article

National parks represent a global initiative for biodiversity conservation and environmentally sustainable societal development, with China having launched its own national park program. The establishment and operation of these parks significantly impact local residents’ livelihoods. Based on DFID’s Sustainable Livelihoods Framework, an assessment tool introduced by the UK Department for International Development (DFID) for evaluating the livelihood standards of residents, this study constructs a structural equation modeling (SEM) framework to analyze how national parks affect residents’ livelihoods, discussing livelihood risk management and feasible capacity-building interventions. Focusing on the Northeast Tiger and Leopard National Park as a case study, the research reveals that indirect wildlife-inflicted damage poses more pronounced negative impacts on local communities than park establishment policies. Both regulatory land-use restrictions and wildlife conflicts disrupt land-based livelihood activities, ultimately affecting residents’ livelihood stability. Mitigation requires comprehensive measures, including retaining essential farmland; providing vocational skill training; offering specialized loans; diversifying employment channels; and improving compensation mechanisms to safeguard residents’ livelihood security. Full article

Geo-historical information deduced from geo-iconographical resources, derived from extensive research and the selection of cartographies and historical documents, enabled the investigation of the natural and anthropic transformations of the perifluvial area of the Po River in the Emilia-Romagna region (Italy). This territory, significant in terms of its historical, cultural, and environmental contexts, for centuries has been the scene of flood events. These have characterised the morphological and dynamic variability in the riverbed and relative floodplain. The close relationship between man and river is well documented: the interference induced by anthropic activity has alternated with the sometimes-damaging effects of river dynamics. The attention given to the fluvial region of the Po River and its main tributaries, in a peculiar lowland sector near Parma, is critical for understanding spatial–temporal changes contributing to current geo-hydrological risks. A GIS project outlined the geomorphological aspects that define the considerable variations in the course of the Po River (involving width reductions of up to 66% and length changes of up to 14%) and its confluences from the 16th to the 21st century. Knowledge of anthropic modifications is essential as a tool within land-use planning and enhancing community awareness in risk-mitigation activities and strategic management. This study highlights the importance of interdisciplinary geo-historical studies that are complementary in order to decode river dynamics in damaging flood events and latent hazards in an altered river environment. Full article

Guadua amplexifolia J. Presl is a Neotropical bamboo native to southern Mexico through Central America to Colombia, where it thrives in riparian zones of the San Jorge River basin. Despite its ecological and socio-economic importance, its environmental dynamics and provision of ecosystem services remain poorly understood. This study (1) quantifies spatial and temporal land use/cover changes in the municipality of Montelíbano between 2002 and 2022 and (2) evaluates the ecosystem services that local communities derive from in 2002, 2012, and 2022, and they were classified in QGIS using G. amplexifolia. We applied a supervised classification of Landsat imagery (2002, 2012, 2022) in QGIS, achieving 85% overall accuracy and a Cohen’s Kappa of 0.82 (n = 45 reference points). For the social assessment, we held participatory workshops and conducted semi-structured interviews with artisans, fishers, authorities, and NGO representatives; responses were manually coded to extract key themes. The results show a 12% decline in total vegetated area from 2002 to 2012, followed by an 8% recovery by 2022, with bamboo-dominated stands following a similar pattern. Communities identified raw material provision (87% of mentions), climate regulation (82%), and cultural–recreational benefits (58%) as the most important services provided by G. amplexifolia. This is the first integrated assessment of G. amplexifolia’s landscape dynamics and community-valued services in the San Jorge basin, highlighting its dual function as a renewable resource and a natural safeguard against environmental risks. Our findings offer targeted recommendations for management practices and land use policies to support the species’ conservation and sustainable utilization. Full article

This research paper presents an assessment of geohazards on Lefkas Island, Greece, using Geographic Information System (GIS) technology to map risk and enhance public awareness through an interactive web application. Natural hazards such as landslides, floods, wildfires, and desertification threaten both the safety of residents and the island’s tourism-dependent economy, particularly due to its seismic activity and Mediterranean climate. By combining the Sendai Framework for Disaster Risk Reduction with GIS capabilities, we created detailed hazard maps that visually represent areas of susceptibility and provide critical insights for local authorities and the public. The web application developed serves as a user-friendly platform for disseminating hazard information and educational resources, thus promoting community preparedness and resilience. The findings highlight the necessity for proactive land management strategies and community engagement in disaster risk reduction efforts. This study underscores GIS’s pivotal role in fostering informed decision making and enhancing the safety of Lefkas Island’s inhabitants and visitors in the face of environmental challenges. Full article

Plastic pollution in marine environments is a globally recognized concern that poses ecological and economic threats. While 80% of plastic originates from land, 20% comes from sea-based sources like shipping and fishing. Comprehensive assessments of fishing-related plastics are limited but crucial for mitigation. This study analyzed the distribution and temporal evolution of three fishing-related items (EPS fish boxes, fragments, and buoys) along the Bocassette spit in the northern Adriatic Sea, a region with high fishing and aquaculture activity. UAV monitoring (November 2019, June/October 2020) and structured interviews with Po Delta fishermen were conducted. The collected debris was mainly EPS, with boxes (54.8%) and fragments (39.6%). Fishermen showed strong awareness of degradation, identifying plastic as the primary litter type and reporting gear loss. Litter concentrated in active dunes and the southern sector indicates human and riverine influence. Persistent items (61%) at higher elevations suggest longer residence times. Mapped EPS boxes could generate billions of micro-particles (e.g., ~10¹³). The results reveal a complex interaction between natural processes and human activities in litter distribution. This highlights the need for integrated management strategies, like improved waste management, targeted cleanup, and community involvement, to reduce long-term impacts on vulnerable coastal ecosystems. Full article

The common oak (Quercus robur L.), though ecologically important and long-lived, has declined in Northern Europe due to historical land use and conifer-dominated forestry. In Latvia, where its distribution is limited, oaks support a rich biodiversity through features like tree-related microhabitats (TreMs) and diverse epiphytic communities. This study compared TreM and epiphyte diversity between planted mature oaks and relict champion oak trees across 16 forest stands. Epiphyte species were recorded using fixed-area frames on tree trunks, and TreMs were categorized following a hierarchical typology. Champion trees hosted significantly more TreMs and a greater variety, including 10 unique TreMs. While overall epiphyte diversity indices did not differ significantly, champion trees supported more specialist and woodland key habitat indicator species. The findings underscore the ecological value of legacy trees, which provide complex habitats essential for specialist taxa and indicators of forest continuity. Conserving such trees is vital for maintaining forest biodiversity and supporting ecosystem resilience in managed landscapes. Full article

In recent years, remote sensing and geographic information systems (GISs) have become essential tools for effective landscape management. This study utilizes these technologies to analyze land use and land cover (LULC) changes in Dibru-Saikhowa National Park, a riverine ecosystem in Assam, India, from its designation as a national park in 2000 through 2024. The satellite imagery was used to classify LULC types and track landscape changes over time. In 2000, grasslands were the dominant land cover (28.78%), followed by semi-evergreen forests (25.58%). By 2013, shrubland became the most prominent class (81.31 km²), and degraded forest expanded to 75.56 km². During this period, substantial areas of grassland (29.94 km²), degraded forest (10.87 km²), semi-evergreen forest (12.33 km²), and bareland (10.50 km²) were converted to shrubland. In 2024, degraded forest further increased, covering 80.52 km² (23.47%). This change resulted since numerous areas of shrubland (11.46 km²) and semi-evergreen forest (27.48 km²) were converted into degraded forest. Furthermore, significant shifts were observed in grassland, shrubland, and degraded forest, indicating a substantial and consistent decline in grassland. These changes are largely attributed to recurring Brahmaputra River floods and increasing anthropogenic pressures. This study recommends a targeted Grassland Recovery Project, control of invasive species, improved surveillance, increased staffing, and the relocation of forest villages to reduce human impact and support community-based conservation efforts. Hence, protecting the landscape through informed LULC-based management can help maintain critical habitat patches, mitigate anthropogenic degradation, and enhance the survival prospects of native floral and faunal assemblages in DSNP. Full article

The efficient management of urban parking systems has emerged as a pivotal issue in today’s smart cities, where increasing vehicle populations strain limited parking infrastructure and challenge sustainable urban mobility. Aligned with the United Nations 2030 Agenda for Sustainable Development and the strategic goals of smart city planning, this study presents a sustainability-driven, multiagent simulation-based framework to model, analyze, and optimize smart parking dynamics in congested urban settings. The system architecture integrates ground-level IoT sensors installed in parking spaces, enabling real-time occupancy detection and communication with a centralized system using low-power wide-area communication protocols (LPWAN). This study introduces an intelligent parking guidance mechanism that dynamically directs drivers to the nearest available slots based on location, historical traffic flow, and predicted availability. To manage real-time data flow, the framework incorporates message queuing telemetry transport (MQTT) protocols and edge processing units for low-latency updates. A predictive algorithm, combining spatial data, usage patterns, and time-series forecasting, supports decision-making for future slot allocation and dynamic pricing policies. Field simulations, calibrated with sensor data in a representative high-density urban district, assess system performance under peak and off-peak conditions. A comparative evaluation against traditional first-come-first-served and static parking systems highlights significant gains: average parking search time is reduced by 42%, vehicular congestion near parking zones declines by 35%, and emissions from circling vehicles drop by 27%. The system also improves user satisfaction by enabling mobile app-based reservation and payment options. These findings contribute to broader sustainability goals by supporting efficient land use, reducing environmental impacts, and enhancing urban livability—key dimensions emphasized in sustainable smart city strategies. The proposed framework offers a scalable, interdisciplinary solution for urban planners and policymakers striving to design inclusive, resilient, and environmentally responsible urban mobility systems. Full article