Search Results (346)

River ecological restoration in lowland plain basins is often constrained by fragmented river networks, degraded riparian zones, eutrophication risk, and intensive human disturbance. Conventional monitoring approaches rarely connect watershed-scale dynamics with responses from typical restoration units, limiting quantitative evaluation and the separation of direct project outcomes from broader environmental variability. To address this gap, this study developed a collaborative satellite–unmanned aerial vehicle (UAV)–unmanned surface vehicle (USV) monitoring framework and applied it to the Nihe River Basin, China, a lowland plain river undergoing systematic restoration under the Shan-shui Initiative. The framework combines Sentinel-2 time-series imagery, high-resolution Gaofen-1, Gaofen-2, and Jilin-1 imagery, UAV orthophotos, USV observations, and auxiliary environmental datasets. Unlike single-scale monitoring approaches, it links watershed-scale indicators, including water-body dynamics, chlorophyll-related eutrophication risk, riparian ecological background, and soil-water conservation capacity, with unit-scale diagnosis of riparian buffer and riverine wetland restoration. Results showed that river water-body area increased from 37.78 km² to 40.59 km² during 2021–2024, while normalized difference chlorophyll index (NDCI)-based eutrophication risk improved in 9.12% of the monitored river area and degraded in only 0.47%. Riparian vegetation cover remained high, whereas regional soil-water conservation capacity declined due to climatic factors, revealing asynchronous responses between local recovery and regional background conditions. At the unit scale, riparian buffer restoration enhanced buffer continuity and near-bank water quality, as reflected by decreased chemical oxygen demand (COD), increased dissolved oxygen (DO), and limited ammonia nitrogen (NH₃-N) improvement. Riverine wetland restoration promoted land-use adjustment and ecological spatial reorganization. This cross-scale evidence chain supports adaptive management of inland river and wetland restoration projects. Full article

Croatia’s diverse agroecological zones, from Mediterranean coastal areas to continental lowlands, enable the cultivation of a broad portfolio of traditional fruit species that contribute simultaneously to biodiversity conservation, rural livelihoods, and the development of value-added food and beverage products. This review compiles and harmonizes evidence on six economically and culturally relevant crops and product chains—grapevine and wine, apple, pear, quince, sour cherry, mulberry, and plum with the traditional spirit šljivovica—focusing on genetic resources and cultivar diversity, agronomic and environmental performance, bioactive composition and potential health relevance, processing routes and by-product valorization, and the socio-economic roles of geographical indications, gastronomy, and tourism. Across species, the literature highlights recurring sustainability levers: safeguarding indigenous and old cultivars as reservoirs of adaptive traits under climate change; reducing chemical inputs through cultivar choice, organic and low-input systems, cover crops, and resistant genotypes; strengthening circularity by converting pomace and other residues into spirits, vinegars, functional ingredients, feed, compost, or energy carriers; and increasing rural value capture through branding, protected origin schemes, and experiential tourism. At the same time, production systems face shared constraints, including fragmentation of holdings, labour shortages, phytosanitary pressures, and the need to optimize processing technologies to preserve sensory and bioactive quality while meeting safety and regulatory requirements. By integrating crop-specific evidence with cross-cutting sustainability themes, this review outlines a coherent framework for positioning traditional Croatian fruit resources and their derived products within contemporary sustainable food system transitions. Full article

This study investigates how different rural landscape types shape visual attention and physiological responses, with the aim of informing more targeted rural landscape renewal. Four typical rural landscape types in the suburbs of Hefei, China, were examined: Flat Farmland (FF), Hilly Forest (HF), Developed Plain (DP), and Water-network Lowland (WNL). All four study villages are project villages in the suburban area of Hefei where rural revitalization is currently being advanced. This study therefore treats them as empirical cases within the context of rural revitalization in China, using them to examine perceptual differences among rural landscape types and their implications for rural landscape renewal. A two-stage research design was adopted to balance field realism and laboratory control. In the first stage, 40 representative scene images were selected by combining field video records with fluctuations in on-site skin conductance response (SCR). In the second stage, laboratory experiments were conducted while participants viewed the selected images, during which eye-tracking, skin conductance, and heart rate data were recorded simultaneously. These measures were used to characterize visual attention allocation and autonomic physiological responses across different rural landscape types, rather than to directly measure landscape preference. For Area of Interest (AOI) analysis, each image was coded into six landscape element categories: vegetation, buildings, roads, sky, vernacular buildings, and water bodies. The results revealed significant typological differences in overall visual search patterns and autonomic responses. Gaze hotspots were concentrated on identifiable targets and boundary regions in the foreground and midground, whereas the sky attracted relatively limited attention. FF primarily emphasized vernacular buildings and farmland boundaries, HF emphasized settlement interfaces and spatial transition nodes, DP emphasized road junctions and facilities along routes, and WNL emphasized water bodies and water–land interface zones. These findings suggest that a two-stage multimodal design can provide supporting evidence for understanding type-specific perceptual responses and can support more targeted strategies for rural landscape renewal. Full article

In 2023, Tropical Cyclone Freddy caused severe damage in southern Malawi, flooding much of the lowland area near Lake Chilwa and displacing many residents. This study evaluates long-term, region-specific mitigation strategies to lessen future risks, using a novel approach that combines drone and satellite data, building footprints, and 3D simulations to analyze how building elevation affects flood damage and assess Property-Level Flood Risk Adaptation measures. Results show a significant difference in ground elevation between affected and unaffected buildings, with damaged structures generally at lower levels. The 3D simulation confirmed a water-level rise of approximately 3.0 m caused by Freddy. Scenario analysis indicates that elevating buildings by 2.0, 2.5, and 3.0 m could reduce direct flood exposure and 64%, 76%, and 91% of damage, respectively. These insights can inform the development of targeted regional risk-mitigation strategies through Property-Level Flood Risk Adaptation in high-risk areas. Full article

Climate-driven intensification of pluvial and fluvial flooding increasingly challenges lowland cities in Central Europe, while conventional protection and land-use controls offer limited flexibility under growing hydrological variability. A planning-oriented framework is developed and tested to integrate hydro-adaptive housing into climate-resilient urban development using three typologies: elevated foundations, amphibious dwellings and modular floating platforms. The framework links hazard profiles and site-enabling conditions to typology selection and considers supporting blue–green measures within the broader adaptation context. It is applied to three flood-prone settings in northern Poland representing a coastal delta, a river confluence and a lower-river terrace. The methodology combines GIS-based hazard mapping; one-dimensional unsteady-flow HEC-RAS simulations for 50-, 100- and 500-year design events; and parametric structural modelling in Rhino–Grasshopper. Performance is assessed using maximum inundation depth, surface-water retention time, and a probabilistic building damage index. Amphibious dwellings reduce modelled 100-year flood damage by 62% relative to slab-on-grade construction, while modular floating platforms maintain habitability under water-level rises exceeding 5.0 m. In addition, bioretention and blue–green corridors reduce retention time by 18–31%. The results provide a planning-oriented decision logic for expanding adaptive housing options in flood-prone lowland settings under increasing hydrological variability. Full article

Tropical coastal regions exhibit pronounced spatial and temporal variability in rainfall driven by seasonal atmospheric circulation and coastal–orographic interactions. Accurate representation of the temporal distribution of rainfall is essential for hydrologic modeling and infrastructure design. This study develops regionalized Huff curves for the Department of Magdalena, Colombia, addressing a critical gap in the characterization of rainfall temporal patterns in tropical coastal regions. A total of 270 short-duration (5–6 h) rainfall events from automatic stations were converted into normalized cumulative mass curves. The resulting curves were grouped into homogeneous temporal patterns using clustering algorithms. Three dominant storm types were identified: early-peak (Curve 1), intermediate (Curve 2), and uniform (Curve 3), reflecting the region’s coastal, lowland, and orographic influences. Probability envelopes and representative design hyetographs were derived to quantify intra-event variability. Rainfall–runoff simulations for a 100-km² watershed showed peak-flow differences of up to 132% between storm types, highlighting the sensitivity of hydrologic response to rainfall temporal distributions. The resulting regionalized Huff curves provide a practical and transferable framework for hydrologic modeling, flood-risk assessment, and infrastructure planning in tropical regions with limited high-resolution rainfall data. Full article

Misiones, Argentina, holds one of the largest remnants of the Atlantic Forest, with almost 1.4 million hectares of native forest, representing a critical landscape for sustainable biodiversity conservation. However, connectivity across this ecoregion is increasingly threatened by habitat conversion, landscape fragmentation, and poaching pressures that extend beyond protected area boundaries, undermining long-term sustainability of wildlife populations. Using conservation detection dogs, we located, collected, and genetically confirmed 198 scats belonging to four game species: 20 lowland tapir (Tapirus terrestris), 72 white-lipped peccary (Tayassu pecari), 55 collared peccary (Pecari tajacu), and 51 Azara’s agouti (Dasyprocta azarae). Analyses examining species-specific habitat associations emphasized the importance of extending inference beyond point locations to encompass species’ home ranges, with native forest consistently identified as a key component of habitat use. The high prevalence of scats in mosaics of human-modified habitats outside protected areas, especially along their borders, underscores the importance of managing these areas as part of a broader sustainable landscape matrix. While native forest fragments outside of protected areas may serve as important refugia supporting species persistence, their contribution to sustainable management depends on reducing poaching pressure across these landscapes. There is an urgent need to expand antipoaching efforts beyond protected areas and across the Atlantic Forest in the Green Corridor of Misiones while preventing ongoing deforestation and the expansion of monoculture plantations. Achieving sustainable wildlife management in this region will require integrated strategies that promote sustainable land use, conservation planning, and rural development. Full article

Self-contained local forecasting of wind and solar series can improve operational planning of wind farms and photovoltaic (PV) plant day-cycles in addition to numerical models, which are mostly behind time due to high simulation costs. Unstable electricity production requires balancing the availability of renewable energy (RE) with unpredictable user consumption to achieve effective usage. Artificial intelligence (AI) predictive modelling can minimise the intermittent uncertainty in wind and solar resources by trying to eliminate specific problems in RE-detached system reliability and optimal utilisation. The proposed 24 h day-training and prediction scheme comprises the starting detection and the following similarity re-assessment of sampling day-series intervals. Two-point professional weather stations record standard meteorological variables, of which the most relevant are selected as optimal model inputs. Automatic two-layer altitude observation captures key relationships between hill- and lowland-level data, which comply with pattern progress. New biologically inspired differential learning (DfL) is designed and developed to integrate adaptive neurocomputing (evolving node tree components) with customised numerical procedures of operator calculus (OC) based on derivative transforms. DfL enables the representation of uncertain dynamics related to local weather patterns. Angular and frequency data (wind azimuth, temperature, irradiation) are processed together with the amplitudes to solve simple 2-variable partial differential equations (PDEs) in binomial nodes. Differentiated data provide the fruitful information necessary to model upcoming changes in mid-term day horizons. Additional PDE components in periodic form improve the modelling of hidden complex patterns in cycle data. The DfL efficiency was proved in statistical experiments, compared to a variety of elaborated AI techniques, enhanced by selective difference input preprocessing. Successful LSTM-deep and stochastic tree learning shows little inferior model performances, notably in day-ahead estimation of chaotic 24 h wind series, and slightly better approximation of alterative 8 h solar cycles. Free parametric C++ software with the applied archive data is available for additional comparative and reproducible experiments. Full article

Extreme drought events are increasingly destabilizing European lowland oak forests, yet within-stand variation in drought legacy effects remains poorly characterized. This study integrates UAV-LiDAR canopy structural analysis with a 68-year dendrochronological record (1952–2019) to examine divergent radial growth responses to the 2012 extreme drought in Turkey oak (Quercus cerris L.) forests of Vojvodina, northern Serbia. LiDAR scanning (Wingtra Gen II, 90 m altitude, spring 2024) enabled objective classification of 180 increment cores from 90 trees across four 5–7 ha experimental plots into two structural zones: a preserved-structure zone (PS; gap fraction ≤ 10%) and a disturbed-structure zone (DS; gap fraction > 10%). Ring width index (RWI) chronologies were developed using the modified negative exponential function and analyzed with linear mixed-effects models (LMMs) incorporating AR(1) temporal autocorrelation. Lloret resilience indices (a reference window of seven years) were computed per individual tree and compared between zones using Mann–Whitney U tests with Bonferroni correction. The key finding is a statistically significant zone × period interaction in all four plots (p = 0.0009–0.033): DS zone trees exhibited a marked post-drought RWI increase (mean +0.22–0.36 units; t-test p < 0.0001 in all plots), while PS zone trees showed no significant post-drought change (p = 0.147–0.258). Pooled Lloret analysis revealed significantly higher recovery (Rt: DS median = 1.693 vs. PS = 1.237; U = 1633, p < 0.0001, r = 0.532) and resilience (Rs: DS = 1.232 vs. PS = 0.932; U = 1574, p < 0.0001, r = 0.482), while resistance (Rc) did not differ between zones (p = 0.569), indicating that DS zone trees were equally susceptible to the drought but recovered far more strongly. The equivalence of Rc between zones critically implies that divergent post-drought trajectories cannot be attributed to differential drought tolerance but instead reflect a structural mechanism operating exclusively in the post-drought period. These results are consistent with a competition release mechanism: drought-induced canopy gap formation in DS zones reduced inter-tree competition for surviving trees, enabling accelerated radial growth recovery. Full article

Sustainable spatial development requires land-use allocation that aligns with reflects the environment’s biophysical capacity. However, rapid urbanization and agricultural expansion often result to spatial mismatches between land utilization and land capability, the reby increasing environmental degradation and disaster vulnerability. East Java Province, one of Indonesia’s most densely populated regions, has experienced significant land-use transformation driven by demographic pressure and economic development. This study aims to evaluate the environmental carrying capacity by assessing the spatial compatibility among land capability, existing land use, and the Provincial Spatial Plan (RTRWP) using a Geographic Information System (GIS)-based analytical approach. Land capability was determined based on key biophysical parameters, including slope gradient, soil texture, drainage conditions, erosion susceptibility, effective soil depth, and flood hazard. Spatial overlay analysis was employed to identify areas of conformity and mismatch between land capability and both current and planned land uses. The results indicate that only approximately 52% of the provincial area is utilised in accordance with its land capability. In comparison, the remaining 48% exhibits varying degrees of spatial mismatch. Erosion is identified as the dominant limiting factor, affecting more than 43% of the region, particularly in mountainous and hilly landscapes. Furthermore, over 60% of East Java falls within Land Capability Classes III–VII, indicating moderate to severe environmental constraints on limitations intensive land use. High levels of spatial mismatch are concentrated in the southern upland districts—such as Pacitan, Trenggalek, southern Malang, and Lumajang, which are highly susceptible to landslides, as well as in the northern lowland corridor, including the Surabaya–Gresik–Sidoarjo metropolitan region, which faces a significantly flood risk. These findings suggest that land-use practices exceeding environmental carrying capacity substantially amplify disaster risk. Therefore, integrating land capability assessment into spatial planning and zoning regulations is essential and for promoting ecosystem-based disaster risk reduction and achieving sustainable spatial development in East Java Province. Full article

This study was conducted in the Xinjiang region, China, along the Sino-Kazakh border, an area recognized as high-risk for locust outbreaks and characterized by ongoing shifts in dominant pest species. This study systematically examined the structural characteristics of locust communities across different grassland types and identified the underlying environmental driving mechanisms. Field surveys were conducted to assess the diversity characteristics, density variations, and niche width of the locust communities across the different grassland types. The locust community in the mountain meadows had a significantly lower Shannon diversity index compared with the other grassland types (p < 0.05). Although the Simpson dominance index and Pielou evenness index were also the lowest in the mountain meadows, these differences were not statistically significant (p > 0.05). Permutational multivariate analysis of variance (PermANOVA) revealed highly significant differences in locust density among the grassland types (p = 0.001). Ecological niche analysis revealed stronger interspecific competition in the lowland meadow, and weaker competition in the temperate steppe-enriched deserts and temperate desert grasslands. Structural equation modeling and random forest analysis identified soil organic, plant total potassium, and soil pH as the key factors driving locust community structure across grassland types. This study clarifies the diversity patterns of locust communities in the Xinjiang region along the Sino-Kazakh border and provides empirical data to better understand locust community structure and distribution. It also offers a scientific basis for developing sustainable locust management strategies. Full article

Height anomaly, defined as the separation between the quasi-geoid and the reference ellipsoid, is fundamental to quasi-geoid refinement. While the Goddard Mars Model-3 (GMM-3) developed by NASA’s Goddard Space Flight Center (GSFC) and the JPL Mars gravity field MRO120D (JGMRO_120D) model developed by NASA’s Jet Propulsion Laboratory (JPL) stand as two representative Martian gravity field models, the systematic differences between them and their associated physical implications remain insufficiently quantified. This study establishes a validated computational framework for Martian height anomaly determination using updated physical parameters and spherical harmonic expansions. Validation against terrestrial datasets confirms high reliability (standard deviation: 0.0695 m relative to International Centre for Global Earth Models (ICGEM)), ensuring confidence in subsequent analysis. Our analysis reveals three critical findings: (1) Systematic latitudinal biases between GMM-3 and JGMRO_120D exhibit a monotonic gradient from −1.3 m near the equator to +3.9 m at the North Pole, suggesting differential parameterization of polar mass loading or tidal models between the two centers. (2) Polar clustering of uncertainties and outliers exceeding the 95th percentile (>7 m) concentrate non-randomly at latitudes >60°, which is attributed to sparse satellite tracking and seasonal ice cap modeling limitations. (3) There is error amplification in lowland terrains, where relative errors exceed 60% in flat regions (near-zero anomalies), posing critical risks for precision landing missions. While global consistency between models is high (R² = 0.9999), the identified discrepancies provide new constraints on Mars’s geophysical models and essential guidance for future gravity field improvements and mission planning. Full article

Landslide hazard potential is high across the St. Lawrence lowlands of Québec, Canada, due to sensitive glaciomarine clay deposits and the presence of moderate seismic activity, causing slope failures in the region. The main objectives of the study are to develop a working database for landslides in the region and use that database to improve regional landslide susceptibility analysis. Using high-resolution (1 m by 1 m cells) digital terrain models dated from 2009 and validated with satellite photogrammetry from 2012, a landslide inventory of 263 cases related to the 2010 Val-des-Bois earthquake (moment magnitude 5.0) is created. Relationships between landslide susceptibility factors, such as slope angle, and seismic conditioning factors, such as peak ground acceleration, are examined through machine learning methods. For landslide detection, an overall accuracy of approximately 85% (AUC 0.914) is achieved using random forest and logistic regression models cross-validated through 5-fold analysis, showing improvement over the currently employed Hazus method, which achieves an accuracy of approximately 67%. From a regional perspective, the developed inventory and resultant susceptibility models are unique and form the foundation for future studies to improve the understanding of earthquake-induced landslides in the Western Québec Seismic Zone, which historically lacks detailed landslide inventories. Full article

The Cyrtodactylus chauquangensis species group is a large limestone karst radiation of bent-toed geckos with at least 28 nominal species and has a broad distribution range with seven species found in northwestern Thailand, five in south-central China, five in northern Laos and 11 in northern Vietnam. To trace the biogeographic pattern of this group, we reconstruct its phylogenetic relationships and evolutionary history using three mitochondrial genes and four nuclear genes. Our results show that the C. chauquangensis species group is monophyletic, which can be divided into at least seven subclades. In terms of biogeography, the group might have originated from the Northwest Uplands of the Indochina region, including northern Laos and part of northwestern Vietnam, during the early Miocene and subsequently dispersed into northwestern Thailand. It later colonized the northern Annamites, Northeast Lowland, Northeast Uplands, and South-central China. A majority of lineages within this group likely diverged during the Miocene epoch when the East Asian monsoon was developed and increased precipitation in the region. The changing climate might have promoted plant diversity and provided suitable habitats and food resources for members of the C. chauquangensis group. In addition, the elevated rate of precipitation probably accelerated the dissolution of the limestone substrate and profoundly influenced the development of the karst region. The results of our study further highlight the importance of this unique period of time in shaping evolutionary histories of many different taxonomic groups in the region. Full article

Landscape Character Assessment (LCA) is increasingly used to support landscape-sensitive planning; however, existing approaches often lack an operational integration of visual perception and map-based indicators, particularly in complex Mediterranean island contexts. This study demonstrates a methodology for integrated landscape character and quality assessment, combining landform and landcover mapping with map-based visibility indicators derived from the local road network. The approach was applied to the Platanos community in western Crete, a representative Mediterranean landscape of contrasting coastal resort zones, agricultural lowlands, and cultural heritage sites. The methodology followed three stages: desk-based mapping of Land Description Units (LDUs) using landform and landcover data, field surveys to define Landscape Character Types (LCTs) and assess socio-cultural and perceptual attributes, and GIS-based visibility analysis from 18 road observation points. Six visual indicators (connectivity, complexity, naturalness, disturbance, historicity, and visual scale) were calculated to quantify spatial and perceptual characteristics. Results revealed a spatial division between a core northern area of high visual scale, cultural importance, but also disturbance, and a southern area of greater naturalness but lower visual openness and cultural visibility. These results highlight that high landscape quality is not solely associated with naturalness, but emerges from the interaction between physical structure, cultural elements, and visual perception. The findings underscore the complementary value of combining physical, cultural, and perception-based metrics in LCA. The proposed framework offers a reproducible tool for evidence-based landscape planning and heritage-sensitive development in accordance with the principles of the European Landscape Convention (ELC). Full article