This study delves into the previously uncharted territory of dayas, ephemeral wetlands dotting the arid limestone plateau of Northwest Egypt. As the first comprehensive investigation of these ecologically and geologically vital features, it addresses the critical lack of research on their origins, evolution, and spatiotemporal dynamics. Employing a multi-method approach that integrates high-resolution Sentinel-2 satellite imagery, multi-decadal Landsat time-series analysis, ALOS PALSAR digital elevation model (DEM) processing, and systematic field validation, we identify and delineate 5430 dayas encompassing 258.1 km 2 within a study area of 11,254 km 2 . The supervised maximum-likelihood image classification, validated against 346 stratified field control points, achieved an overall accuracy of 91% (kappa = 0.88). Morphometric analysis characterizes dayas as shallow saucer-shaped depressions with diameters ranging from a few meters to several hundred meters and depths of 0.75 to 5.5 m, etched into the limestone surface filled with loose sediments. 0.75 m is the minimum depth recorded among field-confirmed dayas during the March 2025 survey; the DEM-based automated detection employed a minimum sink-depth threshold of 0.5 m, which represents the lowest depth reliably resolvable at 12.5 m DEM resolution without incurring unacceptable false-positive rates from surface noise. A daya typology comprising bowl-shaped, small flat-bottom, and large flat-bottom classes is established, each reflecting distinct stages within a continuum from active to relict karst. Spatiotemporal analysis of Landsat imagery from 1984 to 2025 documents a 32.63% net increase in daya surface area, corresponding to a mean annual expansion rate of ∼0.8%. Their evolution appears to be a complex interplay of karstic processes, surface-water runoff, hydro-geomorphological interactions, and erosional forces, all influenced by the interplay of structural and climatic factors. This underscores the critical need for sustainable land management practices that acknowledge the dayas’ significance for environmental stability and potential aquifer recharge. In conclusion, this study not only sheds light on the origins and hydrological dynamics of these enigmatic wetlands but also emphasizes their crucial role in the Northwest Egyptian landscape. By advocating for sustainable land-use practices and conservation efforts, we can ensure the continued presence and beneficial influence of these unique dayas for generations to come.
Anthropogenic climate change, land-use patterns and socioeconomic indicators are increasingly shaping wildfire risk. Conceptual risk frameworks, such as the IPCC’s hazard, exposure and vulnerability model, emphasize dynamic interaction of their components, yet most operational wildfire risk assessments still treat these drivers as static by relying on historical baselines for present-day conditions or integrating projections for only one of the risk components in forward-looking assessments. This review highlights the resulting gap between the conceptualization of risk and its operationalization, which limits the ability to anticipate future wildfire risk. We examine global wildfire trends, existing risk frameworks in climate-related risk assessments and evaluate the limitations of applying these frameworks in spatiotemporal assessments. We then propose a framework that treats the determinants of risk as space and time-dependent, integrating historical, current and projected datasets to characterize how wildfire risk changes over time. This approach enhances our capacity to anticipate changes in wildfire risk and supports more forward-looking and adaptive risk management strategies.
Earth surface systems display persistent patterns, directional change, and differential survival of forms that parallel evolutionary processes. Recent developments in complexity science and Earth system theory provide a basis for understanding these dynamics without invoking biological teleology. This paper synthesizes emerging work on abiotic variation–selection–retention (VSR) processes and argues that complexity provides the generative context within which selective pressures operate. Earth surface systems are characterized by numerosity, multiphasicity, hierarchical organization, feedbacks, and nonlinearity, producing self-organized, emergent structures, and multiple stable states. Within this framework, four modes of abiotic selection – gradient, resistance, network, and thermodynamic – favour configurations that are efficient, stable, or persistent. Integrating these selective mechanisms with concepts of attractors, goal functions, and historical contingency yields a unified account of Earth surface evolution. The synthesis clarifies how landscapes and environmental systems generate, filter, and retain form through time, and offers a conceptual bridge between biological and abiotic evolutionary thinking with implications for geomorphology, pedology, hydrology, ecology, and climate science.
Hydromorphological evaluations of riparian zones, following the European Union’s Water Framework Directive, integrate components of channel morphology, hydrology and ecology for sustaining long-term river restoration goals. However, such frameworks have seldom been applied in the Global South, especially in the Indian subcontinent, where river health assessment has traditionally focused on discerning the water quality. We adapt the EU framework to examine reach-level channel quality status and hydromorphological character of the River Silai in eastern India, using an aptly-devised, integrated multi-metric assessment that evaluates the river’s morphological functions and hydrological attributes, while also considering its riparian vegetation structure and water quality. The enumerated Morphological Quality Index (MQI) deftly highlighted geomorphic and hydrological impairments occurring within the examined 117 stream reaches, which were classified as per the Rosgen scheme. Site-specific Horton’s Water Quality Index (WQI), obtained from analysis of over 350 water samples, revealed the direct influence of channel morphology and its related anthropogenic use (such as riverbed sand mining) on the ambient water quality. These results were collated with parameters assessing the riparian vegetation status, such as the Qualitat del Bosc de Ribera (QBR), Riparian Strip Quality Index (RSQI) and Normalised Difference Vegetation Index (NDVI), to gain further insight into the overall stream health status. Finally, the devised overall channel quality rating identified the middle and lower courses of the Silai River to be the most impaired, which equates to just over one-fifth (21.37%) of the entire river’s length. While observer subjectivity/agreement, seasonality of water quality parameters, and accuracy of satellite image classification can affect results, statistical analysis revealed significant associations between these indices, reflecting their aptness for river health assessment. The adopted methodology is thus a rational and holistic framework to ascertain the ambient hydromorphological disturbances (largely human-induced), in addition to pinpointing sites that need management/restoration on a priority basis.
This study aimed to examine the effect of plot size on soil loss under natural rainfall in a humid region. Six experimental plots with areas of 3 to 360 m 2 were established on a hillslope, north of Iran. The soil losses were measured for 14 events. The results showed that absolute soil loss (ASL, g) increased with increasing plot size, whereas specific soil loss (SSL, g m −2 ) decreased, both following a nonlinear pattern. Based on ASL data, soil erosion occurred primarily as sheet erosion in plots 3–22 m long, whereas clear signs of rill formation were observed when plot length increased from 30 to 60 m, which was also confirmed by field observations. While the decreasing trend of SSL was very gradual from plot length of 3 to 10 m and of 30 to 60 m, it decreased sharply by increasing plot length from 10 to 22 meters. Scaling the SSL by two power equations showed that the power varies from −0.58 to −0.29 with a positive correlation to rainfall depth. Both equations did not fit to high SSLs well, showing under-estimation for small plots and over-estimation for big plots. The results revealed a clear scaling relationship between plot length and soil loss variables. Soil loss rates tended to decrease with increasing plot length, indicating that sediment delivery efficiency declines as the flow path becomes longer. These findings highlight the important role of scale effects and sediment redistribution processes in controlling soil erosion on forested hillslopes.
Globally, specific regions are predominantly characterised by particular tree taxa according to their ecological attributes, and this dominance is reflected in modern pollen records. In Anatolia, pine ( Pinus ) and oak ( Quercus ), which have historical and cultural significance, are similarly represented as the two most important taxa in modern pollen assemblages. Based on the largest compilation of modern pollen records currently available (1968–2025), this study analyses the representativeness of arboreal pollen (AP) and the two dominant tree genera ( Pinus and Quercus ) across Anatolia. Regional variation among the sampled sites was also examined, and the relative abundances of deciduous (Qd) and evergreen (Qe) oak taxa were specifically assessed. Results show that AP exceeds non-arboreal pollen (NAP) in 82% of the samples (total 539 samples), with an average AP value of 75%. Pinus is consistently dominant, exceeding 50% in 202 samples, whereas Quercus generally remains below 10% (339 samples). The combined contribution of Pinus and Quercus to AP (QPinAP ratio) averages 74.1% and exceeds 50% in 436 samples, clearly demonstrating the contribution of the two dominant taxa within AP. Clear regional differences are observed in the representation of deciduous versus evergreen oak. The resulting data provide a comprehensive and regionally differentiated contribution to the reconstruction of past forest dynamics in Anatolia through the evaluation of AP ratios and the pollen representation of these two genera.
Quantifying soil erosion in vulnerable tropical drylands is critical for desertification management but remains methodologically challenging due to the spatial limitations of field-based methods. This study introduces a novel framework integrating Small Baseline Subset Interferometric Synthetic Aperture Radar (SBAS-InSAR) with unsupervised statistical clustering to quantify erosion rates and validate spatial heterogeneity in the La Tatacoa dry forest, Colombia. Using 123 Sentinel-1 radar images (from 2018 to 2023), we generated high-resolution displacement velocity maps, which were then integrated with Normalized Difference Vegetation Index (NDVI) data from Sentinel-2 and geomorphometric attributes derived from the ALOS PALSAR Digital Elevation Model. Study-wide mean erosion rates ranged from 0.43 to 0.54 mm/year; however, these averages masked significant localized instability. Time-series K-means clustering of 100 randomized sampling points identified four distinct deformation regimes, statistically confirming that high-velocity zones are structural realities rather than measurement noise. Specifically, Cluster 4 identified critical hotspots where erosion rates reached 30 mm/year exceeding the United States Department of Agriculture (USDA) soil tolerance threshold (0.93 mm/year) by a factor of 32. These hotspots are systematically confined to dissected terrain with slopes > 9 ° and NDVI < 0.15 . By rigorously distinguishing genuine deformation regimes from background variability, this framework provides a scalable, evidence-based tool for prioritizing conservation interventions in data-limited dryland ecosystems.
Gully erosion is an important mechanism of landscape change in tropical mountain environments, yet the interactions among hydro-climatic forcing, soil erodibility, hydrological connectivity, and inherited landscape conditions remain insufficiently understood. This study investigates gully erosion susceptibility in the upper catchments of the Western Ghats, India, with particular emphasis on the role of geomorphic memory under monsoon-dominated climatic conditions. A Random Forest (RF) based Gully Erosion Susceptibility Index (GESI) was developed using topographic, hydrological, climatic, soil, and geomorphic variables, including slope, plan and profile curvature, stream power index, slope length and steepness, stream head density, rainfall erosivity, soil erodibility, and distance to palaeo-landslide initiation locations. The RF model achieved strong predictive performance (accuracy = 0.82; AUC = 0.87), indicating reliable discrimination between gully and non-gully locations. GESI values range from 0 to 0.98 (mean ≈0.30), with approximately 36% of the study area classified as having moderate to very high susceptibility. High-susceptibility zones are concentrated in areas characterized by elevated rainfall erosivity (>10,000 MJ mm ha −1 h −1 yr −1 ), high soil erodibility, and efficient drainage connectivity. Variable importance analysis identifies soil erodibility and rainfall erosivity as the dominant controls, while topographic and hydrological factors regulate runoff concentration and sediment transfer pathways. Rainfall–erosivity analysis reveals strong exponential relationships during peak monsoon months, demonstrating that relatively small increases in rainfall produce disproportionately large increases in erosive energy and promote the exceedance of critical erosion thresholds. August exhibits the highest erosivity values and the strongest rainfall–erosivity relationship, indicating that this period represents the principal window of erosive activity and gully initiation under peak monsoonal conditions. The contribution of distance to palaeo-landslide initiation locations further indicates that inherited geomorphic disturbances influence present-day susceptibility, supporting the importance of geomorphic memory in shaping erosion responses. The results suggest that gully erosion in the upper Western Ghats is governed by the interaction of monsoon-driven hydro-climatic forcing, soil susceptibility, hydrological connectivity, and geomorphic inheritance rather than by any single environmental factor. More broadly, the study highlights how legacy effects and contemporary climatic forcing interact to regulate erosion processes in humid tropical mountain catchments and provides a framework for investigating gully development under increasing rainfall extremes.
This study examines the interactions among drought, heatwaves, and wildfires in Türkiye using compound and cascading hazard frameworks. The aim is to assess how these hazards co-occur or sequentially evolve over time and to quantify their relationships with observed wildfire events. The analysis is based on daily ERA5 reanalysis data covering the period 1970–2025. Compound hazards were identified as the simultaneous exceedance of multiple hazard thresholds on the same day, whereas cascading hazards were defined as sequential hazard processes occurring within specified time windows prior to wildfire events. Fire-day matching results show that 14.55% of the 1,863 recorded wildfires are associated with same-day compound conditions, indicating a limited role of simultaneous hazard interactions. In contrast, when antecedent cascading processes are evaluated using predefined temporal windows, their explanatory capacity increases progressively from 5.05% (7-day) to 22.28% (30-day), highlighting the importance of cumulative preconditioning over multi-week timescales. Across all temporal windows, the heatwave-wildfire (HW→WF) sequence emerges as the dominant cascading pathway, while other configurations contribute only marginally. The discriminatory ability of cascading indicators was evaluated using Receiver Operating Characteristic (ROC) and precision-recall analyses. For the HW→WF indicator, the area under the ROC curve (AUC) increases from 0.67 (7-day) to 0.74 (30-day), indicating improved performance with longer antecedent periods. In contrast, the DR→HW→WF indicator exhibits consistently lower performance, with AUC values ranging between 0.56 and 0.58 across all time windows. Precision-recall results show a similar pattern, although overall AUPR values remain low. Overall performance remains moderate, reflecting the rarity and spatial heterogeneity of wildfire events. The results indicate that wildfire occurrence in Türkiye is more strongly linked to antecedent climatic processes than to same-day conditions alone. However, these relationships represent proxy-based statistical associations and temporal sequencing rather than direct physical causality for individual fire events. The findings highlight the importance of integrating compound and cascading hazard perspectives into wildfire risk assessment and early warning systems. By emphasizing the cumulative and sequential nature of drought-heatwave-wildfire interactions, this study provides a transferable framework for understanding increasingly complex wildfire risks under Mediterranean-type climate conditions.
Microplastic (MP) pollution is a major environmental concern, as particles are transported through interconnected hydrological pathways such as domestic wastewater systems, rivers, and coastal waters, where they accumulate in sediments and pose risks to aquatic ecosystems. Developing effective and affordable approaches to intercept microplastics before they enter natural water bodies is therefore essential. In this study, a magnetically recoverable Fe 3 O 4 /carbon black (Fe 3 O 4 /CB) nanocomposite was surface-modified using oleic acid and stearic acid to enhance its affinity for hydrophobic polyethylene (PE) microplastics. The modified nanocomposite showed a clear improvement in plastic removal compared to the unmodified Fe 3 O 4 /CB material, achieving near-complete removal under optimized conditions. Under optimized conditions (15 mg dosage, 50 r/min, 60 minutes), the modified nanocomposite removed 197.2 mg of PE from 200 mg in synthetic wastewater, corresponding to a removal efficiency of 98.6%. Application to real washing machine effluent further demonstrated its effectiveness, achieving a removal efficiency of 94.2%. The enhanced performance is attributed to increased surface hydrophobicity and the synergistic interaction between Fe 3 O 4 and carbon black. Overall, these findings highlight the potential of surface-modified magnetic nanocomposites as practical intervention tools at critical hydrological control points, such as wastewater discharge pathways, to reduce downstream transport of microplastics into freshwater and coastal environments.
Ecuador lies within the Northern Andes of South America, a mountain chain driven by tectonic processes. Several studies have documented sediment mass transfer between the Andean chain and the Amazon Basin. It has been estimated that up to 95% of the sediment discharged into the Atlantic Ocean by the Amazon River originates from the Andean Range. Within this geological framework, the Ecuadorian Government constructed the Coca Codo Sinclair Hydroelectric Plant (CCSHP), a run-of-river dam, in the Coca River Watershed (CRW). However, in February 2020, the San Rafael Waterfall, located at 19.1 km downstream of the diversion dam, collapsed catastrophically, triggering a rapid headward erosion process that has damaged strategic infrastructure and continues threatening watershed stability. This study assesses how human activity has impacted hydrosedimentary dynamics, accelerating natural erosion processes and altering sediment transport and deposition patterns, with significant consequences for fluvial geomorphology and infrastructure. A multidisciplinary approach integrating hydrology, geomorphology and geology was applied. Hydrological modeling indicates that legacy sediments from the 1987 earthquake and 2002 volcanic eruption increased erosion rates by approximately 28% in the undammed Salado watershed. However, dam construction accounts for approximately 42% of the intensification of erosion observed between 2008 and 2016 in the Coca River reach between the diversion dam and the former San Rafael waterfall, mainly due to disrupted sediment connectivity and the loss of bed armoring. Historically, the Coca River experienced periodic natural damming associated with volcanic eruptions and landslides, responding through erosional adjustment. In contrast, hydroelectric infrastructure permanently altered its discharge and sediment regimes, producing profound geomorphological changes: sediment aggradation formed an unexpected mid-catchment delta upstream of the diversion dam, while the release of sediment-starved waters downstream triggered severe degradation with erosion advancing 15.5 km over a 5-year period through July 2025.
Citizen science approaches are increasingly used to support data generation and public engagement across the environmental sciences, yet their wider pedagogical value within physical geography remains underexamined. To explore the value of mapping-based citizen science for both glaciological investigation and geographical learning, we developed GlacierMap , an interactive online tool enabling participants to map glacier change in Peru’s Cordillera Blanca over a 34-year period. GlacierMap was designed not only to assess the feasibility and value of crowd-sourced glacier mapping, but also as a vehicle to support experiential learning of the trends in, and impacts of, tropical mountain glacier retreat. Participants mapped glacier change from Landsat imagery for two different years, 1984 and 2018, with analysis of glacier extents mapped by both ‘expert’ and ‘non-expert’ participant groups supporting assessment of the value of GlacierMap as a data generation activity. Participant responses to pre- and post-mapping surveys were also analysed to understand the benefits, challenges, and limitations of citizen science for the purposes of crowd-sourcing glacier inventory data, dissemination, and geographical learning. We found that while many of the individual mapping contributions were a good fit to the Randolph Glacier Inventory, there was considerable variability in accuracy, for both experts and non-experts, likely due to challenges of image interpretation, levels of engagement with the task, and a need for more targeted pre-task training. Crucially, however, participants consistently reported improved understanding of glacier change and its downstream impacts, with teachers communicating the value of the tool for classroom use. These findings demonstrate that mapping-based citizen science can meaningfully enhance climate and spatial literacy, highlighting the potential for tools like GlacierMap to strengthen connections between physical geography research, schools, and wider publics.
Wetlands in the Yellow River Basin face the composite pressures of climate change and human disturbances. However, analyzes of the major riverine wetlands remain far less than those of the headwater and estuarine regions in the Yellow River Basin. Based on the Google Earth Engine platform, we combined a sample migration strategy and Random Forest classification to produce an annual 30 m riverine wetland dataset (1986-2022) for the Yellow River Basin (excluding the headwater and estuarine regions). We then analyzed the spatiotemporal change and driving factors of water bodies, mudflats, and marshes. Results show that long-term wetland maps exhibit high reliability, with overall accuracy above 90%, and an average Kappa coefficient exceeding 0.88. The expansion of water bodies and mudflats failed to offset marsh degradation, leading to a net riverine wetland loss of 1326.30 km2, with the total wetland area in 2022 decreasing to 95% of its 1986 level. Increasing temperature and runoff at the Lanzhou station are associated with marsh core loss and fragmentation, accompanied by partial conversion to water bodies and mudflats, thereby threatening wetland biodiversity and carbon sequestration capacity. Water body expansion and increased connectivity are primarily associated with runoff at the Lanzhou station, average temperature, and precipitation. Landscape change of mudflats in the midstream and downstream is associated with average temperature, sediment discharge at the Huayuankou station, runoff at the Toudaoguai station, and regional human activities. This study provides critical data support and spatiotemporal evidence for riverine wetland conservation and restoration in the Yellow River Basin.
The development of varied landforms in the Dehradun valley is the result of tectonic activity and sculptured climatically driven surface processes. Stretching for about 35 km between the Tons and Song river valleys, the Main Boundary Thrust (MBT) in the Dehradun valley is defined by geomorphological attributes that suggest neotectonics along this active geological structure. The MBT and its splay thrusts are arcuate in nature as evident from deformation on the landforms, where north dipping discontinuous fault scarps are developed along the MBT. The conglomerates of the Upper Siwalik rocks in the immediate footwall of the MBT are highly sheared, having dips ranging from steeply dipping to vertical. Three fault traces in the hanging wall of the MBT are observed that stretch for about 1.5 km and are aligned in parallel. The fault traces are represented by linearly arranged paleo-sag ponds, and the fault zones are marked by highly sheared bedrock. Fault traces are also observed along the Main Boundary Fault in the Kalawa-Kalsi area, where the fault plane dips north. Structurally controlled drainages are observed along the trace of the MBT, Santaurgarh Thrust, Santaurgarh Anticline, and Nagsidh Anticline; where numerous paleochannels, incised channels, and radial drainage are observed. Wide wind gaps are formed, some measuring more than 1.5 km in width. Present findings address the adjustment of the fluvial system with the ongoing tectonic activity.
Eutrophication is a nutrient-driven shift in trophic status characterized by the appearance of green or blue green algae and declining water quality. Non-point source (NPS) pollutants are diffuse pollutants originating from multiple sources like agriculture runoff, urban waste, animal or human activities, etc. are major drivers of trophic transitions and algal proliferation. However, their seasonal influences on nutrient balance and trophic state remain understudied. This study provides an integrated framework combining water quality parameters, Carlson trophic state index (CTSI), Redfield ratio, and normalized differentiated chlorophyll index (NDCI) to understand the effect of NPS on nutrient loading and trophic transition across three major wetlands in Guwahati city, Deepor Beel, Dighalipukhuri, and Jorpukhuri during the post-monsoon season. Water quality parameters including temperature, pH, EC, TDS, DO, chlorophyll-a, NO3-, TKN, TN, TP, PO43-, and COD were analyzed from sampling points vulnerable towards NPS pollution across the wetlands. Results showed severe eutrophication intensity with CTSI values ranging from 113 to 115 in Deepor Beel, 110 to 114 in Dighalipukhuri, and 108 to 114 in Jorpukhuri. Redfield ratio of all the three wetlands indicated strong nitrogen dominance (TN/TP >16), with Deepor Beel showing highest spatial heterogeneity, while Dighalipukhuri and Jorpukhuri remain consistently phosphorus-limited across all points. Overall eutrophication intensity is highest in November across sites, with multiple hotspots exceeding TN/TP >50. NDCI mapping validated these findings, showing elevated chl-a concentrations along the pollution-prone margins of Deepor Beel. Across all wetlands, lower DO coincided with elevated chlorophyll-a, phytoplankton driven turbidity (Tchl-a > Tsd) and warmer post-monsoon temperatures are consistent markers of high eutrophication.
The Environmental Kuznets Curve (EKC) provides a theoretical framework for exploring the evolution of human-nature relationships. However, existing EKC-based studies often oversimplify human systems and natural systems, and few studies have conducted a multidimensional analysis of EKC characteristics. To address these limitations, this study conceptualizes the human-nature relationship as the interaction between human activity intensity and environmental quality, quantified using the Human Activity Index (HAI) and the Ecological Quality Index (EQI), respectively. Using panel data from 368 Chinese cities during 2000-2020, we construct composite indicators to characterize the multidimensional states of human and natural systems and apply the EKC framework to analyze their coupled dynamics. Building on the conventional EKC model, we further develop a set of EKC characteristic metrics to systematically describe transition timing, HAI-EQI interactions at the turning point, and dynamic patterns before and after the turning point. Cities exhibiting EKC-type relationships are subsequently classified into distinct human-nature transition pathways, and key driving factors and their heterogeneous effects are examined. The results show that although HAI and EQI increased in most cities, only 147 cities exhibited clear EKC-type trajectories, which can be further grouped into five distinct clusters based on EKC characteristics. Urban expansion, slope, greenspace, forest resilience, and elevation emerged as dominant drivers with heterogeneous influences on EKC dynamics. By extending EKC analysis from simplified indicators to a multidimensional and process-oriented framework, this study advances EKC interpretation beyond pattern identification and provides policy-relevant insights for differentiated urban sustainability strategies and coordinated environmental governance in China.
In recent years, bark beetle outbreaks have become a significant threat to forest ecosystems in Central Europe, a trend exacerbated by climate change, creating favourable environmental conditions for pest proliferation. This has increased the interest in remote-sensing-based detection of bark beetle infestations. The objective of this study is to detect and reconstruct forest disturbances in a mountainous area situated in the Upper Puster Valley (South Tyrol, Italy) and quantify spatio-temporal patterns, with a special focus on bark-beetle-induced damages. The study area was severely impacted by the storm VAIA in autumn 2018 as well as widespread snow breakage in subsequent winters, causing large amounts of residual wood in the forests and providing brood material for bark beetles. Combined with warm and dry summer conditions, populations grew significantly. Using a Sentinel-2 satellite time series spanning from 2018 to 2024, we applied a parametric bi-temporal change detection approach based on linear regression. Validation of infestation data from 2021 to 2023 with a reference dataset yielded detection rates ranging from 52% to 92%. The analysis of elevation influence on damage patterns revealed significant differences between abiotic and biotic disturbances. The interannual clustering of forest disturbances was analysed based on bivariate join count statistics. The results indicate a strong spatial correlation between years for both disturbance types. The highest correlations were found for bark beetle infestations, clustering highly around previous disturbances, underlining the importance of understanding interannual spatial connectivity and implementing timely targeted management strategies to limit the spread of outbreaks.
The Patagonian Icefields in the Andes Mountains represent South America's largest solid freshwater reserves and are highly sensitive indicators of regional climate variability. This study analyzes the contrasting behaviors of two emblematic Glaciers of the Southern Patagonia Icefield: Upsala Glacier, characterized by sustained retreat and Perito Moreno Glacier, historically considered relatively stable. Using Landsat 5, 7, and 8 imageries from 1997-2023, we provide a quantitative assessment of frontal displacement, area change, and retreat dynamics, offering additional insights beyond prior studies. For Upsala Glacier, we confirm and refine earlier reports of significant retreat, measuring similar to 6989 +/- 0.56 m of frontal loss, an average retreat rate of -304.55 +/- 0.78 m/year (p < 0.05), and a statistically significant acceleration of -1.9 +/- 1.11 m/year(2). Surface area declined by similar to 73.5 +/- 0.22 km(2) (similar to 9% of its 1997 extent), at an average rate of -3 +/- 0.17 km(2)/year, with continued retreat after 2023 (100 +/- 15 m in 2024 and 291.5 +/- 15 m in 2025). In contrast, Perito Moreno Glacier exhibited near-equilibrium conditions with no sustained frontal retreat for most of the study period, but since 2016 has undergone a marked transition toward sustained frontal retreat, with retreat rates reaching -55 +/- 0.78 m/year and accounting for nearly two-thirds of its total area loss since 1997 (similar to 3 +/- 0.15 km(2)), with spatially asymmetric retreat-advance dynamics. Recent observations further confirm this shift, with a pronounced retreat event in 2025 reaching similar to-385 +/- 15 m representing the largest frontal recession recorded over the study period. These contrasting Glacier responses highlight the strong influence of Glacier geometry and local dynamics on frontal behavior, emphasizing the importance of sustained satellite monitoring and the integration of complementary datasets for understanding the future evolution of Patagonian Glaciers.
