Regional Scale Research Articles

Using satellite imagery to assess the glacier retreat in King George Island, Antarctica

In recent decades, remote sensing has become a powerful tool for continuously monitoring glacier dynamics in remote areas, enabling the identification of significant spatiotemporal changes due to its capacity to provide multitemporal information at regional and global scales. In this study, Landsat satellite images (1989–2020) were used to quantify glacier retreat in the ice cap of King George Island (KGI), located in the Antarctic Peninsula, and to evaluate the teleconnections of El Niño – Southern Oscillation - ENSO (ONI and SOI indices) with climaticvariables (temperature and precipitation) in this region. Our findings reveal a 10% loss in glacier coverage over the last 31 years, with a slower glacier retreat observed since 2008. Glaciers with smaller areas and marine terminating were the most affected. Of the 73 glaciers on KGI, 42% had continental terminating, 21% had marine terminating, and 37% had mixed terminating (continental and marine). Of the total glacier area lost, 35% corresponds to glaciers with marine terminating, while 16% corresponds to glaciers with continental terminating. Furthermore, climatic variables exhibited heterogeneous responses during ENSO events, with a significant correlation between mean temperature and ONI at the annual level and during the austral spring, which may be influencing glacier retreat in the study area to some extent.

A New Pabs Model for Quantitatively Diagnosing Phosphorus Nutritional Status in Corn Plants

Accurate diagnosis of plant phosphorus nutritional status is critical for optimizing agricultural practices and enhancing resource efficiency. Existing methods are limited to qualitatively assessing plant phosphorus nutritional status and cannot quantitatively estimate the plant’s phosphorus requirements. Moreover, these methods are time-consuming, making them impractical for large-scale application. In this study, we developed an advanced phosphorus absorption model (Pabs) that integrates the phosphorus nutrition index (PNI) and phosphorus use efficiency (PUE). The PUE, a critical metric for assessing phosphate fertilizer use efficiency, was quantified by comparing yields under fertilized and unfertilized conditions. Utilizing the Agricultural Production Systems Simulator (APSIM) model, we simulated maize (Zea mays L.) phosphorus concentration (P) and aboveground biomass (Bio) under varying phosphorus application rates. The model exhibited robust performance, achieving an R2 above 0.95 and an RMSE below 0.22. Based on the APSIM model simulations, a phosphorus dilution curve (Pc = 3.17 Bio−0.29, R2 = 0.98) was established, reflecting the dilution trends of phosphorus across growth stages. Furthermore, the use of vegetation indices (VIS) to evaluate phosphorus nutritional status also showed promising results, with inversion accuracies exceeding 0.70. To validate the model, field sampling was conducted in maize-growing regions of Changchun. Results demonstrated a correct diagnosis rate of 75%, underscoring the model’s capacity to accurately estimate phosphorus requirements on a regional scale. These findings highlight the Pabs model as a reliable tool for precision phosphorus management, offering significant potential to optimize fertilization strategies and support sustainable agricultural systems.

Network-Based Identification of Key Toxic Compounds in Airborne Chemical Exposome.

Air pollution is a leading contributor to the global disease burden. However, the complex nature of the chemicals to which humans are exposed through inhalation has obscured the identification of the key compounds responsible for diseases. Here, we develop a network topology-based framework to identify key toxic compounds in the airborne chemical exposome. Using cardiovascular diseases (CVDs) as a model disease, we found that toxic network modules of various compounds are closely linked to the modules of CVDs. The proximity of compound target modules to disease modules can indicate the extent of toxicity induced by the compounds. By integrating mass spectrometry-based external exposure concentrations and machine learning-predicted internal exposure concentrations, we established a comprehensive linkage connecting exposure to disease-related risk for the identification of toxic compounds. These findings were subsequently validated using exposure and disease data on the regional scale. This work provides an effective strategy for identifying key compounds within environmental exposomes and establishes a new paradigm for understanding the pathogenicity of air pollution.

Temporal trends of community and climate changes in the anthropocene: 21-year dynamics of four major functional groups in a rocky intertidal habitat along the Pacific coast of Japan

The influence of climate change on marine organism abundance has rarely been assessed (1) at the functional-group level; (2) simultaneously in major functional groups within the same ecosystem; (3) for >10 years; and (4) at metapopulation/community scales. A study simultaneously addressing these gaps would greatly enhance our understanding of the influence of climate change on marine ecosystems. Here, we analyzed 21 years of abundance data at the functional-group and species levels on a regional scale for four major functional groups (benthic algae, sessile animals, herbivorous benthos, and carnivorous benthos) in a rocky intertidal habitat along the northeastern Pacific coast of Japan. We aimed to examine the 21-year trends in regional abundance at both functional-group and species levels, plus their driving mechanisms and their dependence on species properties (thermal niche, calcification status, and vertical niche). Significant temporal trends in abundance were detected at functional-group levels for benthic algae (increasing) and herbivores and carnivores (both decreasing); they followed the temporal population trends of the dominant species. At species level, the metapopulation size of 12 of 31 species were increasing and 4 of those were decreasing, depending on the thermal niche and species calcification status. At both functional-group and species levels, temporal trends in abundance are caused by the direct or indirect influence of warming and ocean acidification. Comparing these results with community responses to marine heat waves in the same study area offered two implications: (1) long-term ecosystem changes associated with global warming will be unpredictable from the community response to marine heat waves, possibly owing to a lack of knowledge of the influence of calcifying status on species’ responses to climate change; and (2) thermal niches contribute greatly to predictions of the influence of warming on population size, regardless of the time scale.

Interdecadal Variation of Springtime Compound Temperature‐Precipitation Extreme Events in China and Its Association With Atlantic Multidecadal Oscillation and Interdecadal Pacific Oscillation

AbstractThe concurrent occurrence of temperature and precipitation extremes, known as compound temperature‐precipitation extreme events (CTPEEs), leads to more pronounced consequences for human society and ecosystems than when these extremes occur separately. However, such compound extremes have not been sufficiently studied, especially during boreal spring. Spring is an important transition season, during which the CTPEEs plays a pivotal role in plant growth and revival of terrestrial ecosystems. This study investigates the spatio‐temporal variation characteristics of spring CTPEEs in China, including warm‐dry, warm‐wet, cold‐dry, and cold‐wet combinations. The compound cold‐wet extreme events occur most frequently, followed by warm‐dry, warm‐wet, and cold‐dry events. The frequency of CTPEEs associated with warm (cold) extremes shows a marked interdecadal increase (decrease) around the mid‐to‐late 1990s. It is found that the interdecadal change in CTPEEs is primarily determined by the variation in temperature extremes. This interdecadal shift coincides with the phase transitions of the Atlantic Multidecadal Oscillation (AMO) and the Interdecadal Pacific Oscillation (IPO). After the mid‐to‐late 1990s, the configuration of a positive AMO and a negative IPO excited atmospheric wave trains over mid‐high latitudes, causing high‐pressure and anticyclonic anomalies over East Asia. This leads to less cloudiness, allowing an increase in downward solar radiation, which enhances surface warming and contributes to an increase (decrease) in warm‐dry and warm‐wet extremes. The above observations are confirmed by the Pacemaker experiments. The results of this study highlight a significant contribution of internal climate variability to interdecadal changes in CTPEEs at the regional scale.

On the Existence of Long-period Decayless Oscillations in Short Active Region Loops

Abstract Decayless kink oscillations, characterized by their lack of decay in amplitude, have been detected in coronal loops of varying scales in active regions, the quiet Sun, and coronal holes. Short-period (<50 s) decayless oscillations have been detected in short loops (< 50 Mm) within active regions. Nevertheless, long-period decayless oscillations in these loops remain relatively unexplored and crucial for understanding the wave modes and excitation mechanisms of decayless oscillations. We present the statistical analysis of decayless oscillations from two active regions observed by the Extreme Ultraviolet Imager onboard Solar Orbiter. The average loop length and period of the detected oscillations are 19 Mm and 151 s, respectively. We find 82 long-period and 23 short-period oscillations in these loops. We do not obtain a significant correlation between loop length and period. We discuss the possibility of different wave modes in short loops, although standing waves cannot be excluded from possible wave modes. Furthermore, a different branch exists for active region short loops in the loop length versus period relation, similar to decayless waves in short loops in the quiet Sun and coronal holes. The magnetic fields derived from MHD seismology, based on standing kink modes, show lower values for multiple oscillations compared to previous estimates for long loops in active regions. Additionally, the comparison of period distributions in short loops across different coronal regions indicates that different excitation mechanisms may trigger short-period kink oscillations in active regions compared to the quiet Sun and coronal holes.

A CO2–Δ14CO2 inversion setup for estimating European fossil CO2 emissions

Abstract. Independent estimation and verification of fossil CO2 emissions on a regional and national scale are crucial for evaluating the fossil CO2 emissions and reductions reported by countries as part of their nationally determined contributions (NDCs). Top-down methods, such as the assimilation of in situ and satellite observations of different tracers (e.g., CO2, CO, Δ14CO2, XCO2), have been increasingly used for this purpose. In this paper, we use the Lund University Modular Inversion Algorithm (LUMIA) to estimate fossil CO2 emissions and natural fluxes by simultaneously inverting in situ synthetic observations of CO2 and Δ14CO2 over Europe. We evaluate the inversion system by conducting a series of observing system simulation experiments (OSSEs). We find that in regions with a dense sampling network, such as western/central Europe, adding Δ14CO2 observations in an experiment where the prior fossil CO2 and biosphere fluxes are set to zero allows LUMIA to recover the time series of both categories. This reduces the prior-to-truth root mean square error (RMSE) from 1.26 to 0.12 TgC d−1 in fossil CO2 and from 0.97 to 0.17 TgC d−1 in biosphere fluxes, reflecting the true total CO2 budget by 91 %. In a second set of experiments using realistic prior fluxes, we find that in addition to retrieving the time series of the optimized fluxes, we are able to recover the true regional fossil CO2 budget in western/central Europe by 95 % and in Germany by 97 %. In all experiments, regions with low sampling coverage, such as southern Europe and the British Isles, show poorly resolved posterior fossil CO2 emissions. Although the posterior biosphere fluxes in these regions follow the seasonal patterns of the true fluxes, a significant bias remains, making it impossible to close the total CO2 budget. We find that the prior uncertainty of fossil CO2 emissions does not significantly impact the posterior estimates, showing similar results in regions with good sampling coverage like western/central Europe and northern Europe. Finally, having a good prior estimate of the terrestrial isotopic disequilibrium is important to avoid introducing additional noise into the posterior fossil CO2 fluxes.

Soil Degradation of Sloping Cropland in the Typical Black Soil Region in Northeast China: Risk Assessment and Uncertainty Analysis

ABSTRACTSoil degradation in the typical black soil region in Northeast China poses a threat to agricultural productivity and sustainability. However, little is known about the distribution of soil with different degradation degrees on a regional scale. This study aimed to map soil degradation status based on a newly developed soil degradation index (SDI) and assessed the uncertainty of degradation risk through the combination of ordinary Kriging and sequential Gaussian simulation (SGS) in order to enhance the accuracy and credibility of predictive results. The mean SDI was 0.445, with a coefficient of variation of 30%. The realization with 200 times by SGS was the best showed an increasing pattern of soil degradation degree from north to south in the study area. Slightly and moderately degraded sloping cropland accounted for 35.3% and 52.4% of all sloping cropland, respectively. High‐risk areas were mainly located in the Daxing'an and Changbai Mountains to the Songnen Plain. Proactive measures are necessary to control and mitigate further degradation by improving soil management and weakening the impact of runoff on sloping cropland. The developed risk assessment maps provide baseline information for regional sustainable development.

Global and Regional Trends in Paediatric Neuroblastoma Incidence and Mortality, 1990-2021: An Inequality and Projection Analysis.

Neuroblastoma stands as the most prevalent extracranial solid tumour in children, yet its epidemiological profile on global, regional, and national scales remains insufficiently explored. Long-term trends in the incidence and mortality of paediatric neuroblastoma from 1990 to 2021 were analysed globally, regionally, and nationally using estimated annual percentage changes. Cross-national disparities in the burden of paediatric neuroblastoma were quantified through standard health equity methodologies, with projections of burden shifts extending to 2035. From 1990 to 2021, the global age-standardised death rate for paediatric neuroblastoma increased from 0.19 (95% UI, 0.16-0.23) to 0.21 (95% UI, 0.14-0.28) per 100 000 population, with an EAPC of 0.2. Regionally, both mortality and incidence rates were highest in low-middle SDI regions and lowest in Oceania. Mortality rates were highest among males aged 12-23 months and females aged 6-11 months, while incidence rates were most pronounced in children aged 2-4 years. Cross-country inequality analyses indicated a reduction in disparities between high and low SDI countries; however, the concentration index revealed an increase in the inequality of burden distribution. The global burden of paediatric neuroblastoma is projected to continue rising through 2035. Over the past 30 years, global incidence and mortality rates for paediatric neuroblastoma have risen, particularly in low-SDI regions, whereas high-SDI regions have witnessed a downward trend. Although disparities between high- and low-SDI countries have diminished, inequality in burden distribution has grown more pronounced. The global burden of paediatric neuroblastoma is expected to continue its upward trajectory over the next 15 years.

Empowering Regional Conservation: Genetic Diversity Assessments as a Tool for Eelgrass Management.

To halt the loss of biodiversity, collaboration among scientists, managers and decision-makers is vital. Although biodiversity loss is a global problem, management actions influencing diversity are often on a local to regional scale. Our study is an example of a regional conservation genomic assessment developed in collaboration between scientists and managers. We used 2bRAD sequencing to assess 18 eelgrass (Zostera marina) meadows in northwestern Sweden, an area that has experienced large losses of eelgrass since the 1980s. Genetic diversity was comparable to other assessed meadows in the Atlantic, but an order of magnitude lower than eelgrass in the Pacific. All but one meadow showed high rates of sexual reproduction. Almost all meadows were divergent but grouped into five genetic clusters. Four of the clusters correspond to geographic regions that can be used to define management units. Meadows in areas with a high decline in eelgrass between the 1980s and 2020s are more inbred than meadows in areas with an increase in eelgrass. Overall, our results indicate that striving to protect a number of large eelgrass meadows within each genetic cluster is important for maintaining the genetic diversity and connectivity of eelgrass in northwestern Sweden and is likely beneficial for the wider ecosystem. We estimate current indicators and essential biodiversity variables and discuss their challenges in marine facultative clonal species. We showcase how regional-scale conservation genomic assessments can serve as a foundation for protection and restoration of a priority species.

Spatiotemporal Dynamics of Drought in the Huai River Basin (2012–2018): Analyzing Patterns Through Hydrological Simulation and Geospatial Methods

As climate change intensifies, extreme drought events have become more frequent, and investigating the mechanisms of watershed drought has become highly significant for basin water resource management. This study utilizes the WRF-Hydro model in conjunction with standardized drought indices, including the standardized precipitation index (SPI), standardized soil moisture index (SSMI), and Standardized Streamflow Index (SSFI), to comprehensively investigate the spatiotemporal characteristics of drought in the Huai River Basin, China, from 2012 to 2018. The simulation performance of the WRF-Hydro model was evaluated by comparing model outputs with reanalysis data at the regional scale and site observational data at the site scale, respectively. Our results demonstrate that the model showed a correlation coefficient of 0.74, a bias of −0.29, and a root mean square error of 2.66% when compared with reanalysis data in the 0–10 cm soil layer. Against the six observational sites, the model achieved a maximum correlation coefficient of 0.81, a minimum bias of −0.54, and a minimum root mean square error of 3.12%. The simulation results at both regional and site scales demonstrate that the model achieves high accuracy in simulating soil moisture in this basin. The analysis of SPI, SSMI, and SSFI from 2012 to 2018 shows that the summer months rarely experience drought, and droughts predominantly occurred in December, January, and February in the Huai River Basin. Moreover, we found that the drought characteristics in this basin have significant seasonal and interannual variability and spatial heterogeneity. On the one hand, the middle and southern parts of the basin experience more frequent and severe agricultural droughts compared to the northern regions. On the other hand, we identified a time–lag relationship among meteorological, agricultural, and hydrological droughts, uncovering interactions and propagation mechanisms across different drought types in this basin. Finally, we concluded that the WRF-Hydro model can provide highly accurate soil moisture simulation results and can be used to assess the spatiotemporal variations in regional drought events and the propagation mechanisms between different types of droughts.

Habitat preference of the dinosaurs from the Ibero-Armorican domain (Upper Cretaceous, south-western Europe)

Paleoenvironmental preferences for Cretaceous dinosaurs at a regional scale have been mainly assessed in North America. In south-western Europe, the dinosaur-bearing formations ranging the late Campanian to the latest Maastrichtian encompass coastal and lowland environments that produced hundreds of fossil localities with evidence of titanosaurian sauropods, maniraptoran and abelisauroid theropods, and nodosaurid ankylosaurs, together with rhabdodontid and hadrosauroid ornithopods. In order to study environmental associations of dinosaur taxa, we have revised, updated, and expanded upon an existing database that compiles the occurrence and minimum number of individuals for the dinosaur-bearing formations spanning the upper Campanian to the uppermost Maastrichtian of South-Western Europe. Based on this database, the habitat preferences of dinosaur groups in the region were determined by means of statistical tests of independence. All chi-square tests showed positive, mostly moderate-to-strong, and statistically significant associations between the studied groups and the environment they inhabited. The analysis of the residuals indicated that most dinosaur groups preferred lowland environments (including, contrary to previous studies, nodosaurids). The only exception were abelisauroids, which showed no habitat preference. Our results concur with recent works indicating that titanosaur sauropods and hadrosauroids preferred inland environments but clearly disagree with others suggesting that the latter as well as nodosaurid ankylosaurs were positively associated with marine or coastal settings. Considering the changes in occurrence distribution throughout the Maastrichtian turnover in the region, both titanosaurians and nodosaurids probably stablished a feeding strategy-based niche partitioning with ornithopods, although additional data is required to confidently confirm this relationship.

Dispersal promotes stability and persistence of exploited yeast mutualisms.

Multi-species mutualistic interactions are ubiquitous and essential in nature, yet they face several threats, many of which have been exacerbated in the Anthropocene era. Understanding the factors that drive the stability and persistence of mutualism has become increasingly important in light of global change. Although dispersal is widely recognized as a crucial spatially explicit process in maintaining biodiversity and community structure, knowledge about how the dispersal of mutualists contributes to the persistence of mutualistic systems remains limited. In this study, we used a synthetic mutualism formed by genetically modified budding yeast to investigate the effect of dispersal on the persistence and stability of mutualisms under exploitation. We found that dispersal increased the persistence of exploited mutualisms by 80% compared to the isolated systems. Furthermore, our results showed that dispersal increased local diversity, decreased beta diversity among local communities, and stabilized community structure at the regional scale. Our results indicate that dispersal can allow mutualisms to persist in meta-communities by reintroducing species that are locally competitively excluded by exploiters. With limited dispersal, e.g., due to increased fragmentation of meta-communities, mutualisms might be more prone to breakdown. Taken together, our results highlight the critical role of dispersal in facilitating the persistence of mutualism.

The genetic structure of the ash obligate moth prays fraxinella suggests that it is not affected by current habitat fragmentation

Tree diseases may cause the extirpation or functional extinction of a common tree species on large spatial scales. For example, ash dieback (Hymenoscyphus fraxineus) is expected to cause widespread loss of European ash (Fraxinus excelsior). This type of widespread loss of a tree species may have consequences for the ability of some insects to move between woodlands, particularly obligate species (species reliant on one tree species for food). Our aim was to use ddRAD-seq genetic data to determine the population structure of Prays fraxinella (ash bud moth), an ash-obligate micro-moth, and to assess its ability to maintain connectivity across fragmented patches of native broadleaf woodlands. We found no evidence of genetic structuring at local (up to 44 km) spatial scales, and no evidence of inbreeding. At regional scales (up to 426 km), we found evidence of mixed ancestry and long-distance dispersal. Our research highlights that given its ability to maintain gene flow in areas where woodlands have historically been very fragmented, P. fraxinella may continue to maintain connectivity under moderate future tree losses under ongoing ash dieback outbreaks. Implications for insect conservation: Our research highlights the potential indirect impacts of ash-dieback through losses in connectivity. This approach should be extended to other ash-obligate species, under various levels of existing fragmentation, to inform conservation strategies more fully for managing ash dieback.

Drivers of forest productivity in two regions of the United States: Relative impacts of management and environmental variables.

Climate, environmental conditions, and management strategies are key factors affecting forest net ecosystem production (NEP). However, little is known about the relationship between management approaches and regional to continental-scale forest productivity. In this study, we utilized forests of the U.S. Southeast (SEUS) and Pacific Northwest (PNW), two ecologically and socio-politically distinct regions, to answer the question: Does management exert a stronger influence on NEP than environmental factors? We estimated Geographically Weighted Regression models of NEP derived from the Ecosystem Demography Model as a function of soil, topography, climate, and forest management practices for the period 2000-2015 using 383 and 407 10×10km2 landscapes in SEUS and PNW, respectively. Results showed that forest management practices were important in predicting NEP only in mountainous northeastern areas of the SEUS; in the PNW, NEP had a more complex relationship with management and was positively related to ecological, preservation, and passive management. Management, topography, and soil were more strongly correlated with NEP in the PNW than in the SEUS, in which 81%, 83%, and 83% of PNW locations showed significant relationships with at least one management, topography, or soil variable, repectively. In contrast, seasonal precipitation and temperature were stronger predictors of NEP in the SEUS than other drivers, with 99% and 84% of the locations influenced by at least one seasonal temperature or precipitation variable, respectively. The findings of this study may provide a valuable framework for forest management - climate change strategies that could be extended across regional scales.

Nitrogen content of herbarium specimens from arable fields and mesic meadows reflect the intensifying agricultural management during the 20th century

Abstract Arable fields and mesic meadows have been affected by intensifying agricultural management and nutrient input during the 20th century, but direct evidence for the long‐term impact of intensification on plant nutrient contents remains scarce. Non‐destructive novel spectroscopic methods can produce such data from herbarium specimens, making it possible to investigate how contents of leaf nutrient traits, especially nitrogen and phosphorus, changed over the last century, and what role habitat type and management practices play. We carried out a resurvey study of functional traits in arable field and mesic meadow communities. We used specimens from two German herbaria with a high coverage of their local floras: the herbaria Senckenberg Görlitz and Senckenberg Haussknecht in Jena. Following specimen information, the same plant species were resampled in the field in 2022 at the same locations. We employed near‐infrared spectroscopy to predict leaf nitrogen, phosphorus and carbon content of herbarium and field specimens. Nutrient content changes over time were compared with public records of regional P and N fertilization. Overall, 1270 specimens of 76 species from both herbarium and field were studied, the oldest from the 19th century. Leaf nitrogen and the leaf nitrogen:phosphorus ratio increased significantly through time, while leaf phosphorus and carbon content decreased significantly over time. Arable field species showed a stronger response in leaf phosphorus content and leaf nitrogen:phosphorus ratio than mesic meadow species. The total amount of nitrogen or phosphorus fertilizer applied per year on a regional scale was found to be significantly correlated with the respective leaf nutrient content levels. Synthesis: Our study shows a long‐term increase of leaf nitrogen in the studied habitats, paralleling increased chemical fertilizer applications in Germany. Our data indicate a shift from predominantly N‐limited towards more P‐limited growth conditions. The stronger response of species from arable fields compared to species from mesic meadows could indicate a faster adjustment to environmental pressures. This study thus also serves to showcase the potential of the combination of herbarium collections and NIR spectroscopy.

Coupling tree-ring and geomorphic analyses to reconstruct the 1950s massive Glacier Lake Outburst Flood at Grosse Glacier, Chilean Patagonia.

Over recent decades, global warming has led to sustained glacier mass reduction and the formation of glacier lakes dammed by potentially unstable moraines. When such dams break, devastating Glacial Lake Outburst Floods (GLOFs) can occur in high mountain environments with catastrophic effects on populations and infrastructure. To understand the occurrence of GLOFs in space and time, build frequency-magnitude relationships for disaster risk reduction or identify regional links between GLOF frequency and climate warming, comprehensive databases are critically needed. GLOF inventories have thus been compiled at both regional and global scales. While these accounts offer valuable data for hazard assessment, many GLOF events are omitted because they occurred before the satellite era or prior to the installation of river gauges, went unreported or were only mentioned in local media but not documented in the scientific literature. In addition, while geomorphic evidence of past GLOFs exist, their timing oftentimes remains unknown. These discontinuities preclude the identification of return periods for the most disastrous events and makes the link between GLOFs and ongoing climate warming remain inconclusive. To overcome these limitations, long-term records have been developed using a wide variety of proxies. Here, we explore the potential of coupling dendrogeomorphology and geomorphic analyses to reconstruct a GLOF event that occurred before the satellite era. The Grosse Glacier outlet, in San Rafael National Park, Chilean Patagonia, was selected based on satellite imagery, historical photographs and local testimonies indicating a previous lake drainage. Tree-ring analysis allowed identification of a massive GLOF and five smaller floods from 105 disturbed Nothofagus and Podocarpus trees. Unmanned aerial vehicle (UAV) imagery and object-based image analysis (OBIA) were used to identify boulders and to estimate flow direction in the glacio-fluvial floodplain and point to the occurrence of at least one high-energy flow event. Aerial photo analysis also revealed the formation of a 200-m-wide breach in the frontal moraine and the disappearance of a lateral lake, estimated to be 1.8km2 in size, sometimes after 1944-45. An in-depth interview with an eyewitness pinpointed the date of the GLOF to October 1957, in line with the estimated date of damage in the tree-ring records and precipitation records at Puerto Aysén. When used in conjunction, the different approaches contribute valuable insights into the timing and consequences of past extreme events, thus aiding in future assessments of GLOF hazards, not only at the Grosse Glacier but also in other high-mountain environments.

Mapping of water spread dynamics of a tropical Ramsar wetland of India for conservation and management.

Wetlands are dynamic ecosystems vital for sustaining ecological health and development at regional and global scales. Geospatial tools have emerged as essential for managing wetland ecosystems. This study assessed the spatiotemporal dynamics of water spread in the Point Calimere Wetland, a coastal Ramsar site located along the Bay of Bengal, India, from 1984 to 2023. The analysis based on Global Surface Water Explorer (GSWE) and Normalized Difference Water Index (NDWI) derived from Landsat 5, 7, and 8 data revealed that 21% of the total wetland area showed an increasing trend. In comparison, 5.7% of the area showed a decreasing trend of surface water coverage, largely driven by erosion and climatic variability. The mean water spread increased from 119.47 km2 (2000-2003) to 160.88 km2 (2020-2023), with notable seasonal fluctuations. Among all seasons, the monsoon with the highest surge (41.1%) in water dynamics reported the largest water spread in 2020-2023 (221.87 km2). A moderate positive and negative relationship was noted between rainfall and water spread (r = 0.35) and temperature and water spread (r = - 0.43). A marked increase in habitat patches and edge density between 2000-2003 and 2020-2023 indicates the wetland's vulnerability to changing climatic conditions and the critical role of seawater intrusion, shoreline changes, and tidal forces in shaping its hydrological dynamics. The data presented on the historical water dynamics in this study is invaluable for the conservation planning and management of wetlands to support the associated coastal biodiversity and livelihood of the dependent communities.

Season and Flow Drive Productivity of a Regulated River

Flow regimes of river ecosystems worldwide have undergone substantial changes because of water resource development, altering the way in which organic matter is generated and cycled throughout entire river catchments. Flow–ecology studies have focused on structural variables measured at small spatial scales. This creates a challenging mismatch when applying adaptive flow management for ecosystem functioning at a catchment or regional scale. Here, we sought to inform flow management by evaluating the drivers of ecosystem metabolism in a regulated river and assessing our ability to predict metabolism at unmonitored locations. We estimated rates of ecosystem metabolism from high-frequency monitoring of dissolved oxygen concentration at eight sites on the Lachlan River of Australia’s Murray–Darling Basin. We then applied a spatio-temporal stream network model to predict metabolism at unmonitored locations using only remotely sensed and gauging station predictor variables. Gross primary productivity (GPP) was higher at sites with lower mean annual discharge, and strong seasonal patterns in rates of productivity tended to be disrupted by rising flows. Similarly, ecosystem respiration (ER) was higher at sites with lower mean annual discharge and lower annual flow variation, but increased slightly in response to higher daily flows. Predictions at validation sites were generally accurate, albeit with substantial site-to-site variation. Our results suggest that flow changes may have altered metabolic rates from conditions prior to water abstraction and dam construction. These findings will assist in managing flows for ecosystem function outcomes and support extrapolation from monitored sites to the broad scales required for evaluating catchment-scale outcomes of river management.

Synchrony dynamics of dissolved organic carbon in high‐mountain streams: Insights into scale‐dependent processes

AbstractIn high‐mountain landscapes, organic carbon (OC) is often limited and heterogeneously stored in poorly developed soils, snow, ground ice, and glaciers. Climate change influences the dynamics of OC mobilization to—and processing into—the recipient streams. Dynamics vary from seasonal (e.g., snow melt in spring) to daily (e.g., ice melt in summer) depending on the location of the streams within the catchment. Capturing the temporal richness of stream biogeochemical signals has become a reality with the advent of high‐resolution sensors. In this study, we applied wavelet analysis to high‐frequency discharge (Q) and dissolved organic carbon (DOC) measurements from nine streams in the Swiss Alps to investigate the persistence of synchrony in Q (SQ) and DOC (SDOC) among streams, and their response to drainage network position, climate, and land cover gradients across different time scales. Our findings revealed that SQ and SDOC decayed non‐linearly over the first ~ 5 km and stabilized from this point onwards, indicating that localized controls influenced synchrony within single basins, but drivers operating at regional scale acted as synchrony stabilizers. We also showed that short‐term (0–10 d) SQ and SDOC were strongly influenced by the distance between streams and network connectivity. In contrast, catchment‐related properties (i.e., altitude or land cover) were more important drivers of SQ and SDOC dynamics at longer time scales (> 50 d). However, the degree to which local catchment properties controlled synchrony patterns at the longest timescales depended both on response variables (i.e., Q vs. DOC) and land cover (i.e., vegetation vs. glacier). Elucidating the most prominent timescales of SDOC is relevant given the hydrological alterations projected for high‐mountain regions. We show that glaciers impose a unique seasonal regime on DOC concentration, potentially overriding the effects of other local hydrological or biogeochemical processes during downstream transport. Consequently, SDOC dynamics in high‐mountain streams may change as glaciers shrink, thereby altering downstream opportunities for biogeochemical transformations.