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Institute
- Institut für Geowissenschaften (240) (remove)
The immense advances in computer power achieved in the last decades have had a significant impact in Earth science, providing valuable research outputs that allow the simulation of complex natural processes and systems, and generating improved forecasts. The development and implementation of innovative geoscientific software is currently evolving towards a sustainable and efficient development by integrating models of different aspects of the Earth system. This will set the foundation for a future digital twin of the Earth. The codification and update of this software require great effort from research groups and therefore, it needs to be preserved for its reuse by future generations of geoscientists. Here, we report on Geo-Soft-CoRe, a Geoscientific Software & Code Repository, hosted at the archive DIGITAL.CSIC. This is an open source, multidisciplinary and multiscale collection of software and code developed to analyze different aspects of the Earth system, encompassing tools to: 1) analyze climate variability; 2) assess hazards, and 3) characterize the structure and dynamics of the solid Earth. Due to the broad range of applications of these software packages, this collection is useful not only for basic research in Earth science, but also for applied research and educational purposes, reducing the gap between the geosciences and the society. By providing each software and code with a permanent identifier (DOI), we ensure its self-sustainability and accomplish the FAIR (Findable, Accessible, Interoperable and Reusable) principles. Therefore, we aim for a more transparent science, transferring knowledge in an easier way to the geoscience community, and encouraging an integrated use of computational infrastructure.
Pedogenic carbonate is widespread at mid latitudes where warm and dry conditions favor soil carbonate growth from spring to fall. The mechanisms and timing of pedogenic carbonate formation are more ambiguous in the tropical domain, where long periods of soil water saturation and high soil respiration enhance calcite dissolution. This paper provides stable carbon, oxygen and clumped isotope values from Quaternary and Miocene pedogenic carbonates in the tropical domain of Myanmar, in areas characterized by warm (>18°C) winters and annual rainfall up to 1,700 mm. We show that carbonate growth in Myanmar is delayed to the driest and coldest months of the year by sustained monsoonal rainfall from mid spring to late fall. The range of isotopic variability in Quaternary pedogenic carbonates can be solely explained by temporal changes of carbonate growth within the dry season, from winter to early spring. We propose that high soil moisture year-round in the tropical domain narrows carbonate growth to the driest months and makes it particularly sensitive to the seasonal distribution of rainfall. This sensitivity is also enabled by high winter temperatures, allowing carbonate growth to occur outside the warmest months of the year. This high sensitivity is expected to be more prominent in the geological record during times with higher temperatures and greater expansion of the tropical realm. Clumped isotope temperatures, δ13C and δ18O values of tropical pedogenic carbonates are impacted by changes of both rainfall seasonality and surface temperatures; this sensitivity can potentially be used to track past tropical rainfall distribution.
At the junction of greenhouse and icehouse climate states, the Eocene-Oligocene Transition (EOT) is a key moment in Cenozoic climate history. While it is associated with severe extinctions and biodiversity turnovers on land, the role of terrestrial climate evolution remains poorly resolved, especially the associated changes in seasonality. Some paleobotanical and geochemical continental records in parts of the Northern Hemisphere suggest the EOT is associated with a marked cooling in winter, leading to the development of more pronounced seasons (i.e., an increase in the mean annual range of temperature, MATR). However, the MATR increase has been barely studied by climate models and large uncertainties remain on its origin, geographical extent and impact. In order to better understand and describe temperature seasonality changes between the middle Eocene and the early Oligocene, we use the Earth system model IPSL-CM5A2 and a set of simulations reconstructing the EOT through three major climate forcings: pCO(2) decrease (1120, 840 and 560 ppm), the Antarctic ice-sheet (AIS) formation and the associated sea-level decrease. Our simulations suggest that pCO(2) lowering alone is not sufficient to explain the seasonality evolution described by the data through the EOT but rather that the combined effects of pCO(2) , AIS formation and increased continentality provide the best data-model agreement.pCO(2) decrease induces a zonal pattern with alternating increasing and decreasing seasonality bands particularly strong in the northern high latitudes (up to 8 degrees C MATR increase) due to sea-ice and surface albedo feedback. Conversely, the onset of the AIS is responsible for a more constant surface albedo yearly, which leads to a strong decrease in seasonality in the southern midlatitudes to high latitudes (> 40 degrees S). Finally, continental areas that emerged due to the sea-level lowering cause the largest increase in seasonality and explain most of the global heterogeneity in MATR changes (1MATR) patterns. The Delta MATR patterns we reconstruct are generally consistent with the variability of the EOT biotic crisis intensity across the Northern Hemisphere and provide insights on their underlying mechanisms.
Quantifying the resilience of vegetated ecosystems is key to constraining both present-day and future global impacts of anthropogenic climate change. Here we apply both empirical and theoretical resilience metrics to remotely-sensed vegetation data in order to examine the role of water availability and variability in controlling vegetation resilience at the global scale. We find a concise global relationship where vegetation resilience is greater in regions with higher water availability. We also reveal that resilience is lower in regions with more pronounced inter-annual precipitation variability, but find less concise relationships between vegetation resilience and intra-annual precipitation variability. Our results thus imply that the resilience of vegetation responds differently to water deficits at varying time scales. In view of projected increases in precipitation variability, our findings highlight the risk of ecosystem degradation under ongoing climate change.
Vegetation dynamics depend on both the amount of precipitation and its variability over time. Here, the authors show that vegetation resilience is greater where water availability is higher and where precipitation is more stable from year to year.
Changes in snowpack associated with climatic warming has drastic impacts on surface energy balance in the cryosphere. Yet, traditional monitoring techniques, such as punctual measurements in the field, do not cover the full snowpack spatial and temporal variability, which hampers efforts to upscale measurements to the global scale. This variability is one of the primary constraints in model development. In terms of spatial resolution, active microwaves (synthetic aperture radar - SAR) can address the issue and outperform methods based on passive microwaves. Thus, high-spatial-resolution monitoring of snow depth (SD) would allow for better parameterization of local processes that drive the spatial variability of snow. The overall objective of this study is to evaluate the potential of the TerraSAR-X (TSX) SAR sensor and the wave co-polar phase difference (CPD) method for characterizing snow cover at high spatial resolution. Consequently, we first (1) investigate SD and depth hoar fraction (DHF) variability between different vegetation classes in the Ice Creek catchment (Qikiqtaruk/Herschel Island, Yukon, Canada) using in situ measurements collected over the course of a field campaign in 2019; (2) evaluate linkages between snow characteristics and CPD distribution over the 2019 dataset; and (3) determine CPD seasonality considering meteorological data over the 2015-2019 period. SD could be extracted using the CPD when certain conditions are met. A high incidence angle (>30 circle) with a high topographic wetness index (TWI) (>7.0) showed correlation between SD and CPD (R2 up to 0.72). Further, future work should address a threshold of sensitivity to TWI and incidence angle to map snow depth in such environments and assess the potential of using interpolation tools to fill in gaps in SD information on drier vegetation types.
Organic carbon (OC) stored in Arctic permafrost represents one of Earth's largest and most vulnerable terrestrial carbon pools. Amplified climate warming across the Arctic results in widespread permafrost thaw. Permafrost deposits exposed at river cliffs and coasts are particularly susceptible to thawing processes. Accelerating erosion of terrestrial permafrost along shorelines leads to increased transfer of organic matter (OM) to nearshore waters. However, the amount of terrestrial permafrost carbon and nitrogen as well as the OM quality in these deposits is still poorly quantified. We define the OM quality as the intrinsic potential for further transformation, decomposition and mineralisation. Here, we characterise the sources and the quality of OM supplied to the Lena River at a rapidly eroding permafrost river shoreline cliff in the eastern part of the delta (Sobo-Sise Island). Our multi-proxy approach captures bulk elemental, molecu- lar geochemical and carbon isotopic analyses of Late Pleistocene Yedoma permafrost and Holocene cover deposits, discontinuously spanning the last similar to 52 kyr. We showed that the ancient permafrost exposed in the Sobo-Sise cliff has a high organic carbon content (mean of about 5 wt %). The oldest sediments stem from Marine Isotope Stage (MIS) 3 interstadial deposits (dated to 52 to 28 cal ka BP) and are overlaid by last glacial MIS 2 (dated to 28 to 15 cal ka BP) and Holocene MIS 1 (dated to 7-0 cal ka BP) deposits. The relatively high average chain length (ACL) index of n-alkanes along the cliff profile indicates a predominant contribution of vascular plants to the OM composition. The elevated ratio of isoand anteiso-branched fatty acids (FAs) relative to mid- and long-chain (C >= 20) n-FAs in the interstadial MIS 3 and the interglacial MIS 1 deposits suggests stronger microbial activity and consequently higher input of bacterial biomass during these climatically warmer periods. The overall high carbon preference index (CPI) and higher plant fatty acid (HPFA) values as well as high C/N ratios point to a good quality of the preserved OM and thus to a high potential of the OM for decomposition upon thaw. A decrease in HPFA values downwards along the profile probably indicates stronger OM decomposition in the oldest (MIS 3) deposits of the cliff. The characterisation of OM from eroding permafrost leads to a better assessment of the greenhouse gas potential of the OC released into river and nearshore waters in the future.
The first step towards assessing hazards in seismically active regions involves mapping capable faults and estimating their recurrence times. While the mapping of active faults is commonly based on distinct geologic and geomorphic features evident at the surface, mapping blind seismogenic faults is complicated by the absence of on-fault diagnostic features. Here we investigated the Pichilemu Fault in coastal Chile, unknown until it generated a Mw 7.0 earthquake in 2010. The lack of evident surface faulting suggests activity along a partly-hidden blind fault. We used off-fault deformed marine terraces to estimate a fault-slip rate of 0.52 +/- 0.04 m/ka, which, when integrated with satellite geodesy suggests a 2.12 +/- 0.2 ka recurrence time for Mw similar to 7.0 normal-faulting earthquakes. We propose that extension in the Pichilemu region is associated with stress changes during megathrust earthquakes and accommodated by sporadic slip during upper-plate earthquakes, which has implications for assessing the seismic potential of cryptic faults along convergent margins and elsewhere.
Arctic river deltas and deltaic near-shore zones represent important land-ocean transition zones influencing sediment dynamics and nutrient fluxes from permafrost-affected terrestrial ecosystems into the coastal Arctic Ocean. To accurately model fluvial carbon and freshwater export from rapidly changing river catchments as well as assess impacts of future change on the Arctic shelf and coastal ecosystems, we need to understand the sea floor characteristics and topographic variety of the coastal zones. To date, digital bathymetrical data from the poorly accessible, shallow, and large areas of the eastern Siberian Arctic shelves are sparse. We have digitized bathymetrical information for nearly 75 000 locations from large-scale (1 V 25000-1 V 500000) current and historical nautical maps of the Lena Delta and the Kolyma Gulf region in northeastern Siberia. We present the first detailed and seamless digital models of coastal zone bathymetry for both delta and gulf regions in 50 and 200m spatial resolution. We validated the resulting bathymetry layers using a combination of our own water depth measurements and a collection of available depth measurements, which showed a strong correlation (r>0.9). Our bathymetrical models will serve as an input for a high-resolution coupled hydrodynamic-ecosystem model to better quantify fluvial and coastal carbon fluxes to the Arctic Ocean, but they may be useful for a range of other studies related to Arctic delta and near-shore dynamics such as modeling of submarine permafrost, near-shore sea ice, or shelf sediment transport. The new digital high-resolution bathymetry products are available on the PANGAEA data set repository for the Lena Delta (https://doi.org/10.1594/PANGAEA.934045; Fuchs et al., 2021a) and Kolyma Gulf region (https://doi.org/10.1594/PANGAEA.934049; Fuchs et al., 2021b), respectively. Likewise, the depth validation data are available on PANGAEA as well (https://doi.org/10.1594/PANGAEA.933187; Fuchs et al., 2021c).
The Palaeocene-Eocene Thermal Maximum (ca. 56 million years ago) offers a primary analogue for future global warming and carbon cycle recovery. Yet, where and how massive carbon emissions were mitigated during this climate warming event remains largely unknown. Here we show that organic carbon burial in the vast epicontinental seaways that extended over Eurasia provided a major carbon sink during the Palaeocene-Eocene Thermal Maximum. We coupled new and existing stratigraphic analyses to a detailed paleogeographic framework and using spatiotemporal interpolation calculated ca. 720–1300 Gt organic carbon excess burial, focused in the eastern parts of the Eurasian epicontinental seaways. A much larger amount (2160–3900 Gt C, and when accounting for the increase in inundated shelf area 7400–10300 Gt C) could have been sequestered in similar environments globally. With the disappearance of most epicontinental seas since the Oligocene-Miocene, an effective negative carbon cycle feedback also disappeared making the modern carbon cycle critically dependent on the slower silicate weathering feedback.
An earthquake swarm affected the Bransfield Strait, Antarctica, a unique rift basin in transition from intra-arc rifting to ocean spreading. The swarm, counting similar to 85,000 volcano-tectonic earthquakes since August 2020, is located close to the Orca submarine volcano, previously considered inactive. Simultaneously, geodetic data reported up to similar to 11 cm north-westward displacement over King George Island. We use a broad variety of geophysical data and methods to reveal the complex migration of seismicity, accompanying the intrusion of 0.26-0.56 km(3) of magma. Strike-slip earthquakes mark the intrusion at depth, while shallower normal faulting the similar to 20 km long lateral growth of a dike. Seismicity abruptly decreased after a Mw 6.0 earthquake, suggesting the magmatic dike lost pressure with the slipping of a large fault. A seafloor eruption is likely, but not confirmed by sea surface temperature anomalies. The unrest documents episodic magmatic intrusion in the Bransfield Strait, providing unique insights into active continental rifting.
Oxygen (O-2) availability in soils is vital for plant growth and productivity. The transport and consumption of O-2 in the root zone is closely linked to soil moisture content, the spatial distribution of roots, as well as structure and heterogeneity of the surrounding soil. In this study, we measure three-dimensional root system architecture and the spatiotemporal dynamics of soil moisture (& theta;) and O-2 concentrations in the root zone of maize (Zea mays) via non-invasive imaging, and then construct and parameterize a reactive transport model based on the experimental data. The combination of three non-invasive imaging methods allowed for a direct comparison of simulation results with observations at high spatial and temporal resolution. In three different modeling scenarios, we investigated how the results obtained for different levels of conceptual complexity in the model were able to match measured & theta; and O-2 concentration patterns. We found that the modeling scenario that considers heterogeneous soil structure and spatial variability of hydraulic parameters (permeability, porosity, and van Genuchten & alpha; and n), better reproduced the measured & theta; and O-2 patterns relative to a simple model with a homogenous soil domain. The results from our combined imaging and modeling analysis reveal that experimental O-2 and water dynamics can be reproduced quantitatively in a reactive transport model, and that O-2 and water dynamics are best characterized when conditions unique to the specific system beyond the distribution of roots, such as soil structure and its effect on water saturation and macroscopic gas transport pathways, are considered.
Ore precipitation in porphyry copper systems is generally characterized by metal zoning (Cu-Mo to Zn-Pb-Ag), which is suggested to be variably related to solubility decreases during fluid cooling, fluid-rock interactions, partitioning during fluid phase separation and mixing with external fluids. Here, we present new advances of a numerical process model by considering published constraints on the temperature- and salinity-dependent solubility of Cu, Pb and Zn in the ore fluid. We quantitatively investigate the roles of vapor-brine separation, halite saturation, initial metal contents, fluid mixing and remobilization as first-order controls of the physical hydrology on ore formation. The results show that the magmatic vapor and brine phases ascend with different residence times but as miscible fluid mixtures, with salinity increases generating metal-undersaturated bulk fluids. The release rates of magmatic fluids affect the location of the thermohaline fronts, leading to contrasting mechanisms for ore precipitation: higher rates result in halite saturation without significant metal zoning, lower rates produce zoned ore shells due to mixing with meteoric water. Varying metal contents can affect the order of the final metal precipitation sequence. Redissolution of precipitated metals results in zoned ore shell patterns in more peripheral locations and also decouples halite saturation from ore precipitation.
Knowledge on the response of sediment export to recent climate change in glacierized areas in the European Alps is limited, primarily because long-term records of suspended sediment concentrations (SSCs) are scarce. Here we tested the estimation of sediment export of the past five decades using quantile regression forest (QRF), a nonparametric, multivariate regression based on random forest. The regression builds on short-term records of SSCs and long records of the most important hydroclimatic drivers (discharge, precipitation and air temperature - QPT). We trained independent models for two nested and partially glacier-covered catchments, Vent (98 km(2)) and Vernagt (11.4 km(2)), in the upper otztal in Tyrol, Austria (1891 to 3772 m a.s.l.), where available QPT records start in 1967 and 1975. To assess temporal extrapolation ability, we used two 2-year SSC datasets at gauge Vernagt, which are almost 20 years apart, for a validation. For Vent, we performed a five-fold cross-validation on the 15 years of SSC measurements. Further, we quantified the number of days where predictors exceeded the range represented in the training dataset, as the inability to extrapolate beyond this range is a known limitation of QRF. Finally, we compared QRF performance to sediment rating curves (SRCs). We analyzed the modeled sediment export time series, the predictors and glacier mass balance data for trends (Mann-Kendall test and Sen's slope estimator) and step-like changes (using the widely applied Pettitt test and a complementary Bayesian approach).Our validation at gauge Vernagt demonstrated that QRF performs well in estimating past daily sediment export (Nash-Sutcliffe efficiency (NSE) of 0.73) and satisfactorily for SSCs (NSE of 0.51), despite the small training dataset. The temporal extrapolation ability of QRF was superior to SRCs, especially in periods with high-SSC events, which demonstrated the ability of QRF to model threshold effects. Days with high SSCs tended to be underestimated, but the effect on annual yields was small. Days with predictor exceedances were rare, indicating a good representativity of the training dataset. Finally, the QRF reconstruction models outperformed SRCs by about 20 percent points of the explained variance.Significant positive trends in the reconstructed annual suspended sediment yields were found at both gauges, with distinct step-like increases around 1981. This was linked to increased glacier melt, which became apparent through step-like increases in discharge at both gauges as well as change points in mass balances of the two largest glaciers in the Vent catchment. We identified exceptionally high July temperatures in 1982 and 1983 as a likely cause. In contrast, we did not find coinciding change points in precipitation. Opposing trends at the two gauges after 1981 suggest different timings of "peak sediment". We conclude that, given large-enough training datasets, the presented QRF approach is a promising tool with the ability to deepen our understanding of the response of high-alpine areas to decadal climate change.
The Kolumbo submarine volcano in the southern Aegean (Greece) is associated with repeated seismic unrest since at least two decades and the causes of this unrest are poorly understood. We present a ten-month long microseismicity data set for the period 2006-2007. The majority of earthquakes cluster in a cone-shaped portion of the crust below Kolumbo. The tip of this cone coincides with a low Vp-anomaly at 2-4 km depth, which is interpreted as a crustal melt reservoir. Our data set includes several earthquake swarms, of which we analyze the four with the highest events numbers in detail. Together the swarms form a zone of fracturing elongated in the SW-NE direction, parallel to major regional faults. All four swarms show a general upward migration of hypocenters and the cracking front propagates unusually fast, compared to swarms in other volcanic areas. We conclude that the swarm seismicity is most likely triggered by a combination of pore-pressure perturbations and the re-distribution of elastic stresses. Fluid pressure perturbations are induced likely by obstructions in the melt conduits in a rheologically strong layer between 6 and 9 km depth. We conclude that the zone of fractures below Kolumbo is exploited by melts ascending from the mantle and filling the crustal melt reservoir. Together with the recurring seismic unrest, our study suggests that a future eruption is probable and monitoring of the Kolumbo volcanic system is highly advisable.
Wildfires play an essential role in the ecology of boreal forests.
In eastern Siberia, fire activity has been increasing in recent years, challenging the livelihoods of local communities. Intensifying fire regimes also increase disturbance pressure on the boreal forests, which currently protect the permafrost beneath from accelerated degradation.
However, long-term relationships between changes in fire regime and forest structure remain largely unknown.
We assess past fire-vegetation feedbacks using sedimentary proxy records from Lake Satagay, Central Yakutia, Siberia, covering the past c. 10,800 years.
Results from macroscopic and microscopic charcoal analyses indicate high amounts of burnt biomass during the Early Holocene, and that the present-day, low-severity surface fire regime has been in place since c. 4,500 years before present.
A pollen-based quantitative reconstruction of vegetation cover and a terrestrial plant record based on sedimentary ancient DNA metabarcoding suggest a pronounced shift in forest structure toward the Late Holocene.
Whereas the Early Holocene was characterized by postglacial open larch-birch woodlands, forest structure changed toward the modern, mixed larch-dominated closed-canopy forest during the Mid-Holocene.
We propose a potential relationship between open woodlands and high amounts of burnt biomass, as well as a mediating effect of dense larch forest on the climate-driven intensification of fire regimes.
Considering the anticipated increase in forest disturbances (droughts, insect invasions, and wildfires), higher tree mortality may force the modern state of the forest to shift toward an open woodland state comparable to the Early Holocene.
Such a shift in forest structure may result in a positive feedback on currently intensifying wildfires.
These new long-term data improve our understanding of millennial-scale fire regime changes and their relationships to changes of vegetation in Central Yakutia, where the local population is already being confronted with intensifying wildfire seasons.
Through its magnetic activity, the Sun governs the conditions in Earth's vicinity, creating space weather events, which have drastic effects on our space- and ground-based technology.
One of the most important solar magnetic features creating the space weather is the solar wind that originates from the coronal holes (CHs).
The identification of the CHs on the Sun as one of the source regions of the solar wind is therefore crucial to achieve predictive capabilities.
In this study, we used an unsupervised machine-learning method, k-means, to pixel-wise cluster the passband images of the Sun taken by the Atmospheric Imaging Assembly on the Solar Dynamics Observatory in 171, 193, and 211 angstrom in different combinations.
Our results show that the pixel-wise k-means clustering together with systematic pre- and postprocessing steps provides compatible results with those from complex methods, such as convolutional neural networks.
More importantly, our study shows that there is a need for a CH database where a consensus about the CH boundaries is reached by observers independently.
This database then can be used as the "ground truth," when using a supervised method or just to evaluate the goodness of the models.
Modern pollen-vegetation-climate relationships underpin palaeovegetation and palaeoclimate reconstructions from fossil pollen records. East Siberia is an ideal area for investigating the relationships between modern pollen assemblages and near natural vegetation under cold continental climate conditions. Reliable pollen-based quantitative vegetation and climate reconstructions are still scarce due to the limited number of modern pollen datasets. Furthermore, differences in pollen representation of samples from lake sediments and soils are not well understood. Here, we present a new pollen dataset of 48 moss/soil and 24 lake surface-sediment samples collected in Chukotka and central Yakutia in East Siberia. The pollen-vegetation-climate relationships were investigated by ordination analyses. Generally, tundra and taiga vegetation types can be well distinguished in the surface pollen assemblages. Moss/soil and lake samples contain generally similar pollen assemblages as revealed by a Procrustes comparison with some exceptions. Overall, modern pollen assemblages reflect the temperature and precipitation gradients in the study areas as revealed by constrained ordination analysis. We estimate the relative pollen productivity (RPP) of major taxa and the relevant source area of pollen (RSAP) for moss/soil samples from Chukotka and central Yakutia using Extended R-Value (ERV) analysis. The RSAP of the tundra-forest transition area in Chukotka and taiga area in central Yakutia are ca. 1300 and 360 m, respectively. For Chukotka, RPPs relative to both Poaceae and Ericaceae were estimated while RPPs for central Yakutia were relative only to Ericaceae. Relative to Ericaceae (reference taxon, RPP = 1), Larix, Betula, Picea, and Pinus are overrepresented while Alnus, Cyperaceae, Poaceae, and Salix are underrepresented in the pollen spectra. Our estimates are in general agreement with previously published values and provide the basis for reliable quantitative reconstructions of East Siberian vegetation.
As the recent permafrost thawing of northern Asia proceeds due to anthropogenic climate change, precise and detailed palaeoecological records from past warm periods are essential to anticipate the extent of future permafrost variations. Here, based on the modern relationship between permafrost and vegetation (represented by pollen assemblages), we trained a Random Forest model using pollen and permafrost data and verified its reliability to reconstruct the history of permafrost in northern Asia during the Holocene. An early Holocene (12-8 cal ka BP) strong thawing trend, a middle-to-late Holocene (8-2 cal ka BP) relatively slow thawing trend, and a late Holocene freezing trend of permafrost in northern Asia are consistent with climatic proxies such as summer solar radiation and Northern Hemisphere temperature. The extensive distribution of permafrost in northern Asia inhibited the spread of evergreen coniferous trees during the early Holocene warming and might have decelerated the enhancement of the East Asian summer monsoon (EASM) by altering hydrological processes and albedo. Based on these findings, we suggest that studies of the EASM should consider more the state of permafrost and vegetation in northern Asia, which are often overlooked and may have a profound impact on climate change in this region.
We investigate whether the distribution of maximum seasonal streamflow is significantly affected by catchment or climate state of the season/month ahead. We fit the Generalized Extreme Value (GEV) distribution to extreme seasonal streamflow for around 600 stations across Europe by conditioning the GEV location and scale parameters on 14 indices, which represent the season-ahead climate or catchment state. The comparison of these climate-informed models with the classical GEV distribution, with time-constant parameters, suggests that there is a substantial potential for seasonal forecasting of flood probabilities. The potential varies between seasons and regions. Overall, the season-ahead catchment wetness shows the highest potential, although climate indices based on large-scale atmospheric circulation, sea surface temperature or sea ice concentration also show some skill for certain regions and seasons. Spatially coherent patterns and a substantial fraction of climate-informed models are promising signs towards early alerts to increase flood preparedness already a season ahead.
Fast Holocene slip and localized strain along the Liquiñe-Ofqui strike-slip fault system, Chile
(2021)
In active tectonic settings dominated by strike-slip kinematics, slip partitioning across subparallel faults is a common feature; therefore, assessing the degree of partitioning and strain localization is paramount for seismic hazard assessments. Here, we estimate a slip rate of 18.8 +/- 2.0 mm/year over the past 9.0 +/- 0.1 ka for a single strand of the Liquirie-Ofqui Fault System, which straddles the Main Cordillera in Southern Chile. This Holocene rate accounts for similar to 82% of the trench-parallel component of oblique plate convergence and is similar to million-year estimates integrated over the entire fault system. Our results imply that strain localizes on a single fault at millennial time scale but over longer time scales strain localization is not sustained. The fast millennial slip rate in the absence of historical Mw> 6.5 earthquakes along the Liquine-Ofqui Fault System implies either a component of aseismic slip or Mw similar to 7 earthquakes involving multi-trace ruptures and > 150-year repeat times. Our results have implications for the understanding of strike-slip fault system dynamics within volcanic arcs and seismic hazard assessments.
Thousands of glacier lakes have been forming behind natural dams in high mountains following glacier retreat since the early 20th century. Some of these lakes abruptly released pulses of water and sediment with disastrous downstream consequences. Yet it remains unclear whether the reported rise of these glacier lake outburst floods (GLOFs) has been fueled by a warming atmosphere and enhanced meltwater production, or simply a growing research effort. Here we estimate trends and biases in GLOF reporting based on the largest global catalog of 1,997 dated glacier-related floods in six major mountain ranges from 1901 to 2017. We find that the positive trend in the number of reported GLOFs has decayed distinctly after a break in the 1970s, coinciding with independently detected trend changes in annual air temperatures and in the annual number of field-based glacier surveys (a proxy of scientific reporting). We observe that GLOF reports and glacier surveys decelerated, while temperature rise accelerated in the past five decades. Enhanced warming alone can thus hardly explain the annual number of reported GLOFs, suggesting that temperature-driven glacier lake formation, growth, and failure are weakly coupled, or that outbursts have been overlooked. Indeed, our analysis emphasizes a distinct geographic and temporal bias in GLOF reporting, and we project that between two to four out of five GLOFs on average might have gone unnoticed in the early to mid-20th century. We recommend that such biases should be considered, or better corrected for, when attributing the frequency of reported GLOFs to atmospheric warming.
Rupture directivity, implying a predominant earthquake rupture propagation direction, is typically inferred upon the identification of 2D azimuthal patterns of seismic observations for weak to large earthquakes using surface-monitoring networks. However, the recent increase of 3D monitoring networks deployed in the shallow subsurface and underground laboratories toward the monitoring of microseismicity allows to extend the directivity analysis to 3D modeling, beyond the usual range of magnitudes. The high-quality full waveforms recorded for the largest, decimeter-scale acoustic emission (AE) events during a meter-scale hydraulic fracturing experiment in granites at similar to 410 m depth allow us to resolve the apparent durations observed at each AE sensor to analyze 3D-directivity effects. Unilateral and (asymmetric) bilateral ruptures are then characterized by the introduction of a parameter kappa, representing the angle between the directivity vector and the station vector. While the cloud of AE activity indicates the planes of the hydrofractures, the resolved directivity vectors show off-plane orientations, indicating that rupture planes of microfractures on a scale of centimeters have different geometries. Our results reveal a general alignment of the rupture directivity with the orientation of the minimum horizontal stress, implying that not only the slip direction but also the fracture growth produced by the fluid injections is controlled by the local stress conditions.
Data driven high resolution modeling and spatial analyses of the COVID-19 pandemic in Germany
(2021)
The SARS-CoV-2 virus has spread around the world with over 100 million infections to date, and currently many countries are fighting the second wave of infections. With neither sufficient vaccination capacity nor effective medication, non-pharmaceutical interventions (NPIs) remain the measure of choice.
However, NPIs place a great burden on society, the mental health of individuals, and economics. Therefore the cost/benefit ratio must be carefully balanced and a target-oriented small-scale implementation of these NPIs could help achieve this balance.
To this end, we introduce a modified SEIRD-class compartment model and parametrize it locally for all 412 districts of Germany. The NPIs are modeled at district level by time varying contact rates. This high spatial resolution makes it possible to apply geostatistical methods to analyse the spatial patterns of the pandemic in Germany and to compare the results of different spatial resolutions.
We find that the modified SEIRD model can successfully be fitted to the COVID-19 cases in German districts, states, and also nationwide. We propose the correlation length as a further measure, besides the weekly incidence rates, to describe the current situation of the epidemic.
Woody plants are expanding into the Arctic in response to the warming climate. The impact on arctic plant communities is not well understood due to the limited knowledge about plant assembly rules.
Records of past plant diversity over long time series are rare. Here, we applied sedimentary ancient DNA metabarcoding targeting the P6 loop of the chloroplast trnL gene to a sediment record from Lake Ilirney (central Chukotka, Far Eastern Russia) covering the last 28 thousand years.
Our results show that forb-rich steppe-tundra and dwarf-shrub tundra dominated during the cold climate before 14 ka, while deciduous erect-shrub tundra was abundant during the warm period since 14 ka. Larix invasion during the late Holocene substantially lagged behind the likely warmest period between 10 and 6 ka, where the vegetation biomass could be highest.
We reveal highest richness during 28-23 ka and a second richness peak during 13-9 ka, with both periods being accompanied by low relative abundance of shrubs. During the cold period before 14 ka, rich plant assemblages were phylogenetically clustered, suggesting low genetic divergence in the assemblages despite the great number of species. This probably originates from environmental filtering along with niche differentiation due to limited resources under harsh environmental conditions. In contrast, during the warmer period after 14 ka, rich plant assemblages were phylogenetically overdispersed.
This results from a high number of species which were found to harbor high genetic divergence, likely originating from an erratic recruitment process in the course of warming. Some of our evidence may be of relevance for inferring future arctic plant assembly rules and diversity changes. By analogy to the past, we expect a lagged response of tree invasion. Plant richness might overshoot in the short term; in the long-term, however, the ongoing expansion of deciduous shrubs will eventually result in a phylogenetically more diverse community.
Efforts have been made in the past to enhance building exposure models on a regional scale with increasing spatial resolutions by integrating different data sources. This work follows a similar path and focuses on the downscaling of the existing SARA exposure model that was proposed for the residential building stock of the communes of Valparaiso and Vina del Mar (Chile). Although this model allowed great progress in harmonising building classes and characterising their differential physical vulnerabilities, it is now outdated, and in any case, it is spatially aggregated over large administrative units. Hence, to more accurately consider the impact of future earthquakes on these cities, it is necessary to employ more reliable exposure models. For such a purpose, we propose updating this existing model through a Bayesian approach by integrating ancillary data that has been made increasingly available from Volunteering Geo-Information (VGI) activities. Its spatial representation is also optimised in higher resolution aggregation units that avoid the inconvenience of having incomplete building-by-building footprints. A worst-case earthquake scenario is presented to calculate direct economic losses and highlight the degree of uncertainty imposed by exposure models in comparison with other parameters used to generate the seismic ground motions within a sensitivity analysis. This example study shows the great potential of using increasingly available VGI to update worldwide building exposure models as well as its importance in scenario-based seismic risk assessment.
Assessment of climate change impact on discharge of the lakhmass catchment (Northwest Tunisia)
(2022)
The Mediterranean region is increasingly recognized as a climate change hotspot but is highly underrepresented in hydrological climate change studies. This study aims to investigate the climate change effects on the hydrology of Lakhmass catchment in Tunisia. Lakhmass catchment is a part of the Medium Valley of Medjerda in northwestern Tunisia that drains an area of 126 km(2). First, the Hydrologiska Byrans Vattenbalansavdelning light (HBV-light) model was calibrated and validated successfully at a daily time step to simulate discharge during the 1981-1986 period. The Nash Sutcliffe Efficiency and Percent bias (NSE, PBIAS) were (0.80, +2.0%) and (0.53, -9.5%) for calibration (September 1982-August 1984) and validation (September 1984-August 1986) periods, respectively. Second, HBV-light model was considered as a predictive tool to simulate discharge in a baseline period (1981-2009) and future projections using data (precipitation and temperature) from thirteen combinations of General Circulation Models (GCMs) and Regional Climatic Models (RCMs). We used two trajectories of Representative Concentration Pathways, RCP4.5 and RCP8.5, suggested by the Intergovernmental Panel on Climate Change (IPCC). Each RCP is divided into three projection periods: near-term (2010-2039), mid-term (2040-2069) and long-term (2070-2099). For both scenarios, a decrease in precipitation and discharge will be expected with an increase in air temperature and a reduction in precipitation with almost 5% for every +1 degrees C of global warming. By long-term (2070-2099) projection period, results suggested an increase in temperature with about 2.7 degrees C and 4 degrees C, and a decrease in precipitation of approximately 7.5% and 15% under RCP4.5 and RCP8.5, respectively. This will likely result in a reduction of discharge of 12.5% and 36.6% under RCP4.5 and RCP8.5, respectively. This situation calls for early climate change adaptation measures under a participatory approach, including multiple stakeholders and water users.
Marine sedimentary archives are routinely used to reconstruct past environmental changes. In many cases, bioturbation and sedimentary mixing affect the proxy time-series and the age-depth relationship. While idealized models of bioturbation exist, they usually assume homogeneous mixing, thus that a single sample is representative for the sediment layer it is sampled from.
However, it is largely unknown to which extent this assumption holds for sediments used for paleoclimate reconstructions.
To shed light on
1) the age-depth relationship and its full uncertainty,
2) the magnitude of mixing processes affecting the downcore proxy variations, and
3) the representativity of the discrete sample for the sediment layer, we designed and performed a case study on South China Sea sediment material which was collected using a box corer and which covers the last glacial cycle.
Using the radiocarbon content of foraminiferal tests as a tracer of time, we characterize the spatial age-heterogeneity of sediments in a three-dimensional setup. In total, 118 radiocarbon measurements were performed on defined small- and large-volume bulk samples ( similar to 200 specimens each) to investigate the horizontal heterogeneity of the sediment. Additionally, replicated measurements on small numbers of specimens (10 x 5 specimens) were performed to assess the heterogeneity within a sample volume. Visual assessment of X-ray images and a quantitative assessment of the mixing strength show typical mixing from bioturbation corresponding to around 10 cm mixing depth.
Notably, our 3D radiocarbon distribution reveals that the horizontal heterogeneity (up to 1,250 years), contributing to the age uncertainty, is several times larger than the typically assumed radiocarbon based age-model error (single errors up to 250 years). Furthermore, the assumption of a perfectly bioturbated layer with no mixing underneath is not met.
Our analysis further demonstrates that the age-heterogeneity might be a function of sample size; smaller samples might contain single features from the incomplete mixing and are thus less representative than larger samples.
We provide suggestions for future studies, optimal sampling strategies for quantitative paleoclimate reconstructions and realistic uncertainty in age models, as well as discuss possible implications for the interpretation of paleoclimate records.
In this study we present a novel method for the automatic detection of minerals and elements using hyperspectral transmittance imaging microscopy measurements of complete thin sections (HyperTIM).
This is accomplished by using a hyperspectral camera system that operates in the visible and near-infrared (VNIR) range with a specifically designed sample holder, scanning setup, and a microscope lens.
We utilize this method on a monazite ore thin section from Steenkampskraal (South Africa), which we analyzed for the rare earth element (REE)-bearing mineral monazite ((Ce,Nd,La)PO4), with high concentrations of Nd. The transmittance analyses with the hyperspectral VNIR camera can be used to identify REE minerals and Nd in thin sections.
We propose a three-point band depth index, the Nd feature depth index (NdFD), and its related product the Nd band depth index (NdBDI), which enables automatic mineral detection and classification for the Nd-bearing monazites in thin sections. In combination with the average concentration of the relative Nd content, it permits a destruction-free, total concentration calculation for Nd across the entire thin section.
Sedimentary ancient DNA-based studies have been used to probe centuries of climate and environmental changes and how they affected cyanobacterial assemblages in temperate lakes. Due to cyanobacteria containing potential bloom-forming and toxin-producing taxa, their approximate reconstruction from sediments is crucial, especially in lakes lacking long-term monitoring data. To extend the resolution of sediment record interpretation, we used high-throughput sequencing, amplicon sequence variant (ASV) analysis, and quantitative PCR to compare pelagic cyanobacterial composition to that in sediment traps (collected monthly) and surface sediments in Lake Tiefer See. Cyanobacterial composition, species richness, and evenness was not significantly different among the pelagic depths, sediment traps and surface sediments (p > 0.05), indicating that the cyanobacteria in the sediments reflected the cyanobacterial assemblage in the water column. However, total cyanobacterial abundances (qPCR) decreased from the metalimnion down the water column. The aggregate-forming (Aphanizomenon) and colony-forming taxa (Snowella) showed pronounced sedimentation. In contrast, Planktothrix was only very poorly represented in sediment traps (meta- and hypolimnion) and surface sediments, despite its highest relative abundance at the thermocline (10 m water depth) during periods of lake stratification (May-October). We conclude that this skewed representation in taxonomic abundances reflects taphonomic processes, which should be considered in future DNA-based paleolimnological investigations.
LegacyPollen 1.0
(2022)
Here we describe the LegacyPollen 1.0, a dataset of 2831 fossil pollen records with metadata, a harmonized taxonomy, and standardized chronologies.
A total of 1032 records originate from North America, 1075 from Europe, 488 from Asia, 150 from Latin America, 54 from Africa, and 32 from the Indo-Pacific.
The pollen data cover the late Quaternary (mostly the Holocene). The original 10 110 pollen taxa names (including variations in the notations) were harmonized to 1002 terrestrial taxa (including Cyperaceae), with woody taxa and major herbaceous taxa harmonized to genus level and other herbaceous taxa to family level.
The dataset is valuable for synthesis studies of, for example, taxa areal changes, vegetation dynamics, human impacts (e.g., deforestation), and climate change at global or continental scales.
The harmonized pollen and metadata as well as the harmonization table are available from PANGAEA (https://doi.org/10.1594/PANGAEA.929773; Herzschuh et al., 2021). R code for the harmonization is provided at Zenodo (https://doi.org/10.5281/zenodo.5910972; Herzschuh et al., 2022) so that datasets at a customized harmonization level can be easily established.
Planned decommissioning of coal-fired plants in Europe requires innovative technical and economic strategies to support coal regions on their path towards a climate-resilient future. The repurposing of open pit mines into hybrid pumped hydro power storage (HPHS) of excess energy from the electric grid, and renewable sources will contribute to the EU Green Deal, increase the economic value, stabilize the regional job market and contribute to the EU energy supply security. This study aims to present a preliminary phase of a geospatial workflow used to evaluate land suitability by implementing a multi-criteria decision making (MCDM) technique with an advanced geographic information system (GIS) in the context of an interdisciplinary feasibility study on HPHS in the Kardia lignite open pit mine (Western Macedonia, Greece). The introduced geospatial analysis is based on the utilization of the constraints and ranking criteria within the boundaries of the abandoned mine regarding specific topographic and proximity criteria. The applied criteria were selected from the literature, while for their weights, the experts' judgement was introduced by implementing the analytic hierarchy process (AHP), in the framework of the ATLANTIS research program. According to the results, seven regions were recognized as suitable, with a potential energy storage capacity from 1.09 to 5.16 GWh. Particularly, the present study's results reveal that 9.27% (212,884 m(2)) of the area had a very low suitability, 15.83% (363,599 m(2)) had a low suitability, 23.99% (550,998 m(2)) had a moderate suitability, 24.99% (573,813 m(2)) had a high suitability, and 25.92% (595,125 m(2)) had a very high suitability for the construction of the upper reservoir. The proposed semi-automatic geospatial workflow introduces an innovative tool that can be applied to open pit mines globally to identify the optimum design for an HPHS system depending on the existing lower reservoir.
Soil bacteria play a fundamental role in pedogenesis. However, knowledge about both the impact of climate and slope aspects on microbial communities and the consequences of these items in pedogenesis is lacking. Therefore, soil-bacterial communities from four sites and two different aspects along the climate gradient of the Chilean Coastal Cordillera were investigated. Using a combination of microbiological and physicochemical methods, soils that developed in arid, semi-arid, mediterranean, and humid climates were analyzed. Proteobacteria, Acidobacteria, Chloroflexi, Verrucomicrobia, and Planctomycetes were found to increase in abundance from arid to humid climates, while Actinobacteria and Gemmatimonadetes decreased along the transect. Bacterial-community structure varied with climate and aspect and was influenced by pH, bulk density, plant-available phosphorus, clay, and total organic-matter content. Higher bacterial specialization was found in arid and humid climates and on the south-facing slope and was likely promoted by stable microclimatic conditions. The presence of specialists was associated with ecosystem-functional traits, which shifted from pioneers that accumulated organic matter in arid climates to organic decomposers in humid climates. These findings provide new perspectives on how climate and slope aspects influence the composition and functional capabilities of bacteria, with most of these capabilities being involved in pedogenetic processes.
Reducing greenhouse gas emissions in food systems is becoming more challenging as food is increasingly consumed away from producer regions, highlighting the need to consider emissions embodied in trade in agricultural emissions accounting.
To address this, our study explores recent trends in trade-adjusted agricultural emissions of food items at the global, regional, and national levels.
We find that emissions are largely dependent on a country’s consumption patterns and their agricultural emission intensities relative to their trading partners’.
The absolute differences between the production-based and trade-adjusted emissions accounting approaches are especially apparent for major agricultural exporters and importers and where large shares of emission-intensive items such as ruminant meat, milk products and rice are involved.
In relative terms, some low-income and emerging and developing economies with consumption of high emission intensity food products show large differences between approaches.
Similar trends are also found under various specifications that account for trade and re-exports differently.
These findings could serve as an important element towards constructing national emissions reduction targets that consider trading partners, leading to more effective emissions reductions overall.
The concepts of CO2 emission, global warming, climate change, and their environmental impacts are of utmost importance for the understanding and protection of the ecosystems.
Among the natural sources of gases into the atmosphere, the contribution of geogenic sources plays a crucial role. However, while subaerial emissions are widely studied, submarine outgassing is not yet well understood.
In this study, we review and catalog 122 literature and unpublished data of submarine emissions distributed in ten coastal areas of the Aegean Sea. This catalog includes descriptions of the degassing vents through in situ observations, their chemical and isotopic compositions, and flux estimations.
Temperatures and pH data of surface seawaters in four areas affected by submarine degassing are also presented.
This overview provides useful information to researchers studying the impact of enhanced seawater CO2 concentrations related either to increasing CO2 levels in the atmosphere or leaking carbon capture and storage systems.
In-depth understanding of the reorganization of the hydrological cycle in response to global climate change is crucial in highly sensitive regions like the eastern Mediterranean, where water availability is a major factor for socioeconomic and political development.
The sediments of Lake Lisan provide a unique record of hydroclimatic change during the last glacial to Holocene transition (ca. 24-11 ka) with its tremendous water level drop of similar to 240 m that finally led to its transition into the present hypersaline water body-the Dead Sea.
Here we utilize high-resolution sedimentological analyses from the marginal terraces and deep lake to reconstruct an unprecedented seasonal record of the last millennia of Lake Lisan. Aragonite varve formation in intercalated intervals of our record demonstrates that a stepwise long-term lake level decline was interrupted by almost one millennium of rising or stable water level.
Even periods of pronounced water level drops indicated by gypsum deposition were interrupted by decades of positive water budgets.
Our results thus highlight that even during major climate change at the end of the last glacial, decadal to millennial periods of relatively stable or positive moisture supply occurred which could have been an important premise for human sedentism.
The Arctic is rich in aquatic systems and experiences rapid warming due to climate change. The accelerated warming causes permafrost thaw and the mobilization of organic carbon.
When dissolved organic carbon is mobilized, this DOC can be transported to aquatic systems and degraded in the water bodies and further downstream. Here, we analyze the influence of different landscape components on DOC concentrations and export in a small (6.45 km(2)) stream catchment in the Lena River Delta.
The catchment includes lakes and ponds, with the flow path from Pleistocene yedoma deposits across Holocene non-yedoma deposits to the river outlet. In addition to DOC concentrations, we use radiocarbon dating of DOC as well as stable oxygen and hydrogen isotopes (delta O-18 and delta D) to assess the origin of DOC.
We find significantly higher DOC concentrations in the Pleistocene yedoma area of the catchment compared to the Holocene non-yedoma area with medians of 5 and 4.5 mg L-1 (p < 0.05), respectively. When yedoma thaw streams with high DOC concentration reach a large yedoma thermokarst lake, we observe an abrupt decrease in DOC concentration, which we attribute to dilution and lake processes such as mineralization. The DOC ages in the large thermokarst lake (between 3,428 and 3,637 C-14 y BP) can be attributed to a mixing of mobilized old yedoma and Holocene carbon.
Further downstream after the large thermokarst lake, we find progressively younger DOC ages in the stream water to its mouth, paired with decreasing DOC concentrations. This process could result from dilution with leaching water from Holocene deposits and/or emission of ancient yedoma carbon to the atmosphere. Our study shows that thermokarst lakes and ponds may act as DOC filters, predominantly by diluting incoming waters of higher DOC concentrations or by re-mineralizing DOC to CO2 and CH4.
Nevertheless, our results also confirm that the small catchment still contributes DOC on the order of 1.2 kg km(-2) per day from a permafrost landscape with ice-rich yedoma deposits to the Lena River.
In this study, we analyzed a large seismological dataset from temporary and permanent networks in the southern and eastern Alps to establish high-precision hypocenters and 1-D V-P and V-P/V-S models. The waveform data of a subset of local earthquakes with magnitudes in the range of 1-4.2 M-L were recorded by the dense, temporary SWATH-D network and selected stations of the AlpArray network between September 2017 and the end of 2018. The first arrival times of P and S waves of earthquakes are determined by a semi-automatic procedure. We applied a Markov chain Monte Carlo inversion method to simultaneously calculate robust hypocenters, a 1-D velocity model, and station corrections without prior assumptions, such as initial velocity models or earthquake locations. A further advantage of this method is the derivation of the model parameter uncertainties and noise levels of the data. The precision estimates of the localization procedure is checked by inverting a synthetic travel time dataset from a complex 3-D velocity model and by using the real stations and earthquakes geometry. The location accuracy is further investigated by a quarry blast test. The average uncertainties of the locations of the earthquakes are below 500m in their epicenter and similar to 1.7 km in depth. The earthquake distribution reveals seismicity in the upper crust (0-20 km), which is characterized by pronounced clusters along the Alpine frontal thrust, e.g., the Friuli-Venetia (FV) region, the Giudicarie-Lessini (GL) and Schio-Vicenza domains, the Austroalpine nappes, and the Inntal area. Some seismicity also occurs along the Periadriatic Fault. The general pattern of seismicity reflects head-on convergence of the Adriatic indenter with the Alpine orogenic crust. The seismicity in the FV and GL regions is deeper than the modeled frontal thrusts, which we interpret as indication for southward propagation of the southern Alpine deformation front (blind thrusts).
Dryland xeric conditions exert a deterministic effect on microbial communities, forcing life into refuge niches. Deposited rocks can form a lithic niche for microorganisms in desert regions. Mineral weathering is a key process in soil formation and the importance of microbial-driven mineral weathering for nutrient extraction is increasingly accepted. Advances in geobiology provide insight into the interactions between microorganisms and minerals that play an important role in weathering processes. In this study, we present the examination of the microbial diversity in dryland rocks from the Tsauchab River banks in Namibia. We paired culture-independent 16S rRNA gene amplicon sequencing with culture-dependent (isolation of bacteria) techniques to assess the community structure and diversity patterns. Bacteria isolated from dryland rocks are typical of xeric environments and are described as being involved in rock weathering processes. For the first time, we extracted extra- and intracellular DNA from rocks to enhance our understanding of potentially rock-weathering microorganisms. We compared the microbial community structure in different rock types (limestone, quartz-rich sandstone and quartz-rich shale) with adjacent soils below the rocks. Our results indicate differences in the living lithic and sublithic microbial communities.
The release of greenhouse gases from the large organic carbon stock in permafrost deposits in the circumarctic regions may accelerate global warming upon thaw. The extent of this positive climate feedback is thought to be largely controlled by the microbial degradability of the organic matter preserved in these sediments. In addition, weathering and oxidation processes may release inorganic carbon preserved in permafrost sediments as CO2, which is generally not accounted for. We used C-13 and C-14 analysis and isotopic mass balances to differentiate and quantify organic and inorganic carbon released as CO2 in the field from an active retrogressive thaw slump of Pleistocene-age Yedoma and during a 1.5-years incubation experiment. The results reveal that the dominant source of the CO2 released from freshly thawed Yedoma exposed as thaw mound is Pleistocene-age organic matter (48-80%) and to a lesser extent modern organic substrate (3-34%). A significant portion of the CO2 originated from inorganic carbon in the Yedoma (17-26%). The mixing of young, active layer material with Yedoma at a site on the slump floor led to the preferential mineralization of this young organic carbon source. Admixtures of younger organic substrates in the Yedoma thaw mound were small and thus rapidly consumed as shown by lower contributions to the CO2 produced during few weeks of aerobic incubation at 4 degrees C corresponding to approximately one thaw season. Future CO2 fluxes from the freshly thawed Yedoma will contain higher proportions of ancient inorganic (22%) and organic carbon (61-78%) as suggested by the results at the end, after 1.5 years of incubation. The increasing contribution of inorganic carbon during the incubation is favored by the accumulation of organic acids from microbial organic matter degradation resulting in lower pH values and, in consequence, in inorganic carbon dissolution. Because part of the inorganic carbon pool is assumed to be of pedogenic origin, these emissions would ultimately not alter carbon budgets. The results of this study highlight the preferential degradation of younger organic substrates in freshly thawed Yedoma, if available, and a substantial release of CO2 from inorganic sources.
We present two new empirical models of radiation belt electron flux at geostationary orbit. GOES-15 measurements of 0.8 MeV electrons were used to train a Nonlinear Autoregressive with Exogenous input (NARX) neural network for both modeling GOES-15 flux values and an upper boundary condition scaling factor (BF). The GOES-15 flux model utilizes an input and feedback delay of 2 and 2 time steps (i.e., 5 min time steps) with the most efficient number of hidden layers set to 10. Magnetic local time, Dst, Kp, solar wind dynamic pressure, AE, and solar wind velocity were found to perform as predicative indicators of GOES-15 flux and therefore were used as the exogenous inputs. The NARX-derived upper boundary condition scaling factor was used in conjunction with the Versatile Electron Radiation Belt (VERB) code to produce reconstructions of the radiation belts during the period of July-November 1990, independent of in-situ observations. Here, Kp was chosen as the sole exogenous input to be more compatible with the VERB code. This Combined Release and Radiation Effects Satellite-era reconstruction showcases the potential to use these neural network-derived boundary conditions as a method of hindcasting the historical radiation belts. This study serves as a companion paper to another recently published study on reconstructing the radiation belts during Solar Cycles 17-24 (Saikin et al., 2021, ), for which the results featured in this paper were used.
Regional flood frequency analysis (RFFA) is a powerful method for interrogating hydrological series since it combines observational time series from several sites within a region to estimate risk-relevant statistical parameters with higher accuracy than from single-site series. Since RFFA extreme value estimates depend on the shape of the selected distribution of the data-generating stochastic process, there is need for a suitable goodness-of-distributional-fit measure in order to optimally utilize given data. Here we present a novel, least-squares-based measure to select the optimal fit from a set of five distributions, namely Generalized Extreme Value (GEV), Generalized Logistic, Gumbel, Log-Normal Type III and Log-Pearson Type III. The fit metric is applied to annual maximum discharge series from six hydrological stations along the Sava River in South-eastern Europe, spanning the years 1961 to 2020. Results reveal that (1) the Sava River basin can be assessed as hydrologically homogeneous and (2) the GEV distribution provides typically the best fit. We offer hydrological-meteorological insights into the differences among the six stations. For the period studied, almost all stations exhibit statistically insignificant trends, which renders the conclusions about flood risk as relevant for hydrological sciences and the design of regional flood protection infrastructure.
Climate Benefits of Cleaner Energy Transitions in East and South Asia Through Black Carbon Reduction
(2022)
The state of air pollution has historically been tightly linked to how we produce and use energy. Air pollutant emissions over Asia are now changing rapidly due to cleaner energy transitions; however, magnitudes of benefits for climate and air quality remain poorly quantified. The associated risks involve adverse health impacts, reduced agricultural yields, reduced freshwater availability, contributions to climate change, and economic costs. We focus particularly on climate benefits of energy transitions by making first-time use of two decades of high quality observations of atmospheric loading of light-absorbing black carbon (BC) over Kanpur (South Asia) and Beijing (East Asia) and relating these observations to changing energy, emissions, and economic trends in India and China. Our analysis reveals that absorption aerosol optical depth (AAOD) due to BC has decreased substantially, by 40% over Kanpur and 60% over Beijing between 2001 and 2017, and thus became decoupled from regional economic growth. Furthermore, the resultant decrease in BC emissions and BC AAOD over Asia is regionally coherent and occurs primarily due to transitions into cleaner energies (both renewables and fossil fuels) and not due to the decrease in primary energy supply or decrease in use of fossil use and biofuels and waste. Model simulations show that BC aerosols alone contribute about half of the surface temperature change (warming) of the total forcing due to greenhouse gases, natural and internal variability, and aerosols, thus clearly revealing the climate benefits due to a reduction in BC emissions, which would significantly reduce global warming. However, this modeling study excludes responses from natural variability, circulation, and sea ice responses, which cause relatively strong temperature fluctuations that may mask signals from BC aerosols. Our findings show additional benefits for climate (beyond benefits of CO2 reduction) and for several other issues of sustainability over South and East Asia, provide motivation for ongoing cleaner energy production, and consumption transitions, especially when they are associated with reduced emissions of air pollutants. Such an analysis connecting the trends in energy transitions and aerosol absorption loading, unavailable so far, is crucial for simulating the aerosol climate impacts over Asia which is quite uncertain.
Extracting information about past tectonic or climatic environmental changes from sedimentary records is a key objective of provenance research. Interpreting the imprint of such changes remains challenging as signals might be altered in the sediment-routing system.
We investigate the sedimentary provenance of the Oligocene/Miocene Upper Austrian Northern Alpine Foreland Basin and its response to the tectonically driven exhumation of the Tauern Window metamorphic dome (28 +/- 1 Ma) in the Eastern European Alps by using the unprecedented combination of Nd isotopic composition of bulk-rock clay-sized samples and partly previously published multi-proxy (Nd isotopic composition, trace-element geochemistry, U-Pb dating) sand-sized apatite single-grain analysis.
The basin offers an excellent opportunity to investigate environmental signal propagation into the sedimentary record because comprehensive stratigraphic and seismic datasets can be combined with present research results. The bulk-rock clay-sized fraction epsilon Nd values of well-cutting samples from one well on the northern basin slope remained stable at similar to-9.7 from 27 to 19 Ma but increased after 19 Ma to similar to-9.1. In contrast, apatite single-grain distributions, which were extracted from 22 drill-core samples, changed significantly around 23.3 Ma from apatites dominantly from low-grade (<upper amphibolite-facies) metamorphic sources with Permo-Mesozoic and late Variscan U-Pb ages and epsilon Nd values of -4.4 to dominantly high-grade metamorphic apatites with late Variscan U-Pb ages and epsilon Nd values of -2.2.
The change in apatite single-grain distributions at 23.3 Ma is interpreted to result from the exposure of a new Upper Austroalpine source nappe with less negative epsilon Nd values triggered by the ongoing Tauern Window exhumation. Combining these data with the clay-sized bulk-rock epsilon Nd values reveals that the provenance changed 4-5 Myrs later at 19 Ma in the clay-sized fraction.
Reasons for the delayed provenance-change recording are rooted in the characteristics of the applied methods.
Whereas single-grain distributions of orogen-wide sediment-routing systems can be dominated by geographically small areas with high erosion and mineral fertility rates, bulk-rock methods integrate over the entire drainage basin, thus diminishing extreme values. Hence, by combining these two methods, spatial information are uncovered, enabling a previously unattained understanding of the underlying environmental change.
Ice-rich permafrost has been subject to abrupt thaw and thermokarst formation in the past and is vulnerable to current global warming. The ice-rich permafrost domain includes Yedoma sediments that have never thawed since deposition during the late Pleistocene and Alas sediments that were formed by previous thermokarst processes during the Lateglacial and Holocene warming. Permafrost thaw unlocks organic carbon (OC) and minerals from these deposits and exposes OC to mineralization. A portion of the OC can be associated with iron (Fe), a redox-sensitive element acting as a trap for OC. Post-depositional thaw processes may have induced changes in redox conditions in these deposits and thereby affected Fe distribution and interactions between OC and Fe, with knock-on effects on the role that Fe plays in mediating present day OC mineralization. To test this hypothesis, we measured Fe concentrations and proportion of Fe oxides and Fe complexed with OC in unthawed Yedoma and previously thawed Alas deposits. Total Fe concentrations were determined on 1,292 sediment samples from the Yedoma domain using portable X-ray fluorescence; these concentrations were corrected for trueness using a calibration based on a subset of 144 samples measured by inductively coupled plasma optical emission spectrometry after alkaline fusion (R (2) = 0.95). The total Fe concentration is stable with depth in Yedoma deposits, but we observe a depletion or accumulation of total Fe in Alas deposits, which experienced previous thaw and/or flooding events. Selective Fe extractions targeting reactive forms of Fe on unthawed and previously thawed deposits highlight that about 25% of the total Fe is present as reactive species, either as crystalline or amorphous oxides, or complexed with OC, with no significant difference in proportions of reactive Fe between Yedoma and Alas deposits. These results suggest that redox driven processes during past thermokarst formation impact the present-day distribution of total Fe, and thereby the total amount of reactive Fe in Alas versus Yedoma deposits. This study highlights that ongoing thermokarst lake formation and drainage dynamics in the Arctic influences reactive Fe distribution and thereby interactions between Fe and OC, OC mineralization rates, and greenhouse gas emissions.
How biased are our models?
(2021)
Geophysical process simulations play a crucial role in the understanding of the subsurface. This understanding is required to provide, for instance, clean energy sources such as geothermal energy. However, the calibration and validation of the physical models heavily rely on state measurements such as temperature. In this work, we demonstrate that focusing analyses purely on measurements introduces a high bias. This is illustrated through global sensitivity studies. The extensive exploration of the parameter space becomes feasible through the construction of suitable surrogate models via the reduced basis method, where the bias is found to result from very unequal data distribution. We propose schemes to compensate for parts of this bias. However, the bias cannot be entirely compensated. Therefore, we demonstrate the consequences of this bias with the example of a model calibration.
Cyanobacteria are important primary producers in temperate freshwater ecosystems. However, studies on the seasonal and spatial distribution of cyanobacteria in deep lakes based on high-throughput DNA sequencing are still rare. In this study, we combined monthly water sampling and monitoring in 2019, amplicon sequence variants analysis (ASVs; a proxy for different species) and quantitative PCR targeting overall cyanobacteria abundance to describe the seasonal and spatial dynamics of cyanobacteria in the deep hard-water oligo-mesotrophic Lake Tiefer See, NE Germany. We observed significant seasonal variation in the cyanobacterial community composition (p < 0.05) in the epi- and metalimnion layers, but not in the hypolimnion. In winter-when the water column is mixed-picocyanobacteria (Synechococcus and Cyanobium) were dominant. With the onset of stratification in late spring, we observed potential niche specialization and coexistence among the cyanobacteria taxa driven mainly by light and nutrient dynamics. Specifically, ASVs assigned to picocyanobacteria and the genus Planktothrix were the main contributors to the formation of deep chlorophyll maxima along a light gradient. While Synechococcus and different Cyanobium ASVs were abundant in the epilimnion up to the base of the euphotic zone from spring to fall, Planktothrix mainly occurred in the metalimnetic layer below the euphotic zone where also overall cyanobacteria abundance was highest in summer. Our data revealed two potentially psychrotolerant (cold-adapted) Cyanobium species that appear to cope well under conditions of lower hypolimnetic water temperature and light as well as increasing sediment-released phosphate in the deeper waters in summer. The potential cold-adapted Cyanobium species were also dominant throughout the water column in fall and winter. Furthermore, Snowella and Microcystis-related ASVs were abundant in the water column during the onset of fall turnover. Altogether, these findings suggest previously unascertained and considerable spatiotemporal changes in the community of cyanobacteria on the species level especially within the genus Cyanobium in deep hard-water temperate lakes.
Strong hydroclimatic controls on vulnerability to subsurface nitrate contamination across Europe
(2020)
Subsurface contamination due to excessive nutrient surpluses is a persistent and widespread problem in agricultural areas across Europe. The vulnerability of a particular location to pollution from reactive solutes, such as nitrate, is determined by the interplay between hydrologic transport and biogeochemical transformations. Current studies on the controls of subsurface vulnerability do not consider the transient behaviour of transport dynamics in the root zone. Here, using state-of-the-art hydrologic simulations driven by observed hydroclimatic forcing, we demonstrate the strong spatiotemporal heterogeneity of hydrologic transport dynamics and reveal that these dynamics are primarily controlled by the hydroclimatic gradient of the aridity index across Europe. Contrasting the space-time dynamics of transport times with reactive timescales of denitrification in soil indicate that similar to 75% of the cultivated areas across Europe are potentially vulnerable to nitrate leaching for at least onethird of the year. We find that neglecting the transient nature of transport and reaction timescale results in a great underestimation of the extent of vulnerable regions by almost 50%. Therefore, future vulnerability and risk assessment studies must account for the transient behaviour of transport and biogeochemical transformation processes.
Water bodies are a highly abundant feature of Arctic permafrost ecosystems and strongly influence their hydrology, ecology and biogeochemical cycling. While very high resolution satellite images enable detailed mapping of these water bodies, the increasing availability and abundance of this imagery calls for fast, reliable and automatized monitoring. This technical work presents a largely automated and scalable workflow that removes image noise, detects water bodies, removes potential misclassifications from infrastructural features, derives lake shoreline geometries and retrieves their movement rate and direction on the basis of ortho-ready very high resolution satellite imagery from Arctic permafrost lowlands. We applied this workflow to typical Arctic lake areas on the Alaska North Slope and achieved a successful and fast detection of water bodies. We derived representative values for shoreline movement rates ranging from 0.40-0.56 m yr(-1) for lake sizes of 0.10 ha-23.04 ha. The approach also gives an insight into seasonal water level changes. Based on an extensive quantification of error sources, we discuss how the results of the automated workflow can be further enhanced by incorporating additional information on weather conditions and image metadata and by improving the input database. The workflow is suitable for the seasonal to annual monitoring of lake changes on a sub-meter scale in the study areas in northern Alaska and can readily be scaled for application across larger regions within certain accuracy limitations.
The subsurface is a temporally dynamic and spatially heterogeneous compartment of the Earth's critical zone, and biogeochemical transformations taking place in this compartment are crucial for the cycling of nutrients.
The impact of spatial heterogeneity on such microbially mediated nutrient cycling is not well known, which imposes a severe challenge in the prediction of in situ biogeochemical transformation rates and further of nutrient loading contributed by the groundwater to the surface water bodies.
Therefore, we used a numerical modelling approach to evaluate the sensitivity of groundwater microbial biomass distribution and nutrient cycling to spatial heterogeneity in different scenarios accounting for various residence times.
The model results gave us an insight into domain characteristics with respect to the presence of oxic niches in predominantly anoxic zones and vice versa depending on the extent of spatial heterogeneity and the flow regime.
The obtained results show that microbial abundance, distribution, and activity are sensitive to the applied flow regime and that the mobile (i.e. observable by groundwater sampling) fraction of microbial biomass is a varying, yet only a small, fraction of the total biomass in a domain. Furthermore, spatial heterogeneity resulted in anaerobic niches in the domain and shifts in microbial biomass between active and inactive states. The lack of consideration of spatial heterogeneity, thus, can result in inaccurate estimation of microbial activity. In most cases this leads to an overestimation of nutrient removal (up to twice the actual amount) along a flow path.
We conclude that the governing factors for evaluating this are the residence time of solutes and the Damkohler number (Da) of the biogeochemical reactions in the domain. We propose a relationship to scale the impact of spatial heterogeneity on nutrient removal governed by the logioDa.
This relationship may be applied in upscaled descriptions of microbially mediated nutrient cycling dynamics in the subsurface thereby resulting in more accurate predictions of, for example, carbon and nitrogen cycling in groundwater over long periods at the catchment scale.
Understanding the key factors influencing the water quality of large river systems forms an important basis for the assessment and protection of cross-regional ecosystems and the implementation of adapted water management concepts. However, identifying these factors requires in-depth comprehension of the unique environmental systems, which can only be achieved by detailed water quality monitoring.
Within the scope of the joint science and sports event "Elbschwimmstaffel" (swimming relay on the river Elbe) in June/July 2017 organized by the German Ministry of Education and Research, water quality data were acquired along a 550 km long stretch of the Elbe River in Germany. During the survey, eight physiochemical water quality parameters were recorded in high spatial and temporal resolution with the BIOFISH multisensor system. Multivariate statistical methods were applied to identify and delineate processes influencing the water quality.
The BIOFISH dataset revealed that phytoplankton activity has a major impact on the water quality of the Elbe River in the summer months. The results suggest that phytoplankton biomass constitutes a substantial proportion of the suspended particles and that photosynthetic activity of phytoplankton is closely related to significant temporal changes in pH and oxygen saturation.
An evaluation of the BIOFISH data based on the combination of statistical analysis with weather and discharge data shows that the hydrological and meteorological history of the sampled water body was the main driver of phytoplankton dynamics. This study demonstrates the capacity of longitudinal river surveys with the BIOFISH or similar systems for water quality assessment, the identification of pollution sources and their utilization for online in situ monitoring of rivers.