ALBERT

Description: We compare differences and similarities in the annual stratospheric HNO3 cycle derived from ground‐based measurements at the South Pole during 1993 and 1995, after correcting an error in earlier published profile retrievals for 1993 which led to under estimation of mixing ratios. The data series presented here provide profiling over the range ∼16–48 km, and cover the fall‐winter‐spring cycle in the behavior of HNO3 in the extreme Antarctic with a large degree of temporal overlap. With the exception of one gap of 20 days, the combined data sets cover a full annual cycle. The record shows an increase in HNO3 above 30 km occurring about 20 days before sunset, which appears to be the result of higher altitude heterogeneous conversion of NOx as photolysis diminishes. Both years show a strong increase in HNO3 beginning about polar sunset, in a layer peaking at about 25 km, as additional NOx is heterogeneously converted to nitric acid. When temperatures drop to the polar stratospheric cloud (PSC) formation range near the end of May, gas phase HNO3 is rapidly reduced in the lower stratosphere, although at least 2–3 weeks of temperatures ≤192 K appear to be required to complete most of the gas‐phase removal at the upper end of the depletion range (22–25 km). Despite a significant difference in residual sulfate loading from the explosion of Mount Pinatubo, there appears to be little gross difference in the timing and effects of PSC formation in removing gas phase HNO3 in these 2 years, though removal may be more rapid in 1995. Incorporation of gas phase HNO3 into PSCs appears to be nearly complete up to ∼25 km by midwinter. We also see a repeat of the formation of gas phase HNO3 in the middle stratosphere in early midwinter of 1995 with about the same timing as in 1993, suggesting that this phenomenon is driven by a repetition of dynamical transport and appropriate temperatures and pressures in the polar night, and not (as has been suggested) by ion‐based heterogeneous chemistry that requires triggering by large relativistic electron fluxes. High‐altitude HNO3 production peaks during a period of ∼20 days, but appears to persist for up to ∼40 days in the 40–45 km range, ceasing well before sunrise. This HNO3 descends rapidly throughout the production period, at a rate in good agreement with theoretically determined midwinter subsidence rates. As noted in earlier studies, later warming of this region above PSC evaporation temperatures does not cause reappearance of large amounts of HNO3, indicating that most PSCs gravitationally sink out of the stratosphere before early spring. We present evidence that smaller PSCs do evaporate to ∼1 to 3.5 ppbv of HNO3 in the lower stratosphere, however, working downward from ∼25 km as temperatures rise during the late winter. There is a delay of ∼15 days after sunrise before photolysis causes significant depletion in the altitude range below ∼30 km, where subsidence has carried virtually all higher‐altitude HNO3 by polar sunrise. Some continued subsidence and photolysis combine to keep mixing ratios less than ∼5 ppbv below 30 km until the final breakdown of the vortex in November brings larger amounts of HNO3 with air from lower latitudes.

Description: Published

Description: 17739-17750

Description: 5A. Ricerche polari e paleoclima

Description: JCR Journal

Description: We propose a version of the pure temporal epidemic type aftershock sequences (ETAS) model: the ETAS model with correlated magnitudes. As for the standard case, we assume the Gutenberg-Richter law to be the probability density for the magnitudes of the background events. Instead, the magnitude of the triggered shocks is assumed to be probabilistically dependent on that of the relative mother events. This probabilistic dependence is motivated by some recent works in the literature and by the results of a statistical analysis made on some seismic catalogs [Spassiani and Sebastiani, J. Geophys. Res. 121, 903 (2016)10.1002/2015JB012398]. On the basis of the experimental evidences obtained in the latter paper for the real catalogs, we theoretically derive the probability density function for the magnitudes of the triggered shocks proposed in Spassiani and Sebastiani and there used for the analysis of two simulated catalogs. To this aim, we impose a fundamental condition: averaging over all the magnitudes of the mother events, we must obtain again the Gutenberg-Richter law. This ensures the validity of this law at any event's generation when ignoring past seismicity. The ETAS model with correlated magnitudes is then theoretically analyzed here. In particular, we use the tool of the probability generating function and the Palm theory, in order to derive an approximation of the probability of zero events in a small time interval and to interpret the results in terms of the interevent time between consecutive shocks, the latter being a very useful random variable in the assessment of seismic hazard.

Description: Published

Description: 042134

Description: 6T. Studi di pericolosità sismica e da maremoto

Description: JCR Journal

Description: Seismic hazard modeling is a multidisciplinary science that aims to forecast earthquake occurrence and its resultant ground shaking. Such models consist of a probabilistic framework that quantifies uncertainty across a complex system; typically, this includes at least two model components developed from Earth science: seismic source and ground motion models. Although there is no scientific prescription for the forecast length, the most common probabilistic seismic hazard analyses consider forecasting windows of 30 to 50 years, which are typically an engineering demand for building code purposes. These types of analyses are the topic of this review paper. Although the core methods and assumptions of seismic hazard modeling have largely remained unchanged for more than 50 years, we review the most recent initiatives, which face the difficult task of meeting both the increasingly sophisticated demands of society and keeping pace with advances in scientific understanding. A need for more accurate and spatially precise hazard forecasting must be balanced with increased quantification of uncertainty and new challenges such as moving from time‐independent hazard to forecasts that are time dependent and specific to the time period of interest. Meeting these challenges requires the development of science‐driven models, which integrate all information available, the adoption of proper mathematical frameworks to quantify the different types of uncertainties in the hazard model, and the development of a proper testing phase of the model to quantify its consistency and skill. We review the state of the art of the National Seismic Hazard Modeling and how the most innovative approaches try to address future challenges.

Description: Published

Description: e2019RG000653

Description: 6T. Studi di pericolosità sismica e da maremoto

Description: JCR Journal

Description: An edited version of this paper was published by AGU. Copyright (2016) American Geophysical Union.

Description: The accuracy of earthquake locations and their correspondence with subsurface geology depends strongly on the accuracy of the available seismic velocity model. Most modern methods to construct a velocity model for earthquake location are based on the inversion of passive source seismological data. Another approach is the integration of high-resolution geological and geophysical data to construct deterministic velocity models in which earthquake locations can be directly correlated to the geological structures. Such models have to be kinematically consistent with independent seismological data in order to provide precise hypocenter solutions. We present the Altotiberina (AT) seismic model, a three-dimensional velocity model for the Upper Tiber Valley region (Northern Apennines, Italy), constructed by combining 300 km of seismic reflection profiles, 6 deep boreholes (down to 5 km depth), detailed data from geological surveys and direct measurements of P- and S-wave velocities performed in situ and in laboratory. We assess the robustness of the AT seismic model by locating 11,713 earthquakes with a non-linear, global-search inversion method and comparing the probabilistic hypocenter solutions to those calculated in three previously published velocity models, constructed by inverting passive seismological data only. Our results demonstrate that the AT seismic model is able to provide higher-quality hypocenter locations than the previous velocity models. Earthquake locations are consistent with the subsurface geological structures and show a high degree of spatial correlation with specific lithostratigraphic units, suggesting a lithological control on the seismic activity evolution.

Description: Published

Description: 8113-8135

Description: 4T. Sismicità dell'Italia

Description: JCR Journal

Description: [1] We present the first intercomparison between the two most comprehensive records of gas‐phase HNO3 profiles in the Antarctic stratosphere, covering the greater part of 1993 and 1995. We compare measurements by the Stony Brook Ground‐Based Millimeter‐wave Spectrometer (GBMS) at the South Pole with Version 5 HNO3 data from the Microwave Limb Sounder (MLS) aboard the Upper Atmospheric Research Satellite. Trajectory tracing was used to select MLS measurements in the 70°–80°S latitude band that sampled air observed by the GBMS during passage over the Pole. When temperatures were near the HNO3 condensation range, additional screening was performed to select MLS measurements that sampled air parcels within 1.5 K of the temperature they experienced over the Pole. Quantitative comparisons are given at 7 different potential temperature levels spanning the range ∼19–30 km. Agreement between the data sets is quite good between 465 and 655 K (∼20–25 km) during a large fraction of the year. Agreement is best during winter and spring, when seasonally averaged differences are generally within 1 ppbv below ∼25 km. At higher altitudes, and during summer and fall, the agreement becomes worse, and GBMS measurements can exceed MLS values by more than 3 ppbv. We provide evidence that differences occurring in the lower stratosphere during fall are due to lack of colocation between the two data sets during a period of strong poleward gradients in HNO3. Remaining discrepancies between GBMS and MLS V5 HNO3 measurements are thought to be due to instrumental or retrieval biases.

Description: Published

Description: id 4809

Description: 5A. Ricerche polari e paleoclima

Description: JCR Journal

Description: Mineral dust plays an important role in the atmospheric radiation budget as well as in the ocean carbon cycle through fertilization and by ballasting of settling organic matter. However, observational records of open‐ocean dust deposition are sparse. Here, we present the spatial and temporal evolution of Saharan dust deposition over 2 years from marine sediment traps across the North Atlantic, directly below the core of the Saharan dust plume, with highest dust fluxes observed in summer. We combined the observed deposition fluxes with model simulations and satellite observations and argue that dust deposition in the Atlantic is predominantly controlled by summer rains. The dominant depositional pathway changes from wet deposition in summer to dry deposition in winter. Wet deposition has previously been suggested to increase the release of dust‐derived nutrients and their bioavailability, which may be a key contributor to surface‐ocean productivity in remote and oligotrophic parts of the oceans.

Description: The Northeast Greenland Ice Stream (NEGIS) is an important dynamic component contributing to the total mass balance of the Greenland ice sheet, as it reaches up to the central divide and drains 12% of the ice sheet. The ice stream geometry and surface velocities in the onset region of the NEGIS are not yet sufficiently well reproduced by ice sheet models. We present an assessment of the basal conditions of the onset region in a systematic analysis of airborne ultra-wideband radar data. Our data yield a new detailed model of ice-thickness distribution and basal topography in the upstream part of the ice stream. We observe a change from a smooth to a rougher bed where the ice stream widens from 10 to 60 km, and a distinct roughness anisotropy, indicating a preferred orientation of subglacial structures. The observation of off-nadir reflections that are symmetrical to the bed reflection in the radargrams suggests that these structures are elongated subglacial landforms, which in turn indicate potential streamlining of the bed. Together with basal water routing pathways, our observations hint to two different zones in this part of the NEGIS: an accelerating and smooth upstream region, which is collecting water, with reduced basal traction, and in the further downstream part, where the ice stream is slowing down and is widening, with a distribution of basal water towards the shear margins. Our findings support the hypothesis that the NEGIS is strongly interconnected to the subglacial water system in its onset region, but also to the subglacial substrate and morphology.

Description: Species’ vulnerability to climate change depends on the most temperature-sensitive life stages, but for major animal groups such as fish, life cycle bottlenecks are often not clearly defined. We used observational, experimental, and phylogenetic data to assess stage-specific thermal tolerance metrics for 694 marine and freshwater fish species from all climate zones. Our analysis shows that spawning adults and embryos consistently have narrower tolerance ranges than larvae and nonreproductive adults and are most vulnerable to climate warming. The sequence of stage-specific thermal tolerance corresponds with the oxygen-limitation hypothesis, suggesting a mechanistic link between ontogenetic changes in cardiorespiratory (aerobic) capacity and tolerance to temperature extremes. A logarithmic inverse correlation between the temperature dependence of physiological rates (development and oxygen consumption) and thermal tolerance range is proposed to reflect a fundamental, energetic trade-off in thermal adaptation. Scenario-based climate projections considering the most critical life stages (spawners and embryos) clearly identify the temperature requirements for reproduction as a critical bottleneck in the life cycle of fish. By 2100, depending on the Shared Socioeconomic Pathway (SSP) scenario followed, the percentages of species potentially affected by water temperatures exceeding their tolerance limit for reproduction range from ~10% (SSP 1–1.9) to ~60% (SSP 5–8.5). Efforts to meet ambitious climate targets (SSP 1–1.9) could therefore benefit many fish species and people who depend on healthy fish stocks.

Description: Changes in ocean gateway configuration can induce basin‐scale rearrangements in ocean current characteristics. However, there is large uncertainty in the relative timing of the Oligocene/Miocene subsidence histories of the Greenland‐Scotland Ridge (GSR) and the Fram Strait (FS). By using a climate model, we investigate the temperature and salinity changes in response to the subsidence of these two key ocean gateways during early to middle Miocene. For a singular subsidence of the GSR, we detect warming and a salinity increase in the Nordic Seas and the Arctic Ocean. As convection sites shift to the north of Iceland, North Atlantic Deep Water (NADW) is formed at cooler temperatures. The associated deep ocean cooling and upwelling of deep waters to the Southern Ocean surface can cause a cooling in the southern high latitudes. These characteristic responses to the GSR deepening are independent of the FS being shallow or deep. An isolated subsidence of the FS gateway for a deep GSR shows less pronounced warming and salinity increase in the Nordic Seas. Arctic temperatures remain unaltered, but a stronger salinity increase is detected, which further increases the density of NADW. The increase in salinity enhances the contribution of NADW to the abyssal ocean at the expense of the colder southern source water component. These relative changes largely counteract each other and cause a negligible warming in the upwelling regions of the Southern Ocean.

Description: The Antarctic Circumpolar Current (ACC) is the world's largest current system connecting all three major basins of the global ocean. Our knowledge of glacial‐interglacial changes in ACC dynamics in the southeast Pacific is not well constrained and presently only based on reconstructions covering the last glacial cycle. Here we use a combination of mean sortable silt grain size of the terrigenous sediment fraction (10–63 μm, "Sortable Silt") and X‐ray fluorescence scanner‐derived Zr/Rb ratios as flow strength proxies to examine ACC variations at the Pacific entrance to the Drake Passage (DP) in the vicinity of the Subantarctic Front. Our results indicate that at the DP entrance, ACC strength varied by ~6–16% on glacial‐interglacial time scales, yielding higher current speeds during interglacial times and reduced current speeds during glacials. We provide evidence that previous observations of a reduction in DP throughflow during the last glacial period are part of a consistent pattern extending for at least the last 1.3 Ma. The orbital‐scale cyclicity follows well‐known global climate changes from prevailing ca. 41‐kyr cycles in the early part of the record (1.3 Ma to 850 ka; marine isotope stage 21) across the mid‐Pleistocene transition into the middle and late Pleistocene 100‐kyr world. A comparison to a bottom water flow record from the deep western boundary current off New Zealand (Ocean Drilling Program Site 1123) reveals anti‐phased changes between the two sites. The enhanced supply of deep water along the DP and into the Atlantic Ocean during interglacials corresponds to a weakened flow of the SW Pacific deep western boundary current.

Description: Efforts to collaboratively manage the risk of flooding are ultimately based on individuals learning about risks, the decision process, and the effectiveness of decisions made in prior situations. This article argues that much can be learned about a governance setting by explicitly evaluating the relationships through which influential individuals and their immediate contacts receive and send information to one another. We define these individuals as “brokers,” and the networks that emerge from their interactions as “learning spaces.” The aim of this article is to develop strategies to identify and evaluate the properties of a broker's learning space that are indicative of a collaborative flood risk management arrangement. The first part of this article introduces a set of indicators, and presents strategies to employ this list so as to systematically identify brokers, and compare their learning spaces. The second part outlines the lessons from an evaluation that explored cases in two distinct flood risk management settings in Germany. The results show differences in the observed brokers' learning spaces. The contacts and interactions of the broker in Baden‐Württemberg imply a collaborative setting. In contrast, learning space of the broker in North Rhine‐Westphalia lacks the same level of diversity and polycentricity.

Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659

Description: MWK Baden‐Württemberg

Description: Most common machine learning (ML) algorithms usually work well on balanced training sets, that is, datasets in which all classes are approximately represented equally. Otherwise, the accuracy estimates may be unreliable and classes with only a few values are often misclassified or neglected. This is known as a class imbalance problem in machine learning and datasets that do not meet this criterion are referred to as imbalanced data. Most datasets of soil classes are, therefore, imbalanced data. One of our main objectives is to compare eight resampling strategies that have been developed to counteract the imbalanced data problem. We compared the performance of five of the most common ML algorithms with the resampling approaches. The highest increase in prediction accuracy was achieved with SMOTE (the synthetic minority oversampling technique). In comparison to the baseline prediction on the original dataset, we achieved an increase of about 10, 20 and 10% in the overall accuracy, kappa index and F‐score, respectively. Regarding the ML approaches, random forest (RF) showed the best performance with an overall accuracy, kappa index and F‐score of 66, 60 and 57%, respectively. Moreover, the combination of RF and SMOTE improved the accuracy of the individual soil classes, compared to RF trained on the original dataset and allowed better prediction of soil classes with a low number of samples in the corresponding soil profile database, in our case for Chernozems. Our results show that balancing existing soil legacy data using synthetic sampling strategies can significantly improve the prediction accuracy in digital soil mapping (DSM). Highlights Spatial distribution of soil classes in Iran can be predicted using machine learning (ML) algorithms. The synthetic minority oversampling technique overcomes the drawback of imbalanced and highly biased soil legacy data. When combining a random forest model with synthetic sampling strategies the prediction accuracy of the soil model improves significantly. The resulting new soil map of Iran has a much higher spatial resolution compared to existing maps and displays new soil classes that have not yet been mapped in Iran.

Description: Alexander von Humboldt‐Stiftung http://dx.doi.org/10.13039/100005156

Description: German Research Foundation http://dx.doi.org/10.13039/501100001659

Description: Soil and Water Research Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran

Description: The application of biochar to agricultural soils to increase nutrient availability, crop production and carbon sequestration has gained increasing interest but data from field experiments on temperate, marginal soils are still under‐represented. In the current study, biochar, produced from organic residues (digestates) from a biogas plant, was applied with and without digestates at low (3.4 t ha−1) and intermediate (17.1 t ha−1) rates to two acidic and sandy soils in northern Germany that are used for corn (Zea mays L.) production. Soil nutrient availability, crop yields, microbial biomass and carbon dioxide (CO2) emissions from heterotrophic respiration were measured over two consecutive years. The effects of biochar application depended on the intrinsic properties of the two tested soils and the biochar application rates. Although the soils at the fallow site, with initially low nutrient concentrations, showed a significant increase in pH, soil nutrients and crop yield after low biochar application rates, a similar response was found at the cornfield site only after application of substantially larger amounts of biochar. The effect of a single dose of biochar at the beginning of the experiment diminished over time but was still detectable after 2 years. Whereas plant available nutrient concentrations increased after biochar application, the availability of potentially phytotoxic trace elements (Zn, Pb, Cd, Cr) decreased significantly, and although slight increases in microbial biomass carbon and heterotrophic CO2 fluxes were observed after biochar application, they were mostly not significant. The results indicate that the application of relatively small amounts of biochar could have positive effects on plant available nutrients and crop yields of marginal arable soils and may decrease the need for mineral fertilizers while simultaneously increasing the sequestration of soil organic carbon. Highlights A low rate of biochar increased plant available nutrients and crop yield on marginal soils. Biochar application reduced the availability of potentially harmful trace elements. Heterotrophic respiration showed no clear response to biochar application. Biochar application may reduce fertilizer need and increase carbon sequestration on marginal soils.

Description: German Academic Exchange Service http://dx.doi.org/10.13039/501100001655

Description: Institute Strategic Programme grants, “Soils to Nutrition”

Description: Social inequalities lead to flood resilience inequalities across social groups, a topic that requires improved documentation and understanding. The objective of this paper is to attend to these differences by investigating self‐stated flood recovery across genders in Vietnam as a conceptual replication of earlier results from Germany. This study employs a regression‐based analysis of 1,010 respondents divided between a rural coastal and an urban community in Thua Thien‐Hue province. The results highlight an important set of recovery process‐related variables. The set of relevant variables is similar across genders in terms of inclusion and influence, and includes age, social capital, internal and external support after a flood, perceived severity of previous flood impacts, and the perception of stress‐resilience. However, women were affected more heavily by flooding in terms of longer recovery times, which should be accounted for in risk management. Overall, the studied variables perform similarly in Vietnam and Germany. This study, therefore, conceptually replicates previous results suggesting that women display slightly slower recovery levels as well as that psychological variables influence recovery rates more than adverse flood impacts. This provides an indication of the results' potentially robust nature due to the different socio‐environmental contexts in Germany and Vietnam.

Description: Nitrogen (N) fertilization is the major contributor to nitrous oxide (N2O) emissions from agricultural soil, especially in post‐harvest seasons. This study was carried out to investigate whether ryegrass serving as cover crop affects soil N2O emissions and denitrifier community size. A microcosm experiment was conducted with soil planted with perennial ryegrass (Lolium perenne L.) and bare soil, each with four levels of N fertilizer (0, 5, 10 and 20 g N m−2; applied as calcium ammonium nitrate). The closed‐chamber approach was used to measure soil N2O fluxes. Real‐time PCR was used to estimate the biomass of bacteria and fungi and the abundance of genes involved in denitrification in soil. The results showed that the presence of ryegrass decreased the nitrate content in soil. Cumulative N2O emissions of soil with grass were lower than in bare soil at 5 and 10 g N m−2. Fertilization levels did not affect the abundance of soil bacteria and fungi. Soil with grass showed greater abundances of bacteria and fungi, as well as microorganisms carrying narG, napA, nirK, nirS and nosZ clade I genes. It is concluded that ryegrass serving as a cover crop holds the potential to mitigate soil N2O emissions in soils with moderate or high NO3− concentrations. This highlights the importance of cover crops for the reduction of N2O emissions from soil, particularly following N fertilization. Future research should explore the full potential of ryegrass to reduce soil N2O emissions under field conditions as well as in different soils. Highlights This study was to investigate whether ryegrass serving as cover crop affects soil N2O emissions and denitrifier community size; Plant reduced soil N substrates on one side, but their root exudates stimulated denitrification on the other side; N2O emissions were lower in soil with grass than bare soil at medium fertilizer levels, and growing grass stimulated the proliferation of almost all the denitrifying bacteria except nosZ clade II; Ryegrass serving as a cover crop holds the potential to mitigate soil N2O emissions.

Description: China Scholarship Council http://dx.doi.org/10.13039/501100004543

Description: The National Science Project for University of Anhui Province

Description: High‐performance numerical codes are an indispensable tool for hydrogeologists when modeling subsurface flow and transport systems. But as they are written in compiled languages, like C/C++ or Fortran, established software packages are rarely user‐friendly, limiting a wider adoption of such tools. OpenGeoSys (OGS), an open‐source, finite‐element solver for thermo‐hydro‐mechanical–chemical processes in porous and fractured media, is no exception. Graphical user interfaces may increase usability, but do so at a dramatic reduction of flexibility and are difficult or impossible to integrate into a larger workflow. Python offers an optimal trade‐off between these goals by providing a highly flexible, yet comparatively user‐friendly environment for software applications. Hence, we introduce ogs5py, a Python‐API for the OpenGeoSys 5 scientific modeling package. It provides a fully Python‐based representation of an OGS project, a large array of convenience functions for users to interact with OGS and connects OGS to the scientific and computational environment of Python.

Description: German Federal Environmental Foundation http://dx.doi.org/10.13039/100007636

Description: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659

Description: Transport processes that lead to exchange of mass between surface water and groundwater play a significant role for the ecological functioning of aquatic systems, for hydrological processes and for biogeochemical transformations. In this study, we present a novel integral modeling approach for flow and transport at the sediment–water interface. The model allows us to simultaneously simulate turbulent surface and subsurface flow and transport with the same conceptual approach. For this purpose, a conservative transport equation was implemented to an existing approach that uses an extended version of the Navier–Stokes equations. Based on previous flume studies which investigated the spreading of a dye tracer under neutral, losing and gaining flow conditions the new solver is validated. Tracer distributions of the experiments are in close agreement with the simulations. The simulated flow paths are significantly affected by in‐ and outflowing groundwater flow. The highest velocities within the sediment are found for losing condition, which leads to shorter residence times compared to neutral and gaining conditions. The largest extent of the hyporheic exchange flow is observed under neutral condition. The new solver can be used for further examinations of cases that are not suitable for the conventional coupled models, for example, if Reynolds numbers are larger than 10. Moreover, results gained with the integral solver provide high‐resolution information on pressure and velocity distributions at the rippled streambed, which can be used to improve flow predictions. This includes the extent of hyporheic exchange under varying ambient groundwater flow conditions.

Description: Technische Universität Berlin, Germany

Description: German Research Foundation http://dx.doi.org/10.13039/501100001659

Description: Sustainable arable cropping relies on repeated liming. Yet, the associated increase in soil pH can reduce the availability of iron (Fe) to plants. We hypothesized that repeated liming, but not pedogenic processes such as lessivage (i.e., translocation of clay particles), alters the Fe cycle in Luvisol soil, thereby affecting Fe isotope composition in soils and crops. Hence, we analysed Fe concentrations and isotope compositions in soil profiles and winter rye from the long‐term agricultural experimental site in Berlin‐Dahlem, Germany, where a controlled liming trial with three field replicates per treatment has been conducted on Albic Luvisols since 1923. Heterogeneity in subsoil was observed at this site for Fe concentration but not for Fe isotope composition. Lessivage had not affected Fe isotope composition in the soil profiles. The results also showed that almost 100 years of liming lowered the concentration of the HCl‐extractable Fe that was potentially available for plant uptake in the surface soil (0–15 cm) from 1.03 (standard error (SE) 0.03) to 0.94 (SE 0.01) g kg−1. This HCl‐extractable Fe pool contained isotopically lighter Fe (δ56Fe = −0.05 to −0.29‰) than the bulk soil (δ56Fe = −0.08 to 0.08‰). However, its Fe isotope composition was not altered by the long‐term lime application. Liming resulted in relatively lower Fe concentrations in the roots of winter rye. In addition, liming led to a heavier Fe isotope composition of the whole plants compared with those grown in the non‐limed plots (δ56FeWholePlant_ + Lime = −0.12‰, SE 0.03 vs. δ56FeWholePlant_‐Lime = −0.21‰, SE 0.01). This suggests that the elevated soil pH (increased by one unit due to liming) promoted the Fe uptake strategy through complexation of Fe(III) from the rhizosphere, which favoured heavier Fe isotopes. Overall, the present study showed that liming and a related increase in pH did not affect the Fe isotope compositions of the soil, but may influence the Fe isotope composition of plants grown in the soil if they alter their Fe uptake strategy upon the change of Fe availability. Highlights Fe concentrations and stocks, but not Fe isotope compositions, were more heterogeneous in subsoil than in topsoil. Translocation of clay minerals did not result in Fe isotope fractionation in the soil profile of a Luvisol. Liming decreased Fe availability in topsoil, but did not affect its δ56Fe values. Uptake of heavier Fe isotopes by graminaceous crops was more pronounced at elevated pH.

Description: Bundesministerium für Bildung und Forschung http://dx.doi.org/10.13039/501100002347

Description: Coping with the growing impacts of flooding in EU countries, a paradigm shift in flood management can be observed, moving from safety‐based towards risk‐based approaches and holistic perspectives. Flood resilience is a common denominator of most of the approaches. In this article, we present the ‘Flood Resilience Rose’ (FRR), a management tool to promote harmonised action towards flood resilience in European regions and beyond. The FRR is a result of a two‐step process. First, based on scientific concepts as well as analysis of relevant policy documents, we identified three ‘levels of operation’. The first level refers to the EU Floods Directive and an extended multi‐layer safety approach, comprising the four different layers of protection, prevention, preparedness and recovery, and related measures to be taken. This level is not independent but depends both on the institutional (second level) and the wider (third level) context. Second, we used surveys, semi‐structured interviews and group discussions during workshops with experts from Belgium, Denmark, Germany, the Netherlands and the United Kingdom to validate the definitions and the FRR's practical relevance. The presented FRR is thus the result of rigorous theoretical and practical consideration and provides a tool capable to strengthen flood risk management practice.

Description: European Regional Development Fund http://dx.doi.org/10.13039/501100008530

Description: Methane emissions from northern high latitude wetlands constitute a major uncertainty in the atmospheric methane (CH4) budget during the Holocene. To reconstruct northern wetland methane emissions, we used an empirical model based on syntheses of observations of peat initiation from more than 3600 radiocarbon-dated basal peat ages, plant-macrofossil-derived peatland type from more than 250 peat cores from sites across the northern high latitudes, and observed CH4 emissions averaged from modern-day wetland types in order to explore the effects of wetland expansion and changes in wetland type. Peatland basal ages and plant macrofossil records showed the widespread formation of fens in major northern wetland complexes before 8000 BP. After 8000 BP, new fen formation continued, but widespread peatland succession (to bogs) and permafrost aggradation also occurred. Reconstructed CH4 emissions from peatlands increased rapidly between 10,600 BP and 6900 BP due to fen formation and expansion, then stabilized after 5000 BP at 42 ± 25 Tg CH4 y-1, as high methane-emitting fens transitioned to lower methane-emitting bogs and permafrost peatlands. Permafrost formation in northern peatlands after 1000 BP decreased CH4 emissions by 20% to 34 ± 21 Tg y-1 by the present day. Warming temperatures, changes in peatland hydrology, and permafrost thaw will likely change the magnitude of northern peatland emissions in the future.

Description: Infrastructure and anthropogenic impacts are expanding across the Arctic. A consistent record of human impact is required in order to quantify the changes and to assess climate change impacts on the communities. We derived a first panarctic satellite-based record of expanding infrastructure and anthropogenic impacts along all permafrost affected coasts (100 km buffer) within the H2020 project Nunataryuk based on Sentinel-1/2 satellite imagery. C-band synthetic aperture radar and multi-spectral information is combined through a machine learning framework. Depending on region, we identified up to 50% more information (human presence) than in OpenStreetMap. The combination with satellite records on vegetation change (specifically NDVI from Landsat since 2000) allowed quantification of recent expansion of infrastructure. Most of the expanded human presence occurred in Russia related predominantly to oil/gas industry. The majority of areas with human presence will be subject to thaw by mid-21st century based on ground temperature trends derived from the ESA CCI+ Permafrost time series (1997-2019). Of specific concern in this context are also settlements located directly at permafrost affected coasts. An efficient erosion rate monitoring scheme needs to be developed and combined with settlement records in order to assess the risk for local communities and infrastructure. Relevant progress in the framework of the ESA EO4PAC project will be discussed.

Description: Retrogressive thaw slumps (RTS) are typical landforms indicating processes of rapid thawing and degrading permafrost. Their abundance is increasing in many regions and quantifying their dynamics is of high importance for assessing geomorphic, hydrologic, and biogeochemical impacts of climate change in the Arctic. Here we present a deep-learning (DL) based semantic segmentation framework to detect RTS, using high-resolution multi-spectral PlanetScope, topographic (ArcticDEM elevation and slope), and medium-resolution multi-temporal Landsat Trend data. We created a highly automated processing pipeline, which is designed to allow reproducible results and to be flexible for multiple input data types. The processing workflow is based on the pytorch deep-learning framework and includes a variety of different segmentation architectures (UNet, UNet++, DeepLabV3), backbones and includes common data transformation techniques such as augmentation or normalization. We tested (training, validation) our DL based model in six different regions of 100 to 300 km² size across Canada, and Siberia. We performed a regional cross-validation (5 regions training, 1 region validation) to test the spatial robustness and transferability of the algorithm. Furthermore, we tested different architectures, backbones and loss-functions to identify the best performing and most robust parameter sets. For training the models we created a database of manually digitized and validated RTS polygons. The resulting model performance varied strongly between different regions with maximum Intersection over Union (IoU) scores between 0.15 and 0.58. The strong regional variation emphasizes the need for sufficiently large training data, which is representative of the diversity of RTS types. However, the creation of good training data proved to be challenging due to the fuzzy definition and delineation of RTS. We are further continuing to improve the usability and the functionality to add further datasets and classes. We will show first results from the upscaling beyond small test areas towards large spatial clusters of extensive RTS presence e.g. Peel Plateau in NW Canada.

Description: With the Earth’s climate rapidly warming, the Arctic represents one of the most vulnerable regions to environmental change. These northern high latitude regions experience intensified fire seasons and especially tundra fires are projected to become more frequent and severe. Fires in permafrost regions have extensive impacts, including the initiation of thermokarst (rapid thaw of ice-rich ground), as they combust the upper organic soil layers which provide insulation to the permafrost below. Rapid permafrost thaw is, thus, often observable in fire scars in the first years post-disturbance. In polygonal ice-wedge landscapes, this becomes most prevalent through melting ice wedges and degrading troughs. The further these ice wedges degrade, the more troughs will likely connect and build an extensive hydrological network with changing patterns and degrees of connectivity that influences hydrology and runoff. While subsiding troughs over melting ice wedges may host new ponds, an increasing connectivity may also subsequently lead to more drainage of ponds, which in turn can limit further thaw and help stabilize the landscape. To quantify the changes in such dynamic landscapes over large regions, highly automated methods are needed that allow extracting information on the geomorphic state and changes over time of ice-wedge trough networks from remote sensing data. We developed a computer vision algorithm to automatically derive ice-wedge polygonal networks and the current microtopography of the degrading troughs from very high resolution, airborne laserscanning-based digital terrain models. We represent the networks as graphs (a concept from the computer sciences to describe complex networks) and apply methods from graph theory to describe and quantify hydrological network characteristics of the changing landscape. In fire scars, we especially observe rapidly growing networks and fast micromorphological change in those degrading troughs. In our study, we provide a space-for-time substitution comparing fire scars throughout the Alaskan tundra of up to 70 years since the fire disturbance, to show how this type of disturbed landscape evolves over time.

Description: Using our custom visualization tool for multitemporal Landsat satellite imagery we discovered, to our knowledge, an undocumented mega-landslide in far-east Siberia, which occurred in summer 2017 (https://bit.ly/2WYRLM1; 61.55°N; 170.01°E). To create and visualize this unique dataset, we processed temporal trends of multispectral indices of 〉100,000 Landsat images for a period from 2000-2019 using the freely available Google Earth Engine cloud processing platform (https://ingmarnitze.users.earthengine.app/view/hotspottcvisapp). The megaslide has a size of 3.66 km² and using the ArcticDEM data we estimate a volume movement of ~20 Mm³. With this size and volume, the landslide is among the largest globally known in recent decades. The landslide is accompanied by a smaller one (0.31 km², 1 Mm³) about 600 m further east, which already occurred in summer 2015. The large landslide caused the formation of several small lakes by blocking two valleys with debris and within newly formed crevasses near the hilltop, which are still persisting as of August 2021. As this event occurred in a remote valley far from any settlement, no visible damage to infrastructure or human livelihoods was detected. The remoteness has likely led to being not detected, like many similar, albeit a lot smaller, erosion features in the Arctic permafrost region. In this presentation we will show the main properties of the landslide, potential trigger mechanisms in the traditional sense. As this region is located along the fringes of permafrost presence we will discuss its potential connection to the rapidly warming climate in the high latitudes. Further, we will discuss how such a large event remained undetected for several years. We discuss and highlight the value of our landscape change visualization tool based on Landsat trend analysis (see Nitze et al., AGU 2020), which helped us to identify this extreme event. With more and more available data sources, this tool in addition to automated image analysis (e.g. deep-learning) or seismic analysis will help to uncover the hidden processes and dynamics of the Earth’s surface.

Description: Several decades of research have provided insight into patterns of and controls on thermokarst initiation and expansion, yet studies tend to focus on individual types of thermokarst (i.e., thaw lake formation and subsequent drainage) in particular regions. Today, we are left with uneven knowledge about abrupt permafrost thaw both conceptually and regionally. The goal of this presentation is to summarize recent advancements in monitoring thermokarst and its impact on soil, vegetation, and water while also framing a call to action for the next decade of research. Over the next decade, permafrost researchers must align their efforts on several fronts to not only increase our knowledge about changing permafrost but to align this knowledge with key community and policy needs. To support climate change planning and adaptation, northern communities need future thaw vulnerability mapped at scales relevant to their needs, which will require a suite of downscaled and new mapping and remote sensing products. Thermokarst predisposition maps based on circumpolar datasets greatly overestimate the area vulnerable to thermokarst, which can lead to poor planning and climate anxiety. In some situations, existing mapping products may be useful for downscaling with more detailed input data. In other situations, entirely new approaches may be required to support local action. A second key need for community relevant research is the ability to detect and monitor early warning indicators of thermokarst. Such information is needed to support scenario planning and to help mitigate the risks to social, cultural, and physical infrastructure created by permafrost change. We are evaluating the potential for using changes in vegetation, wetting/drying and topography as early warning indicators of thermokarst, all of which can be remotely sensed. Finally, integrating fine-scale disturbances such as thermokarst into large scale models remains a key challenge but critical for supporting sound climate policy. While a diversity of permafrost modeling approaches is necessary, we outline guiding principles that will help enhance model comparisons, assimilation of simulated data across spatiotemporal scales, and the ability for policy decisions to be rapidly informed by emerging science on permafrost change.

Description: Elemental carbon exists in different structural forms including graphite, diamond, fullerenes, and amorphous carbon. In nature, these materials are produced through abiotic chemical processes under high temperature and pressure but are considered generally inaccessible to biochemical synthesis or breakdown. Here, we identified and characterized elemental carbon isolated from consortia of anaerobic methanotrophic archaea (ANME) and sulfate-reducing bacteria (SRB), which together carry out the anaerobic oxidation of methane (AOM). Two different AOM consortia, ANME-1a/HotSeep-1 and ANME-2a/c/Seep-SRB, produce a black material with similar characteristics to disordered graphite and amorphous carbon. Stable isotope probing studies revealed that the carbon is microbially generated during AOM. In addition, we found that select methanogens also produce amorphous carbon with similar characteristics to the carbon from AOM consortia. Biogenic amorphous carbon may serve as a conductive element to facilitate electron transfer, or redox active functional groups associated with the carbon could act as electron donors and acceptors.

Description: Methanogens are considered as one of the earliest life forms on Earth, and together with anaerobic methane-oxidizing archaea, they have crucial effects on climate stability. However, the origin and evolution of anaerobic alkane metabolism in the domain Archaea remain controversial. Here, we present evidence that methylotrophic methanogenesis was the ancestral form of this metabolism. Carbon dioxide–reducing methanogenesis developed later through the evolution of tetrahydromethanopterin S-methyltransferase, which linked methanogenesis to the Wood-Ljungdahl pathway for energy conservation. Anaerobic multicarbon alkane metabolisms in Archaea also originated early, with genes coding for the activation of short-chain or even long-chain alkanes likely evolving from an ethane-metabolizing ancestor. These genes were likely horizontally transferred to multiple archaeal clades including Candidatus (Ca.) Bathyarchaeia, Ca. Lokiarchaeia, Ca. Hadarchaeia, and the methanogenic Ca. Methanoliparia.