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  • Blackwell Publishing Ltd  (32.386)
  • Frontiers Media  (31.722)
  • Springer Science + Business Media
  • 2020-2022  (31.731)
  • 1995-1999  (25.582)
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  • 1
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    Compound Hot and Dry Events in Europe: Variability and Large-Scale Drivers (2021)
    Frontiers Media
    In:  EPIC3Frontiers in Climate, Frontiers Media, 3, pp. 58, ISSN: 2624-9553
    Details
    Publikationsdatum: 2021-07-01
    Beschreibung: An important aspect of inevitable surprises, for the climate system, is the potential of occurrence of compound extreme events. These can be events that occur at the same time over the same geographic location or at multiple locations within a given country or around the world. In this study, we investigate the spatio-temporal variability of summer compound hot and dry (CHD) events at European level and we quantify the relationship between the occurrence of CHDs and the large-scale atmospheric circulation. Here we show that summer 1955 stands out as the year with the largest spatial extent characterized by hot and dry conditions (~21.2 at European level), followed by 2015 (~20.3), 1959 (~19.4), and 1950 (~16.9). By employing an Empirical Orthogonal Function (EOF) analysis we show that there are three preferred centers of action of CHDs over Europe: Fennoscandia, the central part of Europe, and the south-eastern part of Europe. Overall, hot and dry summers are, in general, associated with persistent high-pressure systems over the regions affected by CHDs, which in turn reduces the zonal flow and diverts the storm tracks southward. The high-pressure systems associated with each mode of variability largely suppresses ascending motions, reduces water vapor condensation and precipitation formation, leading to drought conditions below this atmospheric system. This study may help improve our understanding of the spatio-temporal variability of hot and dry summers, at European level, as well as their driving mechanisms.
    Repository-Name: EPIC Alfred Wegener Institut
    Materialart: Article , peerRev
    Format: application/pdf
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  • 2
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    Imprint of climate change on pan-Arctic marine vegetation (2020)
    Frontiers Media
    In:  EPIC3Frontiers in Marine Science, Frontiers Media, 7, pp. 617324
    Details
    Publikationsdatum: 2021-01-23
    Beschreibung: The Arctic climate is changing rapidly. The warming and resultant longer open water periods suggest a potential for expansion of marine vegetation along the vast Arctic coastline. We compiled and reviewed the scattered time series on Arctic marine vegetation and explored trends for macroalgae and eelgrass (Zostera marina). We identified a total of 38 sites, distributed between Arctic coastal regions in Alaska, Canada, Greenland, Iceland, Norway/Svalbard, and Russia, having time series extending into the 21st Century. The majority of these exhibited increase in abundance, productivity or species richness, and/or expansion of geographical distribution limits, several time series showed no significant trend. Only four time series displayed a negative trend, largely due to urchin grazing or increased turbidity. Overall, the observations support with medium confidence (i.e., 5–8 in 10 chance of being correct, adopting the IPCC confidence scale) the prediction that macrophytes are expanding in the Arctic. Species distribution modeling was challenged by limited observations and lack of information on substrate, but suggested a current (2000– 2017) potential pan-Arctic macroalgal distribution area of 820.000 km2 (145.000 km2 intertidal, 675.000 km2 subtidal), representing an increase of about 30% for subtidaland 6% for intertidal macroalgae since 1940–1950, and associated polar migration rates averaging 18–23 km decade−1 . Adjusting the potential macroalgal distribution area by the fraction of shores represented by cliffs halves the estimate (412,634 km2 ). Warming and reduced sea ice cover along the Arctic coastlines are expected to stimulate further expansion of marine vegetation from boreal latitudes. The changes likely affect the functioning of coastal Arctic ecosystems because of the vegetation’s roles as habitat, and for carbon and nutrient cycling and storage. We encourage apan-Arctic science- and management agenda to incorporate marine vegetation into a coherent understanding of Arctic changes by quantifying distribution and status beyond the scattered studies now available to develop sustainable management strategies for these important ecosystems.
    Repository-Name: EPIC Alfred Wegener Institut
    Materialart: Article , isiRev , info:eu-repo/semantics/article
    Format: application/pdf
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  • 3
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    Synergic Use of Multi-Sensor Satellite Data for Volcanic Hazards Monitoring: The Fogo (Cape Verde) 2014–2015 Effusive Eruption (2020)
    Frontiers Media
    Details
    Publikationsdatum: 2020-05-29
    Beschreibung: Monitoring volcanic eruptions provides key information for hazard assessment and its time evolution. Satellite remote sensing data are nowadays essential to perform such task, thanks to their capability to survey disastrous events also in remote and under-monitored regions, with frequent revisit time and accurate spatial resolution. Even though satellite imageries are presently used to analyze several phenomena related to eruptions, automatic methods and synergic exploitation of different sensors are rarely considered. In this work, we have analyzed satellite images coming from both synthetic apertureradar(SAR)andopticalsensors,tostudytheeffusiveeruptionofFogovolcano, CapeVerde,whichtookplacebetweenNovember2014andJanuary2015.Inparticular, we have exploited multi-sensor images from Sentinel-1, COSMO-SkyMed, Landsat8, and Earth-Observing-1 missions, to retrieve lava flow patterns and volcanic source parameters related to the eruption. The main outcome of our work is the application of a new automatic change detection technique for estimating the lava field and its temporalevolution,combiningtheSARintensityandtheinterferometricSARcoherence. The innovative algorithm is able to take full advantage of the Sentinel-1 mission’s 6day repeat cycle. Such data are here used for the first time for lava mapping, thereby providing an unprecedented example of using the multi-temporal interferometric SAR (InSAR) coherence to automatically monitor lava flow evolution in emergency phase. This new technique, jointly used with optical satellite images, is capable of resolving with spatial and temporal detail the evolution of lava flows. We have also performed differential SAR interferometry (DInSAR) to map the ground deformation and retrieve the feeding dyke by inverting syn-eruptive signals. Results from source modeling show a SW-NE oriented dyke, located inside Chã das Caldeiras, SW of the Pico do Fogo. Our work highlights how multidisciplinary and satellite open data, along with innovative and automatic processing techniques, may be adopted for real-time hazard estimates in an operational environment
    Beschreibung: Published
    Beschreibung: Article 22
    Beschreibung: 1V. Storia eruttiva
    Beschreibung: JCR Journal
    Schlagwort(e): lava, volcanic source modeling, synthetic aperture radar, optical images, change detection, hierarchical-split-based approach, DInSAR coherence, Fogo volcano
    Repository-Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Materialart: article
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  • 4
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    Evaluating learning spaces in flood risk management in Germany: Lessons for governance research (2021)
    Blackwell Publishing Ltd | Oxford, UK
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    Publikationsdatum: 2021-06-28
    Beschreibung: 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.
    Beschreibung: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Beschreibung: MWK Baden‐Württemberg
    Schlagwort(e): 333.91 ; brokerage ; collaborative water governance ; comanagement ; comparative analysis ; social networks
    Materialart: article
    Standort Signatur Erwartet Verfügbarkeit
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    CITATION GEO-LEO
  • 5
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    Synthetic resampling strategies and machine learning for digital soil mapping in Iran (2021)
    Blackwell Publishing Ltd | Oxford, UK
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    Publikationsdatum: 2021-07-04
    Beschreibung: 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.
    Beschreibung: Alexander von Humboldt‐Stiftung http://dx.doi.org/10.13039/100005156
    Beschreibung: German Research Foundation http://dx.doi.org/10.13039/501100001659
    Beschreibung: Soil and Water Research Institute, Agricultural Research, Education and Extension Organization, Karaj, Iran
    Schlagwort(e): 631.4 ; covariates ; imbalanced data ; machine learning ; random forest ; soil legacy data
    Materialart: article
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    CITATION GEO-LEO
  • 6
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    Impact of biochar on nutrient supply, crop yield and microbial respiration on sandy soils of northern Germany (2021)
    Blackwell Publishing Ltd | Oxford, UK
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    Publikationsdatum: 2021-06-16
    Beschreibung: 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.
    Beschreibung: German Academic Exchange Service http://dx.doi.org/10.13039/501100001655
    Beschreibung: Institute Strategic Programme grants, “Soils to Nutrition”
    Schlagwort(e): 631.4 ; black carbon ; carbon sequestration ; corn ; digestate ; heterotrophic respiration ; marginal soils ; microbial biomass
    Materialart: article
    Standort Signatur Erwartet Verfügbarkeit
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    CITATION GEO-LEO
  • 7
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    Self‐stated recovery from flooding: Empirical results from a survey in Central Vietnam (2021)
    Blackwell Publishing Ltd | Oxford, UK
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    Publikationsdatum: 2021-06-27
    Beschreibung: 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.
    Schlagwort(e): 333.7 ; flood recovery ; resilience ; societal equity ; vulnerability
    Materialart: article
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    CITATION GEO-LEO
  • 8
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    The potential of ryegrass as cover crop to reduce soil N2O emissions and increase the population size of denitrifying bacteria (2021)
    Blackwell Publishing Ltd | Oxford, UK
    Details
    Publikationsdatum: 2021-07-05
    Beschreibung: 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.
    Beschreibung: China Scholarship Council http://dx.doi.org/10.13039/501100004543
    Beschreibung: The National Science Project for University of Anhui Province
    Schlagwort(e): 551.9 ; 631.4 ; denitrification ; perennial ryegrass (Lolium perenne L.) ; soil bacteria ; soil CO2 emissions ; soil N2O emissions
    Materialart: article
    Standort Signatur Erwartet Verfügbarkeit
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  • 9
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    Hydrogen and Carbon Monoxide-Utilizing Kyrpidia spormannii Species From Pantelleria Island, Italy (2020)
    Frontiers Media
    Details
    Publikationsdatum: 2020-06-30
    Beschreibung: Volcanic and geothermal areas are hot and often acidic environments that emit geothermal gasses, including H2, CO and CO2. Geothermal gasses mix with air, creating conditions where thermoacidophilic aerobic H2- and CO-oxidizing microorganisms could thrive. Here, we describe the isolation of two Kyrpidia spormannii strains, which can grow autotrophically by oxidizing H2 and CO with oxygen. These strains, FAVT5 and COOX1, were isolated from the geothermal soils of the Favara Grande on Pantelleria Island, Italy. Extended physiology studies were performed with K. spormannii FAVT5, and showed that this strain grows optimally at 55°C and pH 5.0. The highest growth rate is obtained using H2 as energy source (μmax 0.19 ± 0.02 h-1, doubling time 3.6 h). K. spormannii FAVT5 can additionally grow on a variety of organic substrates, including some alcohols, volatile fatty acids and amino acids. The genome of each strain encodes for two O2-tolerant hydrogenases belonging to [NiFe] group 2a hydrogenases and transcriptome studies using K. spormannii FAVT5 showed that both hydrogenases are expressed under H2 limiting conditions. So far no Firmicutes except K. spormannii FAVT5 have been reported to exhibit a high affinity for H2, with a Ks of 327 ± 24 nM. The genomes of each strain encode for one putative CO dehydrogenase, belonging to Form II aerobic CO dehydrogenases. The genomic potential and physiological properties of these Kyrpidia strains seem to be quite well adapted to thrive in the harsh environmental volcanic conditions.
    Beschreibung: Published
    Beschreibung: Article 951
    Beschreibung: 6A. Geochimica per l'ambiente e geologia medica
    Beschreibung: JCR Journal
    Schlagwort(e): CO ; H2 ; Kyrpidia spormannii ; [NiFe]-hydrogenases ; phylogeny ; thermoacidophilic ; 05.09. Miscellaneous
    Repository-Name: Istituto Nazionale di Geofisica e Vulcanologia (INGV)
    Materialart: article
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  • 10
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    ogs5py: A Python‐API for the OpenGeoSys 5 Scientific Modeling Package (2021)
    Blackwell Publishing Ltd | Malden, US
    Details
    Publikationsdatum: 2021-07-04
    Beschreibung: 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.
    Beschreibung: German Federal Environmental Foundation http://dx.doi.org/10.13039/100007636
    Beschreibung: Deutsche Forschungsgemeinschaft http://dx.doi.org/10.13039/501100001659
    Schlagwort(e): 551.49 ; hydrogeology ; subsurface flow ; modeling ; software
    Materialart: article
    Standort Signatur Erwartet Verfügbarkeit
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    CITATION GEO-LEO
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