TY  - JOUR
A1  - Schmidt, Lena Katharina
A1  - Francke, Till
A1  - Grosse, Peter Martin
A1  - Mayer, Christoph
A1  - Bronstert, Axel
T1  - Reconstructing five decades of sediment export from two glacierized high-alpine catchments in Tyrol, Austria, using nonparametric regression
JF  - Hydrology and earth system sciences : HESS
N2  - 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.
Y1  - 2023
U6  - https://doi.org/10.5194/hess-27-1841-2023
SN  - 1027-5606
SN  - 1607-7938
VL  - 27
IS  - 9
SP  - 1841
EP  - 1863
PB  - Copernicus
CY  - Göttingen
ER  - 
TY  - JOUR
A1  - Davidzon, Iary
A1  - Ilbert, Olivier
A1  - Faisst, Andreas L.
A1  - Sparre, Martin
A1  - Capak, Peter L.
T1  - An Alternate Approach to Measure Specific Star Formation Rates at 2 < z < 7
JF  - The astrophysical journal : an international review of spectroscopy and astronomical physics
N2  - We trace the specific star formation rate (sSFR) of massive star-forming galaxies (greater than or similar to 10(10)M(circle dot)) from z similar to 2 to 7. Our method is substantially different from previous analyses, as it does not rely on direct estimates of star formation rate, but on the differential evolution of the galaxy stellar mass function (SMF). We show the reliability of this approach by means of semianalytical and hydrodynamical cosmological simulations. We then apply it to real data, using the SMFs derived in the COSMOS and CANDELS fields. We find that the sSFR is proportional to (1 + z)(1.1) (+/-) (0.2) at z > 2, in agreement with other observations but in tension with the steeper evolution predicted by simulations from z similar to 4 to 2. We investigate the impact of several sources of observational bias, which, however, cannot account for this discrepancy. Although the SMF of high-redshift galaxies is still affected by significant errors, we show that future large-area surveys will substantially reduce them, making our method an effective tool to probe the massive end of the main sequence of star-forming galaxies.
KW  - galaxies: evolution
KW  - galaxies: high-redshift
KW  - galaxies: star formation
Y1  - 2018
U6  - https://doi.org/10.3847/1538-4357/aaa19e
SN  - 0004-637X
SN  - 1538-4357
VL  - 852
IS  - 2
PB  - IOP Publ. Ltd.
CY  - Bristol
ER  - 
TY  - JOUR
A1  - Schrön, Martin
A1  - Rosolem, Rafael
A1  - Köhli, Markus
A1  - Piussi, L.
A1  - Schröter, I.
A1  - Iwema, J.
A1  - Kögler, S.
A1  - Oswald, Sascha
A1  - Wollschläger, U.
A1  - Samaniego, Luis
A1  - Dietrich, Peter
A1  - Zacharias, Steffen
T1  - Cosmic-ray Neutron Rover Surveys of Field Soil Moisture and the Influence of Roads
JF  - Water resources research
N2  - Measurements of root-zone soil moisture across spatial scales of tens to thousands of meters have been a challenge for many decades. The mobile application of Cosmic Ray Neutron Sensing (CRNS) is a promising approach to measure field soil moisture noninvasively by surveying large regions with a ground-based vehicle. Recently, concerns have been raised about a potentially biasing influence of local structures and roads. We employed neutron transport simulations and dedicated experiments to quantify the influence of different road types on the CRNS measurement. We found that roads introduce a substantial bias in the CRNS estimation of field soil moisture compared to off-road scenarios. However, this effect becomes insignificant at distances beyond a few meters from the road. Neutron measurements on the road could overestimate the field value by up to 40 % depending on road material, width, and the surrounding field water content. The bias could be largely removed with an analytical correction function that accounts for these parameters. Additionally, an empirical approach is proposed that can be used without prior knowledge of field soil moisture. Tests at different study sites demonstrated good agreement between road-effect corrected measurements and field soil moisture observations. However, if knowledge about the road characteristics is missing, measurements on the road could substantially reduce the accuracy of this method. Our results constitute a practical advancement of the mobile CRNS methodology, which is important for providing unbiased estimates of field-scale soil moisture to support applications in hydrology, remote sensing, and agriculture. Plain Language Summary Measurements of root-zone soil moisture across spatial scales of tens to thousands of meters have been a challenge for many decades. The mobile application of Cosmic Ray Neutron Sensing (CRNS) is a promising approach to measure field soil moisture noninvasively by surveying large regions with a ground-based vehicle. Recently, concerns have been raised about a potentially biasing influence of roads. We employed physics simulations and dedicated experiments to quantify the influence of different road types on the CRNS measurement. We found that the presence of roads biased the CRNS estimation of field soil moisture compared to nonroad scenarios. Neutron measurements could overestimate the field value by up to 40 % depending on road material, width, surrounding field water content, and distance from the road. We proposed a correction function that successfully removed this bias and works even without prior knowledge of field soil moisture. Tests at different study sites demonstrated good agreement between corrected measurements and other field soil moisture observations. Our results constitute a practical advancement of the mobile CRNS methodology, which is important for providing unbiased estimates of field-scale soil moisture to support applications in hydrology, remote sensing, and agriculture.
KW  - road effect
KW  - field-scale
KW  - soil moisture
KW  - cosmic ray neutrons
KW  - mobile survey
KW  - COSMOS rover
Y1  - 2018
U6  - https://doi.org/10.1029/2017WR021719
SN  - 0043-1397
SN  - 1944-7973
VL  - 54
IS  - 9
SP  - 6441
EP  - 6459
PB  - American Geophysical Union
CY  - Washington
ER  - 
TY  - JOUR
A1  - Schrön, Martin
A1  - Zacharias, Steffen
A1  - Womack, Gary
A1  - Köhli, Markus
A1  - Desilets, Darin
A1  - Oswald, Sascha
A1  - Bumberger, Jan
A1  - Mollenhauer, Hannes
A1  - Kögler, Simon
A1  - Remmler, Paul
A1  - Kasner, Mandy
A1  - Denk, Astrid
A1  - Dietrich, Peter
T1  - Intercomparison of cosmic-ray neutron sensors and water balance monitoring in an urban environment
JF  - Geoscientific instrumentation, methods and data systems
N2  - Sensor-to-sensor variability is a source of error common to all geoscientific instruments that needs to be assessed before comparative and applied research can be performed with multiple sensors. Consistency among sensor systems is especially critical when subtle features of the surrounding terrain are to be identified. Cosmic-ray neutron sensors (CRNSs) are a recent technology used to monitor hectometre-scale environmental water storages, for which a rigorous comparison study of numerous co-located sensors has not yet been performed. In this work, nine stationary CRNS probes of type "CRS1000" were installed in relative proximity on a grass patch surrounded by trees, buildings, and sealed areas. While the dynamics of the neutron count rates were found to be similar, offsets of a few percent from the absolute average neutron count rates were found. Technical adjustments of the individual detection parameters brought all instruments into good agreement. Furthermore, we found a critical integration time of 6 h above which all sensors showed consistent dynamics in the data and their RMSE fell below 1% of gravimetric water content. The residual differences between the nine signals indicated local effects of the complex urban terrain on the scale of several metres. Mobile CRNS measurements and spatial simulations with the URANOS neutron transport code in the surrounding area (25 ha) have revealed substantial sub-footprint heterogeneity to which CRNS detectors are sensitive despite their large averaging volume. The sealed and constantly dry structures in the footprint furthermore damped the dynamics of the CRNS-derived soil moisture. We developed strategies to correct for the sealed-area effect based on theoretical insights about the spatial sensitivity of the sensor. This procedure not only led to reliable soil moisture estimation during dry-out periods, it further revealed a strong signal of intercepted water that emerged over the sealed surfaces during rain events. The presented arrangement offered a unique opportunity to demonstrate the CRNS performance in complex terrain, and the results indicated great potential for further applications in urban climate research.
Y1  - 2018
U6  - https://doi.org/10.5194/gi-7-83-2018
SN  - 2193-0856
SN  - 2193-0864
VL  - 7
IS  - 1
SP  - 83
EP  - 99
PB  - Copernicus
CY  - Göttingen
ER  - 
TY  - JOUR
A1  - Cohen, Sarel
A1  - Hershcovitch, Moshik
A1  - Taraz, Martin
A1  - Kissig, Otto
A1  - Issac, Davis
A1  - Wood, Andrew
A1  - Waddington, Daniel
A1  - Chin, Peter
A1  - Friedrich, Tobias
T1  - Improved and optimized drug repurposing for the SARS-CoV-2 pandemic
JF  - PLoS one
N2  - The active global SARS-CoV-2 pandemic caused more than 426 million cases and 5.8 million deaths worldwide. The development of completely new drugs for such a novel disease is a challenging, time intensive process. Despite researchers around the world working on this task, no effective treatments have been developed yet. This emphasizes the importance of drug repurposing, where treatments are found among existing drugs that are meant for different diseases. A common approach to this is based on knowledge graphs, that condense relationships between entities like drugs, diseases and genes. Graph neural networks (GNNs) can then be used for the task at hand by predicting links in such knowledge graphs. Expanding on state-of-the-art GNN research, Doshi et al. recently developed the Dr-COVID model. We further extend their work using additional output interpretation strategies. The best aggregation strategy derives a top-100 ranking of 8,070 candidate drugs, 32 of which are currently being tested in COVID-19-related clinical trials. Moreover, we present an alternative application for the model, the generation of additional candidates based on a given pre-selection of drug candidates using collaborative filtering. In addition, we improved the implementation of the Dr-COVID model by significantly shortening the inference and pre-processing time by exploiting data-parallelism. As drug repurposing is a task that requires high computation and memory resources, we further accelerate the post-processing phase using a new emerging hardware-we propose a new approach to leverage the use of high-capacity Non-Volatile Memory for aggregate drug ranking.
Y1  - 2023
U6  - https://doi.org/10.1371/journal.pone.0266572
SN  - 1932-6203
VL  - 18
IS  - 3
PB  - PLoS
CY  - San Fransisco
ER  - 
TY  - JOUR
A1  - Mayer, Martin
A1  - Ullmann, Wiebke
A1  - Heinrich, Rebecca
A1  - Fischer, Christina
A1  - Blaum, Niels
A1  - Sunde, Peter
T1  - Seasonal effects of habitat structure and weather on the habitat selection and home range size of a mammal in agricultural landscapes
JF  - Landscape ecology
N2  - Context Human land use intensified over the last century and simultaneously, extreme weather events have become more frequent. However, little is known about the interplay between habitat structure, direct short-term weather effects and indirect seasonal effects on animal space use and behavior. Objectives We used the European hare (Lepus europaeus) as model to investigate how habitat structure and weather conditions affect habitat selection and home range size, predictors for habitat quality and energetic requirements. Methods Using > 100,000 GPS positions of 60 hares in three areas in Denmark and Germany, we analyzed habitat selection and home range size in response to seasonally changing habitat structure, measured as vegetation height and agricultural field size, and weather. We compared daily and monthly home ranges to disentangle between direct short-term weather effects and indirect seasonal effects of climate. Results Habitat selection and home range size varied seasonally as a response to changing habitat structure, potentially affecting the availability of food and shelter. Overall, habitat structure and seasonality were more important in explaining hare habitat selection and home range size compared to direct weather conditions. Nevertheless, hares adjusted habitat selection and daily home range size in response to temperature, wind speed and humidity, possibly in response to thermal constrains and predation risk. Conclusions For effective conservation, habitat heterogeneity should be increased, e.g. by reducing agricultural field sizes and the implementation of set-asides that provide both forage and shelter, especially during the colder months of the year.
KW  - European hare
KW  - GPS
KW  - Habitat selection
KW  - Home range
KW  - Lepus europaeus
KW  - Weather
Y1  - 2019
U6  - https://doi.org/10.1007/s10980-019-00878-9
SN  - 0921-2973
SN  - 1572-9761
VL  - 34
IS  - 10
SP  - 2279
EP  - 2294
PB  - Springer
CY  - Dordrecht
ER  - 
TY  - JOUR
A1  - Mayer, Martin
A1  - Ullmann, Wiebke
A1  - Sunde, Peter
A1  - Fischer, Christina
A1  - Blaum, Niels
T1  - Habitat selection by the European hare in arable landscapes
BT  - The importance of small-scale habitat structure for conservation
JF  - Ecology and Evolution
N2  - Agricultural land-use practices have intensified over the last decades, leading to population declines of various farmland species, including the European hare (Lepus europaeus). In many European countries, arable fields dominate agricultural landscapes. Compared to pastures, arable land is highly variable, resulting in a large spatial variation of food and cover for wildlife over the course of the year, which potentially affects habitat selection by hares. Here, we investigated within-home-range habitat selection by hares in arable areas in Denmark and Germany to identify habitat requirements for their conservation. We hypothesized that hare habitat selection would depend on local habitat structure, that is, vegetation height, but also on agricultural field size, vegetation type, and proximity to field edges. Active hares generally selected for short vegetation (1-25 cm) and avoided higher vegetation and bare ground, especially when fields were comparatively larger. Vegetation >50 cm potentially restricts hares from entering parts of their home range and does not provide good forage, the latter also being the case on bare ground. The vegetation type was important for habitat selection by inactive hares, with fabaceae, fallow, and maize being selected for, potentially providing both cover and forage. Our results indicate that patches of shorter vegetation could improve the forage quality and habitat accessibility for hares, especially in areas with large monocultures. Thus, policymakers should aim to increase areas with short vegetation throughout the year. Further, permanent set-asides, like fallow and wildflower areas, would provide year-round cover for inactive hares. Finally, the reduction in field sizes would increase the density of field margins, and farming different crop types within small areas could improve the habitat for hares and other farmland species.
KW  - agriculture
KW  - arable land
KW  - conservation
KW  - GPS
KW  - habitat selection
KW  - Lepus europaeus
KW  - vegetation height
Y1  - 2018
U6  - https://doi.org/10.1002/ece3.4613
SN  - 2045-7758
VL  - 8
IS  - 23
SP  - 11619
EP  - 11633
PB  - Wiley
CY  - Hoboken
ER  - 
TY  - JOUR
A1  - Buratti, Bonnie J.
A1  - Thomas, P. C.
A1  - Roussos, Elias
A1  - Howett, Carly
A1  - Seiss, Martin
A1  - Hendrix, A. R.
A1  - Helfenstein, Paul
A1  - Brown, R. H.
A1  - Clark, R. N.
A1  - Denk, Tilmann
A1  - Filacchione, Gianrico
A1  - Hoffmann, Holger
A1  - Jones, Geraint H.
A1  - Khawaja, N.
A1  - Kollmann, Peter
A1  - Krupp, Norbert
A1  - Lunine, Jonathan
A1  - Momary, T. W.
A1  - Paranicas, Christopher
A1  - Postberg, Frank
A1  - Sachse, Manuel
A1  - Spahn, Frank
A1  - Spencer, John
A1  - Srama, Ralf
A1  - Albin, T.
A1  - Baines, K. H.
A1  - Ciarniello, Mauro
A1  - Economou, Thanasis
A1  - Hsu, Hsiang-Wen
A1  - Kempf, Sascha
A1  - Krimigis, Stamatios M.
A1  - Mitchell, Donald
A1  - Moragas-Klostermeyer, Georg
A1  - Nicholson, Philip D.
A1  - Porco, C. C.
A1  - Rosenberg, Heike
A1  - Simolka, Jonas
A1  - Soderblom, Laurence A.
T1  - Close Cassini flybys of Saturn’s ring moons Pan, Daphnis, Atlas, Pandora, and Epimetheus
JF  - Science
N2  - Saturn’s main ring system is associated with a set of small moons that either are embedded within it or interact with the rings to alter their shape and composition. Five close flybys of the moons Pan, Daphnis, Atlas, Pandora, and Epimetheus were performed between December 2016 and April 2017 during the ring-grazing orbits of the Cassini mission. Data on the moons’ morphology, structure, particle environment, and composition were returned, along with images in the ultraviolet and thermal infrared. We find that the optical properties of the moons’ surfaces are determined by two competing processes: contamination by a red material formed in Saturn’s main ring system and accretion of bright icy particles or water vapor from volcanic plumes originating on the moon Enceladus.
Y1  - 2019
U6  - https://doi.org/10.1126/science.aat2349
SN  - 0036-8075
SN  - 1095-9203
VL  - 364
IS  - 6445
SP  - 1053
PB  - American Assoc. for the Advancement of Science
CY  - Washington
ER  - 
TY  - GEN
A1  - Schrön, Martin
A1  - Köhli, Markus
A1  - Scheiffele, Lena
A1  - Iwema, Joost
A1  - Bogena, Heye R.
A1  - Lv, Ling
A1  - Martini, Edoardo
A1  - Baroni, Gabriele
A1  - Rosolem, Rafael
A1  - Weimar, Jannis
A1  - Mai, Juliane
A1  - Cuntz, Matthias
A1  - Rebmann, Corinna
A1  - Oswald, Sascha
A1  - Dietrich, Peter
A1  - Schmidt, Ulrich
A1  - Zacharias, Steffen
T1  - Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity
T2  - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe
N2  - In the last few years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters in depth. However, the signal still may contain unidentified features of hydrological processes, and many calibration datasets are often required in order to find reliable relations between neutron intensity and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed one to quantify the contribution of individual sample locations to the CRNS signal. Consequently, data points of calibration and validation datasets are suggested to be averaged using a more physically based weighting approach. In this work, a revised sensitivity function is used to calculate weighted averages of point data. The function is different from the simple exponential convention by the extraordinary sensitivity to the first few meters around the probe, and by dependencies on air pressure, air humidity, soil moisture, and vegetation. The approach is extensively tested at six distinct monitoring sites: two sites with multiple calibration datasets and four sites with continuous time series datasets. In all cases, the revised averaging method improved the performance of the CRNS products. The revised approach further helped to reveal hidden hydrological processes which otherwise remained unexplained in the data or were lost in the process of overcalibration. The presented weighting approach increases the overall accuracy of CRNS products and will have an impact on all their applications in agriculture, hydrology, and modeling.
T3  - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 636 
KW  - forested headwater catchment
KW  - moisture observing system
KW  - soil-water content
KW  - parameterization methods
KW  - scale
KW  - field
KW  - dynamics
KW  - observatories
KW  - networks
Y1  - 2019
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-419134
IS  - 636
SP  - 5009
EP  - 5030
ER  - 
TY  - JOUR
A1  - Schrön, Martin
A1  - Köhli, Markus
A1  - Scheiffele, Lena
A1  - Iwema, Joost
A1  - Bogena, Heye R.
A1  - Lv, Ling
A1  - Martini, Edoardo
A1  - Baroni, Gabriele
A1  - Rosolem, Rafael
A1  - Weimar, Jannis
A1  - Mai, Juliane
A1  - Cuntz, Matthias
A1  - Rebmann, Corinna
A1  - Oswald, Sascha
A1  - Dietrich, Peter
A1  - Schmidt, Ulrich
A1  - Zacharias, Steffen
T1  - Improving calibration and validation of cosmic-ray neutron sensors in the light of spatial sensitivity
JF  - Hydrology and earth system sciences : HESS
N2  - In the last few years the method of cosmic-ray neutron sensing (CRNS) has gained popularity among hydrologists, physicists, and land-surface modelers. The sensor provides continuous soil moisture data, averaged over several hectares and tens of decimeters in depth. However, the signal still may contain unidentified features of hydrological processes, and many calibration datasets are often required in order to find reliable relations between neutron intensity and water dynamics. Recent insights into environmental neutrons accurately described the spatial sensitivity of the sensor and thus allowed one to quantify the contribution of individual sample locations to the CRNS signal. Consequently, data points of calibration and validation datasets are suggested to be averaged using a more physically based weighting approach. In this work, a revised sensitivity function is used to calculate weighted averages of point data. The function is different from the simple exponential convention by the extraordinary sensitivity to the first few meters around the probe, and by dependencies on air pressure, air humidity, soil moisture, and vegetation. The approach is extensively tested at six distinct monitoring sites: two sites with multiple calibration datasets and four sites with continuous time series datasets. In all cases, the revised averaging method improved the performance of the CRNS products. The revised approach further helped to reveal hidden hydrological processes which otherwise remained unexplained in the data or were lost in the process of overcalibration. The presented weighting approach increases the overall accuracy of CRNS products and will have an impact on all their applications in agriculture, hydrology, and modeling.
Y1  - 2017
U6  - https://doi.org/10.5194/hess-21-5009-2017
SN  - 1027-5606
SN  - 1607-7938
VL  - 21
SP  - 5009
EP  - 5030
PB  - Copernicus
CY  - Göttingen
ER  -