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  • English  (3)
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  • 1
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    Testing the use of the silica deposition fluorescent probe PDMPO to estimate in situ growth rates of diatoms (2022)
    John Wiley & Sons, Inc. | Hoboken, USA
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    Publication Date: 2022-12-07
    Description: The fluorophore [2‐(4‐pyridyl)‐5{[4‐dimethylaminoethyl‐aminocarbamoyl‐methoxy]phenyl}oxazole], in short PDMPO, is incorporated in newly polymerized silica in diatom frustules and thereby provides a tool to estimate Si uptake, study diatom cell cycles but also determine mortality‐independent abundance‐based species specific‐growth rates in cultures and natural assemblages. In this study, the theoretical framework and applicability of the PDMPO staining technique to estimate diatom species specific‐growth rates were investigated. Three common polar diatom species, Pseudo‐nitzschia subcurvata, Chaetoceros simplex, and Thalassiosira sp., chosen in order to cover a broad range of species specific frustule and life‐cycle characteristics, were incubated over 24 h in control (no PDMPO) and with 0.125 and 0.6 μM PDMPO addition, respectively. Results indicate that specific‐growth rates of the species tested were not affected in both treatments with PDMPO addition. The specific‐growth rate estimates based on the PDMPO staining patterns (μPDMPO) were comparable and more robust than growth rates estimated from the changes in cell concentrations (μcc). This technique also allowed to investigate and highlight the importance of the illumination cycle (light and dark phases) on cell division in diatoms.
    Keywords: ddc:579.8 ; diatom frustules ; Si uptake ; growth rate estimation
    Language: English
    Type: doc-type:article
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  • 2
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    Generic seismic mass-movement detection leveraging unsupervised statistical learning methods (2023)
    In:  XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG)
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    Publication Date: 2023-07-20
    Description: With global warming potentially increasing the severity and frequency of hazardous mass-movements, monitoring such hazards is crucial to the population and critical infrastructure – especially in alpine areas. Monitoring and early-warning systems have the potential to improve the resilience of mountain communities to catastrophic events. Increasing the spatial coverage of seismic monitoring networks enables new warning perspectives if efficient algorithms screening the seismic data streams for hazardous mass-movements in real-time are available. We propose to combine physical and statistical features of seismic ground velocity recordings from ground motion sensors such as seismometers. These features are then fed to an unsupervised workflow for mass movement detection. We evaluate the performance, consistency, and generalizability of unsupervised learning approaches by comparing a large number of fitted models obtained from various unsupervised methodologies. Focusing on debris-flow records at the Illgraben torrent in Switzerland, we present a mass-movement detector with high accuracy and early-warning capability that combines multiple statistical learning models into an ensemble classifier. Furthermore, our goal is to generalize this detector to measurements from other sites and thus to maximize its transferability. Since our results aim to enable mass-movement monitoring and early-warning worldwide, Open Research Data principles like Findability, Accessibility, Interoperability and Reusability (FAIR) are of high importance for this project. We discuss how using the Renku platform (renkulab.io) of the Swiss Data Science Center ensures FAIR data science principles in our investigation. This is a key step towards our goal to enable seismology-based early warning of mass-movements wherever it may be required.
    Language: English
    Type: info:eu-repo/semantics/conferenceObject
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  • 3
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    How can seismology provide a better understanding of mountain cryosphere hazards? (2023)
    In:  XXVIII General Assembly of the International Union of Geodesy and Geophysics (IUGG)
    Details
    Publication Date: 2023-08-09
    Description: Glacier and slope instabilities pose significant hazards in mountain areas, with a high potential impact on the population. Forecasting glacier and slope instabilities remains challenging as sensing technology focusing on the surface might fail to detect damage and changes in subsurface elastic properties leading to large-scale failures. Seismic methods, such as seismic interferometry, can help address this observational gap by quantifying changes in material integrity. Here, we discuss two case studies in which seismology elucidates the development of cryospheric hazards: a hanging glacier instability and permafrost degradation on an active rockslide. We first analyze seismic data from Switzerland's Eiger hanging glacier before a 15,000 m3 break-off event. Our approach, based on an analysis of multiple icequake waveforms, allows us to measure seismic source migration. Combined with an analytical model based on damage mechanics our results quantify crevasse extension between unstable and stable ice masses. We then move to the second study site, an active rock slope near "Spitze Stei" in the Kandersteg region, Switzerland. The time series of relative seismic velocity variations (dv/v) constrain the lateral and depth-dependent extent of changes in the rock's elastic properties caused by pore pressure increase and potentially by permafrost thawing. The presented case studies illustrate how seismology can give quantitative insights into material damage and allow separating effects of irreversible damage growth from reversible thermoelastic hydrologic variations. This knowledge is needed to better predict the development of large failures and thus improve warning systems.
    Language: English
    Type: info:eu-repo/semantics/conferenceObject
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