Predictors of Vibrio vulnificus occurrence: a machine learning approach Riedinger, David , 1996- (VerfasserIn) Labrenz, Matthias , 1966- (AkademischeR BetreuerIn) Scholz, Holger (AkademischeR BetreuerIn) Universität Rostock (Grad-verleihende Institution) Universität Rostock Mathematisch-Naturwissenschaftliche Fakultät (Grad-verleihende Institution) Text theses Text Hochschulschrift 2024 2024 eng electronic resourceremoteComputermedienOnline-Ressourceapplication/pdf1 Online-Ressource (170 Seiten) Illustrationen, Diagramme, Karten Vibrio vulnificus, a deadly marine bacterium, is expanding due to climate change, warming waters, and eutrophication in estuarine environments. This thesis analyzes its spread using global 16S rRNA data and machine learning models, identifying temperature, salinity, and chlorophyll a as key predictors. A rapid, affordable detection method was developed. In the Baltic Sea, eutrophication stimulates V. vulnificus more than seagrass suppresses it. Reducing nutrient-driven blooms may be key to limiting its growth worldwide.<eng> Open Access Urheberrechtsschutz 1.0 vorgelegt von David Jeroen Riedinger Enthält Zeitschriftenartikel GutachterInnen: Matthias Labrenz (Leibniz-Institut für Ostseeforschung Warnemünde) ; Holger Scholz (Robert Koch Institut) Dissertation Universität Rostock 2024 Kumulative Dissertation 550 570 571.9 570 https://purl.uni-rostock.de/rosdok/id00005322 https://doi.org/10.18453/rosdok_id00005322 https://nbn-resolving.org/urn:nbn:de:gbv:28-rosdok_id00005322-6 https://d-nb.info/1397495162/34 Predictors of Vibrio vulnificus occurrence--(DE-627)1968856072 urn:nbn:de:gbv:28-rosdok_id00005322-6 doi: 10.18453/rosdok_id00005322 oclc: 1586340004 ppn: (DE-627)1968855432