%0 Book
%T Predictors of Vibrio vulnificus occurrence: a machine learning approach
%A Riedinger, David
%D 2024
%C Rostock
%C Universität Rostock
%G English
%F 1968855432
%O vorgelegt von David Jeroen Riedinger
%O Enthält Zeitschriftenartikel
%O GutachterInnen: Matthias Labrenz (Leibniz-Institut für Ostseeforschung Warnemünde) ; Holger Scholz (Robert Koch Institut)
%O Dissertation Universität Rostock 2024 Kumulative Dissertation
%X 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>
%L 550
%9 theses
%9 Text
%9 Hochschulschrift
%R 10.18453/rosdok_id00005322
%U https://purl.uni-rostock.de/rosdok/id00005322
%U https://nbn-resolving.org/urn:nbn:de:gbv:28-rosdok_id00005322-6
%U https://d-nb.info/1397495162/34
%U https://doi.org/10.18453/rosdok_id00005322