@Book{1968855432,
author="Riedinger, David",
title="Predictors of Vibrio vulnificus occurrence: a machine learning approach",
year="2024",
address="Rostock",
abstract="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>",
school="Universit{\"a}t Rostock",
note="vorgelegt von David Jeroen Riedinger",
note="Enth{\"a}lt Zeitschriftenartikel",
note="GutachterInnen: Matthias Labrenz (Leibniz-Institut f{\"u}r Ostseeforschung Warnem{\"u}nde) ; Holger Scholz (Robert Koch Institut)",
note="Dissertation Universit{\"a}t Rostock 2024 Kumulative Dissertation",
doi="10.18453/rosdok_id00005322",
url="https://purl.uni-rostock.de/rosdok/id00005322",
url="https://nbn-resolving.org/urn:nbn:de:gbv:28-rosdok_id00005322-6",
url="https://d-nb.info/1397495162/34",
url="https://doi.org/10.18453/rosdok_id00005322",
language="English"
}