Predictors of Vibrio vulnificus occurrence : a machine learning approach

David Riedinger

doi:10.18453/rosdok_id00005322

David Riedinger

Predictors of Vibrio vulnificus occurrence : a machine learning approach

Universität Rostock, 2024

https://doi.org/10.18453/rosdok_id00005322

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.

Dissertation Freier Zugang

Titel:

Predictors of Vibrio vulnificus occurrence: a machine learning approach

Beteiligte Personen:

David Riedinger[VerfasserIn]
	1396402276
Matthias Labrenz[AkademischeR BetreuerIn]
	13682028X
	Leibniz-Institut für Ostseeforschung Warnemünde
Holger Scholz[AkademischeR BetreuerIn]
	1272433781
	Robert Koch Institut

Beteiligte Körperschaften:

Universität Rostock[Grad-verleihende Institution]
	38329-6
Universität Rostock. Mathematisch-Naturwissenschaftliche Fakultät[Grad-verleihende Institution]
	2147083-2

Zusammenfassung:

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. [Englisch]

Dokumenttyp:

Dissertation

Einrichtung:

Mathematisch-Naturwissenschaftliche Fakultät

Sprache:

Englisch

Sachgruppe der DNB:

550 Geowissenschaften

570 Biowissenschaften, Biologie

Umfang:

1 Online-Ressource (170 Seiten)

Veröffentlichung /
Entstehung: