First Steps towards a near Real-Time Modelling System of Vibrio vulnificus in the Baltic Sea

Over the last two decades, <i>Vibrio vulnificus</i> infections have emerged as an increasingly serious public health threat along the German Baltic coast. To manage related risks, near real-time (NRT) modelling of <i>V. vulnificus</i> quantities has often been proposed. Such models require spatially explicit input data, for example, from remote sensing or numerical model products. We tested if data from a hydrodynamic, a meteorological, and a biogeochemical model are suitable as input for an NRT model system by coupling it with field samples and assessing the models' ability to capture known ecological parameters of <i>V. vulnificus</i>. We also identify the most important predictors for <i>V. vulnificus</i> in the Baltic Sea by leveraging the St. Nicolas House Analysis. Using a 27-year time series of sea surface temperature, we have investigated trends of <i>V. vulnificus</i> season length, which pinpoint hotspots mainly in the east of our study region. Our results underline the importance of water temperature and salinity on <i>V. vulnificus</i> abundance but also highlight the potential of air temperature, oxygen, and precipitation to serve as predictors in a statistical model, albeit their relationship with <i>V. vulnificus</i> may not be causal. The evaluated models cannot be used in an NRT model system due to data availability constraints, but promising alternatives are presented. The results provide a valuable basis for a future NRT model for <i>V. vulnificus</i> in the Baltic Sea.