Predicting and quantifying marine bivalve disease dispersal by biophysical simulations
Title
Predicting and quantifying marine bivalve disease dispersal by biophysical simulations
General information
The ecological as well as economic value of marine organisms is impaired by infectious diseases and mass mortality events are predicted to further intensify with climate change. However, it is difficult to track the spatial and temporal scales of disease outbreaks by observational methods. Therefore, we currently lack a comprehensive understanding of how quickly and to what extent marine diseases can spread with currents in the ocean. This hampers efforts to prevent and control disease dispersal. For this project, I propose an interdisciplinary biophysical modeling approach with the aim to assess the role of ocean dynamics, hydrography, biogeochemistry, and biology in bivalve disease dispersal. Four model bivalve-pathogen pairs along the North-West European shelf will be studied that represent a range of infectious diseases, spatial distributions, population densities, and developmental characteristics. The generated results are expected to improve our understanding of which factors determine disease dispersal in the ocean, and provide a risk assessment and modeling pipeline. Hydrodynamic models and Lagrangian particle dispersal simulations will be used as a tool to predict and quantify disease dispersal with varying biological parameters (work package 1). Dispersing diseases will be simulated as passively drifting disease agents (e.g., viruses), and as associated with infected bivalve larvae. Bivalve larvae have a range of active swimming behavior that will be experimentally assessed in detail for one model bivalve, and used to simulate and quantify the impact of active movement on disease dispersal. The dispersal model will be coupled with an epidemiological infection model to interpret the effect of predicted disease dispersal on the population level. Next, the effect of hydrography and biogeochemistry on dispersal will be assessed based on environmental variability during the past decades (work package 2). Both biological processes (infection dynamics, bivalve reproduction, larval development) as well as physical processes in the ocean dependent on environmental conditions, and thus disease dispersal is expected to be affected by hydrography and biogeochemistry. Lastly, an accessible simulation-tool for predicting disease dispersal and providing risk assessments will be developed and potential stakeholders identified (work package 3). Overall, the proposed project is relevant to improve the early detection, prediction, and ultimately preventing mass mortality events in economically and ecologically relevant bivalves.
Start
August, 2024
End
July, 2027
Funding (total)
-
Funding (GEOMAR)
213000
Funding body / Programme
-
DFG
/
Coordination
Helmholtz-Zentrum für Ozeanforschung Kiel (GEOMAR), Germany
Contact
Partners
University of Edinburgh, UK
Polytechnic University of Milan, Italy
Center for Ocean and Society (CeOS), Germany
Polytechnic University of Milan, Italy
Center for Ocean and Society (CeOS), Germany
