Project: Development of Empirical Models of Myxobolus cerebralis to Predict Risks for Populations of Fish Across River Drainages

Primary Investigator: Christine Moffitt
Project Summary: The investigators developed empirical models that describe both population dynamics and landscape-level factors associated with the prevalence, intensity of infection, and likelihood of risk to fish populations of Myxobolus cerebralis. They created a simple dynamic disease model for M. cerebralis, a discrete compartmental model to explain the course of disease in both fish and worms. They drafted a landscape-level model that incorporate GIS-based information extracted from digital maps. This model uses three landscape attributes: channel slope, catchment area, and elevation. All these factors can indirectly affect the intensity of infections. Through it surrogate, elevation, temperature is correlated with tractinomyxon releases, and overall fish production, growth and reproduction. This project is continuing into another funding cycle to refine the empirical models, to adding other landscape level metrics, and improve the manner that the geospatial data are collected from digital maps.
Funding Period: 2001-2002
Final Report: Moffitt_01-02.pdf
Dataset(s) associated with this project:

There are no datasets associated with this project.