Distinguishing sources of parasites on wild juvenile salmon

• Author(s) / Creator(s)

  • Peacock, Stephanie J.

• Ecological systems are complex. All too often, complex models are fit to ecological data without consideration of whether parameters are estimable. I present a recent example for a parasite transmission model tracking the diffusion of sea lice from salmon farms in coastal British Columbia, fit to data of sea lice abundances on migrating wild juvenile salmon. The estimability of parameters is not clear from published point estimates, but an effort to obtain standard errors on parameter estimates revealed either a lack of information in the data or non-identifiable parameters. I used data cloning techniques to verify an estimability issue, and subsequently revised the model. Results from the revised parasite transmission model support previous work, suggesting that salmon farms are a significant source of sea lice on wild juvenile salmon. But management interventions have altered parasite dynamics on salmon farms in recent years, and the temptation is great to account for these dynamics in the parasite transmission model. Can parameters be estimated if this additional complexity is introduced?

• Date created

  2012-02-24

• Subjects / Keywords

  • Parasites
  • Data cloning
  • Salmon
  • Bayesian inference
  • 2012/02/24
  • Mathematical Biosciences Institute, Ohio State University, Columbus, Ohio

• Type of Item

  Conference/Workshop Poster

• DOI

  https://doi.org/10.7939/R38W3881T

• License

  Attribution 3.0 International