agTrend: A Bayesian approach for estimating trends of aggregated abundance

Authors


Summary

  1. We describe a method and open source R package agTrend for analysing regional trends of abundance from sites with uneven sample schedules over space and time.
  2. The method uses a hierarchical model to augment missing abundance measurements, while accounting for survey methodology changes and variability due to survey replication. A zero-inflated log-normal distribution is used to model abundance (normalized for methodology changes) and a log-normal distribution to model the observed abundance conditional on the true normalized abundance.
  3. The proposed method and software are demonstrated with an analysis of regional abundance index trends of Steller sea lions (Eumetopias jubatus) in Alaska.
  4. The package will be of most use to ecologists and resource managers interested in estimating regional trends of abundance surveys aggregated over several sites when sites have not been surveyed at concurrent times and hence regional abundance measurements cannot be directly calculated.

Ancillary