HIERARCHICAL BAYESIAN MODELS for SEASONAL RADIO TELEMETRY HABITAT DATA Megan C. Dailey*, Alix I. Gitelman , and Fred L. Ramsey *STARMAP, Department of Statistics, Colorado State University STARMAP, Department of Statistics, Oregon State University

1
HIERARCHICAL BAYESIAN MODELS for SEASONAL
RADIO TELEMETRY HABITAT DATAMegan C. Dailey,
Alix I. Gitelman , and Fred L. RamseySTARMAP,
Department of Statistics, Colorado State
University STARMAP, Department of Statistics,
Oregon State University

• Bayesian extensions
• Reformulation of the original non-seasonal
  persistence model
• 2. Different HSPs by season, one persistence
  parameter

• Radio telemetry data
• Sequences of observed habitat use over time

Abstract Radio telemetry data used for
habitat selection studies typically consists of
repeated measures of habitat types for each
individual. Existing models for estimating
habitat selection probabilities have incorporated
covariates in an independent multinomial
selections (IMS) model (McCracken et al., 1998)
and an extension of the IMS to include a
persistence parameter (Ramsey and Usner, 2003).
These models assume that all parameters are fixed
through time. However, this may not be a
realistic assumption in radio telemetry studies
that run through multiple seasons. We extend the
IMS and persistence models using a hierarchical
Bayesian approach that allows for the selection
probabilities, the persistence parameter, or
both, to change with season. These extensions
are particularly important when movement patterns
are expected to be different between seasons, or
when availability of a habitat changes throughout
the study period due to weather or migration.
The models are motivated by radio telemetry data
for westslope cutthroat trout.

• Estimated persistence
• Persistence
• All persistence parameters are less than 1
  indicating presence of persistence and that
  assumption 1 of IMS model is violated

• Habitat association models
• Independent Multinomial Selections (IMS)
• (McCracken, Manly, Vander Heyden ,
  1998)
• Product multinomial likelihood with multinomial
  logit parameterization
• Assumes repeat sightings of same animal are
  independent
• Persistence Model (Ramsey Usner, 2003)
• One parameter extension of IMS model to relax
  independence
• assumption using an H-state Markov chain for
  H habitat types

• Data example
• A year long radio-telemetry study of westslope
  cutthroat trout in 2 streams of the headwaters of
  the John Day River in eastern Oregon
• S 3 seasons Winter, Spring, Summer
  (2000-2001)
• 26 trout radio tracked weekly from stream side
  through the 3 seasons
• Rail Creek F 9
• Roberts Creek F 17
• Each trout located weekly from stream side
• Habitat inventory of entire creek once per season
• Channel unit type structural association of
  pools
• For this analysis H 3 habitat classes
• In-stream-large-wood pool
• Other pool
• Fast water
• Habitat availability measured by total
• area of the habitat for each season
• Data collected by Steve Starcevich, Oregon DFW

• Conclusions
• Bayesian formulation results in a single model
  to use for the estimation of seasonal
  persistence parameters and HSPs along with their
  associated 95 intervals.
• Allows comparisons of seasons and gives a glimpse
  into seasonal differences in movement related to
  specific habitats.
• Model can also be used with other covariates by
  changing the parameterization of the multinomial
  logit

Estimated habitat selection probabilities
(HSPs)

• Future Work
• Incorporate multiple streams into the model

Range of westslope cutthroat trout
FUNDING/DISCLAIMER The work reported here was
developed under the STAR Research Assistance
Agreement CR-829095 awarded by the U.S.
Environmental Protection Agency (EPA) to Colorado
State University. This poster has not been
formally reviewed by EPA.  The views expressed
here are solely those of the authors and STARMAP,
the Program they represent. EPA does not endorse
any products or commercial services mentioned in
this poster.
This research is funded by U.S.EPA Science To
Achieve Results (STAR) Program Cooperative Agreeme
nt
number of moves from habitat h to habitat h
CR - 829095