Rahel Sollmann, Beth Gardner, Richard B. Chandler, J. Andrew Royle, and T. Scott Sillett. 2015. An open-population hierarchical distance sampling model. Ecology 96:325331. http://dx.doi.org/10.1890/14-1625.1


Supplement 1

Data, R code and JAGS model description to repeat simulation study investigating power to detect population trends with correlated abundances between years, using the Markov and the log-linear trend model.
Ecological Archives E096-033-S1.

Copyright


Authors
File list (downloads)
Description


Author(s)

Rahel Sollmann
North Carolina State University,
Department of Forestry and Environmental Resources
Raleigh, NC, USA
E-mail: rsollma@ncsu.edu

Beth Gardner
North Carolina State University
Department of Forestry and Environmental Resources
Raleigh, NC, USA

Richard B. Chandler
University of Georgia
Warnell School of Forestry and Natural Resources
Athens, GA, USA

J. Andrew Royle
USGS Patuxent Wildlife Research Center
Laurel, MD, USA

T. Scott Sillett
Smithsonian Conservation Biology Institute
Migratory Bird Center
Washington, DC, USA


File list

data.100m.R: (MD5: 25cca5e0b23be3915b197a50bcd1fb18) R data object containing data used in the hierarchical distance sampling analysis of island scrub-jay abundance by Sillett et al. (2012); loads the following objects

covs: data frame with survey point covariates
Xall.100m: matrix with detections from fall survey, survey site by 100-m distance band
Xall.spring.100m: matrix with detections from spring survey, survey site by 100-m distance band

Sollmann_et_al_R_script_Markovian_model.txt: (MD5: ) R script file with code to simulate, analyze, and summarize data under a Markovian abundance model where N at time t depends on N at time t-1, using the open-population hierarchical distance sampling model.

Sollmann_et_al_Markovian_model_JAGS_code.txt: (MD5: ) JAGS model description of the open-population hierarchical distance sampling model used in the R script above.

Sollmann_et_al_R_script_Markovian_data_log-linear_trend_model.txt: (MD5: ) R script file with code to simulate data under a Markovian abundance model (see above), and analyze and summarize it under a hierarchical distance sampling model with a log-linear time effect on abundance.

Sollmann_et_al_Independent_years_model_JAGS_code.txt: (MD5: ) JAGS model description of the hierarchical distance sampling model with linear time effect used in the R script above.

Description

Data files and code are set up to repeat the simulation study investigating power to detect population trends with independent and correlated abundances between years, as presented in the Simulation section in the manuscript.