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.

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 <br> Xall.100m: matrix with detections from fall survey, survey site by 100-m distance band<br> 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 <i>N</i> at time <i>t</i> depends on <i>N</i> at time <i>t</i>-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.