Title
R code and output supporting: Time series sightability modeling of animal populations
Published Date
2018-01-16
Authors
Author Contact
ArchMiller, Althea A (althea.archmiller@gmail.com)
Type
Dataset
Abstract
The goal of our study was to expand a previously developed model-based approach to include random effects and a temporal spline for time series modeling of multiple years of operational survey data. We developed a Bayesian hierarchical model as our framework to build and compare fixed-effects and temporal model-based sightability models applied to 12 years of MN moose operational survey data. Here, we share the Program R code and data necessary to replicate the manuscript results that demonstrate how our time series sightability modeling approach can increase the precision of population estimators and predict population dynamics with smoother (and thus more realistic trends) through time.
Funding information
Sponsorship:
Minnesota Department of Natural Resources; Wildlife Restoration (Pittman-Robertson) Program; Minnesota Agricultural Experimental Station
Referenced by
ArchMiller, Dorazio, St. Clair, Fieberg. 2018. Time series sightability modeling of animal populations. PLOS ONE.
Replaces
This is an updated version of the dataset. The g_plots_results.html, programs_R.zip, and model_diagram.pdf files have been updated to reflect changes in the final PLOS ONE publication of the corresponding manuscript. The updates are to reformat the axis labels for the figures in the final publication. Version 1 can be found here:
License
Attribution-NonCommercial-ShareAlike 3.0 United States
Suggested Citation
ArchMiller, Althea A; Fieberg, John R; Dorazio, Robert M; St. Clair, Katherine.
(2018). R code and output supporting: Time series sightability modeling of animal populations.
Retrieved from the Data Repository for the University of Minnesota,
https://doi.org/10.13020/D6N30B.