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This repository contains the data and code necessary to reproduce the analysis in the manuscript “Modeling spatiotemporal abundance of mobile wildlife in highly variable environments using boosted GAMLSS hurdle models” by Smith et al. (accepted at Ecology and Evolution).

Authors (affiliation):

  • Adam D. Smith1 (Department of Natural Resources Science, University of Rhode Island, Kingston, Rhode Island 02881 USA)
  • Benjamin Hofner2 (Department of Medical Informatics, Biometry and Epidemiology, Friedrich-Alexander-University Erlangen-Nuremberg, Waldstraße 6, 91054 Erlangen, Germany)
  • Juliet S. Lamb (Department of Natural Resources Science, University of Rhode Island, Kingston, Rhode Island 02881 USA), - Jason E. Osenkowski (Rhode Island Department of Environmental Management, 277 Great Neck Road, West Kingston, Rhode Island 02892 USA)
  • Taber Allison (American Wind Wildlife Institute, 1110 Vermont Avenue, NW, Suite 950, Washington, D.C. 20005 USA)
  • Giancarlo Sadoti (Department of Geography, University of Nevada, Reno, Nevada, 89557 USA)
  • Scott R. McWilliams (Department of Natural Resources Science, University of Rhode Island, Kingston, Rhode Island 02881 USA)
  • Peter W. C. Paton (Department of Natural Resources Science, University of Rhode Island, Kingston, Rhode Island 02881 USA)

1Present address: United States Fish and Wildlife Service, National Wildlife Refuge System, Inventory and Monitoring Branch, 135 Phoenix Rd., Athens, GA 30605 USA 2Present address: Section Biostatistics, Paul-Ehrlich-Institut, Paul-Ehrlich-Straße 51-59, 63225 Langen, Germany

To run the code and compile the manuscript and supplemental materials, you’ll need:

  1. R

  2. RStudio is highly recommended, though not technically required.

  3. LaTeX distribution: If you don’t know what this means, we recommend you use tinytex. Install tinytex in R using the following command and following the onscreen prompts:


    Other LaTeX distribution options include MiKTeX for Windows, MacTeX for Mac OS X, and TeXLive for Linux.

  4. pandoc: pandoc is installed if you’re using a relatively recent version of RStudio.

Compiling the manuscript and supplemental materials

Provided you have the above software installed, you can compile and generate the manuscript and supplemental material pdfs by opening and knitting the following files:

  1. Manuscript/NanSound_main_document.Rmd
  2. Manuscript/S1_StabilitySelection.Rmd
  3. Manuscript/S2_EarlyStopping.Rmd
  4. Manuscript/S3_StableCovariateEffects.Rmd
  5. Manuscript/S4_ConditionalOverdispersion.Rmd
  6. Manuscript/S5_SeasonalAnimation.Rmd

The Supplemental Rmd files assume the main manuscript Rmd was knit first.

We also include a document that illustrates how to visualize the spatiotemporal covariates used in this study: Manuscript/Visualizing_covariates.Rmd. It can be knit equivalently to the Supplemental material.

Rerunning the analysis

Given the computing power and time necessary to recreate the analysis, the analysis code is maintained separately of manuscript compilation. The relevant files to recreate the analysis are:

  1. R/create_final_data.R: assembles the final data set (duck counts and environmental variables) for analysis
  2. R/model_coei.R, R/model_coei.R, and R/model_coei.R: for each species, slightly restructure the data for analysis and conduct the boosted logistic GAM for occupancy and GAMLSS hurdle model for abundance, including early stopping and stability selection
  3. R/model_formula_decomp.R: this simply sets up the general form (i.e., formulas) of the models (see Materials and Methods - Synthesis section of manuscript) and is called by the modelling functions.

NOTE: The large resulting model files for each species group are stored in the Results_coei, Results_scot, and Results_ltdu directories. These files are necessary for compiling the manuscript and supplemental material and will be overwritten if R/model_****.R is run.

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