Assessing sources of uncertainty in length-based estimates of body growth in populations of fishes and macroinvertebrates with bootstrapped ELEFAN

<b>Supplementary material for the paper</b>:<br>Schwamborn, R, Mildenberger, T.K., Taylor, M.H., submitted. Assessing sources of uncertainty in length-based estimates of body growth in populations of fishes and macroinvertebrates with bootstrapped ELEFAN.<br><br><b>Description</b>:<br>The fileset provides R scripts and results presented in the paper by Schwamborn et al (submitted). The analyses uses functions available in the new R package "fishboot" (Schwamborn et al. 2018), which builds on ELEFAN functions available in the TropFishR package (Mildenberger et al. 2017, 2018, Taylor et al. 2017), to provide confidence intervals of growth parameter estimates using a bootstrapping procedure applied to length frequency data. <br><br><b>Contents</b>:<br><b>Supplement_Schwamborn_etal.Rproj</b> - RStudio project file. When opened in RStudio, script file paths should remain compatible across platforms.<br><b>/results</b> - results of bootstrapping experiments provided as .Rdata and graphical files. <br><b>/scripts</b> - scripts for running bootstrapping analyses on "alba" and "synLFQb" datasets. A basic bootstrapping demonstration using the "alba" dataset is also provided.<br><br><b>References</b>:<br>- Mildenberger, T.K., Taylor, M.H., Wolff, M., 2017. TropFishR: an R package for fisheries analysis with length-frequency data. Methods in Ecology and Evolution. https://doi.org/10.1111/2041-210X.12791<br>- Mildenberger, T.K., Taylor, M.H., and Wolff, M., 2018. TropFishR: Tropical Fisheries Analysis with R. R package version 1.2.1. https://CRAN.R-project.org/package=TropFishR<br>- Schwamborn, R, Mildenberger, TK, Taylor, MH, 2018. fishboot: Bootstrap-based methods for the study of fish stocks and aquatic populations. R package version 0.1. https://github.com/rschwamborn/fishboot<br>- Taylor, M.H, Mildenberger, T.K., 2017. Extending electronic length frequency analysis in R. Fisheries Management and Ecology. 24:330-338. https://doi.org/10.1111/fme.12232