R Shiny app for estimating phenology and reproductive success from annotated time lapse image data. Code was last updated 19 May 2021 with numerous updates to build an R package.
Here are some simple instructions for running the photoR app from RStudio (points 1-7) or online here (points 4-7).
- install the 'shiny' and 'lubridate' and 'devtools' packages from a CRAN repository, if needed, and attach them.
install.packages(c("shiny", "lubridate", 'devtools'))
library(shiny)
library(lubridate)
library(devtools)- install photoR from github and attach
install_github("jthinke/photoR")
library(photoR)-
run the app with
photoR() -
There will be 2 data files to load. The first is the attendance data (an example: test_att.csv) and the second is reproductive data (an example: test_repro.csv). To load your own, navigate to where the data are housed and allow upload. The app will automatically and iteritively identify errors in your data formatting and print messages to the screen to help identify where data errors are likely. Please fix all data errors to enable analysis.
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Specify how the date field is input in the raw data files you just specified. For the test data linked above, it is "m/d/y'.
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Select which data output you want to see.
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Use the download button to download results.
Hinke JT, A Barbosa, L Emmerson, T Hart, M Juáres, M Korczak-Abshire, G Milinevsky, M Santos, P Trathan, G Watters, C Southwell. 2018. Estimating nest-level phenology and reproductive success of colonial seabirds using time-lapse cameras. Methods in Ecology and Evolution. 9:1853-1863. doi:10.1111/2041-210X.13015