Data Science Research in Biology -
Fall 2022

A course for UC Merced undergraduates in data science applications for research in ecology and evolution

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A function for the UHURU data set


The UHURU experiment in Kenya has conducted a survey of Acacia drepanolobium among each of their ungulate exclosure treatments. Data for the survey is available here in a tab delimited ("\t") format. Each of the individuals surveyed were measured for branch circumference (CIRC) and canopy width (AXIS1) and was identified for the associated ant-symbiont species present (ANT).

The following function takes a subset of the data for a given ANT symbiont and evaluates the linear regression (lm()) for a given relationship, returning the symbiont species used for the subset and the r2 of the model.

report_rsquared <- function(data, species, formula){
  subset <- dplyr::filter(data, ANT == species)
  test <- lm(formula, data = subset)
  rsquared <- round(summary(test)$r.squared, 3)
  output <- data.frame(species = species, r2 = rsquared)
  return(output)
}
  1. Explain what each line of code in the body of the function is doing. Add the explanations to your Rmd file as comments, before each line of code.
  2. Execute the function using the UHURU data and specifying species = "CM" and formula = "AXIS1~CIRC".
  3. Modify the function so that it also determines if() the rsquared is significant based on a given threshold. The modified function should return() the species, rsquared and a significance value of "S" for a relationship with an rsquared > threshold or "NS" for an rsquared < threshold.
  4. Execute your modified function for species of "CM", "CS", and "TP" given a threshold = 0.667.