R/data.R

In nls.multstart: Robust Non-Linear Regression using AIC Scores

#' Example metabolic thermal response curves
#'
#' A dataset containing example data of rates of photosynthesis and respiration of the phytoplankton Chlorella vulgaris. Instantaneous rates of metabolism were made across a range of assay temperatures to incorporate the entire thermal response of the populations. The dataset is the cleaned version so some datapoints have been omitted.
#'
#' @format A data frame with 649 rows and 7 variables:
#' \describe{
#'   \item{curve_id}{a unique value for each separate curve}
#'   \item{growth.temp}{the growth temperature that the culture was maintained at before measurements were taken (degrees centigrade)}
#'   \item{process}{whether the cultures had been kept for a long time at their growth temperature (adaptation/~100 generations) or a short time (a measure of acclimation/~10 generations)}
#'   \item{flux}{whether the curve depicts respiration or gross photosynthesis}
#'   \item{temp}{the assay temperature at which the metabolic rate was measured (degrees centigrade)}
#'   \item{K}{the assay temperature in degrees Kelvin}
#'   \item{ln.rate}{the metabolic rate measured (micro mol O2 micro gram C-1 hr-1)}
#' }
#' @source Daniel Padfield
#' @references Padfield, D., Yvon-durocher, G., Buckling, A., Jennings, S. & Yvon-durocher, G. (2015). Rapid evolution of metabolic traits explains thermal adaptation in phytoplankton, Ecology Letters, 19, 133-142.
#' @keywords dataset
#' @docType data
#' @usage data("Chlorella_TRC")
#' @examples
#' data("Chlorella_TRC")
#' library(ggplot2)
#' ggplot(Chlorella_TRC) +
#'  geom_point(aes(temp, ln.rate, col = process)) +
#'  facet_wrap(~ growth.temp + flux)
"Chlorella_TRC"