R/RSFIA_plots.R

In bmcnellis/RSFIA: FIA Tree Mortality Analysis

#' @title Plot functions for RSFIA package
#' @description
#'
#' Multiple functions for plotting. Some generate data.
#'
#' @name RSFIA_plots
NULL
#' @describeIn RSFIA_plots Plots by-section mortality vs. MAT
#' @export
PlotTenYearMAT <- function(source = 'mort_rate') {
  mort <- FIA_mortality_with_explanatory
  mort_cols0 <- c('mort_rate', 'non_harv_fire_beet_mort_rate',
                  'Fire_rate_wrt_ntree', 'Insect_rate_wrt_ntree')
  mort_cols <- c('LAT', 'LON', 'Cleland_province', 'Cleland_section', mort_cols0)
  mort <- mort[, which(colnames(mort) %in% mort_cols)]
  colnames(mort)[which(colnames(mort) == source)] <- 'mortality'
  wth_10 <- FIA_weather_by_year_bin
  wth_10 <- wth_10[, c(1, 2, grep(colnames(wth_10), pattern = '10'))]
  data <- dplyr::left_join(mort, wth_10, by = c('LAT', 'LON'))
  data$Cleland_section <- RSFIA::KeyClelandCode(data$Cleland_section, lvl = 'section')

  ytag <- switch(which(mort_cols0 == source),
                 '10-Year Mean Mortality',
                 '10-Year Non-Harvest/Fire/Insect Mortality',
                 '10-Year Fire Mortality',
                 '10-Year Insect Mortality')
  plot_list <- list()
  cnt <- 0
  for (i in unique(data$Cleland_section)) {
    cnt <- cnt + 1
    xtag <- paste0('10-Year MAT, ', i)
    i_data <- data[which(data$Cleland_section == i), ]
    i_plot <- ggplot() + theme_bw() +
      geom_point(aes(x = mean_max_min_10, y = mortality), data = i_data) +
      ylab(ytag) + xlab(xtag)
    plot_list[[cnt]] <- i_plot
  }
  return(plot_list)
}