R/show_transectavespp.R

In tbep-tech/tbeptools: Data and Indicators for the Tampa Bay Estuary Program

#' Show annual averages of seagrass frequency occurrence by bay segments, year, and species
#'
#' @param transectocc data frame returned by \code{\link{anlz_transectocc}}
#' @param bay_segment chr string for the bay segment, one to many of "OTB", "HB", "MTB", "LTB", "BCB"
#' @param yrrng numeric indicating year ranges to evaluate
#' @param species chr string of species to summarize, one to many of "Halodule", "Syringodium", "Thalassia", "Ruppia", "Halophila", "Caulerpa", "Dapis", "Chaetomorpha"
#' @param total logical indicating if total frequency occurrence for all seagrass species is also returned, only applies if \code{asreact = FALSE}
#' @param alph numeric indicating alpha value for score category colors
#' @param family optional chr string indicating font family for text labels
#' @param plotly logical if matrix is created using plotly
#' @param asreact logical if a reactable table is returned instead of a plot
#' @param width numeric for width of the plot in pixels, only applies of \code{plotly = TRUE}
#' @param height numeric for height of the plot in pixels, only applies of \code{plotly = TRUE}
#' @param sppcol character vector of alternative colors to use for each species, must have length of six
#'
#' @details Results are based on averages across seagrass species (Halodule, Syringodium, Thalassia, Ruppia, Halophila) by date and transect in each bay segment. Drift or attached macroalgae (e.g., Caulerpa, Chaetomorpha) and cyanobacteria (Dapis) estimates may not be accurate prior to 2021.  If \code{total = TRUE}, a line showing the total frequency occurrence for all seagrass species is also shown (does not include macroalgae or cyanobacteria).
#'
#' @return If \code{asreact = F}, a \code{\link[ggplot2]{ggplot}} or \code{\link[plotly]{plotly}} (if \code{plotly = T}) object is returned showing trends over time by species for selected bay segments.  If \code{asreact = T}, a \code{\link[reactable]{reactable}} table showing results by year, segment, and species is returned.
#' @export
#'
#' @concept show
#'
#' @references
#' The plot is a representation of figure 2 in Johansson, R. (2016) Seagrass Transect Monitoring in Tampa Bay: A Summary of Findings from 1997 through 2015, Technical report #08-16, Tampa Bay Estuary Program, St. Petersburg, Florida.
#'
#' The table is a representation of table 2, p. 163 in Yarbro, L. A., and P. R. Carlson, Jr., eds. 2016. Seagrass Integrated Mapping and Monitoring Program: Mapping and Monitoring Report No. 2. Fish and Wildlife Research Institute Technical Report TR-17 version 2. vi + 281 p.
#'
#' @importFrom dplyr "%>%"
#'
#' @examples
#' \dontrun{
#' transect <- read_transect()
#' }
#' transectocc <- anlz_transectocc(transect)
#' show_transectavespp(transectocc)
show_transectavespp <- function(transectocc, bay_segment = c('OTB', 'HB', 'MTB', 'LTB', 'BCB'), yrrng = c(1998, 2024),
                                species = c('Halodule', 'Syringodium', 'Thalassia', 'Halophila', 'Ruppia', 'Caulerpa', 'Dapis', 'Chaetomorpha'),
                                total = TRUE, alph = 1, family = NA, plotly = FALSE, asreact = FALSE, width = NULL,
                                height = NULL, sppcol = NULL){

  # check correct length of optional color vector
  if(!is.null(sppcol)){
    if(length(sppcol) != 8)
      stop('sppcol required length is eight')

    sppcol <- c('#FFFFFF', sppcol)

  }

  # make plot
  if(!asreact){

    # annual average by segment
    toplo <- anlz_transectavespp(transectocc, total = total, bay_segment = bay_segment, yrrng = yrrng, species = species, by_seg = F) %>%
      dplyr::mutate(
        fo = round(100 * foest, 1)
      )

    # sort color palette so its the same regardless of species selected
    if(is.null(sppcol))
      sppcol <- c('#FFFFFF', '#ED90A4', '#CCA65A', '#7EBA68', '#6FB1E7', '#00C1B2', '#D400FF', '#8B2323', '#6AF427')
    names(sppcol) <- c('total', 'Halodule', 'Syringodium', 'Thalassia', 'Halophila', 'Ruppia', 'Caulerpa', 'Dapis', 'Chaetomorpha')
    sppcol <- sppcol[levels(toplo$Savspecies)]

    p <- ggplot2::ggplot(toplo, ggplot2::aes(x = yr, y = fo, fill = Savspecies)) +
      ggplot2::geom_line(alpha = alph) +
      ggplot2::geom_point(pch = 21, size = 3, alpha = alph) +
      ggplot2::scale_fill_manual(values = sppcol) +
      ggplot2::theme_bw() +
      ggplot2::theme(
        axis.title.x = ggplot2::element_blank(),
        legend.title = ggplot2::element_blank(),
        text = ggplot2::element_text(family = family)
      ) +
      ggplot2::labs(
        y = '% frequency occurrence',
        title = paste('Seagrass estimates for', paste(bay_segment, collapse = ', '))
      )

    if(plotly)
      p <- plotly::ggplotly(p, width = width, height = height) %>%
        plotly::config(
          toImageButtonOptions = list(
            format = "svg",
            filename = "myplot"
          )
        )

    out <- p

  }

  # table
  if(asreact){

    # annual average by segment
    totab <- anlz_transectavespp(transectocc, total = total, bay_segment = bay_segment, yrrng = yrrng, species = species, by_seg = T) %>%
      dplyr::mutate(foest = 100 * foest) %>%
      tidyr::spread(Savspecies, foest) %>%
      dplyr::arrange(yr, bay_segment)

    out <- reactable::reactable(totab,
      columns = list(
        yr = reactable::colDef(
          name = 'Year',
          format = reactable::colFormat(digits = 0)
          ),
        bay_segment = reactable::colDef(name = 'Bay segment'),
        nsites = reactable::colDef(
          name = '# of quadrats',
          format = reactable::colFormat(digits = 0)
          )
      ),
      groupBy = 'bay_segment',
      defaultExpanded = T,
      defaultPageSize = nrow(totab),
      defaultColDef = reactable::colDef(
        footerStyle = list(fontWeight = "bold"),
        format = reactable::colFormat(digits = 1, separators = F),
        resizable = TRUE
      ),
      filterable = T
    )

  }

  return(out)

}