R/gather_habitat_for_species.R

In r4atlantis/ratlantis: R package for developing, executing, and assessing Atlantis ecosystem models

#' gather_habitat_for_species function
#'
#' This function aids in gathering data on species occurence that may be useful
#' in constructing functional groups and diet matrices
#' @param species_list_location where is species list located; defaults to working
#' director
#' @param species_list_csv name of csv file with the following column headers:
#' Genus, species,common_name.  functional_group may also be included.
#' @param map_location location of shape file used to create bgm; defaults to working
#' directory
#' @param map_name name of map used for bgm creation; can be produced by rbgmeriser
#' function or created manually; defaults to map_for_bgmeriser (produced by
#' rbgmeriser function)
#' @param habitat_list (optional)list of potential habitat types to be included in the
#' model. defaults to full list avaialble from Fishbase
#' @keywords biology prm, functional groups,
#' @details This function aids in gathering data on species occurrence that may
#' be useful in constructing functional groups and diet matrices.  User submits
#' a list of potential species to be included in the model (may include potential
#' functional groupings). The code gathers data on species from rgbif and rfishbase.
#' @export

gather_habitat_for_species <- function(species_list_location = getwd(), species_list_csv,
                                            map_location = getwd() ,map_name = "map_for_bgmeriser",
                                            habitat_list = c("Intertidal", "Sublittoral",
                                                             "Caves", "Oceanic", "Epipelagic",
                                                             "Mesopelagic", "Bathypelagic",
                                                             "Abyssopelagic", "Hadopelagic",
                                                             "Estuaries", "Mangroves", "MarshesSwamps",
                                                             "Stream", "Lakes", "Benthos","Sessile",
                                                             "Demersal", "Pelagic", "Endofauna",
                                                             "Megabenthos", "Meiobenthos", "SoftBottom",
                                                             "Sand", "Coarse", "Fine", "Level",
                                                             "Sloping", "Silt", "Mud", "Ooze", "HardBottom",
                                                             "Rocky", "Rubble", "SeaGrassBeds",
                                                             "BedsBivalve", "BedsRock", "CoralReefs",
                                                             "DropOffs", "ReefFlats", "Lagoons",
                                                             "DeepWaterCorals")
                                            )
{
  #read in the species_list
  species_input <- read.csv(paste(species_list_location, "/", species_list_csv, sep=""),
                                 header=T)
  if ("Genus" %!in% names(species_input) |
        "species" %!in% names(species_input) |
        "common_name" %!in% names(species_input)){
      stop(message = "Species list needs all of the following columns: Genus,  species, common_name")
      }
  #add scientific name for matching
  species_input$scientific_name <- paste (species_input$Genus, species_input$species,
                                         sep = " ")
  species_input$scientific_name_underscore <- paste (species_input$Genus, species_input$species,
                                    sep = "_")

  #habitat information from fishbase using new fishbase api
  #find species

  species_input$scientific_name_validated <- NA

  for (i in 1:nrow(species_input)){
    scientific_name_validated <- rfishbase::validate_names(species_input$scientific_name[i])
    if (!is.null(scientific_name_validated)){
      species_input$scientific_name_validated[i] <- scientific_name_validated
    }
  }

  #depth info
  depth_info <- rfishbase::species(species_input$scientific_name_validated,
                                   fields = rfishbase::species_fields$habitat)

  #make sciname match column in species name
  names(depth_info)[names(depth_info) == 'sciname'] <- 'scientific_name_validated'

  species_input <- merge(species_input, depth_info, all.x = T)

  #habitat info

  habitat_info <- rfishbase::ecology(species_input$scientific_name_validated,
                                     fields=habitat_list)
  habitat_info[,names(habitat_info) %!in% c("sciname", "SpecCode")] <- abs(habitat_info[,
              names(habitat_info) %!in% c("sciname", "SpecCode")])

  species_input <- merge(species_input, habitat_info, all.x = T)

  #get occurrence data using spocc

  map_area <- rgdal::readOGR(map_location, layer = map_name)
  max_polygons <- max(map_area@data$box_id)
  column_box_names <- c("scientific_name", paste("box", 0:max_polygons, sep = "_"))
  box_occurrence <- as.data.frame(matrix (nrow = 0, ncol = length(column_box_names)))
  names(box_occurrence) <- column_box_names
  order_box_occurrence <-box_occurrence

  for (i in 1:length(species_input$scientific_name)){
    df <- spocc::occ(query = species_input$scientific_name[i], limit = 1000)
    df <- spocc::occ2df(df)
    df <- na.omit(df)
    sp::coordinates(df) <- ~longitude+latitude
    crs.geo <- sp::CRS("+proj=longlat +datum=WGS84 +no_defs +ellps=WGS84 +
                   towgs84=0,0,0")  # geographical, datum WGS84
    sp::proj4string(df) <- crs.geo  # define projection system of our data
    summary(df)

    #put over each polygon and count occurences
    #http://gis.stackexchange.com/questions/110117/counts-the-number-of-points-in-a-polygon-in-r
    #http://r-sig-geo.2731867.n2.nabble.com/Counting-points-within-polygons-td6904827.html

    x <- table(sp::over(df, map_area)$box_id)
    if (length(x) > 0){
      z <- as.data.frame(t(as.matrix(x)))
      colnames(z)=paste("box", colnames(z), sep="_")
      z$scientific_name <- species_input$scientific_name[i]
      box_occurrence <- merge(box_occurrence,z, all.x=T, all.y=T)
    }
  }

  box_occurrence <- box_occurrence[,names(order_box_occurrence)]

  species_input <- merge(species_input, box_occurrence, all.x = T)

  return (species_input)

}