Effect of ENSO on Coral Reefs

“Our group discovered the Scott Reef and Rowley Shoals Coral Bleaching Data dataset while searching the DataOne repository for “coral bleaching.” This particular dataset focuses on long-term monitoring data from 1994 to 2017 at reef slope habitats off the coast of northwestern Australia.”

hide

library(metajam)
library(tidyverse)
library(lubridate)
library(janitor)
library(vegan)
library(zoo)

EDS 213 Group Project

Our group discovered the Scott Reef and Rowley Shoals Coral Bleaching Data dataset while searching the DataOne repository for “coral bleaching.” This particular dataset focuses on long-term monitoring data from 1994 to 2017 at reef slope habitats off the coast of northwestern Australia. Data Source: https://search.dataone.org/view/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fmetadata%2Feml%2Fedi%2F952%2F1. The metadata includes the reef system, date range, taxonomy, habitat type, coral coverage, and dataset methods.

Download data

hide

# assign data url to access coral data from DataOne then download
data_url <- "https://cn.dataone.org/cn/v2/resolve/https%3A%2F%2Fpasta.lternet.edu%2Fpackage%2Fdata%2Feml%2Fedi%2F952%2F1%2Ff6212784c45d0a077f2c863868d22c4b"
# If data is akready up to date, this will throw an error
# error=T in header will move past this issue
download_d1_data(data_url, dir_name = "data", path = ".")

[1] "./data"

Load and tidy data

hide

# assign data path
data_path <- "data"
# Read in data with metajam
coral_list <- read_d1_files(data_path)
# Pick out the data read in above and clean it up
corals <- coral_list$data %>% 
  janitor::clean_names() %>% 
  dplyr::mutate(year_decimal = format(date_decimal(year_decimal), "%Y-%m-%d"),
                month = month(year_decimal),
                year = year(year_decimal)) %>% 
  dplyr::rename(date = year_decimal)
# Read in  ONI to be joined to coral data
oni <- read.table(
  "https://origin.cpc.ncep.noaa.gov/products/analysis_monitoring/ensostuff/detrend.nino34.ascii.txt",
  header = T) %>%
  dplyr::mutate(date = as.Date(ISOdate(YR, MON, 1)),
                date_start = as.Date(ISOdate(YR, MON, 1)),
                date_end = lubridate::ceiling_date(date_start, "month")) %>%
  dplyr::rename(oni_anomaly = ANOM,
                month = MON,
                year = YR) %>% 
  dplyr::select(year, month, oni_anomaly, date_start, date_end) %>% 
  dplyr::mutate(roll_3_month_mean = zoo::rollmean(x = oni_anomaly, k = 3, fill = NA, align = "right")) %>% 
  dplyr::filter(date_start > lubridate::ymd("1994-09-01"))
# Calculate the Simpson's diversity index 
# join corals and ONI data
coral_oni <- corals %>% 
  tidyr::pivot_longer(cols = 5:18, names_to = "species", values_to = "cover") %>% 
  dplyr::group_by(system, reef, year, month, location) %>% 
  dplyr::summarise(simpson_index = vegan::diversity(cover, index = "simpson")) %>% 
  dplyr::left_join(oni %>% dplyr::select(-date_start, -date_end)) %>% 
  dplyr::mutate(date = lubridate::make_date(year = year, month = month, day = 1))

Plot

hide

# Plot the coral diversity data with ONI color bar
ggplot2::ggplot() +
  ggplot2::geom_rect(
    data = oni,
    aes(xmin = date_start, xmax = date_end, ymin = -Inf, ymax = .3, fill = oni_anomaly)) +
  ggplot2::scale_fill_viridis_c(
    option = "plasma",
    guide = guide_colorbar(direction = "horizontal", title.position = "top",
                           order = 2, barheight = unit(.2, "cm"))) +
  ggplot2::scale_x_date(date_breaks = "2 year", date_labels = "%Y", expand = expansion(mult = c(0,0))) +
  ggplot2::geom_line(data = coral_oni, size = 1,
                     aes(x = date, y = simpson_index, color = location)) +
  ggplot2::scale_color_viridis_d() +
  ggplot2::guides(color = guide_legend(order = 1)) +
  ggplot2::labs(fill = "Oceanic Ni\u00f1o Index", color = "Sites", 
                x = "Date", y = "Simpsons Diversity Index") +
  ggplot2::theme_minimal()