Data

Import data

library(dplyr)
library(lubridate)
library(ggridges)
library(ggplot2)

pico <- read.csv('19980101_20211231-OCCCI_GLOBCOLOUR-PICO_PERCENTAGE-STATS_ANOMS-NES_EPU_NOESTUARIES-SOE_V2022-SOE_FORMAT.csv')
nano <- read.csv('19980101_20211231-OCCCI_GLOBCOLOUR-NANO_PERCENTAGE-STATS_ANOMS-NES_EPU_NOESTUARIES-SOE_V2022-SOE_FORMAT.csv')
micro <- read.csv('19980101_20211231-OCCCI_GLOBCOLOUR-MICRO_PERCENTAGE-STATS_ANOMS-NES_EPU_NOESTUARIES-SOE_V2022-SOE_FORMAT.csv')

Modify data

pico$date <- ymd_hms(pico$TIME_START)
nano$date <- ymd_hms(nano$TIME_START)
micro$date <- ymd_hms(micro$TIME_START)
pico$size_class <- 'pico'
nano$size_class <- 'nano'
micro$size_class <- 'micro'
pico <- pico %>%
  mutate(year = year(date),
         week = week(date)) %>%
  filter(VARIABLE == 'WEEKLY_PICO_PERCENTAGE_MEDIAN') %>%
  dplyr::select('date', 'year', 'week', 'SUBAREA', 'VALUE', 'size_class') %>%
  rename_all(., .funs = tolower)

nano <- nano %>%
  mutate(year = year(date),
         week = week(date)) %>%
  filter(VARIABLE == 'WEEKLY_NANO_PERCENTAGE_MEDIAN') %>%
  dplyr::select('date', 'year', 'week', 'SUBAREA', 'VALUE','size_class') %>%
  rename_all(., .funs = tolower)


micro <- micro %>%
  mutate(year = year(date),
         week = week(date)) %>%
  filter(VARIABLE == 'WEEKLY_MICRO_PERCENTAGE_MEDIAN') %>%
  dplyr::select('date', 'year', 'week', 'SUBAREA', 'VALUE','size_class') %>%
  rename_all(., .funs = tolower)


# Generate a dataframe with all size classes 
df <- rbind(pico, nano, micro)

All years

Across all years

ggplot(df, aes(x = value, y = factor(year), fill = size_class)) +
  geom_density_ridges(alpha = .8, color = 'white',
                      scale = 2.5, rel_min_height = .01) +
  labs(x = 'Percent composition', y = 'Year') +
  scale_fill_cyclical(name = "Phytoplankton Size Class:", 
                      guide = "legend",
                      labels = c('pico' = 'Pico, < 2.0 um)',
                                 'nano' = 'Nano, 2.0 - 20 um',
                                 'micro' = 'Micro 20 - 200 um'),
                      values = c("tomato", "dodgerblue", 'goldenrod')) +
  facet_wrap(~subarea)+ 
  theme_ridges()

Comparisons for years 2017 and 2021

df_1721 <- df %>%
  filter(year %in% c(2017,2021)) 
df_08_1721 <- df_1721 %>%
  filter(week %in% c(31:35)) 
ggplot(df_1721, aes(x = value, y = factor(year), fill = size_class)) +
    geom_density_ridges(alpha = .8, color = 'white',
                        scale = 2.5, rel_min_height = .01) +
    labs(x = 'Percent composition', y = 'Year') +
    theme_ridges() + 
  scale_fill_cyclical(name = "Phytoplankton Size Class:", 
                      guide = "legend",
                      labels = c('pico' = 'Pico, < 2.0 um)',
                                 'nano' = 'Nano, 2.0 - 20 um',
                                 'micro' = 'Micro 20 - 200 um'),
                      values = c("tomato", "dodgerblue", 'goldenrod')) +
  facet_wrap(~subarea)

Just the month of August in the 2017 vs 2021

ggplot(df_08_1721, aes(x = value, y = factor(year), fill = size_class)) +
    geom_density_ridges(alpha = .8, color = 'white',
                        scale = 2.5, rel_min_height = .01) +
    labs(x = 'Percent composition: August', y = 'Year') +
    theme_ridges() + 
  scale_fill_cyclical(name = "Phytoplankton Size Class:", 
                      guide = "legend",
                      labels = c('pico' = 'Pico, < 2.0 um)',
                                 'nano' = 'Nano, 2.0 - 20 um',
                                 'micro' = 'Micro 20 - 200 um'),
                      values = c("tomato", "dodgerblue", 'goldenrod')) +
  facet_wrap(~subarea)

Just the month of August across all years, the switch of pico and micro is anomalous in 2021

df_aug <- df %>%
  filter(week %in% c(31:35))

ggplot(df_aug, aes(x = value, y = factor(year), fill = size_class)) +
    geom_density_ridges(alpha = .8, color = 'white',
                        scale = 2.5, rel_min_height = .01) +
    labs(x = 'Percent composition: August', y = 'Year') +
    theme_ridges() + 
  scale_fill_cyclical(name = "Phytoplankton Size Class:", 
                      guide = "legend",
                      labels = c('pico' = 'Pico, < 2.0 um)',
                                 'nano' = 'Nano, 2.0 - 20 um',
                                 'micro' = 'Micro 20 - 200 um'),
                      values = c("tomato", "dodgerblue", 'goldenrod')) +
  facet_wrap(~subarea)

Plots of individual size classes

p_1721 <-pico %>%
  filter(year %in% c(2017,2021)) 

ggplot(p_1721, aes(x = value, y = factor(year), fill = year)) +
    geom_density_ridges(alpha = .8, color = 'white',
                        scale = 2.5, rel_min_height = .01) +
    labs(x = 'Percent Pico-phytoplankton', y = 'Year', title = 'All Months') +
    guides(fill = FALSE) +
    theme_ridges() +
  facet_wrap(~subarea)

p_08_1721 <-pico %>%
  filter(week %in% c(31:35)) 
ggplot(p_08_1721, aes(x = value, y = factor(year), fill = year)) +
    geom_density_ridges(alpha = .8, color = 'white',
                        scale = 2.5, rel_min_height = .01) +
    labs(x = 'Percent Pico-phytoplankton', y = 'Year', title = 'August') +
    guides(fill = FALSE) +
    theme_ridges() +
  facet_wrap(~subarea)

n_1721 <-nano %>%
  filter(year %in% c(2017,2021)) 

ggplot(n_1721, aes(x = value, y = factor(year), fill = year)) +
    geom_density_ridges(alpha = .8, color = 'white',
                        scale = 2.5, rel_min_height = .01) +
    labs(x = 'Percent Nano-phytoplankton', y = 'Year', title = 'All Months') +
    guides(fill = FALSE) +
    theme_ridges() +
  facet_wrap(~subarea)

n_08_1721 <-nano %>%
  filter(week %in% c(31:35)) 

ggplot(n_08_1721, aes(x = value, y = factor(year), fill = year)) +
    geom_density_ridges(alpha = .8, color = 'white',
                        scale = 2.5, rel_min_height = .01) +
    labs(x = 'Percent Nano-phytoplankton', y = 'Year', title = 'August') +
    guides(fill = FALSE) +
    theme_ridges() +
  facet_wrap(~subarea)

m_1721 <-micro %>%
  filter(year %in% c(2017,2021)) 

ggplot(m_1721, aes(x = value, y = factor(year), fill = year)) +
    geom_density_ridges(alpha = .8, color = 'white',
                        scale = 2.5, rel_min_height = .01) +
    labs(x = 'Percent Micro-phytoplankton', y = 'Year', title = 'All Months') +
    guides(fill = FALSE) +
    theme_ridges() +
  facet_wrap(~subarea)

m_08_1721 <- micro %>%
  filter(week %in% c(31:35)) 

ggplot(m_08_1721, aes(x = value, y = factor(year), fill = year)) +
    geom_density_ridges(alpha = .8, color = 'white',
                        scale = 2.5, rel_min_height = .01) +
    labs(x = 'Percent Micro-phytoplankton', y = 'Year', title = 'August') +
    guides(fill = FALSE) +
    theme_ridges() +
  facet_wrap(~subarea)