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plots_experimental.R
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plots_experimental.R
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#################### eDNA expeditions - scientific analysis ####################
########################## Environmental data download #########################
# January of 2024
# Author: Silas Principe, Mike Burrows
# Contact: [email protected], [email protected]
#
########## Read and analyse eDNA data from UNESCO World Heritage Sites #########
# Load packages ----
library(dplyr)
library(stringr)
library(purrr)
library(arrow)
library(data.table)
library(ggplot2)
fs::dir_create("figures")
set.seed(2023)
# Load files and convert to data.table ----
# Species summaries
speciestherm <- read_parquet("results/species_tsummaries.parquet")
speciesthermdt <- data.table(speciestherm)
# Site summaries
speciesthermsite <- read_parquet("results/tsummaries_aggregated.parquet")
speciesthermsitedt <- data.table(speciesthermsite)
# Species list
specieslist <- read_parquet("results/species_list.parquet")
# Select relevant depth/variant ----
speciesthermsst <- speciesthermdt[depth == "depthsurf" & variant == "mean", , ]
speciesthermsstc <- dcast(speciesthermdt,
species ~ metric,
value.var = "value",
fun = mean)
# Get community thermal index
ctihighergeog <- speciesthermsitedt[, list(
ctiavg = mean(q_0.5),
sdcti = sd(q_0.5),
str = mean(q_0.9 - q_0.1),
sstavg = mean(site_current),
nspp = .N
), by = c("higherGeography", "where")]
for (i in 1:100) {
resampled <- speciesthermsitedt[, list(
q_0.5 = sample(q_0.5, .N, replace = T),
q_0.9 = sample(q_0.9, .N, replace = T),
q_0.1 = sample(q_0.1, .N, replace = T),
site_current = sample(site_current, .N, replace = T)
#resample = 1:.N#sample(1:.N, .N, replace = T)
), by = c("higherGeography", "where")]
ctihighergeog_temp <- resampled[, list(
ctiavg = mean(q_0.5),
sdcti = sd(q_0.5),
str = mean(q_0.9 - q_0.1),
sstavg = mean(site_current),
nspp = .N
), by = c("higherGeography", "where")]
if (i == 1) {
ctihighergeog_boot <- ctihighergeog_temp
} else {
ctihighergeog_boot <- rbind(ctihighergeog_boot, ctihighergeog_temp)
}
}
# Make plots ----
plot(data=ctihighergeog,ctiavg~sstavg,pch=16,col=unclass(as.factor(where)),cex=1.5,
xlab="Sea surface temperature (°C)", ylab="Community Temperature Index (°C)",main="Fish")
ggplot(ctihighergeog) +
geom_point(aes(x = sstavg, y = ctiavg, color = where), shape = 16, size = 2) +
xlab("Sea surface temperature (°C)") +
ylab("Community Temperature Index (°C)") +
theme_light() +
theme(panel.grid = element_blank(),
legend.title = element_blank())
### Bootstrap version
ctihighergeog$higherGeography <- substr(ctihighergeog$higherGeography, 1, 10)
ctihighergeog$higherGeography <- factor(ctihighergeog$higherGeography,
levels = unique(ctihighergeog$higherGeography[order(ctihighergeog$sstavg)]))
ctihighergeog_boot$higherGeography <- substr(ctihighergeog_boot$higherGeography, 1, 10)
ctihighergeog_boot$higherGeography <- factor(ctihighergeog_boot$higherGeography,
levels = levels(ctihighergeog$higherGeography))
ctihighergeog_boot_sum <- ctihighergeog_boot[, list(
ctiavg_low = quantile(ctiavg, 0.25),
ctiavg_median = median(ctiavg),
ctiavg_high = quantile(ctiavg, 0.75),
sdcti_low = quantile(sdcti, 0.25),
sdcti_median = median(sdcti),
sdcti_high = quantile(sdcti, 0.75),
str_low = quantile(str, 0.25),
str_median = median(str),
str_high = quantile(str, 0.75)
), by = c("higherGeography", "where")]
ctihighergeog_sst <- ctihighergeog_boot[,list(
sstavg = mean(sstavg)
), by = c("higherGeography", "where")]
ctihighergeog_sst$what = "Average site SST"
ggplot() +
geom_point(data = ctihighergeog_sst, aes(x = higherGeography, y = sstavg, fill = what),
shape = "|", size = 6, alpha = .1) +
geom_jitter(data = ctihighergeog_boot, aes(x = higherGeography, y = ctiavg, color = where),
shape = 16, size = 1, alpha = .05,
position = position_jitterdodge(dodge.width = 0.5,
jitter.height = 0, jitter.width = 0.1)) +
geom_linerange(data = ctihighergeog_boot_sum,
aes(x = higherGeography, ymin = ctiavg_low, ymax = ctiavg_high,
color = where), linewidth = 1,
position = position_dodge(width = 0.5)) +
geom_point(data = ctihighergeog, aes(x = higherGeography, y = ctiavg, color = where),
shape = 16, size = 2.5, position = position_dodge(width = 0.5)) +
scale_color_manual(values = c("#00c3c9", "#5151db", "#f58000")) +
scale_fill_manual(values = c("grey70")) +
guides(fill = guide_legend(override.aes = list(alpha = 1))) +
ylab("Temperature (°C)") +
xlab(NULL) +
theme_light() +
coord_flip() +
theme(panel.grid = element_blank(),
panel.grid.major.y = element_line(colour = "grey90", linewidth = 0.3, linetype = 2),
legend.title = element_blank())
ggsave("figures/test_newcti.png", width = 7, height = 10)
ctihighergeog_sst_b <- ctihighergeog_sst[,list(
sstavg = mean(sstavg)
), by = c("higherGeography")]
ctihighergeog_sst_b$what <- ctihighergeog_sst$what[1]
ggplot() +
geom_col(data = ctihighergeog_sst_b, aes(x = higherGeography, y = sstavg, fill = what),
alpha = .3, width = 0.8) +
geom_jitter(data = ctihighergeog_boot, aes(x = higherGeography, y = ctiavg, color = where),
shape = 16, size = 1, alpha = .05,
position = position_jitterdodge(dodge.width = 0.5,
jitter.height = 0, jitter.width = 0.1)) +
geom_linerange(data = ctihighergeog_boot_sum,
aes(x = higherGeography, ymin = ctiavg_low, ymax = ctiavg_high,
color = where), linewidth = 1,
position = position_dodge(width = 0.5)) +
geom_point(data = ctihighergeog, aes(x = higherGeography, y = ctiavg, color = where),
shape = 16, size = 2.5, position = position_dodge(width = 0.5)) +
scale_color_manual(values = c("#00c3c9", "#5151db", "#f58000")) +
scale_fill_manual(values = c("grey70")) +
guides(fill = guide_legend(override.aes = list(alpha = 1))) +
scale_y_continuous(expand = c(0,0,0,2)) +
ylab("Temperature (°C)") +
xlab(NULL) +
theme_light() +
coord_flip() +
theme(panel.grid = element_blank(),
panel.grid.major.y = element_line(colour = "grey90", linewidth = 0.3, linetype = 2),
legend.title = element_blank())
ggsave("figures/test_newcti_opt2.png", width = 7, height = 10)