R/EROS1_EcoMorphoTypes.R
In SimonDedman/FIUSharkEcol: Shark Ecology at FIU
# 2023-01-23 Ecomorphotypes bars
# Simon Dedman, simondedman@gmail.com
# imports Google sheet & local png images, tidies table, plots, per ecomorphotype: number of studies,
# mean effect size, mean strength of evidence.
# ToDo ####
# fix study with more n for effect than evidence - score the evidence, re-run plots. Unknown ref. Asked Jerry.
# load packages####
# install.packages("googlesheets4")
library(googlesheets4)
library(tidyverse)
library(magrittr) # not used (yet)
library(tidylog)
library(ggplot2)
library(lubridate) # today
library(png) # add images to plots
library(grid) # add images to plots
# https://corybrunson.github.io/ggalluvial/ nicer than
# https://r-charts.com/flow/sankey-diagram-ggplot2/
# install.packages("ggalluvial")
# library(remotes)
# remotes::install_github("corybrunson/ggalluvial@main", build_vignettes = TRUE)
# https://github.com/corybrunson/ggalluvial/issues/110
# alluvial and ggfittext not being installed that are required to build the vignettes.
# Those packages are listed under Suggests: rather than under Imports: in the DESCRIPTION,
# which i understand to be the correct policy for packages that are only required for vignettes.
# Could you install those packages and try again?
library(ggalluvial)
# import data & images####
emt <- read_sheet("https://docs.google.com/spreadsheets/d/1dNDEUENa4M1__VNksolw8Or9ysPutEYWMTgZJ-qOe9I/edit#gid=0")
# nstudies <- read_sheet(ss = "https://docs.google.com/spreadsheets/d/1dNDEUENa4M1__VNksolw8Or9ysPutEYWMTgZJ-qOe9I/edit#gid=0",
# sheet = "Ecomorphotypes Matrix Figure",
# range = "A34:J47")
# meaneffect <- read_sheet(ss = "https://docs.google.com/spreadsheets/d/1dNDEUENa4M1__VNksolw8Or9ysPutEYWMTgZJ-qOe9I/edit#gid=0",
# sheet = "Ecomorphotypes Matrix Figure",
# range = "A50:J63")
# meanevidence <- read_sheet(ss = "https://docs.google.com/spreadsheets/d/1dNDEUENa4M1__VNksolw8Or9ysPutEYWMTgZJ-qOe9I/edit#gid=0",
# sheet = "Ecomorphotypes Matrix Figure",
# range = "A66:J79")
saveloc <- "/home/simon/Documents/Si Work/PostDoc Work/FIU/Ecological Importance of Sharks Workshop/Papers Prep/2022 Science/1_EROS/"
saveloc <- "C:/Users/simon/Documents/Si Work/PostDoc Work/FIU/Ecological Importance of Sharks Workshop/Papers Prep/2022 Science/1_EROS/" # windows
# https://stackoverflow.com/questions/9917049/inserting-an-image-to-ggplot2
littoral <- rasterGrob(readPNG(paste0(saveloc, "Graphics/emt_littoral.png")), interpolate = TRUE)
archipelagic <- rasterGrob(readPNG(paste0(saveloc, "Graphics/emt_archipelagic.png")), interpolate = TRUE)
macroceanic <- rasterGrob(readPNG(paste0(saveloc, "Graphics/emt_macroceanic.png")), interpolate = TRUE)
# rajobenthic <- rasterGrob(readPNG(paste0(saveloc, "Graphics/emt_rajobenthic.png")), interpolate = TRUE) # rays if required
# aquilopelagic <- rasterGrob(readPNG(paste0(saveloc, "Graphics/emt_aquilopelagic.png")), interpolate = TRUE)
# Analysis####
# Only 3/12 EMTs have any studies at all outside of diet.
# bar chart for ecological roles: stacked bars based on realm, habitat, etc.
# Caption.
# clean table, convert low medium high to 1 2 3
emt %<>%
# select cols of interest
select(Ecomorphotype, `Functional Group`, Realm, Ecosystem, `Ocean Basin`, `Top-down: Direct Predation: Effect Size`:`Bottom-up: Nutrient Vector Storage: Excretion & Egestion: Strength of Evidence`) %>%
# remove NA emt rows
drop_na(Ecomorphotype) %>%
# convert High Medium Low to 3 2 1, keep NAs
mutate(across(
.cols = `Top-down: Direct Predation: Effect Size`:`Bottom-up: Nutrient Vector Storage: Excretion & Egestion: Strength of Evidence`,
~ dplyr::case_when(
. == "High" ~ 3,
. == "Medium" ~ 2,
. == "Low" ~ 1
)
)) %>%
# remove rays
filter(!Ecomorphotype %in% c("Aquilopelagic", "Rajobenthic"))
# Loop through nstudies effectSize strengthEffect for 5 grouping variables
for (groupvariable in c("Ecomorphotype", # groupvariable <- "Ecomorphotype"
"Functional Group", # groupvariable <- "Functional Group"
"Realm", # groupvariable <- "Realm"
"Ecosystem", # groupvariable <- "Ecosystem"
"Ocean Basin")) { # open groupvariable loop. # groupvariable <- "Ocean Basin"
# programming with dplyr vignette, loop over multiple variables: .data[[groupvariable]]
# depreciated in tidyselect 1.2.0, use all_of(groupvariable)
# Using `all_of()` outside of a selecting function was deprecated in tidyselect 1.2.0.
# Thus use all_of(groupvariable) in select() and .data[[groupvariable]] elsewhere. UGH.
# nstudies table & plot####
# nstudies <-
emt %>%
select(c(all_of(groupvariable), contains("Effect Size"))) %>% # only select groupvariable & Effect Size columns - s.o.evidence is a dupe
group_by(.data[[groupvariable]]) %>%
summarise(across(
.cols = `Top-down: Direct Predation: Effect Size`:`Bottom-up: Nutrient Vector Storage: Excretion & Egestion: Effect Size`,
# .cols = 2:last_col(), # this should be the same as above but it cuts out the first (2nd) column, TD:DP:ES. Why?
# nstudies = count which rows have values
~ length(which(!is.na(.)))
)) %>%
# remove columns where all effect types/strengths are empty (0)
select(where(~ !all(.x == 0))) %>%
# pivot longer to create plot
pivot_longer(
cols = 2:last_col(),
names_to = "Effect Type"
) %>%
# remove "Effect Size"
mutate(`Effect Type` = str_remove(string = `Effect Type`,
pattern = ": Effect Size"),
# make Effect Type an ordered factor
`Effect Type` = ordered(`Effect Type`, levels = c(
"Top-down: Direct Predation",
"Top-down: Risk Effects",
"Top-down: Trophic Cascade",
"Competition",
"Bottom-up: Nutrient Vector Storage: Bioturbation",
"Bottom-up: Nutrient Vector Storage: Excretion & Egestion"))) %>%
na_if(0) %>% # remove zero rows
drop_na(value) %>%
ggplot(aes(x = .data[[groupvariable]], y = value, fill = `Effect Type`)) +
geom_bar(stat = "identity", position = position_dodge()) +
labs(y = "Number of Studies") +
# for EcoMorphotype only
{if (groupvariable == "Ecomorphotype")
scale_y_continuous(
breaks = c(0, 4, 8, 12, 16, 20, 24),
expand = c(0, 0)
)} +
# add pictures. ymin/max as expected. xmin max presumably based on 3 columns @ 1,2,3, w/ xrange 0:4
{if (groupvariable == "Ecomorphotype") annotation_custom(archipelagic, xmin = 0.5, xmax = 1.5, ymin = 15, ymax = 17)} +
{if (groupvariable == "Ecomorphotype") annotation_custom(littoral, xmin = 1.5, xmax = 2.5, ymin = 15, ymax = 17)} +
{if (groupvariable == "Ecomorphotype") annotation_custom(macroceanic, xmin = 2.5, xmax = 3.5, ymin = 15, ymax = 17)} +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1)),
axis.title = element_text(size = rel(1.5)),
legend.text = element_text(size = rel(1)),
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_", groupvariable, "_NStudies_bars.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, # changes how big lines & legend items & axes & titles are relative to basemap. Smaller number = bigger items
width = 8, # NA default. Manually adjust plot box in RStudio after ggplot()
height = 6, # NA default; Then ggsave with defaults, changes from 7x7" to e.g.
units = "in", # c("in", "cm", "mm"); 6.32x4, tweak as necessary. Removes canvas whitespace
dpi = 300, limitsize = TRUE
)
# mean effect table & plot####
# meaneffect <-
emt %>%
select(c(all_of(groupvariable), contains("Effect Size"))) %>% # only select Effect Size columns
group_by(.data[[groupvariable]]) %>%
summarise_all(mean, na.rm = TRUE) %>%
# remove columns where all effect types/strengths are empty (NaN)
select(where(~ !all(is.nan(.x)))) %>%
# pivot longer to create plot
pivot_longer(
cols = 2:last_col(),
names_to = "Effect Type"
) %>%
# remove "Effect Size"
mutate(`Effect Type` = str_remove(string = `Effect Type`,
pattern = ": Effect Size"),
# make Effect Type an ordered factor
`Effect Type` = ordered(`Effect Type`, levels = c(
"Top-down: Direct Predation",
"Top-down: Risk Effects",
"Top-down: Trophic Cascade",
"Competition",
"Bottom-up: Nutrient Vector Storage: Bioturbation",
"Bottom-up: Nutrient Vector Storage: Excretion & Egestion"))) %>%
na_if(0) %>% # remove zero rows
drop_na(value) %>%
ggplot(aes(x = .data[[groupvariable]], y = value, fill = `Effect Type`)) +
geom_bar(stat = "identity", position = position_dodge()) +
labs(y = "Mean Effect Size") +
scale_y_continuous(expand = c(0, 0)) +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1)),
axis.title = element_text(size = rel(1.5)),
legend.text = element_text(size = rel(1)),
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()) + # removed whitespace buffer around legend boxes which is nice
# add pictures. ymin/max as expected. xmin max presumably based on 3 columns @ 1,2,3, w/ xrange 0:4
{if (groupvariable == "Ecomorphotype") annotation_custom(archipelagic, xmin = 0.5, xmax = 1.5, ymin = 0.33, ymax = 0.66)} +
{if (groupvariable == "Ecomorphotype") annotation_custom(littoral, xmin = 1.5, xmax = 2.5, ymin = 0.33, ymax = 0.66)} +
{if (groupvariable == "Ecomorphotype") annotation_custom(macroceanic, xmin = 2.5, xmax = 3.5, ymin = 0.33, ymax = 0.66)}
ggsave(paste0(saveloc, today(), "_", groupvariable, "_MeanEffect_bars.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, # changes how big lines & legend items & axes & titles are relative to basemap. Smaller number = bigger items
width = 8, # NA default. Manually adjust plot box in RStudio after ggplot()
height = 6, # NA default; Then ggsave with defaults, changes from 7x7" to e.g.
units = "in", # c("in", "cm", "mm"); 6.32x4, tweak as necessary. Removes canvas whitespace
dpi = 300, limitsize = TRUE
)
# mean evidence table####
# meanevidence <-
emt %>%
select(c(all_of(groupvariable), contains("Evidence"))) %>% # only select Effect Size columns
group_by(.data[[groupvariable]]) %>%
summarise_all(mean, na.rm = TRUE) %>%
# remove columns where all effect types/strengths are empty (NaN)
select(where(~ !all(is.nan(.x)))) %>%
# pivot longer to create plot
pivot_longer(
cols = 2:last_col(),
names_to = "Effect Type"
) %>%
mutate(`Effect Type` = str_remove(string = `Effect Type`,
pattern = ": Strength of Evidence"),
# make Effect Type an ordered factor
`Effect Type` = ordered(`Effect Type`, levels = c(
"Top-down: Direct Predation",
"Top-down: Risk Effects",
"Top-down: Trophic Cascade",
"Competition",
"Bottom-up: Nutrient Vector Storage: Bioturbation",
"Bottom-up: Nutrient Vector Storage: Excretion & Egestion"
))) %>%
na_if(0) %>% # remove zero rows
drop_na(value) %>%
ggplot(aes(x = .data[[groupvariable]], y = value, fill = `Effect Type`)) +
geom_bar(stat = "identity", position = position_dodge()) +
labs(y = "Mean Strength of Evidence") +
scale_y_continuous(expand = c(0, 0)) +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1)),
axis.title = element_text(size = rel(1.5)),
legend.text = element_text(size = rel(1)),
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()) + # removed whitespace buffer around legend boxes which is nice
# add pictures. ymin/max as expected. xmin max presumably based on 3 columns @ 1,2,3, w/ xrange 0:4
{if (groupvariable == "Ecomorphotype") annotation_custom(archipelagic, xmin = 0.5, xmax = 1.5, ymin = 0.33, ymax = 0.66)} +
{if (groupvariable == "Ecomorphotype") annotation_custom(littoral, xmin = 1.5, xmax = 2.5, ymin = 0.33, ymax = 0.66)} +
{if (groupvariable == "Ecomorphotype") annotation_custom(macroceanic, xmin = 2.5, xmax = 3.5, ymin = 0.33, ymax = 0.66)}
ggsave(paste0(saveloc, today(), "_", groupvariable, "_MeanEvidence_bars.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, # changes how big lines & legend items & axes & titles are relative to basemap. Smaller number = bigger items
width = 8, # NA default. Manually adjust plot box in RStudio after ggplot()
height = 6, # NA default; Then ggsave with defaults, changes from 7x7" to e.g.
units = "in", # c("in", "cm", "mm"); 6.32x4, tweak as necessary. Removes canvas whitespace
dpi = 300, limitsize = TRUE
)
} # close groupvariable loop
#2023-02-09 EMT scatterplot ####
emt %<>%
# Need to parse each row out into multi rows when they have more than 1 effect type/SoE combo
# Need 1 column each for effect type, SoE, EMT.
tidyr::pivot_longer(cols = contains("Effect Size"),
names_to = "Effect Type",
values_to = "Effect Size") %>%
tidyr::pivot_longer(cols = contains("Strength of Evidence"),
names_to = "Effect Type2",
values_to = "Strength of Evidence") %>%
# remove ": Effect Size" & ": Strength of Evidence"
mutate(`Effect Type` = str_remove_all(string = `Effect Type`, pattern = ": Effect Size"),
`Effect Type2` = str_remove_all(string = `Effect Type2`, pattern = ": Strength of Evidence"),
# double pivot_longer creates n=effecttype^2 rows, all permutations of both. Collapse to where both match
EffectTypesMatch = ifelse(`Effect Type` == `Effect Type2`, TRUE, FALSE),
# also want to remove when both are NA later
BothNA = ifelse(is.na(`Effect Size`) & is.na(`Strength of Evidence`), TRUE, FALSE),
# for plotting, make integer = discrete
`Effect Size` = as.integer(`Effect Size`),
`Strength of Evidence` = as.integer(`Strength of Evidence`),
# so the legend order is logical
`Effect Type` = ordered(`Effect Type`,
levels = c("Top-down: Direct Predation",
"Top-down: Risk Effects",
"Top-down: Trophic Cascade",
"Competition",
"Bottom-up: Nutrient Vector Storage: Sharks as Food",
"Bottom-up: Nutrient Vector Storage: Excretion & Egestion"))) %>%
# filter for only those that match, remove permutation dupes
filter(EffectTypesMatch,
# remove where both are NA
!BothNA) %>%
# remove temp columns
select(!c(`Effect Type2`, EffectTypesMatch, BothNA)) %>%
# keep only columns needed for this plot
select(Ecomorphotype, `Effect Type`, `Effect Size`, `Strength of Evidence`)
saveRDS(emt, file = paste0(saveloc, today(), "_EMTdata.rds"))
ggplot(emt) +
# jitter is a shortcut for geom_point position = "jitter". Not great for discrete 1:3 though.
geom_jitter(mapping = aes(x = `Effect Size`,
y = `Strength of Evidence`,
colour = `Effect Type`,
shape = Ecomorphotype),
size = 3) + # width = 0.9, height = 0.9 does nothing
# change labels 1 2 3 to low medium high
scale_x_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
scale_y_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
# match colours to map figure
scale_colour_manual(values = c("red",
"dodgerblue4",
"darkorchid4",
"darkorange1",
"goldenrod3",
"green3")) +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1.5)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_Scatter_x-EfSz_y-SoEv_col-EfTyp_shp-EMT.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, # changes how big lines & legend items & axes & titles are relative to basemap. Smaller number = bigger items
width = 10, # NA default. Manually adjust plot box in RStudio after ggplot()
height = 6, # NA default; Then ggsave with defaults, changes from 7x7" to e.g.
units = "in", # c("in", "cm", "mm"); 6.32x4, tweak as necessary. Removes canvas whitespace
dpi = 300, limitsize = TRUE
)
# emt scatterplot facet EMT & Effect type ####
# facet this panels with a facet_wrap() so that ecomorphotypes & type of interaction are presented on separate graphs
ggplot(emt) +
# jitter is a shortcut for geom_point position = "jitter". Not great for discrete 1:3 though.
geom_jitter(mapping = aes(x = `Effect Size`,
y = `Strength of Evidence`,
colour = `Effect Type`,
shape = Ecomorphotype),
size = 3) + # width = 0.9, height = 0.9 does nothing
facet_wrap(vars(`Effect Type`, Ecomorphotype)) +
# change labels 1 2 3 to low medium high
scale_x_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
scale_y_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
# match colours to map figure
scale_colour_manual(
values = c("red",
"dodgerblue4",
"darkorchid4",
"darkorange1",
"goldenrod3",
"green3")) +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1.5)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_Scatter_x-EfSz_y-SoEv_col-EfTyp_shp-EMT_FacetEfTypEMT.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, # changes how big lines & legend items & axes & titles are relative to basemap. Smaller number = bigger items
width = 10, # NA default. Manually adjust plot box in RStudio after ggplot()
height = 6, # NA default; Then ggsave with defaults, changes from 7x7" to e.g.
units = "in", # c("in", "cm", "mm"); 6.32x4, tweak as necessary. Removes canvas whitespace
dpi = 300, limitsize = TRUE
)
# emt scatterplot facet EMT ####
ggplot(emt) +
geom_jitter(mapping = aes(x = `Effect Size`,
y = `Strength of Evidence`,
colour = `Effect Type`,
shape = Ecomorphotype),
size = 3) +
facet_wrap(vars(Ecomorphotype)) +
scale_x_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
scale_y_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
scale_colour_manual(
values = c("red",
"dodgerblue4",
"darkorchid4",
"darkorange1",
"goldenrod3",
"green3")) +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1.5)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_Scatter_x-EfSz_y-SoEv_col-EfTyp_shp-EMT_FacetEMT.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 2.5, units = "in", dpi = 300, limitsize = TRUE)
# emt scatterplot facet `Effect Type` ####
ggplot(emt) +
geom_jitter(mapping = aes(x = `Effect Size`,
y = `Strength of Evidence`,
colour = `Effect Type`,
shape = Ecomorphotype),
size = 3) +
facet_wrap(vars(`Effect Type`)) +
scale_x_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
scale_y_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
scale_colour_manual(
values = c("red",
"dodgerblue4",
"darkorchid4",
"darkorange1",
"goldenrod3",
"green3")) +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1.5)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_Scatter_x-EfSz_y-SoEv_col-EfTyp_shp-EMT_FacetEfTyp.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 2023-02-10 Sankey AKA alluvial plot ####
# load & prep variables
saveloc <- "/home/simon/Documents/Si Work/PostDoc Work/FIU/Ecological Importance of Sharks Workshop/Papers Prep/2022 Science/1_EROS/"
emt <- readRDS(file = paste0(saveloc, "2023-02-22", "_EMTdata.rds")) %>%
# make (ordered) factors for all but Freq. Effect type already done above.
mutate(Ecomorphotype = ordered(Ecomorphotype, levels = c("Archipelagic", "Littoral", "Macroceanic")),
`Effect Size` = ordered(`Effect Size`, levels = c(3, 2, 1)),
`Strength of Evidence` = ordered(`Strength of Evidence`, levels = c(3, 2, 1)))
# All 4 variables, no colour ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(Ecomorphotype, `Effect Type`, `Effect Size`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = Ecomorphotype,
axis2 = `Effect Type`,
axis3 = `Effect Size`,
axis4 = `Strength of Evidence`,
y = Count)
) +
scale_x_discrete(limits = c("Ecomorphotype",
"Effect Type",
"Effect Size",
"Strength of Evidence"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium() + # aes(fill = `Strength of Evidence`)
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1.5)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT-EfTyp-EfSiz-SoEv.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 3bar: EMT, EfTyp, EfSiz, SoEv=colour ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(Ecomorphotype, `Effect Type`, `Effect Size`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = Ecomorphotype,
axis2 = `Effect Type`,
axis3 = `Effect Size`,
y = Count)
) +
scale_x_discrete(limits = c("Ecomorphotype",
"Effect Type",
"Effect Size"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Strength of Evidence`)) + #
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1.5)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT-EfTyp-EfSiz_Col-SoEv.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 3bar: EMT, EfSiz, EfTyp rearrange, SoEv=colour ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(Ecomorphotype, `Effect Type`, `Effect Size`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = Ecomorphotype,
axis2 = `Effect Size`,
axis3 = `Effect Type`,
y = Count)
) +
scale_x_discrete(limits = c("Ecomorphotype",
"Effect Size",
"Effect Type"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Strength of Evidence`)) + #
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1.5)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT-EfSiz-EfTyp_Col-SoEv.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 3bar: EMT, EfSiz, SoEv, EfTyp=colour ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(Ecomorphotype, `Effect Type`, `Effect Size`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = Ecomorphotype,
axis2 = `Effect Size`,
axis3 = `Strength of Evidence`,
y = Count)
) +
scale_x_discrete(limits = c("Ecomorphotype",
"Effect Size",
"Strength of Evidence"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Effect Type`)) + #
scale_fill_manual(values = c("red", "dodgerblue4", "darkorchid4", "darkorange1", "goldenrod3", "green3")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT-EfSiz-SoEv_Col-EfTyp.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 3bar: EfTyp, EfSiz, SoEv, EMT=colour ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(Ecomorphotype, `Effect Type`, `Effect Size`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = `Effect Type`,
axis2 = `Effect Size`,
axis3 = `Strength of Evidence`,
y = Count)
) +
scale_x_discrete(limits = c("Effect Type",
"Effect Size",
"Strength of Evidence"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = Ecomorphotype)) + #
# scale_fill_manual(values = c("red", "dodgerblue4", "darkorchid4", "darkorange1", "goldenrod3", "green3")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EfTyp-EfSiz-SoEv_Col-EMT.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 2bar: EfTyp, EMT, EfSiz=colour ####
# SoEv,
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(`Effect Type`, Ecomorphotype, `Effect Size`) %>%
summarise(Count = n()),
aes(axis1 = `Effect Type`,
axis2 = Ecomorphotype,
y = Count)
) +
scale_x_discrete(limits = c("Effect Type",
"Ecomorphotype"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Effect Size`)) + #
# scale_fill_manual(values = c("red", "dodgerblue4", "darkorchid4", "darkorange1", "goldenrod3", "green3")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EfTyp-EMT_Col-EfSiz.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 2bar: EfTyp, EMT, SoEv=colour ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(`Effect Type`, Ecomorphotype, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = `Effect Type`,
axis2 = Ecomorphotype,
y = Count)
) +
scale_x_discrete(limits = c("Effect Type",
"Ecomorphotype"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Strength of Evidence`)) + #
# scale_fill_manual(values = c("red", "dodgerblue4", "darkorchid4", "darkorange1", "goldenrod3", "green3")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EfTyp-EMT_Col-SoEv.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 2bar: EMT, EfTyp, EfSiz=colour ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(Ecomorphotype, `Effect Type`, `Effect Size`) %>%
summarise(Count = n()),
aes(axis1 = Ecomorphotype,
axis2 = `Effect Type`,
y = Count)
) +
scale_x_discrete(limits = c("Ecomorphotype",
"Effect Type"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Effect Size`)) + #
# scale_fill_manual(values = c("red", "dodgerblue4", "darkorchid4", "darkorange1", "goldenrod3", "green3")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT-EfTyp_Col-EfSiz.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 2bar: EMT, EfTyp, col=SoEv ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(Ecomorphotype, `Effect Type`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = Ecomorphotype,
axis2 = `Effect Type`,
y = Count)
) +
scale_x_discrete(limits = c("Ecomorphotype",
"Effect Type"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Strength of Evidence`)) + #
# scale_fill_manual(values = c("red", "dodgerblue4", "darkorchid4", "darkorange1", "goldenrod3", "green3")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT-EfTyp_Col-SoEv.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 2bar, PerEMT: EfTyp, EfSiz, col=SoEv####
for (EMT in levels(emt$Ecomorphotype)) {
ggplot(data = emt %>%
filter(Ecomorphotype == EMT) %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(`Effect Type`, `Effect Size`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = `Effect Type`,
axis2 = `Effect Size`,
y = Count)
) +
scale_x_discrete(limits = c("Effect Type",
"Effect Size"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Strength of Evidence`)) + #
# scale_fill_manual(values = c("red", "dodgerblue4", "darkorchid4", "darkorange1", "goldenrod3", "green3")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
ggtitle(EMT) +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_", EMT, "_EfTyp-EfSize_Col-SoEv.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
}
# 2bar, EMT+EfSz, EfTyp, col=SoEv####
ggplot(data = emt %>%
# join EMT & EffectSize
unite(col = "EMT-EfSz", c(Ecomorphotype, `Effect Size`), sep = ": ") %>%
group_by(`EMT-EfSz`, `Effect Type`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = `EMT-EfSz`,
axis2 = `Effect Type`,
y = Count)) +
scale_x_discrete(limits = c("EMT: Effect Size", "Effect Type"), expand = c(.2, .05)) +
geom_alluvium(aes(fill = `Strength of Evidence`)) + #
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, linewidth = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank())
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT.EfSz-EfTyp_Col-SoEv.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 2bar, EMT+SoEv, EfTyp, col=EfSz####
ggplot(data = emt %>%
# join EMT & EffectSize
unite(col = "EMT-SoEv", c(Ecomorphotype, `Strength of Evidence`), sep = ": ") %>%
group_by(`EMT-SoEv`, `Effect Type`, `Effect Size`) %>%
summarise(Count = n()),
aes(axis1 = `EMT-SoEv`,
axis2 = `Effect Type`,
y = Count)) +
scale_x_discrete(limits = c("EMT: Strength of Evidence", "Effect Type"), expand = c(.2, .05)) +
geom_alluvium(aes(fill = `Effect Size`)) +
scale_fill_manual(values = c("black", "blue", "cadetblue1")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, linewidth = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank())
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT.SoEv-EfTyp_Col-EfSz.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# Archipelagic NA SoE: Tinker et al. 2016, Moxley et al. 2019 [12], and Hughes et al. 2013, Hughes et al. 2019 [15]
# 2023-02-22 FunctionalGroup+Realm####
# replace EMT with this.
emt <- read_sheet("https://docs.google.com/spreadsheets/d/1dNDEUENa4M1__VNksolw8Or9ysPutEYWMTgZJ-qOe9I/edit#gid=0") %>%
# select cols of interest
select(Ecomorphotype, `Functional Group`, Realm, Ecosystem, `Ocean Basin`, `Top-down: Direct Predation: Effect Size`:`Bottom-up: Nutrient Vector Storage: Excretion & Egestion: Strength of Evidence`) %>%
# remove NA emt rows
drop_na(`Functional Group`, Realm) %>%
# convert High Medium Low to 3 2 1, keep NAs
mutate(across(
.cols = `Top-down: Direct Predation: Effect Size`:`Bottom-up: Nutrient Vector Storage: Excretion & Egestion: Strength of Evidence`,
~ dplyr::case_when(
. == "High" ~ 3,
. == "Medium" ~ 2,
. == "Low" ~ 1
)
)) %>%
# remove rays
filter(!Ecomorphotype %in% c("Aquilopelagic", "Rajobenthic")) %>%
# Need to parse each row out into multi rows when they have more than 1 effect type/SoE combo
# Need 1 column each for effect type, SoE, EMT.
tidyr::pivot_longer(cols = contains("Effect Size"),
names_to = "Effect Type",
values_to = "Effect Size") %>%
tidyr::pivot_longer(cols = contains("Strength of Evidence"),
names_to = "Effect Type2",
values_to = "Strength of Evidence") %>%
# remove ": Effect Size" & ": Strength of Evidence"
mutate(`Effect Type` = str_remove_all(string = `Effect Type`, pattern = ": Effect Size"),
`Effect Type2` = str_remove_all(string = `Effect Type2`, pattern = ": Strength of Evidence"),
# double pivot_longer creates n=effecttype^2 rows, all permutations of both. Collapse to where both match
EffectTypesMatch = ifelse(`Effect Type` == `Effect Type2`, TRUE, FALSE),
# also want to remove when both are NA later
BothNA = ifelse(is.na(`Effect Size`) & is.na(`Strength of Evidence`), TRUE, FALSE),
# for plotting, make integer = discrete
`Effect Size` = as.integer(`Effect Size`),
`Strength of Evidence` = as.integer(`Strength of Evidence`),
# Edit Functional Group names
`Functional Group` = case_match(`Functional Group`,
"Apex sharks" ~ "Macropredatory sharks",
"Meso sharks / baby apex sharks" ~ "Mesopredatory sharks"),
# Edit Effect Type Group names
`Effect Type` = case_match(`Effect Type`,
"Bottom-up: Nutrient Vector Storage: Sharks as Food" ~ "BU:NVS:SAF",
"Bottom-up: Nutrient Vector Storage: Excretion & Egestion" ~ "BU:NVS:EAE",
.default = `Effect Type`),
# so the legend order is logical
`Effect Type` = ordered(`Effect Type`,
levels = c("Top-down: Direct Predation",
"Top-down: Risk Effects",
"Top-down: Trophic Cascade",
"Competition",
"BU:NVS:SAF",
"BU:NVS:EAE"))) %>%
# filter for only those that match, remove permutation dupes
filter(EffectTypesMatch,
# remove where both are NA
!BothNA) %>%
unite(col = "FnGpRealm", c(`Functional Group`, Realm), sep = ": ") %>%
# # remove temp columns
# select(!c(`Effect Type2`, EffectTypesMatch, BothNA)) %>%
# keep only columns needed for this plot
select(FnGpRealm, `Effect Type`, `Effect Size`, `Strength of Evidence`) %>%
# make (ordered) factors for all but Freq. Effect type already done above.
mutate(FnGpRealm = ordered(FnGpRealm, levels = c("Macropredatory sharks: Inshore/Shelf",
"Macropredatory sharks: Pelagic",
"Mesopredatory sharks: Inshore/Shelf",
"Mesopredatory sharks: Pelagic")),
`Effect Size` = ordered(`Effect Size`, levels = c(3, 2, 1)),
`Strength of Evidence` = ordered(`Strength of Evidence`, levels = c(3, 2, 1))) %T>% # note matrittr tee pipe
saveRDS(file = paste0(saveloc, today(), "_EMTdataFnGpRealm.rds"))
# 2bar, FnGpRealm, EfTyp, col=EfSz [usethis]####
ggplot(data = emt %>%
mutate(FnGpRealm = stringr::str_replace_all(string = FnGpRealm,
pattern = "Macropredatory sharks",
replacement = "Ma"),
FnGpRealm = stringr::str_replace_all(string = FnGpRealm,
pattern = "Mesopredatory sharks",
replacement = "Me")) %>%
tidyr::drop_na(`Effect Type`) %>% # remove leftover row
# 2023-10-26 edit labels, FnGpRealm, Mesopredatory sharks:
group_by(`FnGpRealm`, `Effect Type`, `Effect Size`) %>%
summarise(Count = n()),
aes(axis1 = `FnGpRealm`,
axis2 = `Effect Type`,
y = Count)) +
scale_x_discrete(limits = c("Functional Group: Realm", "Effect Type"), expand = c(.2, .05)) +
geom_alluvium(mapping = aes(fill = `Effect Size`),
alpha = 0.75 # default is 1/2
) +
scale_fill_manual(values = c(rgb(0.11, 0.62, 0.47),
rgb(0.46, 0.44, 0.7),
rgb(0.85, 0.37, 0.01))) +
# geom_flow() + #just makes everything alpha & greyish?
# geom_stratum(width = 1/12, fill = "white", color = "grey") +
geom_stratum(width = 1/3) + # default colour black, fill white, width 1/3
# geom_label(stat = "stratum", aes(label = after_stat(stratum))) + # label puts in balloon,
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # text just overlays the text. lebel = stringr::str_wrap(after_stat(stratum), 5)
# coord_flip() +
# ggtitle() +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
# legend.position = "none", #to hide legend & put in caption if desired
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, linewidth = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
panel.grid.major.x = element_blank(),
legend.key = element_blank())
# ended up blanking out "Ma: Pelagic" in Gimp and replacing with asterix.
# shrink axes width: geom_stratum(width) but then lines expand past it
# todo: wrap text in strata/axes. Turn sideways? geom_text(angle = 90). Font: family = "Times New Roman"
## could wrap the text itself by addling a line break to specific categories. paste(strwrap(x, ...), collapse = "\n")
# remove dead space outside plot - margin?
# nicer colours
# remove y axis labels & title??
saveloc <- "C:/Users/simon/Documents/Si Work/PostDoc Work/FIU/Ecological Importance of Sharks Workshop/Papers Prep/2022 Science/1_EROS" # windows
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_FnGp.Realm-EfTyp_Col-EfSz.png"),
plot = last_plot(), device = "png", path = "",
scale = 2,
width = 4, # 6
height = 6, # 4
units = "in", dpi = 300, limitsize = TRUE)
tmp <- emt %>%
mutate(FnGpRealm = stringr::str_replace_all(string = FnGpRealm,
pattern = "Macropredatory sharks",
replacement = "Ma"),
FnGpRealm = stringr::str_replace_all(string = FnGpRealm,
pattern = "Mesopredatory sharks",
replacement = "Me")) %>%
tidyr::drop_na(`Effect Type`) %>% # remove leftover row
# 2023-10-26 edit labels, FnGpRealm, Mesopredatory sharks:
group_by(`FnGpRealm`, `Effect Type`, `Effect Size`) %>%
summarise(Count = n())
SimonDedman/FIUSharkEcol documentation built on June 6, 2024, 2:55 p.m.
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# 2023-01-23 Ecomorphotypes bars
# Simon Dedman, simondedman@gmail.com
# imports Google sheet & local png images, tidies table, plots, per ecomorphotype: number of studies,
# mean effect size, mean strength of evidence.
# ToDo ####
# fix study with more n for effect than evidence - score the evidence, re-run plots. Unknown ref. Asked Jerry.
# load packages####
# install.packages("googlesheets4")
library(googlesheets4)
library(tidyverse)
library(magrittr) # not used (yet)
library(tidylog)
library(ggplot2)
library(lubridate) # today
library(png) # add images to plots
library(grid) # add images to plots
# https://corybrunson.github.io/ggalluvial/ nicer than
# https://r-charts.com/flow/sankey-diagram-ggplot2/
# install.packages("ggalluvial")
# library(remotes)
# remotes::install_github("corybrunson/ggalluvial@main", build_vignettes = TRUE)
# https://github.com/corybrunson/ggalluvial/issues/110
# alluvial and ggfittext not being installed that are required to build the vignettes.
# Those packages are listed under Suggests: rather than under Imports: in the DESCRIPTION,
# which i understand to be the correct policy for packages that are only required for vignettes.
# Could you install those packages and try again?
library(ggalluvial)
# import data & images####
emt <- read_sheet("https://docs.google.com/spreadsheets/d/1dNDEUENa4M1__VNksolw8Or9ysPutEYWMTgZJ-qOe9I/edit#gid=0")
# nstudies <- read_sheet(ss = "https://docs.google.com/spreadsheets/d/1dNDEUENa4M1__VNksolw8Or9ysPutEYWMTgZJ-qOe9I/edit#gid=0",
# sheet = "Ecomorphotypes Matrix Figure",
# range = "A34:J47")
# meaneffect <- read_sheet(ss = "https://docs.google.com/spreadsheets/d/1dNDEUENa4M1__VNksolw8Or9ysPutEYWMTgZJ-qOe9I/edit#gid=0",
# sheet = "Ecomorphotypes Matrix Figure",
# range = "A50:J63")
# meanevidence <- read_sheet(ss = "https://docs.google.com/spreadsheets/d/1dNDEUENa4M1__VNksolw8Or9ysPutEYWMTgZJ-qOe9I/edit#gid=0",
# sheet = "Ecomorphotypes Matrix Figure",
# range = "A66:J79")
saveloc <- "/home/simon/Documents/Si Work/PostDoc Work/FIU/Ecological Importance of Sharks Workshop/Papers Prep/2022 Science/1_EROS/"
saveloc <- "C:/Users/simon/Documents/Si Work/PostDoc Work/FIU/Ecological Importance of Sharks Workshop/Papers Prep/2022 Science/1_EROS/" # windows
# https://stackoverflow.com/questions/9917049/inserting-an-image-to-ggplot2
littoral <- rasterGrob(readPNG(paste0(saveloc, "Graphics/emt_littoral.png")), interpolate = TRUE)
archipelagic <- rasterGrob(readPNG(paste0(saveloc, "Graphics/emt_archipelagic.png")), interpolate = TRUE)
macroceanic <- rasterGrob(readPNG(paste0(saveloc, "Graphics/emt_macroceanic.png")), interpolate = TRUE)
# rajobenthic <- rasterGrob(readPNG(paste0(saveloc, "Graphics/emt_rajobenthic.png")), interpolate = TRUE) # rays if required
# aquilopelagic <- rasterGrob(readPNG(paste0(saveloc, "Graphics/emt_aquilopelagic.png")), interpolate = TRUE)
# Analysis####
# Only 3/12 EMTs have any studies at all outside of diet.
# bar chart for ecological roles: stacked bars based on realm, habitat, etc.
# Caption.
# clean table, convert low medium high to 1 2 3
emt %<>%
# select cols of interest
select(Ecomorphotype, `Functional Group`, Realm, Ecosystem, `Ocean Basin`, `Top-down: Direct Predation: Effect Size`:`Bottom-up: Nutrient Vector Storage: Excretion & Egestion: Strength of Evidence`) %>%
# remove NA emt rows
drop_na(Ecomorphotype) %>%
# convert High Medium Low to 3 2 1, keep NAs
mutate(across(
.cols = `Top-down: Direct Predation: Effect Size`:`Bottom-up: Nutrient Vector Storage: Excretion & Egestion: Strength of Evidence`,
~ dplyr::case_when(
. == "High" ~ 3,
. == "Medium" ~ 2,
. == "Low" ~ 1
)
)) %>%
# remove rays
filter(!Ecomorphotype %in% c("Aquilopelagic", "Rajobenthic"))
# Loop through nstudies effectSize strengthEffect for 5 grouping variables
for (groupvariable in c("Ecomorphotype", # groupvariable <- "Ecomorphotype"
"Functional Group", # groupvariable <- "Functional Group"
"Realm", # groupvariable <- "Realm"
"Ecosystem", # groupvariable <- "Ecosystem"
"Ocean Basin")) { # open groupvariable loop. # groupvariable <- "Ocean Basin"
# programming with dplyr vignette, loop over multiple variables: .data[[groupvariable]]
# depreciated in tidyselect 1.2.0, use all_of(groupvariable)
# Using `all_of()` outside of a selecting function was deprecated in tidyselect 1.2.0.
# Thus use all_of(groupvariable) in select() and .data[[groupvariable]] elsewhere. UGH.
# nstudies table & plot####
# nstudies <-
emt %>%
select(c(all_of(groupvariable), contains("Effect Size"))) %>% # only select groupvariable & Effect Size columns - s.o.evidence is a dupe
group_by(.data[[groupvariable]]) %>%
summarise(across(
.cols = `Top-down: Direct Predation: Effect Size`:`Bottom-up: Nutrient Vector Storage: Excretion & Egestion: Effect Size`,
# .cols = 2:last_col(), # this should be the same as above but it cuts out the first (2nd) column, TD:DP:ES. Why?
# nstudies = count which rows have values
~ length(which(!is.na(.)))
)) %>%
# remove columns where all effect types/strengths are empty (0)
select(where(~ !all(.x == 0))) %>%
# pivot longer to create plot
pivot_longer(
cols = 2:last_col(),
names_to = "Effect Type"
) %>%
# remove "Effect Size"
mutate(`Effect Type` = str_remove(string = `Effect Type`,
pattern = ": Effect Size"),
# make Effect Type an ordered factor
`Effect Type` = ordered(`Effect Type`, levels = c(
"Top-down: Direct Predation",
"Top-down: Risk Effects",
"Top-down: Trophic Cascade",
"Competition",
"Bottom-up: Nutrient Vector Storage: Bioturbation",
"Bottom-up: Nutrient Vector Storage: Excretion & Egestion"))) %>%
na_if(0) %>% # remove zero rows
drop_na(value) %>%
ggplot(aes(x = .data[[groupvariable]], y = value, fill = `Effect Type`)) +
geom_bar(stat = "identity", position = position_dodge()) +
labs(y = "Number of Studies") +
# for EcoMorphotype only
{if (groupvariable == "Ecomorphotype")
scale_y_continuous(
breaks = c(0, 4, 8, 12, 16, 20, 24),
expand = c(0, 0)
)} +
# add pictures. ymin/max as expected. xmin max presumably based on 3 columns @ 1,2,3, w/ xrange 0:4
{if (groupvariable == "Ecomorphotype") annotation_custom(archipelagic, xmin = 0.5, xmax = 1.5, ymin = 15, ymax = 17)} +
{if (groupvariable == "Ecomorphotype") annotation_custom(littoral, xmin = 1.5, xmax = 2.5, ymin = 15, ymax = 17)} +
{if (groupvariable == "Ecomorphotype") annotation_custom(macroceanic, xmin = 2.5, xmax = 3.5, ymin = 15, ymax = 17)} +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1)),
axis.title = element_text(size = rel(1.5)),
legend.text = element_text(size = rel(1)),
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_", groupvariable, "_NStudies_bars.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, # changes how big lines & legend items & axes & titles are relative to basemap. Smaller number = bigger items
width = 8, # NA default. Manually adjust plot box in RStudio after ggplot()
height = 6, # NA default; Then ggsave with defaults, changes from 7x7" to e.g.
units = "in", # c("in", "cm", "mm"); 6.32x4, tweak as necessary. Removes canvas whitespace
dpi = 300, limitsize = TRUE
)
# mean effect table & plot####
# meaneffect <-
emt %>%
select(c(all_of(groupvariable), contains("Effect Size"))) %>% # only select Effect Size columns
group_by(.data[[groupvariable]]) %>%
summarise_all(mean, na.rm = TRUE) %>%
# remove columns where all effect types/strengths are empty (NaN)
select(where(~ !all(is.nan(.x)))) %>%
# pivot longer to create plot
pivot_longer(
cols = 2:last_col(),
names_to = "Effect Type"
) %>%
# remove "Effect Size"
mutate(`Effect Type` = str_remove(string = `Effect Type`,
pattern = ": Effect Size"),
# make Effect Type an ordered factor
`Effect Type` = ordered(`Effect Type`, levels = c(
"Top-down: Direct Predation",
"Top-down: Risk Effects",
"Top-down: Trophic Cascade",
"Competition",
"Bottom-up: Nutrient Vector Storage: Bioturbation",
"Bottom-up: Nutrient Vector Storage: Excretion & Egestion"))) %>%
na_if(0) %>% # remove zero rows
drop_na(value) %>%
ggplot(aes(x = .data[[groupvariable]], y = value, fill = `Effect Type`)) +
geom_bar(stat = "identity", position = position_dodge()) +
labs(y = "Mean Effect Size") +
scale_y_continuous(expand = c(0, 0)) +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1)),
axis.title = element_text(size = rel(1.5)),
legend.text = element_text(size = rel(1)),
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()) + # removed whitespace buffer around legend boxes which is nice
# add pictures. ymin/max as expected. xmin max presumably based on 3 columns @ 1,2,3, w/ xrange 0:4
{if (groupvariable == "Ecomorphotype") annotation_custom(archipelagic, xmin = 0.5, xmax = 1.5, ymin = 0.33, ymax = 0.66)} +
{if (groupvariable == "Ecomorphotype") annotation_custom(littoral, xmin = 1.5, xmax = 2.5, ymin = 0.33, ymax = 0.66)} +
{if (groupvariable == "Ecomorphotype") annotation_custom(macroceanic, xmin = 2.5, xmax = 3.5, ymin = 0.33, ymax = 0.66)}
ggsave(paste0(saveloc, today(), "_", groupvariable, "_MeanEffect_bars.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, # changes how big lines & legend items & axes & titles are relative to basemap. Smaller number = bigger items
width = 8, # NA default. Manually adjust plot box in RStudio after ggplot()
height = 6, # NA default; Then ggsave with defaults, changes from 7x7" to e.g.
units = "in", # c("in", "cm", "mm"); 6.32x4, tweak as necessary. Removes canvas whitespace
dpi = 300, limitsize = TRUE
)
# mean evidence table####
# meanevidence <-
emt %>%
select(c(all_of(groupvariable), contains("Evidence"))) %>% # only select Effect Size columns
group_by(.data[[groupvariable]]) %>%
summarise_all(mean, na.rm = TRUE) %>%
# remove columns where all effect types/strengths are empty (NaN)
select(where(~ !all(is.nan(.x)))) %>%
# pivot longer to create plot
pivot_longer(
cols = 2:last_col(),
names_to = "Effect Type"
) %>%
mutate(`Effect Type` = str_remove(string = `Effect Type`,
pattern = ": Strength of Evidence"),
# make Effect Type an ordered factor
`Effect Type` = ordered(`Effect Type`, levels = c(
"Top-down: Direct Predation",
"Top-down: Risk Effects",
"Top-down: Trophic Cascade",
"Competition",
"Bottom-up: Nutrient Vector Storage: Bioturbation",
"Bottom-up: Nutrient Vector Storage: Excretion & Egestion"
))) %>%
na_if(0) %>% # remove zero rows
drop_na(value) %>%
ggplot(aes(x = .data[[groupvariable]], y = value, fill = `Effect Type`)) +
geom_bar(stat = "identity", position = position_dodge()) +
labs(y = "Mean Strength of Evidence") +
scale_y_continuous(expand = c(0, 0)) +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1)),
axis.title = element_text(size = rel(1.5)),
legend.text = element_text(size = rel(1)),
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()) + # removed whitespace buffer around legend boxes which is nice
# add pictures. ymin/max as expected. xmin max presumably based on 3 columns @ 1,2,3, w/ xrange 0:4
{if (groupvariable == "Ecomorphotype") annotation_custom(archipelagic, xmin = 0.5, xmax = 1.5, ymin = 0.33, ymax = 0.66)} +
{if (groupvariable == "Ecomorphotype") annotation_custom(littoral, xmin = 1.5, xmax = 2.5, ymin = 0.33, ymax = 0.66)} +
{if (groupvariable == "Ecomorphotype") annotation_custom(macroceanic, xmin = 2.5, xmax = 3.5, ymin = 0.33, ymax = 0.66)}
ggsave(paste0(saveloc, today(), "_", groupvariable, "_MeanEvidence_bars.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, # changes how big lines & legend items & axes & titles are relative to basemap. Smaller number = bigger items
width = 8, # NA default. Manually adjust plot box in RStudio after ggplot()
height = 6, # NA default; Then ggsave with defaults, changes from 7x7" to e.g.
units = "in", # c("in", "cm", "mm"); 6.32x4, tweak as necessary. Removes canvas whitespace
dpi = 300, limitsize = TRUE
)
} # close groupvariable loop
#2023-02-09 EMT scatterplot ####
emt %<>%
# Need to parse each row out into multi rows when they have more than 1 effect type/SoE combo
# Need 1 column each for effect type, SoE, EMT.
tidyr::pivot_longer(cols = contains("Effect Size"),
names_to = "Effect Type",
values_to = "Effect Size") %>%
tidyr::pivot_longer(cols = contains("Strength of Evidence"),
names_to = "Effect Type2",
values_to = "Strength of Evidence") %>%
# remove ": Effect Size" & ": Strength of Evidence"
mutate(`Effect Type` = str_remove_all(string = `Effect Type`, pattern = ": Effect Size"),
`Effect Type2` = str_remove_all(string = `Effect Type2`, pattern = ": Strength of Evidence"),
# double pivot_longer creates n=effecttype^2 rows, all permutations of both. Collapse to where both match
EffectTypesMatch = ifelse(`Effect Type` == `Effect Type2`, TRUE, FALSE),
# also want to remove when both are NA later
BothNA = ifelse(is.na(`Effect Size`) & is.na(`Strength of Evidence`), TRUE, FALSE),
# for plotting, make integer = discrete
`Effect Size` = as.integer(`Effect Size`),
`Strength of Evidence` = as.integer(`Strength of Evidence`),
# so the legend order is logical
`Effect Type` = ordered(`Effect Type`,
levels = c("Top-down: Direct Predation",
"Top-down: Risk Effects",
"Top-down: Trophic Cascade",
"Competition",
"Bottom-up: Nutrient Vector Storage: Sharks as Food",
"Bottom-up: Nutrient Vector Storage: Excretion & Egestion"))) %>%
# filter for only those that match, remove permutation dupes
filter(EffectTypesMatch,
# remove where both are NA
!BothNA) %>%
# remove temp columns
select(!c(`Effect Type2`, EffectTypesMatch, BothNA)) %>%
# keep only columns needed for this plot
select(Ecomorphotype, `Effect Type`, `Effect Size`, `Strength of Evidence`)
saveRDS(emt, file = paste0(saveloc, today(), "_EMTdata.rds"))
ggplot(emt) +
# jitter is a shortcut for geom_point position = "jitter". Not great for discrete 1:3 though.
geom_jitter(mapping = aes(x = `Effect Size`,
y = `Strength of Evidence`,
colour = `Effect Type`,
shape = Ecomorphotype),
size = 3) + # width = 0.9, height = 0.9 does nothing
# change labels 1 2 3 to low medium high
scale_x_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
scale_y_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
# match colours to map figure
scale_colour_manual(values = c("red",
"dodgerblue4",
"darkorchid4",
"darkorange1",
"goldenrod3",
"green3")) +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1.5)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_Scatter_x-EfSz_y-SoEv_col-EfTyp_shp-EMT.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, # changes how big lines & legend items & axes & titles are relative to basemap. Smaller number = bigger items
width = 10, # NA default. Manually adjust plot box in RStudio after ggplot()
height = 6, # NA default; Then ggsave with defaults, changes from 7x7" to e.g.
units = "in", # c("in", "cm", "mm"); 6.32x4, tweak as necessary. Removes canvas whitespace
dpi = 300, limitsize = TRUE
)
# emt scatterplot facet EMT & Effect type ####
# facet this panels with a facet_wrap() so that ecomorphotypes & type of interaction are presented on separate graphs
ggplot(emt) +
# jitter is a shortcut for geom_point position = "jitter". Not great for discrete 1:3 though.
geom_jitter(mapping = aes(x = `Effect Size`,
y = `Strength of Evidence`,
colour = `Effect Type`,
shape = Ecomorphotype),
size = 3) + # width = 0.9, height = 0.9 does nothing
facet_wrap(vars(`Effect Type`, Ecomorphotype)) +
# change labels 1 2 3 to low medium high
scale_x_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
scale_y_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
# match colours to map figure
scale_colour_manual(
values = c("red",
"dodgerblue4",
"darkorchid4",
"darkorange1",
"goldenrod3",
"green3")) +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1.5)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_Scatter_x-EfSz_y-SoEv_col-EfTyp_shp-EMT_FacetEfTypEMT.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, # changes how big lines & legend items & axes & titles are relative to basemap. Smaller number = bigger items
width = 10, # NA default. Manually adjust plot box in RStudio after ggplot()
height = 6, # NA default; Then ggsave with defaults, changes from 7x7" to e.g.
units = "in", # c("in", "cm", "mm"); 6.32x4, tweak as necessary. Removes canvas whitespace
dpi = 300, limitsize = TRUE
)
# emt scatterplot facet EMT ####
ggplot(emt) +
geom_jitter(mapping = aes(x = `Effect Size`,
y = `Strength of Evidence`,
colour = `Effect Type`,
shape = Ecomorphotype),
size = 3) +
facet_wrap(vars(Ecomorphotype)) +
scale_x_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
scale_y_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
scale_colour_manual(
values = c("red",
"dodgerblue4",
"darkorchid4",
"darkorange1",
"goldenrod3",
"green3")) +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1.5)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_Scatter_x-EfSz_y-SoEv_col-EfTyp_shp-EMT_FacetEMT.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 2.5, units = "in", dpi = 300, limitsize = TRUE)
# emt scatterplot facet `Effect Type` ####
ggplot(emt) +
geom_jitter(mapping = aes(x = `Effect Size`,
y = `Strength of Evidence`,
colour = `Effect Type`,
shape = Ecomorphotype),
size = 3) +
facet_wrap(vars(`Effect Type`)) +
scale_x_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
scale_y_discrete(limits = 1:3,
labels = c("Low", "Medium", "High"),
expand = c(0,0)) +
scale_colour_manual(
values = c("red",
"dodgerblue4",
"darkorchid4",
"darkorange1",
"goldenrod3",
"green3")) +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1.5)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_Scatter_x-EfSz_y-SoEv_col-EfTyp_shp-EMT_FacetEfTyp.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 2023-02-10 Sankey AKA alluvial plot ####
# load & prep variables
saveloc <- "/home/simon/Documents/Si Work/PostDoc Work/FIU/Ecological Importance of Sharks Workshop/Papers Prep/2022 Science/1_EROS/"
emt <- readRDS(file = paste0(saveloc, "2023-02-22", "_EMTdata.rds")) %>%
# make (ordered) factors for all but Freq. Effect type already done above.
mutate(Ecomorphotype = ordered(Ecomorphotype, levels = c("Archipelagic", "Littoral", "Macroceanic")),
`Effect Size` = ordered(`Effect Size`, levels = c(3, 2, 1)),
`Strength of Evidence` = ordered(`Strength of Evidence`, levels = c(3, 2, 1)))
# All 4 variables, no colour ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(Ecomorphotype, `Effect Type`, `Effect Size`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = Ecomorphotype,
axis2 = `Effect Type`,
axis3 = `Effect Size`,
axis4 = `Strength of Evidence`,
y = Count)
) +
scale_x_discrete(limits = c("Ecomorphotype",
"Effect Type",
"Effect Size",
"Strength of Evidence"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium() + # aes(fill = `Strength of Evidence`)
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1.5)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT-EfTyp-EfSiz-SoEv.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 3bar: EMT, EfTyp, EfSiz, SoEv=colour ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(Ecomorphotype, `Effect Type`, `Effect Size`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = Ecomorphotype,
axis2 = `Effect Type`,
axis3 = `Effect Size`,
y = Count)
) +
scale_x_discrete(limits = c("Ecomorphotype",
"Effect Type",
"Effect Size"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Strength of Evidence`)) + #
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1.5)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT-EfTyp-EfSiz_Col-SoEv.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 3bar: EMT, EfSiz, EfTyp rearrange, SoEv=colour ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(Ecomorphotype, `Effect Type`, `Effect Size`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = Ecomorphotype,
axis2 = `Effect Size`,
axis3 = `Effect Type`,
y = Count)
) +
scale_x_discrete(limits = c("Ecomorphotype",
"Effect Size",
"Effect Type"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Strength of Evidence`)) + #
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1.5)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT-EfSiz-EfTyp_Col-SoEv.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 3bar: EMT, EfSiz, SoEv, EfTyp=colour ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(Ecomorphotype, `Effect Type`, `Effect Size`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = Ecomorphotype,
axis2 = `Effect Size`,
axis3 = `Strength of Evidence`,
y = Count)
) +
scale_x_discrete(limits = c("Ecomorphotype",
"Effect Size",
"Strength of Evidence"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Effect Type`)) + #
scale_fill_manual(values = c("red", "dodgerblue4", "darkorchid4", "darkorange1", "goldenrod3", "green3")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT-EfSiz-SoEv_Col-EfTyp.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 3bar: EfTyp, EfSiz, SoEv, EMT=colour ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(Ecomorphotype, `Effect Type`, `Effect Size`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = `Effect Type`,
axis2 = `Effect Size`,
axis3 = `Strength of Evidence`,
y = Count)
) +
scale_x_discrete(limits = c("Effect Type",
"Effect Size",
"Strength of Evidence"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = Ecomorphotype)) + #
# scale_fill_manual(values = c("red", "dodgerblue4", "darkorchid4", "darkorange1", "goldenrod3", "green3")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EfTyp-EfSiz-SoEv_Col-EMT.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 2bar: EfTyp, EMT, EfSiz=colour ####
# SoEv,
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(`Effect Type`, Ecomorphotype, `Effect Size`) %>%
summarise(Count = n()),
aes(axis1 = `Effect Type`,
axis2 = Ecomorphotype,
y = Count)
) +
scale_x_discrete(limits = c("Effect Type",
"Ecomorphotype"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Effect Size`)) + #
# scale_fill_manual(values = c("red", "dodgerblue4", "darkorchid4", "darkorange1", "goldenrod3", "green3")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EfTyp-EMT_Col-EfSiz.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 2bar: EfTyp, EMT, SoEv=colour ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(`Effect Type`, Ecomorphotype, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = `Effect Type`,
axis2 = Ecomorphotype,
y = Count)
) +
scale_x_discrete(limits = c("Effect Type",
"Ecomorphotype"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Strength of Evidence`)) + #
# scale_fill_manual(values = c("red", "dodgerblue4", "darkorchid4", "darkorange1", "goldenrod3", "green3")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EfTyp-EMT_Col-SoEv.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 2bar: EMT, EfTyp, EfSiz=colour ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(Ecomorphotype, `Effect Type`, `Effect Size`) %>%
summarise(Count = n()),
aes(axis1 = Ecomorphotype,
axis2 = `Effect Type`,
y = Count)
) +
scale_x_discrete(limits = c("Ecomorphotype",
"Effect Type"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Effect Size`)) + #
# scale_fill_manual(values = c("red", "dodgerblue4", "darkorchid4", "darkorange1", "goldenrod3", "green3")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT-EfTyp_Col-EfSiz.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 2bar: EMT, EfTyp, col=SoEv ####
ggplot(data = emt %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(Ecomorphotype, `Effect Type`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = Ecomorphotype,
axis2 = `Effect Type`,
y = Count)
) +
scale_x_discrete(limits = c("Ecomorphotype",
"Effect Type"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Strength of Evidence`)) + #
# scale_fill_manual(values = c("red", "dodgerblue4", "darkorchid4", "darkorange1", "goldenrod3", "green3")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
# ggtitle("passengers on the maiden voyage of the Titanic",
# "stratified by demographics and survival") +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT-EfTyp_Col-SoEv.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 2bar, PerEMT: EfTyp, EfSiz, col=SoEv####
for (EMT in levels(emt$Ecomorphotype)) {
ggplot(data = emt %>%
filter(Ecomorphotype == EMT) %>%
# create a Freq column which is a count of all rows with the same attributes for all other columns
group_by(`Effect Type`, `Effect Size`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = `Effect Type`,
axis2 = `Effect Size`,
y = Count)
) +
scale_x_discrete(limits = c("Effect Type",
"Effect Size"),
expand = c(.2, .05)) +
# xlab("Demographic") +
geom_alluvium(aes(fill = `Strength of Evidence`)) + #
# scale_fill_manual(values = c("red", "dodgerblue4", "darkorchid4", "darkorange1", "goldenrod3", "green3")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
ggtitle(EMT) +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, size = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank()
) # removed whitespace buffer around legend boxes which is nice
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_", EMT, "_EfTyp-EfSize_Col-SoEv.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
}
# 2bar, EMT+EfSz, EfTyp, col=SoEv####
ggplot(data = emt %>%
# join EMT & EffectSize
unite(col = "EMT-EfSz", c(Ecomorphotype, `Effect Size`), sep = ": ") %>%
group_by(`EMT-EfSz`, `Effect Type`, `Strength of Evidence`) %>%
summarise(Count = n()),
aes(axis1 = `EMT-EfSz`,
axis2 = `Effect Type`,
y = Count)) +
scale_x_discrete(limits = c("EMT: Effect Size", "Effect Type"), expand = c(.2, .05)) +
geom_alluvium(aes(fill = `Strength of Evidence`)) + #
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, linewidth = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank())
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT.EfSz-EfTyp_Col-SoEv.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# 2bar, EMT+SoEv, EfTyp, col=EfSz####
ggplot(data = emt %>%
# join EMT & EffectSize
unite(col = "EMT-SoEv", c(Ecomorphotype, `Strength of Evidence`), sep = ": ") %>%
group_by(`EMT-SoEv`, `Effect Type`, `Effect Size`) %>%
summarise(Count = n()),
aes(axis1 = `EMT-SoEv`,
axis2 = `Effect Type`,
y = Count)) +
scale_x_discrete(limits = c("EMT: Strength of Evidence", "Effect Type"), expand = c(.2, .05)) +
geom_alluvium(aes(fill = `Effect Size`)) +
scale_fill_manual(values = c("black", "blue", "cadetblue1")) +
geom_stratum() +
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # what does this do?
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, linewidth = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
legend.key = element_blank())
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_EMT.SoEv-EfTyp_Col-EfSz.png"),
plot = last_plot(), device = "png", path = "",
scale = 2, width = 10, height = 4, units = "in", dpi = 300, limitsize = TRUE)
# Archipelagic NA SoE: Tinker et al. 2016, Moxley et al. 2019 [12], and Hughes et al. 2013, Hughes et al. 2019 [15]
# 2023-02-22 FunctionalGroup+Realm####
# replace EMT with this.
emt <- read_sheet("https://docs.google.com/spreadsheets/d/1dNDEUENa4M1__VNksolw8Or9ysPutEYWMTgZJ-qOe9I/edit#gid=0") %>%
# select cols of interest
select(Ecomorphotype, `Functional Group`, Realm, Ecosystem, `Ocean Basin`, `Top-down: Direct Predation: Effect Size`:`Bottom-up: Nutrient Vector Storage: Excretion & Egestion: Strength of Evidence`) %>%
# remove NA emt rows
drop_na(`Functional Group`, Realm) %>%
# convert High Medium Low to 3 2 1, keep NAs
mutate(across(
.cols = `Top-down: Direct Predation: Effect Size`:`Bottom-up: Nutrient Vector Storage: Excretion & Egestion: Strength of Evidence`,
~ dplyr::case_when(
. == "High" ~ 3,
. == "Medium" ~ 2,
. == "Low" ~ 1
)
)) %>%
# remove rays
filter(!Ecomorphotype %in% c("Aquilopelagic", "Rajobenthic")) %>%
# Need to parse each row out into multi rows when they have more than 1 effect type/SoE combo
# Need 1 column each for effect type, SoE, EMT.
tidyr::pivot_longer(cols = contains("Effect Size"),
names_to = "Effect Type",
values_to = "Effect Size") %>%
tidyr::pivot_longer(cols = contains("Strength of Evidence"),
names_to = "Effect Type2",
values_to = "Strength of Evidence") %>%
# remove ": Effect Size" & ": Strength of Evidence"
mutate(`Effect Type` = str_remove_all(string = `Effect Type`, pattern = ": Effect Size"),
`Effect Type2` = str_remove_all(string = `Effect Type2`, pattern = ": Strength of Evidence"),
# double pivot_longer creates n=effecttype^2 rows, all permutations of both. Collapse to where both match
EffectTypesMatch = ifelse(`Effect Type` == `Effect Type2`, TRUE, FALSE),
# also want to remove when both are NA later
BothNA = ifelse(is.na(`Effect Size`) & is.na(`Strength of Evidence`), TRUE, FALSE),
# for plotting, make integer = discrete
`Effect Size` = as.integer(`Effect Size`),
`Strength of Evidence` = as.integer(`Strength of Evidence`),
# Edit Functional Group names
`Functional Group` = case_match(`Functional Group`,
"Apex sharks" ~ "Macropredatory sharks",
"Meso sharks / baby apex sharks" ~ "Mesopredatory sharks"),
# Edit Effect Type Group names
`Effect Type` = case_match(`Effect Type`,
"Bottom-up: Nutrient Vector Storage: Sharks as Food" ~ "BU:NVS:SAF",
"Bottom-up: Nutrient Vector Storage: Excretion & Egestion" ~ "BU:NVS:EAE",
.default = `Effect Type`),
# so the legend order is logical
`Effect Type` = ordered(`Effect Type`,
levels = c("Top-down: Direct Predation",
"Top-down: Risk Effects",
"Top-down: Trophic Cascade",
"Competition",
"BU:NVS:SAF",
"BU:NVS:EAE"))) %>%
# filter for only those that match, remove permutation dupes
filter(EffectTypesMatch,
# remove where both are NA
!BothNA) %>%
unite(col = "FnGpRealm", c(`Functional Group`, Realm), sep = ": ") %>%
# # remove temp columns
# select(!c(`Effect Type2`, EffectTypesMatch, BothNA)) %>%
# keep only columns needed for this plot
select(FnGpRealm, `Effect Type`, `Effect Size`, `Strength of Evidence`) %>%
# make (ordered) factors for all but Freq. Effect type already done above.
mutate(FnGpRealm = ordered(FnGpRealm, levels = c("Macropredatory sharks: Inshore/Shelf",
"Macropredatory sharks: Pelagic",
"Mesopredatory sharks: Inshore/Shelf",
"Mesopredatory sharks: Pelagic")),
`Effect Size` = ordered(`Effect Size`, levels = c(3, 2, 1)),
`Strength of Evidence` = ordered(`Strength of Evidence`, levels = c(3, 2, 1))) %T>% # note matrittr tee pipe
saveRDS(file = paste0(saveloc, today(), "_EMTdataFnGpRealm.rds"))
# 2bar, FnGpRealm, EfTyp, col=EfSz [usethis]####
ggplot(data = emt %>%
mutate(FnGpRealm = stringr::str_replace_all(string = FnGpRealm,
pattern = "Macropredatory sharks",
replacement = "Ma"),
FnGpRealm = stringr::str_replace_all(string = FnGpRealm,
pattern = "Mesopredatory sharks",
replacement = "Me")) %>%
tidyr::drop_na(`Effect Type`) %>% # remove leftover row
# 2023-10-26 edit labels, FnGpRealm, Mesopredatory sharks:
group_by(`FnGpRealm`, `Effect Type`, `Effect Size`) %>%
summarise(Count = n()),
aes(axis1 = `FnGpRealm`,
axis2 = `Effect Type`,
y = Count)) +
scale_x_discrete(limits = c("Functional Group: Realm", "Effect Type"), expand = c(.2, .05)) +
geom_alluvium(mapping = aes(fill = `Effect Size`),
alpha = 0.75 # default is 1/2
) +
scale_fill_manual(values = c(rgb(0.11, 0.62, 0.47),
rgb(0.46, 0.44, 0.7),
rgb(0.85, 0.37, 0.01))) +
# geom_flow() + #just makes everything alpha & greyish?
# geom_stratum(width = 1/12, fill = "white", color = "grey") +
geom_stratum(width = 1/3) + # default colour black, fill white, width 1/3
# geom_label(stat = "stratum", aes(label = after_stat(stratum))) + # label puts in balloon,
geom_text(stat = "stratum", aes(label = after_stat(stratum))) + # text just overlays the text. lebel = stringr::str_wrap(after_stat(stratum), 5)
# coord_flip() +
# ggtitle() +
theme_minimal() %+replace% theme(
axis.text = element_text(size = rel(1.5)),
axis.title = element_text(size = rel(2)),
legend.text = element_text(size = rel(1)),
legend.title = element_text(size = rel(1.5)),
# legend.position = "none", #to hide legend & put in caption if desired
legend.title.align = 0, # otherwise effect type title centre aligned for some reason
plot.background = element_rect(fill = "white", colour = "grey50"), # white background
strip.text.x = element_text(size = rel(2)),
panel.border = element_rect(colour = "black", fill = NA, linewidth = 1),
legend.spacing.x = unit(0, "cm"), # compress spacing between legend items, this is min
legend.background = element_blank(),
panel.background = element_rect(fill = "white", colour = "grey50"),
panel.grid = element_line(colour = "grey90"),
panel.grid.major.x = element_blank(),
legend.key = element_blank())
# ended up blanking out "Ma: Pelagic" in Gimp and replacing with asterix.
# shrink axes width: geom_stratum(width) but then lines expand past it
# todo: wrap text in strata/axes. Turn sideways? geom_text(angle = 90). Font: family = "Times New Roman"
## could wrap the text itself by addling a line break to specific categories. paste(strwrap(x, ...), collapse = "\n")
# remove dead space outside plot - margin?
# nicer colours
# remove y axis labels & title??
saveloc <- "C:/Users/simon/Documents/Si Work/PostDoc Work/FIU/Ecological Importance of Sharks Workshop/Papers Prep/2022 Science/1_EROS" # windows
ggsave(paste0(saveloc, today(), "_SankeyAlluvial_FnGp.Realm-EfTyp_Col-EfSz.png"),
plot = last_plot(), device = "png", path = "",
scale = 2,
width = 4, # 6
height = 6, # 4
units = "in", dpi = 300, limitsize = TRUE)
tmp <- emt %>%
mutate(FnGpRealm = stringr::str_replace_all(string = FnGpRealm,
pattern = "Macropredatory sharks",
replacement = "Ma"),
FnGpRealm = stringr::str_replace_all(string = FnGpRealm,
pattern = "Mesopredatory sharks",
replacement = "Me")) %>%
tidyr::drop_na(`Effect Type`) %>% # remove leftover row
# 2023-10-26 edit labels, FnGpRealm, Mesopredatory sharks:
group_by(`FnGpRealm`, `Effect Type`, `Effect Size`) %>%
summarise(Count = n())
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