Bird Tagging Visualizations
Charlie Wiebe
library(ggplot2)
library(dplyr)##
## Attaching package: 'dplyr'## The following objects are masked from 'package:stats':
##
## filter, lag## The following objects are masked from 'package:base':
##
## intersect, setdiff, setequal, unionlibrary(tidyr)
library(readr)BACKPACK VISUALIZATIONS ###
backpack <- read_csv("/Users/Shared/Tagging/Final/backpack.csv")## Rows: 32 Columns: 17
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (16): species, device_type, material, why_material, methods, why_methods...
## dbl (1): id
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.new_orders <- read_csv("/Users/Shared/Tagging/Final/new_orders.csv")## Rows: 27 Columns: 2
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (2): original_order, new_order
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.sep_species <- separate_rows(backpack,species,sep=",")
sep_species <- merge(x=sep_species,y=new_orders,by.x="species",by.y="original_order")
sep_materials <- separate_rows(sep_species,material,sep=", ")
sep_materials <- sep_materials %>% filter(material != 'leather breast pad to hold ribbons in an \"X\"', material != 'dental floss for sewing knots')
ggplot(data=count(sep_materials,material),aes(x=material,y=(n/nrow(sep_species))))+
geom_col()+
ggtitle(sprintf("Material Use Frequencies When Tagging Using Backpacks, n=%s",nrow(sep_species)))+
ylab("frequency")
#---
sep_methods <- separate_rows(sep_species,methods,sep=", ")
ggplot(data=count(sep_methods,methods), aes(x=methods,y=(n/nrow(sep_species))))+
geom_col()+
ggtitle(sprintf("Method Use Frequencies When Tagging Using Backpacks, n=%s",nrow(sep_species)))+
ylab("frequency")
### IMPACT LEVELS OF DIFFERENT MATERIALS
for (material_alt in unique(sep_materials$material)) {
print(ggplot(data=count(filter(sep_materials,material==material_alt),impact_level),aes(x=impact_level,y=n/nrow(filter(sep_materials,material==material_alt))))+
geom_col()+
ggtitle(sprintf("Impact Levels of Using %s While Attaching Backpacks, n=%s",material_alt,nrow(filter(sep_materials,material==material_alt))))+
ylab("frequency")+
xlab("impact level"))}
print("Original Orders:")## [1] "Original Orders:"table(sep_materials$species,sep_materials$material)##
## Elastic cord Glue Monofilament Neoprene
## anseriformes 1 0 0 0
## cathartiformes 0 3 0 1
## charadriiformes...gulls.and.terns 0 0 0 1
## falconiformes 0 2 1 2
## gruiformes 0 0 1 1
## passeriformes 0 0 0 0
## phoenicopteriformes 0 0 0 0
## podicipediformes 0 1 0 1
## strigiformes 0 0 0 2
## suliformes 0 0 0 0
##
## Ribbon Spectra Teflon Thread
## anseriformes 0 0 3 0
## cathartiformes 1 0 4 3
## charadriiformes...gulls.and.terns 1 0 1 0
## falconiformes 0 2 14 1
## gruiformes 0 1 2 0
## passeriformes 0 0 1 0
## phoenicopteriformes 0 0 1 0
## podicipediformes 1 0 1 0
## strigiformes 0 2 6 0
## suliformes 0 0 1 0impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_materials$species)) {
order_data_materials <- filter(sep_materials, species==order_alt)
order_data_materials$impact_level <- factor(order_data_materials$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
order_data_methods <- filter(sep_methods, species==order_alt)
order_data_methods$impact_level <- factor(order_data_methods$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_materials$impact_level,order_data_materials$material))
print(table(order_data_methods$impact_level,order_data_methods$methods))
print(order_alt)}##
## Elastic cord Teflon
## Very high 0 0
## High 0 0
## Modest 1 2
## Low Impact 0 0
## No impact 0 1
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 2 2 0 2
## Low Impact 0 0 0 0
## No impact 0 1 1 0
## Not sure 0 0 0 0
## N/A 0 0 0 0
## [1] "anseriformes"
##
## Glue Neoprene Ribbon Teflon Thread
## Very high 0 0 0 0 0
## High 0 0 0 0 0
## Modest 0 0 0 1 0
## Low Impact 1 0 1 1 1
## No impact 1 1 0 1 1
## Not sure 1 0 0 1 1
## N/A 0 0 0 0 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 1 1 1 1
## Low Impact 1 1 0 1
## No impact 0 1 1 1
## Not sure 0 1 1 1
## N/A 0 0 0 0
## [1] "cathartiformes"
##
## Neoprene Ribbon Teflon
## Very high 0 0 0
## High 0 0 0
## Modest 1 1 1
## Low Impact 0 0 0
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 1 1 1 1
## Low Impact 0 0 0 0
## No impact 0 0 0 0
## Not sure 0 0 0 0
## N/A 0 0 0 0
## [1] "charadriiformes...gulls.and.terns"
##
## Glue Monofilament Neoprene Spectra Teflon Thread
## Very high 0 0 0 0 0 0
## High 0 0 0 0 0 0
## Modest 1 1 1 1 2 0
## Low Impact 0 0 1 0 7 0
## No impact 0 0 0 1 4 0
## Not sure 1 0 0 0 1 1
## N/A 0 0 0 0 0 0
##
## Crimp Bead Glue Knot Sew Surgical
## Very high 0 0 0 0 0
## High 0 0 0 0 0
## Modest 1 1 0 1 0
## Low Impact 5 4 3 5 0
## No impact 2 2 4 4 1
## Not sure 0 1 1 1 0
## N/A 0 0 0 0 0
## [1] "falconiformes"
##
## Monofilament Neoprene Spectra Teflon
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 0 0 0 0
## Low Impact 0 0 0 1
## No impact 1 1 1 1
## Not sure 0 0 0 0
## N/A 0 0 0 0
##
## Glue Knot Sew
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 0 1 1
## No impact 1 1 1
## Not sure 0 0 0
## N/A 0 0 0
## [1] "gruiformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 0
## Not sure 0
## N/A 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 0 0 0 0
## Low Impact 1 1 1 1
## No impact 0 0 0 0
## Not sure 0 0 0 0
## N/A 0 0 0 0
## [1] "passeriformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
##
## Crimp Bead Knot Sew
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 0 0 0
## No impact 1 1 1
## Not sure 0 0 0
## N/A 0 0 0
## [1] "phoenicopteriformes"
##
## Glue Neoprene Ribbon Teflon
## Very high 1 1 1 1
## High 0 0 0 0
## Modest 0 0 0 0
## Low Impact 0 0 0 0
## No impact 0 0 0 0
## Not sure 0 0 0 0
## N/A 0 0 0 0
##
## Glue Knot Sew
## Very high 1 1 1
## High 0 0 0
## Modest 0 0 0
## Low Impact 0 0 0
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
## [1] "podicipediformes"
##
## Neoprene Spectra Teflon
## Very high 0 0 0
## High 0 0 0
## Modest 1 0 1
## Low Impact 1 1 4
## No impact 0 1 1
## Not sure 0 0 0
## N/A 0 0 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 0 1 1 1
## Low Impact 3 4 4 3
## No impact 1 1 0 1
## Not sure 0 0 0 0
## N/A 0 0 0 0
## [1] "strigiformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
##
## Crimp Bead Knot
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 0 0
## No impact 1 1
## Not sure 0 0
## N/A 0 0
## [1] "suliformes"print("New Orders:")## [1] "New Orders:"table(sep_materials$new_order,sep_materials$material)##
## Elastic cord Glue Monofilament Neoprene Ribbon Spectra
## Accipitriformes 0 5 1 5 1 4
## Anseriformes 1 0 0 0 0 0
## Charadriiformes 0 0 0 1 1 0
## Gruiformes 0 0 1 1 0 1
## Passeriformes 0 0 0 0 0 0
## Pelecaniformes 0 0 0 0 0 0
## Podicipediformes 0 1 0 1 1 0
## Suliformes 0 0 0 0 0 0
##
## Teflon Thread
## Accipitriformes 24 4
## Anseriformes 3 0
## Charadriiformes 1 0
## Gruiformes 2 0
## Passeriformes 1 0
## Pelecaniformes 1 0
## Podicipediformes 1 0
## Suliformes 1 0impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_materials$new_order)) {
order_data_materials <- filter(sep_materials, new_order==order_alt)
order_data_materials$impact_level <- factor(order_data_materials$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
order_data_methods <- filter(sep_methods, new_order==order_alt)
order_data_methods$impact_level <- factor(order_data_methods$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_materials$impact_level,order_data_materials$material))
print(table(order_data_methods$impact_level,order_data_methods$methods))
print(order_alt)}##
## Elastic cord Teflon
## Very high 0 0
## High 0 0
## Modest 1 2
## Low Impact 0 0
## No impact 0 1
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 2 2 0 2
## Low Impact 0 0 0 0
## No impact 0 1 1 0
## Not sure 0 0 0 0
## N/A 0 0 0 0
## [1] "Anseriformes"
##
## Glue Monofilament Neoprene Ribbon Spectra Teflon Thread
## Very high 0 0 0 0 0 0 0
## High 0 0 0 0 0 0 0
## Modest 1 1 2 0 1 4 0
## Low Impact 1 0 2 1 1 12 1
## No impact 1 0 1 0 2 6 1
## Not sure 2 0 0 0 0 2 2
## N/A 0 0 0 0 0 0 0
##
## Crimp Bead Glue Knot Sew Surgical
## Very high 0 0 0 0 0
## High 0 0 0 0 0
## Modest 2 3 2 3 0
## Low Impact 9 9 7 9 0
## No impact 3 4 5 6 1
## Not sure 0 2 2 2 0
## N/A 0 0 0 0 0
## [1] "Accipitriformes"
##
## Neoprene Ribbon Teflon
## Very high 0 0 0
## High 0 0 0
## Modest 1 1 1
## Low Impact 0 0 0
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 1 1 1 1
## Low Impact 0 0 0 0
## No impact 0 0 0 0
## Not sure 0 0 0 0
## N/A 0 0 0 0
## [1] "Charadriiformes"
##
## Monofilament Neoprene Spectra Teflon
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 0 0 0 0
## Low Impact 0 0 0 1
## No impact 1 1 1 1
## Not sure 0 0 0 0
## N/A 0 0 0 0
##
## Glue Knot Sew
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 0 1 1
## No impact 1 1 1
## Not sure 0 0 0
## N/A 0 0 0
## [1] "Gruiformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 0
## Not sure 0
## N/A 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 0 0 0 0
## Low Impact 1 1 1 1
## No impact 0 0 0 0
## Not sure 0 0 0 0
## N/A 0 0 0 0
## [1] "Passeriformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
##
## Crimp Bead Knot Sew
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 0 0 0
## No impact 1 1 1
## Not sure 0 0 0
## N/A 0 0 0
## [1] "Pelecaniformes"
##
## Glue Neoprene Ribbon Teflon
## Very high 1 1 1 1
## High 0 0 0 0
## Modest 0 0 0 0
## Low Impact 0 0 0 0
## No impact 0 0 0 0
## Not sure 0 0 0 0
## N/A 0 0 0 0
##
## Glue Knot Sew
## Very high 1 1 1
## High 0 0 0
## Modest 0 0 0
## Low Impact 0 0 0
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
## [1] "Podicipediformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
##
## Crimp Bead Knot
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 0 0
## No impact 1 1
## Not sure 0 0
## N/A 0 0
## [1] "Suliformes"### IMPACT LEVELS OF DIFFERENT METHODS
for (methods_alt in unique(sep_methods$methods)) {
print(ggplot(data=count(filter(sep_methods,methods==methods_alt),impact_level),aes(x=impact_level,y=n/nrow(filter(sep_methods,methods==methods_alt))))+
geom_col()+
ggtitle(sprintf("Impact Levels of Using %s While Attaching Backpacks, n=%s",methods_alt,nrow(filter(sep_methods,methods==methods_alt))))+
ylab("frequency")+
xlab("impact level"))}
### IMPACT LEVELS OF DIFFERENT MATERIALS BY EFFECTS
abrasion <- group_by(sep_materials,abrasion,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'abrasion'. You can override using the
## `.groups` argument.callous <- group_by(sep_materials,callous,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'callous'. You can override using the
## `.groups` argument.feather_loss <- group_by(sep_materials,feather_loss,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'feather_loss'. You can override using the
## `.groups` argument.fell_off <- group_by(sep_materials,fell_off,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'fell_off'. You can override using the
## `.groups` argument.strangulation <- group_by(sep_materials,strangulation,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'strangulation'. You can override using the
## `.groups` argument.flight_impairment <- group_by(sep_materials,flight_impairment,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'flight_impairment'. You can override using
## the `.groups` argument.immobilization <- group_by(sep_materials,immobilization,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'immobilization'. You can override using
## the `.groups` argument.other <- group_by(sep_materials,other,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'other'. You can override using the
## `.groups` argument.# Orders the effect frequencies
abrasion$abrasion <- factor(abrasion$abrasion, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
callous$callous <- factor(callous$callous, levels=c('Often (41-80%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
feather_loss$feather_loss <- factor(feather_loss$feather_loss, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
fell_off$fell_off <- factor(fell_off$fell_off, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
strangulation$strangulation <- factor(strangulation$strangulation, levels=c('Rare (<10%)','Never','NA','Unknown','Not sure'))
flight_impairment$flight_impairment <- factor(flight_impairment$flight_impairment, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
immobilization$immobilization <- factor(immobilization$immobilization, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
other$other <- factor(other$other, levels=c('Always (>80%)','Rare (<10%)','Never','NA','N/A','Not sure'))
###
# Creates labels for abrasion plot along with sample sizes
abrasion_vector <- c()
for (material_alt in sort(unique(abrasion$material))) {
abrasion_vector <- c(abrasion_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)),sep="\n"))
}
callous_vector <- c()
for (material_alt in sort(unique(callous$material))) {
callous_vector <- c(callous_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
feather_loss_vector <- c()
for (material_alt in sort(unique(feather_loss$material))) {
feather_loss_vector <- c(feather_loss_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
fell_off_vector <- c()
for (material_alt in sort(unique(fell_off$material))) {
fell_off_vector <- c(fell_off_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)),sep="\n"))
}
strangulation_vector <- c()
for (material_alt in sort(unique(strangulation$material))) {
strangulation_vector <- c(strangulation_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
flight_impairment_vector <- c()
for (material_alt in sort(unique(flight_impairment$material))) {
flight_impairment_vector <- c(flight_impairment_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
immobilization_vector <- c()
for (material_alt in sort(unique(immobilization$material))) {
immobilization_vector <- c(immobilization_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
other_vector <- c()
for (material_alt in sort(unique(other$material))) {
other_vector <- c(other_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
ggplot(data=abrasion, aes(fill=abrasion, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Abrasian Frequencies Using Backpacks By Material") +
scale_x_discrete(labels=abrasion_vector)
ggplot(data=callous, aes(fill=callous, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Callous Frequencies Using Backpacks By Material") +
scale_x_discrete(labels=callous_vector)
ggplot(data=feather_loss, aes(fill=feather_loss, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Feather Loss Frequencies Using Backpacks By Material") +
scale_x_discrete(labels=feather_loss_vector)
ggplot(data=fell_off, aes(fill=fell_off, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Frequencies Of Backpacks Falling Off By Material")) +
scale_x_discrete(labels=fell_off_vector)
ggplot(data=strangulation, aes(fill=strangulation, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Strangulation Frequencies Using Backpacks By Material")) +
scale_x_discrete(labels=strangulation_vector)
ggplot(data=flight_impairment, aes(fill=flight_impairment, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Flight Impairment Frequencies Using Backpacks By Material")) +
scale_x_discrete(labels=flight_impairment_vector)
ggplot(data=immobilization, aes(fill=immobilization, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Immobilization Frequencies Using Backpacks By Material")) +
scale_x_discrete(labels=immobilization_vector)
ggplot(data=other, aes(fill=other, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Other Frequencies Using Backpacks By Material")) +
scale_x_discrete(labels=other_vector)
# IMPACT LEVELS OF DIFFERENT EFFECTS BY METHODS
abrasion <- group_by(sep_methods,abrasion,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'abrasion'. You can override using the
## `.groups` argument.callous <- group_by(sep_methods,callous,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'callous'. You can override using the
## `.groups` argument.feather_loss <- group_by(sep_methods,feather_loss,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'feather_loss'. You can override using the
## `.groups` argument.fell_off <- group_by(sep_methods,fell_off,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'fell_off'. You can override using the
## `.groups` argument.strangulation <- group_by(sep_methods,strangulation,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'strangulation'. You can override using the
## `.groups` argument.flight_impairment <- group_by(sep_methods,flight_impairment,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'flight_impairment'. You can override using
## the `.groups` argument.immobilization <- group_by(sep_methods,immobilization,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'immobilization'. You can override using
## the `.groups` argument.other <- group_by(sep_methods,other,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'other'. You can override using the
## `.groups` argument.# Orders the effect frequencies
abrasion$abrasion <- factor(abrasion$abrasion, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
callous$callous <- factor(callous$callous, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
feather_loss$feather_loss <- factor(feather_loss$feather_loss, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
fell_off$fell_off <- factor(fell_off$fell_off, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
strangulation$strangulation <- factor(strangulation$strangulation, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
flight_impairment$flight_impairment <- factor(flight_impairment$flight_impairment, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
immobilization$immobilization <- factor(immobilization$immobilization, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
other$other <- factor(other$other, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
abrasion_vector <- c()
for (method_alt in sort(unique(abrasion$methods))) {
abrasion_vector <- c(abrasion_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)),sep="\n"))
}
callous_vector <- c()
for (method_alt in sort(unique(callous$methods))) {
callous_vector <- c(callous_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
feather_loss_vector <- c()
for (method_alt in sort(unique(feather_loss$methods))) {
feather_loss_vector <- c(feather_loss_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
fell_off_vector <- c()
for (method_alt in sort(unique(fell_off$methods))) {
fell_off_vector <- c(fell_off_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)),sep="\n"))
}
strangulation_vector <- c()
for (method_alt in sort(unique(strangulation$methods))) {
strangulation_vector <- c(strangulation_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
flight_impairment_vector <- c()
for (method_alt in sort(unique(flight_impairment$methods))) {
flight_impairment_vector <- c(flight_impairment_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
immobilization_vector <- c()
for (method_alt in sort(unique(immobilization$methods))) {
immobilization_vector <- c(immobilization_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
other_vector <- c()
for (method_alt in sort(unique(other$methods))) {
other_vector <- c(other_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
ggplot(data=abrasion, aes(fill=abrasion, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Abrasian Frequencies Using Backpacks By Method") +
scale_x_discrete(labels=abrasion_vector)
ggplot(data=callous, aes(fill=callous, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Callous Frequencies Using Backpacks By Method") +
scale_x_discrete(labels=callous_vector)
ggplot(data=feather_loss, aes(fill=feather_loss, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Feather Loss Frequencies Using Backpacks By Method") +
scale_x_discrete(labels=feather_loss_vector)
ggplot(data=fell_off, aes(fill=fell_off, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Frequencies Of Backpacks Falling Off By Method")) +
scale_x_discrete(labels=fell_off_vector)
ggplot(data=strangulation, aes(fill=strangulation, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Strangulation Frequencies Using Backpacks By Method")) +
scale_x_discrete(labels=strangulation_vector)
ggplot(data=flight_impairment, aes(fill=flight_impairment, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Flight Impairment Frequencies Using Backpacks By Method")) +
scale_x_discrete(labels=flight_impairment_vector)
ggplot(data=immobilization, aes(fill=immobilization, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Immobilization Frequencies Using Backpacks By Method")) +
scale_x_discrete(labels=immobilization_vector)
ggplot(data=other, aes(fill=other, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Other Frequencies Using Backpacks By Method")) +
scale_x_discrete(labels=other_vector)
BREAST-BODY HARNESS VISUALIZATIONS ###
breast_body <- read_csv("/Users/Shared/Tagging/Final/breast_body.csv")## Rows: 18 Columns: 17
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (16): species, device_type, material, why_material, methods, why_methods...
## dbl (1): id
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.sep_species <- separate_rows(breast_body,species,sep=",")
sep_species <- merge(x=sep_species,y=new_orders,by.x="species",by.y="original_order")
sep_materials <- separate_rows(sep_species,material,sep=", ")
sep_materials <- sep_materials %>% filter(material != 'steel leader passed through pvc tubing (i.e." "Dwyer 1972)', material != 'tubing provided with transmitter (PVC)')
ggplot(data=count(sep_materials,material),aes(x=material,y=(n/nrow(sep_species))))+
geom_col()+
ggtitle(sprintf("Material Use Frequencies When Tagging Using Breast-Body Harnesses, n=%s",nrow(sep_species)))+
ylab("frequency")
#---
sep_methods <- separate_rows(sep_species,methods,sep=", ")
ggplot(data=count(sep_methods,methods), aes(x=methods,y=(n/nrow(sep_species))))+
geom_col()+
ggtitle(sprintf("Method Use Frequencies When Tagging Using Breast-Body Harnesses, n=%s",nrow(sep_species)))+
ylab("frequency")
### IMPACT LEVELS OF DIFFERENT MATERIALS
for (material_alt in unique(sep_materials$material)) {
print(ggplot(data=count(filter(sep_materials,material==material_alt),impact_level),aes(x=impact_level,y=n/nrow(filter(sep_materials,material==material_alt))))+
geom_col()+
ggtitle(sprintf("Impact Levels of Using %s While Attaching Breast-Body Harnesses, n=%s",material_alt,nrow(filter(sep_materials,material==material_alt))))+
ylab("frequency")+
xlab("impact level"))}
print("Original Orders:")## [1] "Original Orders:"table(sep_materials$species,sep_materials$material)##
## Dwyer 1972) Elastic cord Glue Neoprene
## anseriformes 1 3 2 1
## charadriiformes...gulls.and.terns 0 0 1 1
## passeriformes 0 0 0 0
## pelecaniformes 0 0 1 1
## strigiformes 0 0 0 0
## suliformes 0 0 0 0
##
## Ribbon Spectra
## anseriformes 2 1
## charadriiformes...gulls.and.terns 0 0
## passeriformes 0 1
## pelecaniformes 1 0
## strigiformes 0 1
## suliformes 0 0
##
## steel leader passed through pvc tubing (i.e.
## anseriformes 1
## charadriiformes...gulls.and.terns 0
## passeriformes 0
## pelecaniformes 0
## strigiformes 0
## suliformes 0
##
## Teflon
## anseriformes 8
## charadriiformes...gulls.and.terns 1
## passeriformes 1
## pelecaniformes 0
## strigiformes 1
## suliformes 1impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_materials$species)) {
order_data_materials <- filter(sep_materials, species==order_alt)
order_data_materials$impact_level <- factor(order_data_materials$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
order_data_methods <- filter(sep_methods, species==order_alt)
order_data_methods$impact_level <- factor(order_data_methods$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_materials$impact_level,order_data_materials$material))
print(table(order_data_methods$impact_level,order_data_methods$methods))
print(order_alt)}##
## Dwyer 1972) Elastic cord Glue Neoprene Ribbon Spectra
## Very high 0 0 0 0 0 0
## High 0 0 0 0 0 0
## Modest 0 1 2 1 1 0
## Low Impact 1 2 0 0 1 0
## No impact 0 0 0 0 0 1
## Not sure 0 0 0 0 0 0
## N/A 0 0 0 0 0 0
##
## steel leader passed through pvc tubing (i.e. Teflon
## Very high 0 0
## High 0 2
## Modest 0 3
## Low Impact 1 3
## No impact 0 0
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 1 2 3 0
## Modest 1 3 3 0
## Low Impact 3 4 2 2
## No impact 1 1 1 0
## Not sure 0 0 0 0
## N/A 0 0 0 0
## [1] "anseriformes"
##
## Glue Neoprene Teflon
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 0 0 0
## No impact 0 0 0
## Not sure 1 1 1
## N/A 0 0 0
##
## Glue Knot
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 0 0
## No impact 0 0
## Not sure 1 1
## N/A 0 0
## [1] "charadriiformes...gulls.and.terns"
##
## Spectra Teflon
## Very high 0 0
## High 0 0
## Modest 1 1
## Low Impact 0 0
## No impact 0 0
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead Sew
## Very high 0 0
## High 0 0
## Modest 1 1
## Low Impact 0 0
## No impact 0 0
## Not sure 0 0
## N/A 0 0
## [1] "passeriformes"
##
## Glue Neoprene Ribbon
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 0 0 0
## No impact 0 0 0
## Not sure 1 1 1
## N/A 0 0 0
##
## Glue Knot
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 0 0
## No impact 0 0
## Not sure 1 1
## N/A 0 0
## [1] "pelecaniformes"
##
## Spectra Teflon
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 0 0
## No impact 1 1
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 0 0 0 0
## Low Impact 0 0 0 0
## No impact 1 1 1 1
## Not sure 0 0 0 0
## N/A 0 0 0 0
## [1] "strigiformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 0
## Not sure 1
## N/A 0
##
## Crimp Bead Glue Knot
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 0 0 0
## No impact 0 0 0
## Not sure 1 1 1
## N/A 0 0 0
## [1] "suliformes"print("New Orders:")## [1] "New Orders:"table(sep_materials$new_order,sep_materials$material)##
## Dwyer 1972) Elastic cord Glue Neoprene Ribbon Spectra
## Accipitriformes 0 0 0 0 0 1
## Anseriformes 1 3 2 1 2 1
## Charadriiformes 0 0 1 1 0 0
## Passeriformes 0 0 0 0 0 1
## Pelecaniformes 0 0 1 1 1 0
## Suliformes 0 0 0 0 0 0
##
## steel leader passed through pvc tubing (i.e. Teflon
## Accipitriformes 0 1
## Anseriformes 1 8
## Charadriiformes 0 1
## Passeriformes 0 1
## Pelecaniformes 0 0
## Suliformes 0 1impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_materials$new_order)) {
order_data_materials <- filter(sep_materials, new_order==order_alt)
order_data_materials$impact_level <- factor(order_data_materials$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
order_data_methods <- filter(sep_methods, new_order==order_alt)
order_data_methods$impact_level <- factor(order_data_methods$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_materials$impact_level,order_data_materials$material))
print(table(order_data_methods$impact_level,order_data_methods$methods))
print(order_alt)}##
## Dwyer 1972) Elastic cord Glue Neoprene Ribbon Spectra
## Very high 0 0 0 0 0 0
## High 0 0 0 0 0 0
## Modest 0 1 2 1 1 0
## Low Impact 1 2 0 0 1 0
## No impact 0 0 0 0 0 1
## Not sure 0 0 0 0 0 0
## N/A 0 0 0 0 0 0
##
## steel leader passed through pvc tubing (i.e. Teflon
## Very high 0 0
## High 0 2
## Modest 0 3
## Low Impact 1 3
## No impact 0 0
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 1 2 3 0
## Modest 1 3 3 0
## Low Impact 3 4 2 2
## No impact 1 1 1 0
## Not sure 0 0 0 0
## N/A 0 0 0 0
## [1] "Anseriformes"
##
## Glue Neoprene Teflon
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 0 0 0
## No impact 0 0 0
## Not sure 1 1 1
## N/A 0 0 0
##
## Glue Knot
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 0 0
## No impact 0 0
## Not sure 1 1
## N/A 0 0
## [1] "Charadriiformes"
##
## Spectra Teflon
## Very high 0 0
## High 0 0
## Modest 1 1
## Low Impact 0 0
## No impact 0 0
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead Sew
## Very high 0 0
## High 0 0
## Modest 1 1
## Low Impact 0 0
## No impact 0 0
## Not sure 0 0
## N/A 0 0
## [1] "Passeriformes"
##
## Glue Neoprene Ribbon
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 0 0 0
## No impact 0 0 0
## Not sure 1 1 1
## N/A 0 0 0
##
## Glue Knot
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 0 0
## No impact 0 0
## Not sure 1 1
## N/A 0 0
## [1] "Pelecaniformes"
##
## Spectra Teflon
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 0 0
## No impact 1 1
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 0 0 0 0
## Low Impact 0 0 0 0
## No impact 1 1 1 1
## Not sure 0 0 0 0
## N/A 0 0 0 0
## [1] "Accipitriformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 0
## Not sure 1
## N/A 0
##
## Crimp Bead Glue Knot
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 0 0 0
## No impact 0 0 0
## Not sure 1 1 1
## N/A 0 0 0
## [1] "Suliformes"### IMPACT LEVELS OF DIFFERENT METHODS
for (methods_alt in unique(sep_methods$methods)) {
print(ggplot(data=count(filter(sep_methods,methods==methods_alt),impact_level),aes(x=impact_level,y=n/nrow(filter(sep_methods,methods==methods_alt))))+
geom_col()+
ggtitle(sprintf("Impact Levels of Using %s While Attaching Breast-Body Harnesses, n=%s",methods_alt,nrow(filter(sep_methods,methods==methods_alt))))+
ylab("frequency")+
xlab("impact level"))}
### IMPACT LEVELS OF DIFFERENT MATERIALS BY EFFECTS
abrasion <- group_by(sep_materials,abrasion,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'abrasion'. You can override using the
## `.groups` argument.callous <- group_by(sep_materials,callous,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'callous'. You can override using the
## `.groups` argument.feather_loss <- group_by(sep_materials,feather_loss,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'feather_loss'. You can override using the
## `.groups` argument.fell_off <- group_by(sep_materials,fell_off,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'fell_off'. You can override using the
## `.groups` argument.strangulation <- group_by(sep_materials,strangulation,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'strangulation'. You can override using the
## `.groups` argument.flight_impairment <- group_by(sep_materials,flight_impairment,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'flight_impairment'. You can override using
## the `.groups` argument.immobilization <- group_by(sep_materials,immobilization,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'immobilization'. You can override using
## the `.groups` argument.other <- group_by(sep_materials,other,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'other'. You can override using the
## `.groups` argument.# Orders the effect frequencies
abrasion$abrasion <- factor(abrasion$abrasion, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
callous$callous <- factor(callous$callous, levels=c('Often (41-80%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
feather_loss$feather_loss <- factor(feather_loss$feather_loss, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
fell_off$fell_off <- factor(fell_off$fell_off, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
strangulation$strangulation <- factor(strangulation$strangulation, levels=c('Rare (<10%)','Never','NA','Unknown','Not sure'))
flight_impairment$flight_impairment <- factor(flight_impairment$flight_impairment, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
immobilization$immobilization <- factor(immobilization$immobilization, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
other$other <- factor(other$other, levels=c('Always (>80%)','Rare (<10%)','Never','NA','N/A','Not sure'))
###
# Creates labels for abrasion plot along with sample sizes
abrasion_vector <- c()
for (material_alt in sort(unique(abrasion$material))) {
abrasion_vector <- c(abrasion_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)),sep="\n"))
}
callous_vector <- c()
for (material_alt in sort(unique(callous$material))) {
callous_vector <- c(callous_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
feather_loss_vector <- c()
for (material_alt in sort(unique(feather_loss$material))) {
feather_loss_vector <- c(feather_loss_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
fell_off_vector <- c()
for (material_alt in sort(unique(fell_off$material))) {
fell_off_vector <- c(fell_off_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)),sep="\n"))
}
strangulation_vector <- c()
for (material_alt in sort(unique(strangulation$material))) {
strangulation_vector <- c(strangulation_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
flight_impairment_vector <- c()
for (material_alt in sort(unique(flight_impairment$material))) {
flight_impairment_vector <- c(flight_impairment_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
immobilization_vector <- c()
for (material_alt in sort(unique(immobilization$material))) {
immobilization_vector <- c(immobilization_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
other_vector <- c()
for (material_alt in sort(unique(other$material))) {
other_vector <- c(other_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
ggplot(data=abrasion, aes(fill=abrasion, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Abrasian Frequencies Using Breast-Body Harnesses By Material") +
scale_x_discrete(labels=abrasion_vector)
ggplot(data=callous, aes(fill=callous, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Callous Frequencies Using Breast-Body Harnesses By Material") +
scale_x_discrete(labels=callous_vector)
ggplot(data=feather_loss, aes(fill=feather_loss, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Feather Loss Frequencies Using Breast-Body Harnesses By Material") +
scale_x_discrete(labels=feather_loss_vector)
ggplot(data=fell_off, aes(fill=fell_off, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Frequencies Of Breast-Body Harnesses Falling Off By Material")) +
scale_x_discrete(labels=fell_off_vector)
ggplot(data=strangulation, aes(fill=strangulation, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Strangulation Frequencies Using Breast-Body Harnesses By Material")) +
scale_x_discrete(labels=strangulation_vector)
ggplot(data=flight_impairment, aes(fill=flight_impairment, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Flight Impairment Frequencies Using Breast-Body Harnesses By Material")) +
scale_x_discrete(labels=flight_impairment_vector)
ggplot(data=immobilization, aes(fill=immobilization, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Immobilization Frequencies Using Breast-Body Harnesses By Material")) +
scale_x_discrete(labels=immobilization_vector)
ggplot(data=other, aes(fill=other, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Other Frequencies Using Breast-Body Harnesses By Material")) +
scale_x_discrete(labels=other_vector)
# IMPACT LEVELS OF DIFFERENT EFFECTS BY METHODS
abrasion <- group_by(sep_methods,abrasion,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'abrasion'. You can override using the
## `.groups` argument.callous <- group_by(sep_methods,callous,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'callous'. You can override using the
## `.groups` argument.feather_loss <- group_by(sep_methods,feather_loss,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'feather_loss'. You can override using the
## `.groups` argument.fell_off <- group_by(sep_methods,fell_off,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'fell_off'. You can override using the
## `.groups` argument.strangulation <- group_by(sep_methods,strangulation,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'strangulation'. You can override using the
## `.groups` argument.flight_impairment <- group_by(sep_methods,flight_impairment,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'flight_impairment'. You can override using
## the `.groups` argument.immobilization <- group_by(sep_methods,immobilization,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'immobilization'. You can override using
## the `.groups` argument.other <- group_by(sep_methods,other,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'other'. You can override using the
## `.groups` argument.# Orders the effect frequencies
abrasion$abrasion <- factor(abrasion$abrasion, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
callous$callous <- factor(callous$callous, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
feather_loss$feather_loss <- factor(feather_loss$feather_loss, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
fell_off$fell_off <- factor(fell_off$fell_off, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
strangulation$strangulation <- factor(strangulation$strangulation, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
flight_impairment$flight_impairment <- factor(flight_impairment$flight_impairment, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
immobilization$immobilization <- factor(immobilization$immobilization, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
other$other <- factor(other$other, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
abrasion_vector <- c()
for (method_alt in sort(unique(abrasion$methods))) {
abrasion_vector <- c(abrasion_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)),sep="\n"))
}
callous_vector <- c()
for (method_alt in sort(unique(callous$methods))) {
callous_vector <- c(callous_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
feather_loss_vector <- c()
for (method_alt in sort(unique(feather_loss$methods))) {
feather_loss_vector <- c(feather_loss_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
fell_off_vector <- c()
for (method_alt in sort(unique(fell_off$methods))) {
fell_off_vector <- c(fell_off_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)),sep="\n"))
}
strangulation_vector <- c()
for (method_alt in sort(unique(strangulation$methods))) {
strangulation_vector <- c(strangulation_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
flight_impairment_vector <- c()
for (method_alt in sort(unique(flight_impairment$methods))) {
flight_impairment_vector <- c(flight_impairment_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
immobilization_vector <- c()
for (method_alt in sort(unique(immobilization$methods))) {
immobilization_vector <- c(immobilization_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
other_vector <- c()
for (method_alt in sort(unique(other$methods))) {
other_vector <- c(other_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
ggplot(data=abrasion, aes(fill=abrasion, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Abrasian Frequencies Using Breast-Body Harnesses By Method") +
scale_x_discrete(labels=abrasion_vector)
ggplot(data=callous, aes(fill=callous, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Callous Frequencies Using Breast-Body Harnesses By Method") +
scale_x_discrete(labels=callous_vector)
ggplot(data=feather_loss, aes(fill=feather_loss, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Feather Loss Frequencies Using Breast-Body Harnesses By Method") +
scale_x_discrete(labels=feather_loss_vector)
ggplot(data=fell_off, aes(fill=fell_off, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Frequencies Of Breast-Body Harnesses Falling Off By Method")) +
scale_x_discrete(labels=fell_off_vector)
ggplot(data=strangulation, aes(fill=strangulation, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Strangulation Frequencies Using Breast-Body Harnesses By Method")) +
scale_x_discrete(labels=strangulation_vector)
ggplot(data=flight_impairment, aes(fill=flight_impairment, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Flight Impairment Frequencies Using Breast-Body Harnesses By Method")) +
scale_x_discrete(labels=flight_impairment_vector)
ggplot(data=immobilization, aes(fill=immobilization, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Immobilization Frequencies Using Breast-Body Harnesses By Method")) +
scale_x_discrete(labels=immobilization_vector)
ggplot(data=other, aes(fill=other, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Other Frequencies Using Breast-Body Harnesses By Method")) +
scale_x_discrete(labels=other_vector)
CHAN-PIERSMA HARNESS VISUALIZATIONS ###
chan_piersma <- read_csv("/Users/Shared/Tagging/Final/chan_piersma.csv")## Rows: 7 Columns: 17
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (16): species, device_type, material, why_material, methods, why_methods...
## dbl (1): id
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.sep_species <- separate_rows(chan_piersma,species,sep=",")
sep_species <- merge(x=sep_species,y=new_orders,by.x="species",by.y="original_order")
sep_materials <- separate_rows(sep_species,material,sep=", ")
sep_materials <- sep_materials %>% filter(material != '4 mm diameter')
ggplot(data=count(sep_materials,material),aes(x=material,y=(n/nrow(sep_species))))+
geom_col()+
ggtitle(sprintf("Material Use Frequencies When Tagging Using Chan-Piersma Harnesses, n=%s",nrow(sep_species)))+
ylab("frequency")
#---
sep_methods <- separate_rows(sep_species,methods,sep=", ")
ggplot(data=count(sep_methods,methods), aes(x=methods,y=(n/nrow(sep_species))))+
geom_col()+
ggtitle(sprintf("Method Use Frequencies When Tagging Using Chan-Piersma Harnesses, n=%s",nrow(sep_species)))+
ylab("frequency")
### IMPACT LEVELS OF DIFFERENT MATERIALS
for (material_alt in unique(sep_materials$material)) {
print(ggplot(data=count(filter(sep_materials,material==material_alt),impact_level),aes(x=impact_level,y=n/nrow(filter(sep_materials,material==material_alt))))+
geom_col()+
ggtitle(sprintf("Impact Levels of Using %s While Attaching Chan-Piersma Harnesses, n=%s",material_alt,nrow(filter(sep_materials,material==material_alt))))+
ylab("frequency")+
xlab("impact level"))}
print("Original Orders:")## [1] "Original Orders:"table(sep_materials$species,sep_materials$material)##
## Elastic cord Glue Jewelry crimps
## caprimulgiformes 1 0 0
## charadriiformes...gulls.and.terns 0 1 0
## charadriiformes...shorebirds 0 0 0
## ciconiiformes 0 1 0
## falconiformes 0 0 0
## passeriformes 0 0 0
## strigiformes 1 1 1
##
## Monofilament Neoprene soft Nylon cord
## caprimulgiformes 0 0 0
## charadriiformes...gulls.and.terns 0 1 0
## charadriiformes...shorebirds 1 0 0
## ciconiiformes 0 1 1
## falconiformes 0 0 0
## passeriformes 0 0 0
## strigiformes 0 0 0
##
## Stretch magic Teflon
## caprimulgiformes 1 0
## charadriiformes...gulls.and.terns 0 1
## charadriiformes...shorebirds 1 0
## ciconiiformes 0 0
## falconiformes 0 1
## passeriformes 1 0
## strigiformes 1 1impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_materials$species)) {
order_data_materials <- filter(sep_materials, species==order_alt)
order_data_materials$impact_level <- factor(order_data_materials$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
order_data_methods <- filter(sep_methods, species==order_alt)
order_data_methods$impact_level <- factor(order_data_methods$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_materials$impact_level,order_data_materials$material))
print(table(order_data_methods$impact_level,order_data_methods$methods))
print(order_alt)}##
## Elastic cord Stretch magic
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 1
## No impact 0 0
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 0
## Not sure 0
## N/A 0
## [1] "caprimulgiformes"
##
## Glue Neoprene Teflon
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 1 1 1
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
##
## Glue Knot Sew
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 1 1 1
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
## [1] "charadriiformes...gulls.and.terns"
##
## Monofilament Stretch magic
## Very high 0 0
## High 0 0
## Modest 1 1
## Low Impact 0 0
## No impact 0 0
## Not sure 0 0
## N/A 0 0
##
## Knot
## Very high 0
## High 0
## Modest 1
## Low Impact 0
## No impact 0
## Not sure 0
## N/A 0
## [1] "charadriiformes...shorebirds"
##
## Glue Neoprene soft Nylon cord
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 1 1 1
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
##
## Glue Heat shrink tube
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 1
## No impact 0 0
## Not sure 0 0
## N/A 0 0
## [1] "ciconiiformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
##
## Glue Knot
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 0 0
## No impact 1 1
## Not sure 0 0
## N/A 0 0
## [1] "falconiformes"
##
## Stretch magic
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
##
## Crimp Bead Knot
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 0 0
## No impact 1 1
## Not sure 0 0
## N/A 0 0
## [1] "passeriformes"
##
## Elastic cord Glue Jewelry crimps Stretch magic Teflon
## Very high 0 0 0 0 0
## High 0 0 0 0 0
## Modest 0 0 0 0 0
## Low Impact 1 1 1 1 1
## No impact 0 0 0 0 0
## Not sure 0 0 0 0 0
## N/A 0 0 0 0 0
##
## Crimp Bead Glue Knot
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 1 1 1
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
## [1] "strigiformes"print("New Orders:")## [1] "New Orders:"table(sep_materials$new_order,sep_materials$material)##
## Elastic cord Glue Jewelry crimps Monofilament Neoprene
## Accipitriformes 1 1 1 0 0
## Caprimulgiformes 1 0 0 0 0
## Charadriiformes 0 1 0 1 1
## Passeriformes 0 0 0 0 0
## Pelecaniformes 0 1 0 0 1
##
## soft Nylon cord Stretch magic Teflon
## Accipitriformes 0 1 2
## Caprimulgiformes 0 1 0
## Charadriiformes 0 1 1
## Passeriformes 0 1 0
## Pelecaniformes 1 0 0impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_materials$new_order)) {
order_data_materials <- filter(sep_materials, new_order==order_alt)
order_data_materials$impact_level <- factor(order_data_materials$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
order_data_methods <- filter(sep_methods, new_order==order_alt)
order_data_methods$impact_level <- factor(order_data_methods$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_materials$impact_level,order_data_materials$material))
print(table(order_data_methods$impact_level,order_data_methods$methods))
print(order_alt)}##
## Elastic cord Stretch magic
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 1
## No impact 0 0
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 0
## Not sure 0
## N/A 0
## [1] "Caprimulgiformes"
##
## Glue Monofilament Neoprene Stretch magic Teflon
## Very high 0 0 0 0 0
## High 0 0 0 0 0
## Modest 0 1 0 1 0
## Low Impact 1 0 1 0 1
## No impact 0 0 0 0 0
## Not sure 0 0 0 0 0
## N/A 0 0 0 0 0
##
## Glue Knot Sew
## Very high 0 0 0
## High 0 0 0
## Modest 0 1 0
## Low Impact 1 1 1
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
## [1] "Charadriiformes"
##
## Glue Neoprene soft Nylon cord
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 1 1 1
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
##
## Glue Heat shrink tube
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 1
## No impact 0 0
## Not sure 0 0
## N/A 0 0
## [1] "Pelecaniformes"
##
## Elastic cord Glue Jewelry crimps Stretch magic Teflon
## Very high 0 0 0 0 0
## High 0 0 0 0 0
## Modest 0 0 0 0 0
## Low Impact 1 1 1 1 1
## No impact 0 0 0 0 1
## Not sure 0 0 0 0 0
## N/A 0 0 0 0 0
##
## Crimp Bead Glue Knot
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 1 1 1
## No impact 0 1 1
## Not sure 0 0 0
## N/A 0 0 0
## [1] "Accipitriformes"
##
## Stretch magic
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
##
## Crimp Bead Knot
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 0 0
## No impact 1 1
## Not sure 0 0
## N/A 0 0
## [1] "Passeriformes"### IMPACT LEVELS OF DIFFERENT METHODS
for (methods_alt in unique(sep_methods$methods)) {
print(ggplot(data=count(filter(sep_methods,methods==methods_alt),impact_level),aes(x=impact_level,y=n/nrow(filter(sep_methods,methods==methods_alt))))+
geom_col()+
ggtitle(sprintf("Impact Levels of Using %s While Attaching Chan-Piersma Harnesses, n=%s",methods_alt,nrow(filter(sep_methods,methods==methods_alt))))+
ylab("frequency")+
xlab("impact level"))}
### IMPACT LEVELS OF DIFFERENT MATERIALS BY EFFECTS
abrasion <- group_by(sep_materials,abrasion,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'abrasion'. You can override using the
## `.groups` argument.callous <- group_by(sep_materials,callous,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'callous'. You can override using the
## `.groups` argument.feather_loss <- group_by(sep_materials,feather_loss,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'feather_loss'. You can override using the
## `.groups` argument.fell_off <- group_by(sep_materials,fell_off,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'fell_off'. You can override using the
## `.groups` argument.strangulation <- group_by(sep_materials,strangulation,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'strangulation'. You can override using the
## `.groups` argument.flight_impairment <- group_by(sep_materials,flight_impairment,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'flight_impairment'. You can override using
## the `.groups` argument.immobilization <- group_by(sep_materials,immobilization,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'immobilization'. You can override using
## the `.groups` argument.other <- group_by(sep_materials,other,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'other'. You can override using the
## `.groups` argument.# Orders the effect frequencies
abrasion$abrasion <- factor(abrasion$abrasion, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
callous$callous <- factor(callous$callous, levels=c('Often (41-80%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
feather_loss$feather_loss <- factor(feather_loss$feather_loss, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
fell_off$fell_off <- factor(fell_off$fell_off, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
strangulation$strangulation <- factor(strangulation$strangulation, levels=c('Rare (<10%)','Never','NA','Unknown','Not sure'))
flight_impairment$flight_impairment <- factor(flight_impairment$flight_impairment, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
immobilization$immobilization <- factor(immobilization$immobilization, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
other$other <- factor(other$other, levels=c('Always (>80%)','Rare (<10%)','Never','NA','N/A','Not sure'))
###
# Creates labels for abrasion plot along with sample sizes
abrasion_vector <- c()
for (material_alt in sort(unique(abrasion$material))) {
abrasion_vector <- c(abrasion_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)),sep="\n"))
}
callous_vector <- c()
for (material_alt in sort(unique(callous$material))) {
callous_vector <- c(callous_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
feather_loss_vector <- c()
for (material_alt in sort(unique(feather_loss$material))) {
feather_loss_vector <- c(feather_loss_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
fell_off_vector <- c()
for (material_alt in sort(unique(fell_off$material))) {
fell_off_vector <- c(fell_off_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)),sep="\n"))
}
strangulation_vector <- c()
for (material_alt in sort(unique(strangulation$material))) {
strangulation_vector <- c(strangulation_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
flight_impairment_vector <- c()
for (material_alt in sort(unique(flight_impairment$material))) {
flight_impairment_vector <- c(flight_impairment_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
immobilization_vector <- c()
for (material_alt in sort(unique(immobilization$material))) {
immobilization_vector <- c(immobilization_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
other_vector <- c()
for (material_alt in sort(unique(other$material))) {
other_vector <- c(other_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
ggplot(data=abrasion, aes(fill=abrasion, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Abrasian Frequencies Using Chan-Piersma Harnesses By Material") +
scale_x_discrete(labels=abrasion_vector)
ggplot(data=callous, aes(fill=callous, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Callous Frequencies Using Chan-Piersma Harnesses By Material") +
scale_x_discrete(labels=callous_vector)
ggplot(data=feather_loss, aes(fill=feather_loss, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Feather Loss Frequencies Using Chan-Piersma Harnesses By Material") +
scale_x_discrete(labels=feather_loss_vector)
ggplot(data=fell_off, aes(fill=fell_off, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Frequencies Of Chan-Piersma Harnesses Falling Off By Material")) +
scale_x_discrete(labels=fell_off_vector)
ggplot(data=strangulation, aes(fill=strangulation, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Strangulation Frequencies Using Chan-Piersma Harnesses By Material")) +
scale_x_discrete(labels=strangulation_vector)
ggplot(data=flight_impairment, aes(fill=flight_impairment, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Flight Impairment Frequencies Using Chan-Piersma Harnesses By Material")) +
scale_x_discrete(labels=flight_impairment_vector)
ggplot(data=immobilization, aes(fill=immobilization, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Immobilization Frequencies Using Chan-Piersma Harnesses By Material")) +
scale_x_discrete(labels=immobilization_vector)
ggplot(data=other, aes(fill=other, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Other Frequencies Using Chan-Piersma Harnesses By Material")) +
scale_x_discrete(labels=other_vector)
# IMPACT LEVELS OF DIFFERENT EFFECTS BY METHODS
abrasion <- group_by(sep_methods,abrasion,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'abrasion'. You can override using the
## `.groups` argument.callous <- group_by(sep_methods,callous,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'callous'. You can override using the
## `.groups` argument.feather_loss <- group_by(sep_methods,feather_loss,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'feather_loss'. You can override using the
## `.groups` argument.fell_off <- group_by(sep_methods,fell_off,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'fell_off'. You can override using the
## `.groups` argument.strangulation <- group_by(sep_methods,strangulation,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'strangulation'. You can override using the
## `.groups` argument.flight_impairment <- group_by(sep_methods,flight_impairment,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'flight_impairment'. You can override using
## the `.groups` argument.immobilization <- group_by(sep_methods,immobilization,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'immobilization'. You can override using
## the `.groups` argument.other <- group_by(sep_methods,other,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'other'. You can override using the
## `.groups` argument.# Orders the effect frequencies
abrasion$abrasion <- factor(abrasion$abrasion, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
callous$callous <- factor(callous$callous, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
feather_loss$feather_loss <- factor(feather_loss$feather_loss, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
fell_off$fell_off <- factor(fell_off$fell_off, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
strangulation$strangulation <- factor(strangulation$strangulation, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
flight_impairment$flight_impairment <- factor(flight_impairment$flight_impairment, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
immobilization$immobilization <- factor(immobilization$immobilization, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
other$other <- factor(other$other, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
abrasion_vector <- c()
for (method_alt in sort(unique(abrasion$methods))) {
abrasion_vector <- c(abrasion_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)),sep="\n"))
}
callous_vector <- c()
for (method_alt in sort(unique(callous$methods))) {
callous_vector <- c(callous_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
feather_loss_vector <- c()
for (method_alt in sort(unique(feather_loss$methods))) {
feather_loss_vector <- c(feather_loss_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
fell_off_vector <- c()
for (method_alt in sort(unique(fell_off$methods))) {
fell_off_vector <- c(fell_off_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)),sep="\n"))
}
strangulation_vector <- c()
for (method_alt in sort(unique(strangulation$methods))) {
strangulation_vector <- c(strangulation_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
flight_impairment_vector <- c()
for (method_alt in sort(unique(flight_impairment$methods))) {
flight_impairment_vector <- c(flight_impairment_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
immobilization_vector <- c()
for (method_alt in sort(unique(immobilization$methods))) {
immobilization_vector <- c(immobilization_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
other_vector <- c()
for (method_alt in sort(unique(other$methods))) {
other_vector <- c(other_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
ggplot(data=abrasion, aes(fill=abrasion, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Abrasian Frequencies Using Chan-Piersma Harnesses By Method") +
scale_x_discrete(labels=abrasion_vector)
ggplot(data=callous, aes(fill=callous, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Callous Frequencies Using Chan-Piersma Harnesses By Method") +
scale_x_discrete(labels=callous_vector)
ggplot(data=feather_loss, aes(fill=feather_loss, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Feather Loss Frequencies Using Chan-Piersma Harnesses By Method") +
scale_x_discrete(labels=feather_loss_vector)
ggplot(data=fell_off, aes(fill=fell_off, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Frequencies Of Chan-Piersma Harnesses Falling Off By Method")) +
scale_x_discrete(labels=fell_off_vector)
ggplot(data=strangulation, aes(fill=strangulation, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Strangulation Frequencies Using Chan-Piersma Harnesses By Method")) +
scale_x_discrete(labels=strangulation_vector)
ggplot(data=flight_impairment, aes(fill=flight_impairment, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Flight Impairment Frequencies Using Chan-Piersma Harnesses By Method")) +
scale_x_discrete(labels=flight_impairment_vector)
ggplot(data=immobilization, aes(fill=immobilization, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Immobilization Frequencies Using Chan-Piersma Harnesses By Method")) +
scale_x_discrete(labels=immobilization_vector)
ggplot(data=other, aes(fill=other, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Other Frequencies Using Chan-Piersma Harnesses By Method")) +
scale_x_discrete(labels=other_vector)
FULL-BODY HARNESS VISUALIZATIONS ###
fullbody <- read_csv("/Users/Shared/Tagging/Final/fullbody.csv")## Rows: 14 Columns: 17
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (16): species, device_type, material, why_material, methods, why_methods...
## dbl (1): id
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.sep_species <- separate_rows(fullbody,species,sep=",")
sep_species <- merge(x=sep_species,y=new_orders,by.x="species",by.y="original_order")
sep_materials <- separate_rows(sep_species,material,sep=", ")
unique(sep_materials$material)## [1] "Elastic cord"
## [2] "Teflon"
## [3] "3 layers: rope through rubber tube and teflon around"
## [4] "Spectra"
## [5] "Monofilament"
## [6] "Stretch magic"
## [7] "surgical material"sep_materials <- sep_materials %>% filter(material != '3 layers: rope through rubber tube and teflon around')
ggplot(data=count(sep_materials,material),aes(x=material,y=(n/nrow(sep_species))))+
geom_col()+
ggtitle(sprintf("Material Use Frequencies When Tagging Using Full Body Harnesses, n=%s",nrow(sep_species)))+
ylab("frequency")
#---
sep_methods <- separate_rows(sep_species,methods,sep=", ")
ggplot(data=count(sep_methods,methods), aes(x=methods,y=(n/nrow(sep_species))))+
geom_col()+
ggtitle(sprintf("Method Use Frequencies When Tagging Using Full Body Harnesses, n=%s",nrow(sep_species)))+
ylab("frequency")
### IMPACT LEVELS OF DIFFERENT MATERIALS
for (material_alt in unique(sep_materials$material)) {
print(ggplot(data=count(filter(sep_materials,material==material_alt),impact_level),aes(x=impact_level,y=n/nrow(filter(sep_materials,material==material_alt))))+
geom_col()+
ggtitle(sprintf("Impact Levels of Using %s While Attaching Full Body Harnesses, n=%s",material_alt,nrow(filter(sep_materials,material==material_alt))))+
ylab("frequency")+
xlab("impact level"))}
print("Original Orders:")## [1] "Original Orders:"table(sep_materials$species,sep_materials$material)##
## Elastic cord Monofilament Spectra
## anseriformes 1 0 0
## charadriiformes...gulls.and.terns 0 0 0
## charadriiformes...shorebirds 0 1 1
## falconiformes 0 0 0
## gruiformes 0 0 0
## pelecaniformes 0 0 0
##
## Stretch magic surgical material Teflon
## anseriformes 0 0 1
## charadriiformes...gulls.and.terns 0 0 4
## charadriiformes...shorebirds 1 1 0
## falconiformes 0 0 4
## gruiformes 0 0 1
## pelecaniformes 0 0 1impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_materials$species)) {
order_data_materials <- filter(sep_materials, species==order_alt)
order_data_materials$impact_level <- factor(order_data_materials$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
order_data_methods <- filter(sep_methods, species==order_alt)
order_data_methods$impact_level <- factor(order_data_methods$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_materials$impact_level,order_data_materials$material))
print(table(order_data_methods$impact_level,order_data_methods$methods))
print(order_alt)}##
## Elastic cord Teflon
## Very high 0 0
## High 0 0
## Modest 1 1
## Low Impact 0 0
## No impact 0 0
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead Glue
## Very high 0 0
## High 0 0
## Modest 1 2
## Low Impact 0 0
## No impact 0 0
## Not sure 0 0
## N/A 0 0
## [1] "anseriformes"
##
## Teflon
## Very high 0
## High 0
## Modest 1
## Low Impact 1
## No impact 2
## Not sure 0
## N/A 0
##
## Crimp Bead Glue Knot Sew Surgical
## Very high 0 0 0 0 0
## High 0 0 0 0 0
## Modest 0 1 1 1 0
## Low Impact 0 1 0 1 0
## No impact 1 2 1 2 1
## Not sure 0 0 0 0 0
## N/A 0 0 0 0 0
## [1] "charadriiformes...gulls.and.terns"
##
## Monofilament Spectra Stretch magic surgical material
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 0 0 0 0
## Low Impact 0 0 1 1
## No impact 0 0 0 0
## Not sure 0 0 0 0
## N/A 0 0 0 0
##
## Crimp Bead Glue Knot
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 0 1 1
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
## [1] "charadriiformes...shorebirds"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 3
## No impact 1
## Not sure 0
## N/A 0
##
## aluminium clip glued to tag Crimp Bead Glue Knot Sew Surgical
## Very high 0 0 0 0 0 0
## High 0 0 0 0 0 0
## Modest 0 0 0 0 0 0
## Low Impact 1 1 2 3 1 0
## No impact 0 1 0 1 1 1
## Not sure 0 0 0 0 0 0
## N/A 0 0 0 0 0 0
## [1] "falconiformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 0
## Not sure 0
## N/A 0
##
## Crimp Bead Glue Knot
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 1 1 1
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
## [1] "gruiformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 0
## Not sure 0
## N/A 0
##
## Crimp Bead Glue Knot
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 1 1 1
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
## [1] "pelecaniformes"print("New Orders:")## [1] "New Orders:"table(sep_materials$new_order,sep_materials$material)##
## Elastic cord Monofilament Spectra Stretch magic
## Accipitriformes 0 0 0 0
## Anseriformes 1 0 0 0
## Charadriiformes 0 1 1 1
## Gruiformes 0 0 0 0
## Pelecaniformes 0 0 0 0
##
## surgical material Teflon
## Accipitriformes 0 4
## Anseriformes 0 1
## Charadriiformes 1 4
## Gruiformes 0 1
## Pelecaniformes 0 1impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_materials$new_order)) {
order_data_materials <- filter(sep_materials, new_order==order_alt)
order_data_materials$impact_level <- factor(order_data_materials$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
order_data_methods <- filter(sep_methods, new_order==order_alt)
order_data_methods$impact_level <- factor(order_data_methods$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_materials$impact_level,order_data_materials$material))
print(table(order_data_methods$impact_level,order_data_methods$methods))
print(order_alt)}##
## Elastic cord Teflon
## Very high 0 0
## High 0 0
## Modest 1 1
## Low Impact 0 0
## No impact 0 0
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead Glue
## Very high 0 0
## High 0 0
## Modest 1 2
## Low Impact 0 0
## No impact 0 0
## Not sure 0 0
## N/A 0 0
## [1] "Anseriformes"
##
## Monofilament Spectra Stretch magic surgical material Teflon
## Very high 0 0 0 0 0
## High 0 0 0 0 0
## Modest 0 0 0 0 1
## Low Impact 0 0 1 1 1
## No impact 0 0 0 0 2
## Not sure 0 0 0 0 0
## N/A 0 0 0 0 0
##
## Crimp Bead Glue Knot Sew Surgical
## Very high 0 0 0 0 0
## High 0 0 0 0 0
## Modest 0 1 1 1 0
## Low Impact 0 2 1 1 0
## No impact 1 2 1 2 1
## Not sure 0 0 0 0 0
## N/A 0 0 0 0 0
## [1] "Charadriiformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 3
## No impact 1
## Not sure 0
## N/A 0
##
## aluminium clip glued to tag Crimp Bead Glue Knot Sew Surgical
## Very high 0 0 0 0 0 0
## High 0 0 0 0 0 0
## Modest 0 0 0 0 0 0
## Low Impact 1 1 2 3 1 0
## No impact 0 1 0 1 1 1
## Not sure 0 0 0 0 0 0
## N/A 0 0 0 0 0 0
## [1] "Accipitriformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 0
## Not sure 0
## N/A 0
##
## Crimp Bead Glue Knot
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 1 1 1
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
## [1] "Gruiformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 0
## Not sure 0
## N/A 0
##
## Crimp Bead Glue Knot
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 1 1 1
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
## [1] "Pelecaniformes"### IMPACT LEVELS OF DIFFERENT METHODS
for (methods_alt in unique(sep_methods$methods)) {
print(ggplot(data=count(filter(sep_methods,methods==methods_alt),impact_level),aes(x=impact_level,y=n/nrow(filter(sep_methods,methods==methods_alt))))+
geom_col()+
ggtitle(sprintf("Impact Levels of Using %s While Attaching Full Body Harnesses, n=%s",methods_alt,nrow(filter(sep_methods,methods==methods_alt))))+
ylab("frequency")+
xlab("impact level"))}
### IMPACT LEVELS OF DIFFERENT MATERIALS BY EFFECTS
abrasion <- group_by(sep_materials,abrasion,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'abrasion'. You can override using the
## `.groups` argument.callous <- group_by(sep_materials,callous,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'callous'. You can override using the
## `.groups` argument.feather_loss <- group_by(sep_materials,feather_loss,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'feather_loss'. You can override using the
## `.groups` argument.fell_off <- group_by(sep_materials,fell_off,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'fell_off'. You can override using the
## `.groups` argument.strangulation <- group_by(sep_materials,strangulation,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'strangulation'. You can override using the
## `.groups` argument.flight_impairment <- group_by(sep_materials,flight_impairment,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'flight_impairment'. You can override using
## the `.groups` argument.immobilization <- group_by(sep_materials,immobilization,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'immobilization'. You can override using
## the `.groups` argument.other <- group_by(sep_materials,other,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'other'. You can override using the
## `.groups` argument.# Orders the effect frequencies
abrasion$abrasion <- factor(abrasion$abrasion, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
callous$callous <- factor(callous$callous, levels=c('Often (41-80%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
feather_loss$feather_loss <- factor(feather_loss$feather_loss, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
fell_off$fell_off <- factor(fell_off$fell_off, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
strangulation$strangulation <- factor(strangulation$strangulation, levels=c('Rare (<10%)','Never','NA','Unknown','Not sure'))
flight_impairment$flight_impairment <- factor(flight_impairment$flight_impairment, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
immobilization$immobilization <- factor(immobilization$immobilization, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
other$other <- factor(other$other, levels=c('Always (>80%)','Rare (<10%)','Never','NA','N/A','Not sure'))
###
# Creates labels for abrasion plot along with sample sizes
abrasion_vector <- c()
for (material_alt in sort(unique(abrasion$material))) {
abrasion_vector <- c(abrasion_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)),sep="\n"))
}
callous_vector <- c()
for (material_alt in sort(unique(callous$material))) {
callous_vector <- c(callous_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
feather_loss_vector <- c()
for (material_alt in sort(unique(feather_loss$material))) {
feather_loss_vector <- c(feather_loss_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
fell_off_vector <- c()
for (material_alt in sort(unique(fell_off$material))) {
fell_off_vector <- c(fell_off_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)),sep="\n"))
}
strangulation_vector <- c()
for (material_alt in sort(unique(strangulation$material))) {
strangulation_vector <- c(strangulation_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
flight_impairment_vector <- c()
for (material_alt in sort(unique(flight_impairment$material))) {
flight_impairment_vector <- c(flight_impairment_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
immobilization_vector <- c()
for (material_alt in sort(unique(immobilization$material))) {
immobilization_vector <- c(immobilization_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
other_vector <- c()
for (material_alt in sort(unique(other$material))) {
other_vector <- c(other_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
ggplot(data=abrasion, aes(fill=abrasion, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Abrasian Frequencies Using Full Body Harnesses By Material") +
scale_x_discrete(labels=abrasion_vector)
ggplot(data=callous, aes(fill=callous, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Callous Frequencies Using Full Body Harnesses By Material") +
scale_x_discrete(labels=callous_vector)
ggplot(data=feather_loss, aes(fill=feather_loss, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Feather Loss Frequencies Using Full Body Harnesses By Material") +
scale_x_discrete(labels=feather_loss_vector)
ggplot(data=fell_off, aes(fill=fell_off, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Frequencies Of Full Body Harnesses Falling Off By Material")) +
scale_x_discrete(labels=fell_off_vector)
ggplot(data=strangulation, aes(fill=strangulation, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Strangulation Frequencies Using Full Body Harnesses By Material")) +
scale_x_discrete(labels=strangulation_vector)
ggplot(data=flight_impairment, aes(fill=flight_impairment, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Flight Impairment Frequencies Using Full Body Harnesses By Material")) +
scale_x_discrete(labels=flight_impairment_vector)
ggplot(data=immobilization, aes(fill=immobilization, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Immobilization Frequencies Using Full Body Harnesses By Material")) +
scale_x_discrete(labels=immobilization_vector)
ggplot(data=other, aes(fill=other, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Other Frequencies Using Full Body Harnesses By Material")) +
scale_x_discrete(labels=other_vector)
# IMPACT LEVELS OF DIFFERENT EFFECTS BY METHODS
abrasion <- group_by(sep_methods,abrasion,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'abrasion'. You can override using the
## `.groups` argument.callous <- group_by(sep_methods,callous,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'callous'. You can override using the
## `.groups` argument.feather_loss <- group_by(sep_methods,feather_loss,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'feather_loss'. You can override using the
## `.groups` argument.fell_off <- group_by(sep_methods,fell_off,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'fell_off'. You can override using the
## `.groups` argument.strangulation <- group_by(sep_methods,strangulation,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'strangulation'. You can override using the
## `.groups` argument.flight_impairment <- group_by(sep_methods,flight_impairment,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'flight_impairment'. You can override using
## the `.groups` argument.immobilization <- group_by(sep_methods,immobilization,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'immobilization'. You can override using
## the `.groups` argument.other <- group_by(sep_methods,other,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'other'. You can override using the
## `.groups` argument.# Orders the effect frequencies
abrasion$abrasion <- factor(abrasion$abrasion, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
callous$callous <- factor(callous$callous, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
feather_loss$feather_loss <- factor(feather_loss$feather_loss, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
fell_off$fell_off <- factor(fell_off$fell_off, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
strangulation$strangulation <- factor(strangulation$strangulation, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
flight_impairment$flight_impairment <- factor(flight_impairment$flight_impairment, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
immobilization$immobilization <- factor(immobilization$immobilization, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
other$other <- factor(other$other, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
abrasion_vector <- c()
for (method_alt in sort(unique(abrasion$methods))) {
abrasion_vector <- c(abrasion_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)),sep="\n"))
}
callous_vector <- c()
for (method_alt in sort(unique(callous$methods))) {
callous_vector <- c(callous_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
feather_loss_vector <- c()
for (method_alt in sort(unique(feather_loss$methods))) {
feather_loss_vector <- c(feather_loss_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
fell_off_vector <- c()
for (method_alt in sort(unique(fell_off$methods))) {
fell_off_vector <- c(fell_off_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)),sep="\n"))
}
strangulation_vector <- c()
for (method_alt in sort(unique(strangulation$methods))) {
strangulation_vector <- c(strangulation_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
flight_impairment_vector <- c()
for (method_alt in sort(unique(flight_impairment$methods))) {
flight_impairment_vector <- c(flight_impairment_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
immobilization_vector <- c()
for (method_alt in sort(unique(immobilization$methods))) {
immobilization_vector <- c(immobilization_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
other_vector <- c()
for (method_alt in sort(unique(other$methods))) {
other_vector <- c(other_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
ggplot(data=abrasion, aes(fill=abrasion, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Abrasian Frequencies Using Full Body Harnesses By Method") +
scale_x_discrete(labels=abrasion_vector)
ggplot(data=callous, aes(fill=callous, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Callous Frequencies Using Full Body Harnesses By Method") +
scale_x_discrete(labels=callous_vector)
ggplot(data=feather_loss, aes(fill=feather_loss, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Feather Loss Frequencies Using Full Body Harnesses By Method") +
scale_x_discrete(labels=feather_loss_vector)
ggplot(data=fell_off, aes(fill=fell_off, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Frequencies Of Full Body Harnesses Falling Off By Method")) +
scale_x_discrete(labels=fell_off_vector)
ggplot(data=strangulation, aes(fill=strangulation, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Strangulation Frequencies Using Full Body Harnesses By Method")) +
scale_x_discrete(labels=strangulation_vector)
ggplot(data=flight_impairment, aes(fill=flight_impairment, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Flight Impairment Frequencies Using Full Body Harnesses By Method")) +
scale_x_discrete(labels=flight_impairment_vector)
ggplot(data=immobilization, aes(fill=immobilization, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Immobilization Frequencies Using Full Body Harnesses By Method")) +
scale_x_discrete(labels=immobilization_vector)
ggplot(data=other, aes(fill=other, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Other Frequencies Using Full Body Harnesses By Method")) +
scale_x_discrete(labels=other_vector)
LEG-LOOP HARNESS ###
legloop <- read_csv("/Users/Shared/Tagging/Final/legloop.csv")## Rows: 83 Columns: 17
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (16): species, device_type, material, why_material, methods, why_methods...
## dbl (1): id
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.sep_species <- separate_rows(legloop,species,sep=",")
sep_species <- merge(x=sep_species,y=new_orders,by.x="species",by.y="original_order")
sep_materials <- separate_rows(sep_species,material,sep=", ")
unique(sep_materials$material)## [1] "Teflon"
## [2] "Elastic cord"
## [3] "Thread"
## [4] "Silicone"
## [5] "Spectra"
## [6] "Stretch magic"
## [7] "Neoprene"
## [8] "Glue"
## [9] "surgical tubing over stretch magic"
## [10] "Ribbon"
## [11] "Monofilament"
## [12] "catheter tubing"
## [13] "not sure what the scrub jay harness material was"
## [14] "some sort of thread"sep_materials <- sep_materials %>% filter(material != 'surgical tubing over stretch magic', material != 'not sure what the scrub jay harness material was',material != 'some sort of thread')
ggplot(data=count(sep_materials,material),aes(x=material,y=(n/nrow(sep_species))))+
geom_col()+
ggtitle(sprintf("Material Use Frequencies When Tagging Using Leg-Loop Harnesses, n=%s",nrow(sep_species)))+
ylab("frequency")
#---
sep_methods <- separate_rows(sep_species,methods,sep=", ")
unique(sep_methods$methods)## [1] "Crimp Bead"
## [2] "Knot"
## [3] "Sew"
## [4] "Glue"
## [5] "Solder"
## [6] "Crimp used was an aluminium fishing crimp"
## [7] NA
## [8] "melting stretch magic together"sep_methods <- sep_methods %>% filter(methods != 'Crimp used was an aluminium fishing crimp', methods != 'melting stretch magic together')
ggplot(data=count(sep_methods,methods), aes(x=methods,y=(n/nrow(sep_species))))+
geom_col()+
ggtitle(sprintf("Method Use Frequencies When Tagging Using Leg-Loop Harnesses, n=%s",nrow(sep_species)))+
ylab("frequency")
### IMPACT LEVELS OF DIFFERENT MATERIALS
for (material_alt in unique(sep_materials$material)) {
print(ggplot(data=count(filter(sep_materials,material==material_alt),impact_level),aes(x=impact_level,y=n/nrow(filter(sep_materials,material==material_alt))))+
geom_col()+
ggtitle(sprintf("Impact Levels of Using %s While Attaching Leg-Loop Harnesses, n=%s",material_alt,nrow(filter(sep_materials,material==material_alt))))+
ylab("frequency")+
xlab("impact level"))}
print("Original Orders:")## [1] "Original Orders:"table(sep_materials$species,sep_materials$material)##
## catheter tubing Elastic cord Glue
## cathartiformes 0 1 0
## charadriiformes...gulls.and.terns 0 1 1
## charadriiformes...shorebirds 0 3 3
## coraciiformes 0 1 0
## falconiformes 0 2 0
## galliformes 0 0 0
## gruiformes 0 1 0
## passeriformes 2 18 1
## piciformes 0 3 1
## strigiformes 0 0 0
## suliformes 0 0 0
##
## Monofilament Neoprene Ribbon Silicone
## cathartiformes 0 0 0 1
## charadriiformes...gulls.and.terns 0 1 0 1
## charadriiformes...shorebirds 0 1 1 3
## coraciiformes 1 0 0 0
## falconiformes 0 0 0 0
## galliformes 0 0 0 0
## gruiformes 0 0 0 0
## passeriformes 1 0 1 0
## piciformes 1 1 0 0
## strigiformes 0 1 0 0
## suliformes 0 0 0 0
##
## Spectra Stretch magic Teflon Thread
## cathartiformes 0 0 3 1
## charadriiformes...gulls.and.terns 2 2 7 0
## charadriiformes...shorebirds 1 11 10 0
## coraciiformes 0 0 0 0
## falconiformes 2 0 7 0
## galliformes 0 0 3 0
## gruiformes 0 2 0 0
## passeriformes 0 27 2 4
## piciformes 0 0 2 1
## strigiformes 0 0 1 0
## suliformes 0 0 1 0impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_materials$species)) {
order_data_materials <- filter(sep_materials, species==order_alt)
order_data_materials$impact_level <- factor(order_data_materials$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
order_data_methods <- filter(sep_methods, species==order_alt)
order_data_methods$impact_level <- factor(order_data_methods$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_materials$impact_level,order_data_materials$material))
print(table(order_data_methods$impact_level,order_data_methods$methods))
print(order_alt)}##
## Elastic cord Silicone Teflon Thread
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 0 0 0 0
## Low Impact 1 0 2 1
## No impact 0 1 1 0
## Not sure 0 0 0 0
## N/A 0 0 0 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 0 0 0 0
## Low Impact 2 0 1 1
## No impact 1 1 1 0
## Not sure 0 0 0 0
## N/A 0 0 0 0
## [1] "cathartiformes"
##
## Elastic cord Glue Neoprene Silicone Spectra Stretch magic Teflon
## Very high 0 0 0 0 0 0 0
## High 0 0 0 0 0 0 0
## Modest 0 0 0 0 1 0 1
## Low Impact 1 1 1 1 1 2 4
## No impact 0 0 0 0 0 0 0
## Not sure 0 0 0 0 0 0 2
## N/A 0 0 0 0 0 0 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 1 2 2 0
## Low Impact 3 2 3 1
## No impact 0 0 0 0
## Not sure 1 2 2 0
## N/A 0 0 0 0
## [1] "charadriiformes...gulls.and.terns"
##
## Elastic cord Glue Neoprene Ribbon Silicone Spectra Stretch magic
## Very high 0 0 0 0 0 0 0
## High 0 0 0 0 0 0 0
## Modest 1 2 0 0 1 0 4
## Low Impact 2 0 0 1 2 1 6
## No impact 0 1 1 0 0 0 1
## Not sure 0 0 0 0 0 0 0
## N/A 0 0 0 0 0 0 0
##
## Teflon
## Very high 0
## High 0
## Modest 1
## Low Impact 6
## No impact 3
## Not sure 0
## N/A 0
##
## Crimp Bead Glue Knot Sew Solder
## Very high 0 0 0 0 0
## High 0 0 0 0 0
## Modest 4 5 4 0 0
## Low Impact 8 6 8 0 1
## No impact 2 3 3 1 0
## Not sure 0 0 0 0 0
## N/A 0 0 0 0 0
## [1] "charadriiformes...shorebirds"
##
## Elastic cord Monofilament
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 1
## No impact 0 0
## Not sure 0 0
## N/A 0 0
## < table of extent 7 x 0 >
## [1] "coraciiformes"
##
## Elastic cord Spectra Teflon
## Very high 0 0 0
## High 0 0 0
## Modest 1 1 3
## Low Impact 0 1 1
## No impact 1 0 3
## Not sure 0 0 0
## N/A 0 0 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 2 1 2 1
## Low Impact 1 1 1 1
## No impact 1 2 1 1
## Not sure 0 0 0 0
## N/A 0 0 0 0
## [1] "falconiformes"
##
## Teflon
## Very high 0
## High 1
## Modest 0
## Low Impact 0
## No impact 0
## Not sure 0
## N/A 2
##
## Crimp Bead Glue Knot
## Very high 0 0 0
## High 1 1 1
## Modest 0 0 0
## Low Impact 0 0 0
## No impact 0 0 0
## Not sure 0 0 0
## N/A 2 1 0
## [1] "galliformes"
##
## Elastic cord Stretch magic
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 1
## No impact 0 1
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead Glue Knot
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 1 1 1
## No impact 0 1 1
## Not sure 0 0 0
## N/A 0 0 0
## [1] "gruiformes"
##
## catheter tubing Elastic cord Glue Monofilament Ribbon
## Very high 0 1 0 0 0
## High 0 0 0 0 0
## Modest 0 3 0 0 1
## Low Impact 0 13 1 0 0
## No impact 0 1 0 1 0
## Not sure 1 0 0 0 0
## N/A 1 0 0 0 0
##
## Stretch magic Teflon Thread
## Very high 0 0 0
## High 0 0 0
## Modest 8 0 1
## Low Impact 13 2 2
## No impact 4 0 1
## Not sure 2 0 0
## N/A 0 0 0
##
## Crimp Bead Glue Knot Sew Solder
## Very high 0 1 1 0 0
## High 0 0 0 0 0
## Modest 2 6 5 0 3
## Low Impact 3 15 12 1 4
## No impact 3 4 5 0 1
## Not sure 2 2 2 0 0
## N/A 1 0 0 0 0
## [1] "passeriformes"
##
## Elastic cord Glue Monofilament Neoprene Teflon Thread
## Very high 0 0 0 0 0 0
## High 0 0 0 0 0 0
## Modest 0 0 0 0 0 0
## Low Impact 2 1 1 1 2 1
## No impact 1 0 0 0 0 0
## Not sure 0 0 0 0 0 0
## N/A 0 0 0 0 0 0
##
## Glue Knot
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 3 3
## No impact 0 1
## Not sure 0 0
## N/A 0 0
## [1] "piciformes"
##
## Neoprene Teflon
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 0 0
## No impact 0 0
## Not sure 1 1
## N/A 0 0
##
## Crimp Bead
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 0
## Not sure 1
## N/A 0
## [1] "strigiformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
##
## Glue
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
## [1] "suliformes"print("New Orders:")## [1] "New Orders:"table(sep_materials$new_order,sep_materials$material)##
## catheter tubing Elastic cord Glue Monofilament Neoprene
## Accipitriformes 0 3 0 0 1
## Charadriiformes 0 4 4 0 2
## Galliformes 0 0 0 0 0
## Gruiformes 0 1 0 0 0
## Near Passerines 0 4 1 2 1
## Passeriformes 2 18 1 1 0
## Suliformes 0 0 0 0 0
##
## Ribbon Silicone Spectra Stretch magic Teflon Thread
## Accipitriformes 0 1 2 0 11 1
## Charadriiformes 1 4 3 13 17 0
## Galliformes 0 0 0 0 3 0
## Gruiformes 0 0 0 2 0 0
## Near Passerines 0 0 0 0 2 1
## Passeriformes 1 0 0 27 2 4
## Suliformes 0 0 0 0 1 0impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_materials$new_order)) {
order_data_materials <- filter(sep_materials, new_order==order_alt)
order_data_materials$impact_level <- factor(order_data_materials$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
order_data_methods <- filter(sep_methods, new_order==order_alt)
order_data_methods$impact_level <- factor(order_data_methods$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_materials$impact_level,order_data_materials$material))
print(table(order_data_methods$impact_level,order_data_methods$methods))
print(order_alt)}##
## Elastic cord Neoprene Silicone Spectra Teflon Thread
## Very high 0 0 0 0 0 0
## High 0 0 0 0 0 0
## Modest 1 0 0 1 3 0
## Low Impact 1 0 0 1 3 1
## No impact 1 0 1 0 4 0
## Not sure 0 1 0 0 1 0
## N/A 0 0 0 0 0 0
##
## Crimp Bead Glue Knot Sew
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 2 1 2 1
## Low Impact 3 1 2 2
## No impact 2 3 2 1
## Not sure 1 0 0 0
## N/A 0 0 0 0
## [1] "Accipitriformes"
##
## Elastic cord Glue Neoprene Ribbon Silicone Spectra Stretch magic
## Very high 0 0 0 0 0 0 0
## High 0 0 0 0 0 0 0
## Modest 1 2 0 0 1 1 4
## Low Impact 3 1 1 1 3 2 8
## No impact 0 1 1 0 0 0 1
## Not sure 0 0 0 0 0 0 0
## N/A 0 0 0 0 0 0 0
##
## Teflon
## Very high 0
## High 0
## Modest 2
## Low Impact 10
## No impact 3
## Not sure 2
## N/A 0
##
## Crimp Bead Glue Knot Sew Solder
## Very high 0 0 0 0 0
## High 0 0 0 0 0
## Modest 5 7 6 0 0
## Low Impact 11 8 11 1 1
## No impact 2 3 3 1 0
## Not sure 1 2 2 0 0
## N/A 0 0 0 0 0
## [1] "Charadriiformes"
##
## Elastic cord Glue Monofilament Neoprene Teflon Thread
## Very high 0 0 0 0 0 0
## High 0 0 0 0 0 0
## Modest 0 0 0 0 0 0
## Low Impact 3 1 2 1 2 1
## No impact 1 0 0 0 0 0
## Not sure 0 0 0 0 0 0
## N/A 0 0 0 0 0 0
##
## Glue Knot
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 3 3
## No impact 0 1
## Not sure 0 0
## N/A 0 0
## [1] "Near Passerines"
##
## Teflon
## Very high 0
## High 1
## Modest 0
## Low Impact 0
## No impact 0
## Not sure 0
## N/A 2
##
## Crimp Bead Glue Knot
## Very high 0 0 0
## High 1 1 1
## Modest 0 0 0
## Low Impact 0 0 0
## No impact 0 0 0
## Not sure 0 0 0
## N/A 2 1 0
## [1] "Galliformes"
##
## Elastic cord Stretch magic
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 1
## No impact 0 1
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead Glue Knot
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 1 1 1
## No impact 0 1 1
## Not sure 0 0 0
## N/A 0 0 0
## [1] "Gruiformes"
##
## catheter tubing Elastic cord Glue Monofilament Ribbon
## Very high 0 1 0 0 0
## High 0 0 0 0 0
## Modest 0 3 0 0 1
## Low Impact 0 13 1 0 0
## No impact 0 1 0 1 0
## Not sure 1 0 0 0 0
## N/A 1 0 0 0 0
##
## Stretch magic Teflon Thread
## Very high 0 0 0
## High 0 0 0
## Modest 8 0 1
## Low Impact 13 2 2
## No impact 4 0 1
## Not sure 2 0 0
## N/A 0 0 0
##
## Crimp Bead Glue Knot Sew Solder
## Very high 0 1 1 0 0
## High 0 0 0 0 0
## Modest 2 6 5 0 3
## Low Impact 3 15 12 1 4
## No impact 3 4 5 0 1
## Not sure 2 2 2 0 0
## N/A 1 0 0 0 0
## [1] "Passeriformes"
##
## Teflon
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
##
## Glue
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
## [1] "Suliformes"### IMPACT LEVELS OF DIFFERENT METHODS
for (methods_alt in unique(sep_methods$methods)) {
print(ggplot(data=count(filter(sep_methods,methods==methods_alt),impact_level),aes(x=impact_level,y=n/nrow(filter(sep_methods,methods==methods_alt))))+
geom_col()+
ggtitle(sprintf("Impact Levels of Using %s While Attaching Leg-Loop Harnesses, n=%s",methods_alt,nrow(filter(sep_methods,methods==methods_alt))))+
ylab("frequency")+
xlab("impact level"))}
### IMPACT LEVELS OF DIFFERENT MATERIALS BY EFFECTS
abrasion <- group_by(sep_materials,abrasion,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'abrasion'. You can override using the
## `.groups` argument.callous <- group_by(sep_materials,callous,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'callous'. You can override using the
## `.groups` argument.feather_loss <- group_by(sep_materials,feather_loss,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'feather_loss'. You can override using the
## `.groups` argument.fell_off <- group_by(sep_materials,fell_off,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'fell_off'. You can override using the
## `.groups` argument.strangulation <- group_by(sep_materials,strangulation,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'strangulation'. You can override using the
## `.groups` argument.flight_impairment <- group_by(sep_materials,flight_impairment,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'flight_impairment'. You can override using
## the `.groups` argument.immobilization <- group_by(sep_materials,immobilization,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'immobilization'. You can override using
## the `.groups` argument.other <- group_by(sep_materials,other,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'other'. You can override using the
## `.groups` argument.# Orders the effect frequencies
abrasion$abrasion <- factor(abrasion$abrasion, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
callous$callous <- factor(callous$callous, levels=c('Often (41-80%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
feather_loss$feather_loss <- factor(feather_loss$feather_loss, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
fell_off$fell_off <- factor(fell_off$fell_off, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
strangulation$strangulation <- factor(strangulation$strangulation, levels=c('Rare (<10%)','Never','NA','Unknown','Not sure'))
flight_impairment$flight_impairment <- factor(flight_impairment$flight_impairment, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
immobilization$immobilization <- factor(immobilization$immobilization, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
other$other <- factor(other$other, levels=c('Always (>80%)','Rare (<10%)','Never','NA','N/A','Not sure'))
###
# Creates labels for abrasion plot along with sample sizes
abrasion_vector <- c()
for (material_alt in sort(unique(abrasion$material))) {
abrasion_vector <- c(abrasion_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)),sep="\n"))
}
callous_vector <- c()
for (material_alt in sort(unique(callous$material))) {
callous_vector <- c(callous_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
feather_loss_vector <- c()
for (material_alt in sort(unique(feather_loss$material))) {
feather_loss_vector <- c(feather_loss_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
fell_off_vector <- c()
for (material_alt in sort(unique(fell_off$material))) {
fell_off_vector <- c(fell_off_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)),sep="\n"))
}
strangulation_vector <- c()
for (material_alt in sort(unique(strangulation$material))) {
strangulation_vector <- c(strangulation_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
flight_impairment_vector <- c()
for (material_alt in sort(unique(flight_impairment$material))) {
flight_impairment_vector <- c(flight_impairment_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
immobilization_vector <- c()
for (material_alt in sort(unique(immobilization$material))) {
immobilization_vector <- c(immobilization_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
other_vector <- c()
for (material_alt in sort(unique(other$material))) {
other_vector <- c(other_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
ggplot(data=abrasion, aes(fill=abrasion, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Abrasian Frequencies Using Leg-Loop Harnesses By Material") +
scale_x_discrete(labels=abrasion_vector)
ggplot(data=callous, aes(fill=callous, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Callous Frequencies Using Leg-Loop Harnesses By Material") +
scale_x_discrete(labels=callous_vector)
ggplot(data=feather_loss, aes(fill=feather_loss, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Feather Loss Frequencies Using Leg-Loop Harnesses By Material") +
scale_x_discrete(labels=feather_loss_vector)
ggplot(data=fell_off, aes(fill=fell_off, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Frequencies Of Leg-Loop Harnesses Falling Off By Material")) +
scale_x_discrete(labels=fell_off_vector)
ggplot(data=strangulation, aes(fill=strangulation, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Strangulation Frequencies Using Leg-Loop Harnesses By Material")) +
scale_x_discrete(labels=strangulation_vector)
ggplot(data=flight_impairment, aes(fill=flight_impairment, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Flight Impairment Frequencies Using Leg-Loop Harnesses By Material")) +
scale_x_discrete(labels=flight_impairment_vector)
ggplot(data=immobilization, aes(fill=immobilization, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Immobilization Frequencies Using Leg-Loop Harnesses By Material")) +
scale_x_discrete(labels=immobilization_vector)
ggplot(data=other, aes(fill=other, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Other Frequencies Using Leg-Loop Harnesses By Material")) +
scale_x_discrete(labels=other_vector)
# IMPACT LEVELS OF DIFFERENT EFFECTS BY METHODS
abrasion <- group_by(sep_methods,abrasion,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'abrasion'. You can override using the
## `.groups` argument.callous <- group_by(sep_methods,callous,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'callous'. You can override using the
## `.groups` argument.feather_loss <- group_by(sep_methods,feather_loss,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'feather_loss'. You can override using the
## `.groups` argument.fell_off <- group_by(sep_methods,fell_off,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'fell_off'. You can override using the
## `.groups` argument.strangulation <- group_by(sep_methods,strangulation,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'strangulation'. You can override using the
## `.groups` argument.flight_impairment <- group_by(sep_methods,flight_impairment,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'flight_impairment'. You can override using
## the `.groups` argument.immobilization <- group_by(sep_methods,immobilization,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'immobilization'. You can override using
## the `.groups` argument.other <- group_by(sep_methods,other,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'other'. You can override using the
## `.groups` argument.# Orders the effect frequencies
abrasion$abrasion <- factor(abrasion$abrasion, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
callous$callous <- factor(callous$callous, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
feather_loss$feather_loss <- factor(feather_loss$feather_loss, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
fell_off$fell_off <- factor(fell_off$fell_off, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
strangulation$strangulation <- factor(strangulation$strangulation, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
flight_impairment$flight_impairment <- factor(flight_impairment$flight_impairment, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
immobilization$immobilization <- factor(immobilization$immobilization, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
other$other <- factor(other$other, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
abrasion_vector <- c()
for (method_alt in sort(unique(abrasion$methods))) {
abrasion_vector <- c(abrasion_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)),sep="\n"))
}
callous_vector <- c()
for (method_alt in sort(unique(callous$methods))) {
callous_vector <- c(callous_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
feather_loss_vector <- c()
for (method_alt in sort(unique(feather_loss$methods))) {
feather_loss_vector <- c(feather_loss_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
fell_off_vector <- c()
for (method_alt in sort(unique(fell_off$methods))) {
fell_off_vector <- c(fell_off_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)),sep="\n"))
}
strangulation_vector <- c()
for (method_alt in sort(unique(strangulation$methods))) {
strangulation_vector <- c(strangulation_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
flight_impairment_vector <- c()
for (method_alt in sort(unique(flight_impairment$methods))) {
flight_impairment_vector <- c(flight_impairment_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
immobilization_vector <- c()
for (method_alt in sort(unique(immobilization$methods))) {
immobilization_vector <- c(immobilization_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
other_vector <- c()
for (method_alt in sort(unique(other$methods))) {
other_vector <- c(other_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
ggplot(data=abrasion, aes(fill=abrasion, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Abrasian Frequencies Using Leg-Loop Harnesses By Method") +
scale_x_discrete(labels=abrasion_vector)
ggplot(data=callous, aes(fill=callous, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Callous Frequencies Using Leg-Loop Harnesses By Method") +
scale_x_discrete(labels=callous_vector)
ggplot(data=feather_loss, aes(fill=feather_loss, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Feather Loss Frequencies Using Leg-Loop Harnesses By Method") +
scale_x_discrete(labels=feather_loss_vector)
ggplot(data=fell_off, aes(fill=fell_off, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Frequencies Of Leg-Loop Harnesses Falling Off By Method")) +
scale_x_discrete(labels=fell_off_vector)
ggplot(data=strangulation, aes(fill=strangulation, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Strangulation Frequencies Using Leg-Loop Harnesses By Method")) +
scale_x_discrete(labels=strangulation_vector)
ggplot(data=flight_impairment, aes(fill=flight_impairment, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Flight Impairment Frequencies Using Leg-Loop Harnesses By Method")) +
scale_x_discrete(labels=flight_impairment_vector)
ggplot(data=immobilization, aes(fill=immobilization, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Immobilization Frequencies Using Leg-Loop Harnesses By Method")) +
scale_x_discrete(labels=immobilization_vector)
ggplot(data=other, aes(fill=other, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Other Frequencies Using Leg-Loop Harnesses By Method")) +
scale_x_discrete(labels=other_vector)
TESA-TAPE VISUALIZATIONS ###
tesatape <- read_csv("/Users/Shared/Tagging/Final/tesatape.csv")## Rows: 46 Columns: 17
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (16): species, device_type, location, why_testape, impact_level, abrasio...
## dbl (1): id
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.sep_species <- separate_rows(tesatape,species,sep=",")
sep_species <- merge(x=sep_species,y=new_orders,by.x="species",by.y="original_order")
sep_location <- separate_rows(sep_species,location,sep=",")
ggplot(data=count(sep_location,location),aes(x=location,y=(n/nrow(sep_species))))+
geom_col()+
ggtitle(sprintf("Location of Tag Frequencies When Using Tesa Tape, n=%s",nrow(sep_species)))+
ylab("frequency")
### IMPACT LEVELS OF DIFFERENT LOCATIONS
for (location_alt in unique(sep_location$location)) {
print(ggplot(data=count(filter(sep_location,location==location_alt),impact_level),aes(x=impact_level,y=n/nrow(filter(sep_location,location==location_alt))))+
geom_col()+
ggtitle(sprintf("Impact Levels of Using Tesa Tape On The %s While Tagging, n=%s",location_alt,nrow(filter(sep_location,location==location_alt))))+
ylab("frequency")+
xlab("impact level"))}
print("Original Orders:")## [1] "Original Orders:"table(sep_location$species,sep_location$location)##
## back keel tail
## cathartiformes 2 0 0
## charadriiformes...alcids 7 1 0
## charadriiformes...gulls.and.terns 7 0 1
## charadriiformes...shorebirds 1 0 0
## phaethontiformes 1 0 1
## sphenisciformes 5 0 0
## suliformes 3 0 10impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_location$species)) {
order_data_location <- filter(sep_location, species==order_alt)
order_data_location$impact_level <- factor(order_data_location$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_location$impact_level,order_data_location$location))
print(order_alt)}##
## back
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 2
## Not sure 0
## N/A 0
## [1] "cathartiformes"
##
## back keel
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 6 1
## No impact 1 0
## Not sure 0 0
## N/A 0 0
## [1] "charadriiformes...alcids"
##
## back tail
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 5 1
## No impact 2 0
## Not sure 0 0
## N/A 0 0
## [1] "charadriiformes...gulls.and.terns"
##
## back
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 0
## Not sure 0
## N/A 0
## [1] "charadriiformes...shorebirds"
##
## back tail
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 1
## No impact 0 0
## Not sure 0 0
## N/A 0 0
## [1] "phaethontiformes"
##
## back
## Very high 0
## High 0
## Modest 0
## Low Impact 3
## No impact 2
## Not sure 0
## N/A 0
## [1] "sphenisciformes"
##
## back tail
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 2 7
## No impact 1 3
## Not sure 0 0
## N/A 0 0
## [1] "suliformes"print("New Orders:")## [1] "New Orders:"table(sep_location$new_order,sep_location$location)##
## back keel tail
## Accipitriformes 2 0 0
## Charadriiformes 15 1 1
## Procellariformes 1 0 1
## Sphenisciformes 5 0 0
## Suliformes 3 0 10impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_location$new_order)) {
order_data_location <- filter(sep_location, new_order==order_alt)
order_data_location$impact_level <- factor(order_data_location$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_location$impact_level,order_data_location$location))
print(order_alt)}##
## back
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 2
## Not sure 0
## N/A 0
## [1] "Accipitriformes"
##
## back keel tail
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 12 1 1
## No impact 3 0 0
## Not sure 0 0 0
## N/A 0 0 0
## [1] "Charadriiformes"
##
## back tail
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 1
## No impact 0 0
## Not sure 0 0
## N/A 0 0
## [1] "Procellariformes"
##
## back
## Very high 0
## High 0
## Modest 0
## Low Impact 3
## No impact 2
## Not sure 0
## N/A 0
## [1] "Sphenisciformes"
##
## back tail
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 2 7
## No impact 1 3
## Not sure 0 0
## N/A 0 0
## [1] "Suliformes"### IMPACT LEVELS OF DIFFERENT MATERIALS BY EFFECTS
abrasion <- group_by(sep_location,abrasion,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'abrasion'. You can override using the
## `.groups` argument.callous <- group_by(sep_location,callous,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'callous'. You can override using the
## `.groups` argument.feather_loss <- group_by(sep_location,feather_loss,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'feather_loss'. You can override using the
## `.groups` argument.fell_off <- group_by(sep_location,fell_off,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'fell_off'. You can override using the
## `.groups` argument.strangulation <- group_by(sep_location,strangulation,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'strangulation'. You can override using the
## `.groups` argument.flight_impairment <- group_by(sep_location,flight_impairment,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'flight_impairment'. You can override using
## the `.groups` argument.immobilization <- group_by(sep_location,immobilization,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'immobilization'. You can override using
## the `.groups` argument.other <- group_by(sep_location,other,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'other'. You can override using the
## `.groups` argument.# Orders the effect frequencies
abrasion$abrasion <- factor(abrasion$abrasion, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
callous$callous <- factor(callous$callous, levels=c('Often (41-80%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
feather_loss$feather_loss <- factor(feather_loss$feather_loss, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
fell_off$fell_off <- factor(fell_off$fell_off, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
strangulation$strangulation <- factor(strangulation$strangulation, levels=c('Rare (<10%)','Never','NA','Unknown','Not sure'))
flight_impairment$flight_impairment <- factor(flight_impairment$flight_impairment, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
immobilization$immobilization <- factor(immobilization$immobilization, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
other$other <- factor(other$other, levels=c('Always (>80%)','Rare (<10%)','Never','NA','N/A','Not sure'))
###
# Creates labels for abrasion plot along with sample sizes
abrasion_vector <- c()
for (location_alt in sort(unique(abrasion$location))) {
abrasion_vector <- c(abrasion_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)),sep="\n"))
}
callous_vector <- c()
for (location_alt in sort(unique(callous$location))) {
callous_vector <- c(callous_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)), sep="\n"))
}
feather_loss_vector <- c()
for (location_alt in sort(unique(feather_loss$location))) {
feather_loss_vector <- c(feather_loss_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)), sep="\n"))
}
fell_off_vector <- c()
for (location_alt in sort(unique(fell_off$location))) {
fell_off_vector <- c(fell_off_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)),sep="\n"))
}
strangulation_vector <- c()
for (location_alt in sort(unique(strangulation$location))) {
strangulation_vector <- c(strangulation_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)), sep="\n"))
}
flight_impairment_vector <- c()
for (location_alt in sort(unique(flight_impairment$location))) {
flight_impairment_vector <- c(flight_impairment_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)), sep="\n"))
}
immobilization_vector <- c()
for (location_alt in sort(unique(immobilization$location))) {
immobilization_vector <- c(immobilization_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)), sep="\n"))
}
other_vector <- c()
for (location_alt in sort(unique(other$location))) {
other_vector <- c(other_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)), sep="\n"))
}
ggplot(data=abrasion, aes(fill=abrasion, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Abrasian Frequencies Using Tesa Tape By Location") +
scale_x_discrete(labels=abrasion_vector)
ggplot(data=callous, aes(fill=callous, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Callous Frequencies UsingTesa Tape By Location") +
scale_x_discrete(labels=callous_vector)
ggplot(data=feather_loss, aes(fill=feather_loss, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Feather Loss Frequencies Using Tesa Tape By Location") +
scale_x_discrete(labels=feather_loss_vector)
ggplot(data=fell_off, aes(fill=fell_off, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Frequencies Of Tesa Tape Falling Off By Location")) +
scale_x_discrete(labels=fell_off_vector)
ggplot(data=strangulation, aes(fill=strangulation, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Strangulation Frequencies Using Tesa Tape By Location")) +
scale_x_discrete(labels=strangulation_vector)
ggplot(data=flight_impairment, aes(fill=flight_impairment, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Flight Impairment Frequencies Using Tesa Tape By Location")) +
scale_x_discrete(labels=flight_impairment_vector)
ggplot(data=immobilization, aes(fill=immobilization, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Immobilization Frequencies Using Tesa Tape By Location")) +
scale_x_discrete(labels=immobilization_vector)
ggplot(data=other, aes(fill=other, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Other Frequencies Using Tesa Tape By Location")) +
scale_x_discrete(labels=other_vector)
WING-LOOP HARNESS VISUALIZATIONS ###
wingloop <- read_csv("/Users/Shared/Tagging/Final/wingloop.csv")## Rows: 7 Columns: 17
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (16): species, device_type, material, why_material, methods, why_methods...
## dbl (1): id
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.sep_species <- separate_rows(wingloop,species,sep=",")
sep_species <- merge(x=sep_species,y=new_orders,by.x="species",by.y="original_order")
sep_materials <- separate_rows(sep_species,material,sep=", ")
ggplot(data=count(sep_materials,material),aes(x=material,y=(n/nrow(sep_species))))+
geom_col()+
ggtitle(sprintf("Material Use Frequencies When Tagging Using Wing-Loop Harnesses, n=%s",nrow(sep_species)))+
ylab("frequency")
#---
sep_methods <- separate_rows(sep_species,methods,sep=", ")
ggplot(data=count(sep_methods,methods), aes(x=methods,y=(n/nrow(sep_species))))+
geom_col()+
ggtitle(sprintf("Method Use Frequencies When Tagging Using Wing-Loop Harnesses, n=%s",nrow(sep_species)))+
ylab("frequency")
### IMPACT LEVELS OF DIFFERENT MATERIALS
for (material_alt in unique(sep_materials$material)) {
print(ggplot(data=count(filter(sep_materials,material==material_alt),impact_level),aes(x=impact_level,y=n/nrow(filter(sep_materials,material==material_alt))))+
geom_col()+
ggtitle(sprintf("Impact Levels of Using %s While Attaching Wing-Loop Harnesses, n=%s",material_alt,nrow(filter(sep_materials,material==material_alt))))+
ylab("frequency")+
xlab("impact level"))}
print("Original Orders:")## [1] "Original Orders:"table(sep_materials$species,sep_materials$material)##
## Elastic cord Thread
## columbiformes 1 0
## galliformes 2 1
## passeriformes 1 1
## strigiformes 1 0impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_materials$species)) {
order_data_materials <- filter(sep_materials, species==order_alt)
order_data_materials$impact_level <- factor(order_data_materials$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
order_data_methods <- filter(sep_methods, species==order_alt)
order_data_methods$impact_level <- factor(order_data_methods$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_materials$impact_level,order_data_materials$material))
print(table(order_data_methods$impact_level,order_data_methods$methods))
print(order_alt)}##
## Elastic cord
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
##
## Glue Knot
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 0 0
## No impact 1 1
## Not sure 0 0
## N/A 0 0
## [1] "columbiformes"
##
## Elastic cord Thread
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 0
## No impact 1 1
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead Glue Knot Solder
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 0 0 0 0
## Low Impact 0 1 1 0
## No impact 1 0 1 1
## Not sure 0 0 0 0
## N/A 0 0 0 0
## [1] "galliformes"
##
## Elastic cord Thread
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 0
## No impact 0 1
## Not sure 0 0
## N/A 0 0
##
## Glue Knot
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 1
## No impact 0 1
## Not sure 0 0
## N/A 0 0
## [1] "passeriformes"
##
## Elastic cord
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
##
## Glue
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
## [1] "strigiformes"print("New Orders:")## [1] "New Orders:"table(sep_materials$new_order,sep_materials$material)##
## Elastic cord Thread
## Accipitriformes 1 0
## Galliformes 2 1
## Near Passerines 1 0
## Passeriformes 1 1impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_materials$new_order)) {
order_data_materials <- filter(sep_materials, new_order==order_alt)
order_data_materials$impact_level <- factor(order_data_materials$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
order_data_methods <- filter(sep_methods, new_order==order_alt)
order_data_methods$impact_level <- factor(order_data_methods$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_materials$impact_level,order_data_materials$material))
print(table(order_data_methods$impact_level,order_data_methods$methods))
print(order_alt)}##
## Elastic cord
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
##
## Glue Knot
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 0 0
## No impact 1 1
## Not sure 0 0
## N/A 0 0
## [1] "Near Passerines"
##
## Elastic cord Thread
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 0
## No impact 1 1
## Not sure 0 0
## N/A 0 0
##
## Crimp Bead Glue Knot Solder
## Very high 0 0 0 0
## High 0 0 0 0
## Modest 0 0 0 0
## Low Impact 0 1 1 0
## No impact 1 0 1 1
## Not sure 0 0 0 0
## N/A 0 0 0 0
## [1] "Galliformes"
##
## Elastic cord Thread
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 0
## No impact 0 1
## Not sure 0 0
## N/A 0 0
##
## Glue Knot
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 1
## No impact 0 1
## Not sure 0 0
## N/A 0 0
## [1] "Passeriformes"
##
## Elastic cord
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
##
## Glue
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
## [1] "Accipitriformes"### IMPACT LEVELS OF DIFFERENT METHODS
for (methods_alt in unique(sep_methods$methods)) {
print(ggplot(data=count(filter(sep_methods,methods==methods_alt),impact_level),aes(x=impact_level,y=n/nrow(filter(sep_methods,methods==methods_alt))))+
geom_col()+
ggtitle(sprintf("Impact Levels of Using %s While Attaching Wing-Loop Harnesses, n=%s",methods_alt,nrow(filter(sep_methods,methods==methods_alt))))+
ylab("frequency")+
xlab("impact level"))}
### IMPACT LEVELS OF DIFFERENT MATERIALS BY EFFECTS
abrasion <- group_by(sep_materials,abrasion,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'abrasion'. You can override using the
## `.groups` argument.callous <- group_by(sep_materials,callous,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'callous'. You can override using the
## `.groups` argument.feather_loss <- group_by(sep_materials,feather_loss,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'feather_loss'. You can override using the
## `.groups` argument.fell_off <- group_by(sep_materials,fell_off,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'fell_off'. You can override using the
## `.groups` argument.strangulation <- group_by(sep_materials,strangulation,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'strangulation'. You can override using the
## `.groups` argument.flight_impairment <- group_by(sep_materials,flight_impairment,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'flight_impairment'. You can override using
## the `.groups` argument.immobilization <- group_by(sep_materials,immobilization,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'immobilization'. You can override using
## the `.groups` argument.other <- group_by(sep_materials,other,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'other'. You can override using the
## `.groups` argument.# Orders the effect frequencies
abrasion$abrasion <- factor(abrasion$abrasion, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
callous$callous <- factor(callous$callous, levels=c('Often (41-80%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
feather_loss$feather_loss <- factor(feather_loss$feather_loss, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
fell_off$fell_off <- factor(fell_off$fell_off, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
strangulation$strangulation <- factor(strangulation$strangulation, levels=c('Rare (<10%)','Never','NA','Unknown','Not sure'))
flight_impairment$flight_impairment <- factor(flight_impairment$flight_impairment, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
immobilization$immobilization <- factor(immobilization$immobilization, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
other$other <- factor(other$other, levels=c('Always (>80%)','Rare (<10%)','Never','NA','N/A','Not sure'))
###
# Creates labels for abrasion plot along with sample sizes
abrasion_vector <- c()
for (material_alt in sort(unique(abrasion$material))) {
abrasion_vector <- c(abrasion_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)),sep="\n"))
}
callous_vector <- c()
for (material_alt in sort(unique(callous$material))) {
callous_vector <- c(callous_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
feather_loss_vector <- c()
for (material_alt in sort(unique(feather_loss$material))) {
feather_loss_vector <- c(feather_loss_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
fell_off_vector <- c()
for (material_alt in sort(unique(fell_off$material))) {
fell_off_vector <- c(fell_off_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)),sep="\n"))
}
strangulation_vector <- c()
for (material_alt in sort(unique(strangulation$material))) {
strangulation_vector <- c(strangulation_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
flight_impairment_vector <- c()
for (material_alt in sort(unique(flight_impairment$material))) {
flight_impairment_vector <- c(flight_impairment_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
immobilization_vector <- c()
for (material_alt in sort(unique(immobilization$material))) {
immobilization_vector <- c(immobilization_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
other_vector <- c()
for (material_alt in sort(unique(other$material))) {
other_vector <- c(other_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
ggplot(data=abrasion, aes(fill=abrasion, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Abrasian Frequencies Using Wing-Loop Harnesses By Material") +
scale_x_discrete(labels=abrasion_vector)
ggplot(data=callous, aes(fill=callous, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Callous Frequencies Using Wing-Loop Harnesses By Material") +
scale_x_discrete(labels=callous_vector)
ggplot(data=feather_loss, aes(fill=feather_loss, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Feather Loss Frequencies Using Wing-Loop Harnesses By Material") +
scale_x_discrete(labels=feather_loss_vector)
ggplot(data=fell_off, aes(fill=fell_off, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Frequencies Of Wing-Loop Harnesses Falling Off By Material")) +
scale_x_discrete(labels=fell_off_vector)
ggplot(data=strangulation, aes(fill=strangulation, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Strangulation Frequencies Using Wing-Loop Harnesses By Material")) +
scale_x_discrete(labels=strangulation_vector)
ggplot(data=flight_impairment, aes(fill=flight_impairment, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Flight Impairment Frequencies Using Wing-Loop Harnesses By Material")) +
scale_x_discrete(labels=flight_impairment_vector)
ggplot(data=immobilization, aes(fill=immobilization, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Immobilization Frequencies Using Wing-Loop Harnesses By Material")) +
scale_x_discrete(labels=immobilization_vector)
ggplot(data=other, aes(fill=other, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Other Frequencies Using Wing-Loop Harnesses By Material")) +
scale_x_discrete(labels=other_vector)
# IMPACT LEVELS OF DIFFERENT EFFECTS BY METHODS
abrasion <- group_by(sep_methods,abrasion,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'abrasion'. You can override using the
## `.groups` argument.callous <- group_by(sep_methods,callous,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'callous'. You can override using the
## `.groups` argument.feather_loss <- group_by(sep_methods,feather_loss,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'feather_loss'. You can override using the
## `.groups` argument.fell_off <- group_by(sep_methods,fell_off,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'fell_off'. You can override using the
## `.groups` argument.strangulation <- group_by(sep_methods,strangulation,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'strangulation'. You can override using the
## `.groups` argument.flight_impairment <- group_by(sep_methods,flight_impairment,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'flight_impairment'. You can override using
## the `.groups` argument.immobilization <- group_by(sep_methods,immobilization,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'immobilization'. You can override using
## the `.groups` argument.other <- group_by(sep_methods,other,methods) %>%
summarise(n=n())## `summarise()` has grouped output by 'other'. You can override using the
## `.groups` argument.# Orders the effect frequencies
abrasion$abrasion <- factor(abrasion$abrasion, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
callous$callous <- factor(callous$callous, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
feather_loss$feather_loss <- factor(feather_loss$feather_loss, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
fell_off$fell_off <- factor(fell_off$fell_off, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
strangulation$strangulation <- factor(strangulation$strangulation, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
flight_impairment$flight_impairment <- factor(flight_impairment$flight_impairment, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
immobilization$immobilization <- factor(immobilization$immobilization, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
other$other <- factor(other$other, levels=c('Always (>80%)','Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
abrasion_vector <- c()
for (method_alt in sort(unique(abrasion$methods))) {
abrasion_vector <- c(abrasion_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)),sep="\n"))
}
callous_vector <- c()
for (method_alt in sort(unique(callous$methods))) {
callous_vector <- c(callous_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
feather_loss_vector <- c()
for (method_alt in sort(unique(feather_loss$methods))) {
feather_loss_vector <- c(feather_loss_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
fell_off_vector <- c()
for (method_alt in sort(unique(fell_off$methods))) {
fell_off_vector <- c(fell_off_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)),sep="\n"))
}
strangulation_vector <- c()
for (method_alt in sort(unique(strangulation$methods))) {
strangulation_vector <- c(strangulation_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
flight_impairment_vector <- c()
for (method_alt in sort(unique(flight_impairment$methods))) {
flight_impairment_vector <- c(flight_impairment_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
immobilization_vector <- c()
for (method_alt in sort(unique(immobilization$methods))) {
immobilization_vector <- c(immobilization_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
other_vector <- c()
for (method_alt in sort(unique(other$methods))) {
other_vector <- c(other_vector,paste(method_alt,nrow(filter(sep_methods,methods==method_alt)), sep="\n"))
}
ggplot(data=abrasion, aes(fill=abrasion, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Abrasian Frequencies Using Wing-Loop Harnesses By Method") +
scale_x_discrete(labels=abrasion_vector)
ggplot(data=callous, aes(fill=callous, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Callous Frequencies Using Wing-Loop Harnesses By Method") +
scale_x_discrete(labels=callous_vector)
ggplot(data=feather_loss, aes(fill=feather_loss, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Feather Loss Frequencies Using Wing-Loop Harnesses By Method") +
scale_x_discrete(labels=feather_loss_vector)
ggplot(data=fell_off, aes(fill=fell_off, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Frequencies Of Wing-Loop Harnesses Falling Off By Method")) +
scale_x_discrete(labels=fell_off_vector)
ggplot(data=strangulation, aes(fill=strangulation, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Strangulation Frequencies Using Wing-Loop Harnesses By Method")) +
scale_x_discrete(labels=strangulation_vector)
ggplot(data=flight_impairment, aes(fill=flight_impairment, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Flight Impairment Frequencies Using Wing-Loop Harnesses By Method")) +
scale_x_discrete(labels=flight_impairment_vector)
ggplot(data=immobilization, aes(fill=immobilization, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Immobilization Frequencies Using Wing-Loop Harnesses By Method")) +
scale_x_discrete(labels=immobilization_vector)
ggplot(data=other, aes(fill=other, x=methods, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Other Frequencies Using Wing-Loop Harnesses By Method")) +
scale_x_discrete(labels=other_vector)
GLUE-ON VISUALIZATIONS ###
glue_on <- read_csv("/Users/Shared/Tagging/Final/glue_on.csv")## Rows: 56 Columns: 17
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (16): species, device_type, location, why_glue_on, impact_level, abrasio...
## dbl (1): id
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.sep_species <- separate_rows(glue_on,species,sep=",")
sep_species <- merge(x=sep_species,y=new_orders,by.x="species",by.y="original_order")
sep_location <- separate_rows(sep_species,location,sep=",")
ggplot(data=count(sep_location,location),aes(x=location,y=(n/nrow(sep_species))))+
geom_col()+
ggtitle(sprintf("Location of Tag Frequencies When Using Glue, n=%s",nrow(sep_species)))+
ylab("frequency")
### IMPACT LEVELS OF DIFFERENT LOCATIONS
for (location_alt in unique(sep_location$location)) {
print(ggplot(data=count(filter(sep_location,location==location_alt),impact_level),aes(x=impact_level,y=n/nrow(filter(sep_location,location==location_alt))))+
geom_col()+
ggtitle(sprintf("Impact Levels of Glue On The %s While Tagging, n=%s",location_alt,nrow(filter(sep_location,location==location_alt))))+
ylab("frequency")+
xlab("impact level"))}
print("Original Orders:")## [1] "Original Orders:"table(sep_location$species,sep_location$location)##
## back tail
## anseriformes 4 0
## apodiformes 2 0
## caprimulgiformes 0 1
## cathartiformes 0 2
## charadriiformes...alcids 3 0
## charadriiformes...gulls.and.terns 4 1
## charadriiformes...shorebirds 24 5
## columbiformes 1 0
## falconiformes 1 3
## gruiformes 1 0
## passeriformes 4 2
## piciformes 0 1
## sphenisciformes 1 0
## strigiformes 0 1impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_location$species)) {
order_data_location <- filter(sep_location, species==order_alt)
order_data_location$impact_level <- factor(order_data_location$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_location$impact_level,order_data_location$location))
print(order_alt)}##
## back
## Very high 0
## High 0
## Modest 1
## Low Impact 3
## No impact 0
## Not sure 0
## N/A 0
## [1] "anseriformes"
##
## back
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 1
## Not sure 0
## N/A 0
## [1] "apodiformes"
##
## tail
## Very high 0
## High 0
## Modest 1
## Low Impact 0
## No impact 0
## Not sure 0
## N/A 0
## [1] "caprimulgiformes"
##
## tail
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 2
## Not sure 0
## N/A 0
## [1] "cathartiformes"
##
## back
## Very high 0
## High 0
## Modest 0
## Low Impact 3
## No impact 0
## Not sure 0
## N/A 0
## [1] "charadriiformes...alcids"
##
## back tail
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 4 1
## No impact 0 0
## Not sure 0 0
## N/A 0 0
## [1] "charadriiformes...gulls.and.terns"
##
## back tail
## Very high 0 0
## High 0 0
## Modest 2 1
## Low Impact 10 4
## No impact 11 0
## Not sure 0 0
## N/A 1 0
## [1] "charadriiformes...shorebirds"
##
## back
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 0
## Not sure 0
## N/A 0
## [1] "columbiformes"
##
## back tail
## Very high 0 0
## High 0 0
## Modest 0 1
## Low Impact 0 0
## No impact 1 2
## Not sure 0 0
## N/A 0 0
## [1] "falconiformes"
##
## back
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 0
## Not sure 0
## N/A 0
## [1] "gruiformes"
##
## back tail
## Very high 0 0
## High 0 0
## Modest 0 1
## Low Impact 0 0
## No impact 4 1
## Not sure 0 0
## N/A 0 0
## [1] "passeriformes"
##
## tail
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
## [1] "piciformes"
##
## back
## Very high 0
## High 1
## Modest 0
## Low Impact 0
## No impact 0
## Not sure 0
## N/A 0
## [1] "sphenisciformes"
##
## tail
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 0
## Not sure 0
## N/A 0
## [1] "strigiformes"print("New Orders:")## [1] "New Orders:"table(sep_location$new_order,sep_location$location)##
## back tail
## Accipitriformes 1 6
## Anseriformes 4 0
## Caprimulgiformes 2 1
## Charadriiformes 31 6
## Gruiformes 1 0
## Near Passerines 1 1
## Passeriformes 4 2
## Sphenisciformes 1 0impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_location$new_order)) {
order_data_location <- filter(sep_location, new_order==order_alt)
order_data_location$impact_level <- factor(order_data_location$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_location$impact_level,order_data_location$location))
print(order_alt)}##
## back
## Very high 0
## High 0
## Modest 1
## Low Impact 3
## No impact 0
## Not sure 0
## N/A 0
## [1] "Anseriformes"
##
## back tail
## Very high 0 0
## High 0 0
## Modest 0 1
## Low Impact 1 0
## No impact 1 0
## Not sure 0 0
## N/A 0 0
## [1] "Caprimulgiformes"
##
## back tail
## Very high 0 0
## High 0 0
## Modest 0 1
## Low Impact 0 1
## No impact 1 4
## Not sure 0 0
## N/A 0 0
## [1] "Accipitriformes"
##
## back tail
## Very high 0 0
## High 0 0
## Modest 2 1
## Low Impact 17 5
## No impact 11 0
## Not sure 0 0
## N/A 1 0
## [1] "Charadriiformes"
##
## back tail
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 0
## No impact 0 1
## Not sure 0 0
## N/A 0 0
## [1] "Near Passerines"
##
## back
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 0
## Not sure 0
## N/A 0
## [1] "Gruiformes"
##
## back tail
## Very high 0 0
## High 0 0
## Modest 0 1
## Low Impact 0 0
## No impact 4 1
## Not sure 0 0
## N/A 0 0
## [1] "Passeriformes"
##
## back
## Very high 0
## High 1
## Modest 0
## Low Impact 0
## No impact 0
## Not sure 0
## N/A 0
## [1] "Sphenisciformes"### IMPACT LEVELS OF DIFFERENT LOCATIONS BY EFFECTS
abrasion <- group_by(sep_location,abrasion,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'abrasion'. You can override using the
## `.groups` argument.callous <- group_by(sep_location,callous,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'callous'. You can override using the
## `.groups` argument.feather_loss <- group_by(sep_location,feather_loss,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'feather_loss'. You can override using the
## `.groups` argument.fell_off <- group_by(sep_location,fell_off,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'fell_off'. You can override using the
## `.groups` argument.strangulation <- group_by(sep_location,strangulation,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'strangulation'. You can override using the
## `.groups` argument.flight_impairment <- group_by(sep_location,flight_impairment,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'flight_impairment'. You can override using
## the `.groups` argument.immobilization <- group_by(sep_location,immobilization,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'immobilization'. You can override using
## the `.groups` argument.other <- group_by(sep_location,other,location) %>%
summarise(n=n())## `summarise()` has grouped output by 'other'. You can override using the
## `.groups` argument.# Orders the effect frequencies
abrasion$abrasion <- factor(abrasion$abrasion, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
callous$callous <- factor(callous$callous, levels=c('Often (41-80%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
feather_loss$feather_loss <- factor(feather_loss$feather_loss, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
fell_off$fell_off <- factor(fell_off$fell_off, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
strangulation$strangulation <- factor(strangulation$strangulation, levels=c('Rare (<10%)','Never','NA','Unknown','Not sure'))
flight_impairment$flight_impairment <- factor(flight_impairment$flight_impairment, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
immobilization$immobilization <- factor(immobilization$immobilization, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
other$other <- factor(other$other, levels=c('Always (>80%)','Rare (<10%)','Never','NA','N/A','Not sure'))
###
# Creates labels for abrasion plot along with sample sizes
abrasion_vector <- c()
for (location_alt in sort(unique(abrasion$location))) {
abrasion_vector <- c(abrasion_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)),sep="\n"))
}
callous_vector <- c()
for (location_alt in sort(unique(callous$location))) {
callous_vector <- c(callous_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)), sep="\n"))
}
feather_loss_vector <- c()
for (location_alt in sort(unique(feather_loss$location))) {
feather_loss_vector <- c(feather_loss_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)), sep="\n"))
}
fell_off_vector <- c()
for (location_alt in sort(unique(fell_off$location))) {
fell_off_vector <- c(fell_off_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)),sep="\n"))
}
strangulation_vector <- c()
for (location_alt in sort(unique(strangulation$location))) {
strangulation_vector <- c(strangulation_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)), sep="\n"))
}
flight_impairment_vector <- c()
for (location_alt in sort(unique(flight_impairment$location))) {
flight_impairment_vector <- c(flight_impairment_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)), sep="\n"))
}
immobilization_vector <- c()
for (location_alt in sort(unique(immobilization$location))) {
immobilization_vector <- c(immobilization_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)), sep="\n"))
}
other_vector <- c()
for (location_alt in sort(unique(other$location))) {
other_vector <- c(other_vector,paste(location_alt,nrow(filter(sep_location,location==location_alt)), sep="\n"))
}
ggplot(data=abrasion, aes(fill=abrasion, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Abrasian Frequencies Using Glue By Location") +
scale_x_discrete(labels=abrasion_vector)
ggplot(data=callous, aes(fill=callous, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Callous Frequencies Using Glue By Location") +
scale_x_discrete(labels=callous_vector)
ggplot(data=feather_loss, aes(fill=feather_loss, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Feather Loss Frequencies Using Glue By Location") +
scale_x_discrete(labels=feather_loss_vector)
ggplot(data=fell_off, aes(fill=fell_off, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Frequencies Of Tag Falling Off By Location When Using Glue")) +
scale_x_discrete(labels=fell_off_vector)
ggplot(data=strangulation, aes(fill=strangulation, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Strangulation Frequencies Using Glue By Location")) +
scale_x_discrete(labels=strangulation_vector)
ggplot(data=flight_impairment, aes(fill=flight_impairment, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Flight Impairment Frequencies Using Glue By Location")) +
scale_x_discrete(labels=flight_impairment_vector)
ggplot(data=immobilization, aes(fill=immobilization, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Immobilization Frequencies Using Glue By Location")) +
scale_x_discrete(labels=immobilization_vector)
ggplot(data=other, aes(fill=other, x=location, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Other Frequencies Using Glue By Location")) +
scale_x_discrete(labels=other_vector)
LEG/TARSAL MOUNTS VISUALIZATIONS ###
leg_tarsal <- read_csv("/Users/Shared/Tagging/Final/leg_tarsal.csv")## Rows: 54 Columns: 19
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (18): species, device_type, material, why_material, methods, why_methods...
## dbl (1): id
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.sep_species <- separate_rows(leg_tarsal,species,sep=",")
sep_species <- merge(x=sep_species,y=new_orders,by.x="species",by.y="original_order")
sep_materials <- separate_rows(sep_species,material,sep=",")
ggplot(data=count(sep_materials,material),aes(x=material,y=(n/nrow(sep_species))))+
geom_col()+
ggtitle(sprintf("Material Use Frequencies When Tagging Using Leg/Tarsal Mounts, n=%s",nrow(sep_species)))+
ylab("frequency")
### IMPACT LEVELS OF DIFFERENT MATERIALS
for (material_alt in unique(sep_materials$material)) {
print(ggplot(data=count(filter(sep_materials,material==material_alt),impact_level),aes(x=impact_level,y=n/nrow(filter(sep_materials,material==material_alt))))+
geom_col()+
ggtitle(sprintf("Impact Levels of Using %s While Attaching Leg/Tarsal Mounts, n=%s",material_alt,nrow(filter(sep_materials,material==material_alt))))+
ylab("frequency")+
xlab("impact level"))}
print("Original Orders:")## [1] "Original Orders:"table(sep_materials$species,sep_materials$material)##
## cable glue metal plastic tape tesa tape
## anseriformes 0 0 0 2 0 0
## charadriiformes...alcids 0 2 0 7 0 0
## charadriiformes...gulls.and.terns 0 3 1 12 1 0
## charadriiformes...shorebirds 0 1 0 11 0 0
## gaviiformes 0 0 1 1 0 0
## gruiformes 0 0 0 5 0 0
## passeriformes 0 0 0 2 0 0
## phaethontiformes 0 0 1 0 0 0
## sphenisciformes 2 0 0 1 1 0
## strigiformes 0 0 0 1 0 0
## suliformes 0 0 1 3 0 1
##
## zip-tie
## anseriformes 1
## charadriiformes...alcids 3
## charadriiformes...gulls.and.terns 3
## charadriiformes...shorebirds 0
## gaviiformes 0
## gruiformes 0
## passeriformes 0
## phaethontiformes 0
## sphenisciformes 0
## strigiformes 0
## suliformes 0impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_materials$species)) {
order_data_materials <- filter(sep_materials, species==order_alt)
order_data_materials$impact_level <- factor(order_data_materials$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_materials$impact_level,order_data_materials$material))
print(order_alt)}##
## plastic zip-tie
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 1
## No impact 1 0
## Not sure 0 0
## N/A 0 0
## [1] "anseriformes"
##
## glue plastic zip-tie
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 2 7 3
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
## [1] "charadriiformes...alcids"
##
## glue metal plastic tape zip-tie
## Very high 0 0 0 0 0
## High 0 0 0 0 0
## Modest 0 0 1 0 0
## Low Impact 0 1 7 0 1
## No impact 3 0 4 1 2
## Not sure 0 0 0 0 0
## N/A 0 0 0 0 0
## [1] "charadriiformes...gulls.and.terns"
##
## glue plastic
## Very high 0 0
## High 0 0
## Modest 0 4
## Low Impact 1 5
## No impact 0 2
## Not sure 0 0
## N/A 0 0
## [1] "charadriiformes...shorebirds"
##
## metal plastic
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 0
## No impact 0 1
## Not sure 0 0
## N/A 0 0
## [1] "gaviiformes"
##
## plastic
## Very high 0
## High 0
## Modest 2
## Low Impact 2
## No impact 1
## Not sure 0
## N/A 0
## [1] "gruiformes"
##
## plastic
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 1
## Not sure 0
## N/A 0
## [1] "passeriformes"
##
## metal
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
## [1] "phaethontiformes"
##
## cable plastic tape
## Very high 0 0 0
## High 0 0 0
## Modest 1 1 1
## Low Impact 1 0 0
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
## [1] "sphenisciformes"
##
## plastic
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
## [1] "strigiformes"
##
## metal plastic tesa tape
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 0 2 0
## No impact 1 1 1
## Not sure 0 0 0
## N/A 0 0 0
## [1] "suliformes"print("New Orders:")## [1] "New Orders:"table(sep_materials$new_order,sep_materials$material)##
## cable glue metal plastic tape tesa tape zip-tie
## Accipitriformes 0 0 0 1 0 0 0
## Anseriformes 0 0 0 2 0 0 1
## Charadriiformes 0 6 1 30 1 0 6
## Gaviiformes 0 0 1 1 0 0 0
## Gruiformes 0 0 0 5 0 0 0
## Passeriformes 0 0 0 2 0 0 0
## Procellariformes 0 0 1 0 0 0 0
## Sphenisciformes 2 0 0 1 1 0 0
## Suliformes 0 0 1 3 0 1 0impact_levels <- c("Very High", "High", "Modest", "Low Impact", "No Impact", "Not Sure", "N/A")
for (order_alt in unique(sep_materials$new_order)) {
order_data_materials <- filter(sep_materials, new_order==order_alt)
order_data_materials$impact_level <- factor(order_data_materials$impact_level, order = TRUE, levels =c("Very high", "High", "Modest", "Low Impact", "No impact", "Not sure", "N/A"))
print(table(order_data_materials$impact_level,order_data_materials$material))
print(order_alt)}##
## plastic zip-tie
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 1
## No impact 1 0
## Not sure 0 0
## N/A 0 0
## [1] "Anseriformes"
##
## glue metal plastic tape zip-tie
## Very high 0 0 0 0 0
## High 0 0 0 0 0
## Modest 0 0 5 0 0
## Low Impact 3 1 19 0 4
## No impact 3 0 6 1 2
## Not sure 0 0 0 0 0
## N/A 0 0 0 0 0
## [1] "Charadriiformes"
##
## metal plastic
## Very high 0 0
## High 0 0
## Modest 0 0
## Low Impact 1 0
## No impact 0 1
## Not sure 0 0
## N/A 0 0
## [1] "Gaviiformes"
##
## plastic
## Very high 0
## High 0
## Modest 2
## Low Impact 2
## No impact 1
## Not sure 0
## N/A 0
## [1] "Gruiformes"
##
## plastic
## Very high 0
## High 0
## Modest 0
## Low Impact 1
## No impact 1
## Not sure 0
## N/A 0
## [1] "Passeriformes"
##
## metal
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
## [1] "Procellariformes"
##
## cable plastic tape
## Very high 0 0 0
## High 0 0 0
## Modest 1 1 1
## Low Impact 1 0 0
## No impact 0 0 0
## Not sure 0 0 0
## N/A 0 0 0
## [1] "Sphenisciformes"
##
## plastic
## Very high 0
## High 0
## Modest 0
## Low Impact 0
## No impact 1
## Not sure 0
## N/A 0
## [1] "Accipitriformes"
##
## metal plastic tesa tape
## Very high 0 0 0
## High 0 0 0
## Modest 0 0 0
## Low Impact 0 2 0
## No impact 1 1 1
## Not sure 0 0 0
## N/A 0 0 0
## [1] "Suliformes"### IMPACT LEVELS OF DIFFERENT MATERIALS BY EFFECTS
abrasion <- group_by(sep_materials,abrasion,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'abrasion'. You can override using the
## `.groups` argument.callous <- group_by(sep_materials,callous,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'callous'. You can override using the
## `.groups` argument.feather_loss <- group_by(sep_materials,feather_loss,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'feather_loss'. You can override using the
## `.groups` argument.fell_off <- group_by(sep_materials,fell_off,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'fell_off'. You can override using the
## `.groups` argument.strangulation <- group_by(sep_materials,strangulation,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'strangulation'. You can override using the
## `.groups` argument.flight_impairment <- group_by(sep_materials,flight_impairment,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'flight_impairment'. You can override using
## the `.groups` argument.immobilization <- group_by(sep_materials,immobilization,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'immobilization'. You can override using
## the `.groups` argument.other <- group_by(sep_materials,other,material) %>%
summarise(n=n())## `summarise()` has grouped output by 'other'. You can override using the
## `.groups` argument.# Orders the effect frequencies
abrasion$abrasion <- factor(abrasion$abrasion, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
callous$callous <- factor(callous$callous, levels=c('Often (41-80%)','Rare (<10%)','Never','NA','N/A','Unknown','Not sure'))
feather_loss$feather_loss <- factor(feather_loss$feather_loss, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
fell_off$fell_off <- factor(fell_off$fell_off, levels=c('Often (41-80%)','Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
strangulation$strangulation <- factor(strangulation$strangulation, levels=c('Rare (<10%)','Never','NA','Unknown','Not sure'))
flight_impairment$flight_impairment <- factor(flight_impairment$flight_impairment, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
immobilization$immobilization <- factor(immobilization$immobilization, levels=c('Sometimes (10-40%)','Rare (<10%)','Never','NA','Unknown','Not sure'))
other$other <- factor(other$other, levels=c('Always (>80%)','Rare (<10%)','Never','NA','N/A','Not sure'))
###
# Creates labels for abrasion plot along with sample sizes
abrasion_vector <- c()
for (material_alt in sort(unique(abrasion$material))) {
abrasion_vector <- c(abrasion_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)),sep="\n"))
}
callous_vector <- c()
for (material_alt in sort(unique(callous$material))) {
callous_vector <- c(callous_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
feather_loss_vector <- c()
for (material_alt in sort(unique(feather_loss$material))) {
feather_loss_vector <- c(feather_loss_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
fell_off_vector <- c()
for (material_alt in sort(unique(fell_off$material))) {
fell_off_vector <- c(fell_off_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)),sep="\n"))
}
strangulation_vector <- c()
for (material_alt in sort(unique(strangulation$material))) {
strangulation_vector <- c(strangulation_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
flight_impairment_vector <- c()
for (material_alt in sort(unique(flight_impairment$material))) {
flight_impairment_vector <- c(flight_impairment_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
immobilization_vector <- c()
for (material_alt in sort(unique(immobilization$material))) {
immobilization_vector <- c(immobilization_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
other_vector <- c()
for (material_alt in sort(unique(other$material))) {
other_vector <- c(other_vector,paste(material_alt,nrow(filter(sep_materials,material==material_alt)), sep="\n"))
}
ggplot(data=abrasion, aes(fill=abrasion, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Abrasian Frequencies Using Leg/Tarsal Mounts By Material") +
scale_x_discrete(labels=abrasion_vector)
ggplot(data=callous, aes(fill=callous, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Callous Frequencies Using Leg/Tarsal Mounts By Material") +
scale_x_discrete(labels=callous_vector)
ggplot(data=feather_loss, aes(fill=feather_loss, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle("Feather Loss Frequencies Using Leg/Tarsal Mounts By Material") +
scale_x_discrete(labels=feather_loss_vector)
ggplot(data=fell_off, aes(fill=fell_off, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Frequencies Of Leg/Tarsal Mounts Falling Off By Material")) +
scale_x_discrete(labels=fell_off_vector)
ggplot(data=strangulation, aes(fill=strangulation, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Strangulation Frequencies Using Leg/Tarsal Mounts By Material")) +
scale_x_discrete(labels=strangulation_vector)
ggplot(data=flight_impairment, aes(fill=flight_impairment, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Flight Impairment Frequencies Using Leg/Tarsal Mounts By Material")) +
scale_x_discrete(labels=flight_impairment_vector)
ggplot(data=immobilization, aes(fill=immobilization, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Immobilization Frequencies Using Leg/Tarsal Mounts By Material")) +
scale_x_discrete(labels=immobilization_vector)
ggplot(data=other, aes(fill=other, x=material, y=n)) +
geom_bar(position="fill", stat="identity") +
ggtitle(sprintf("Other Frequencies Using Leg/Tarsal Mounts By Material")) +
scale_x_discrete(labels=other_vector)