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smoothing effects for badr analysis
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@mabecker89
mabecker89 committed Mar 20, 2024
1 parent aabfda6 commit 90c8288
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166 changes: 139 additions & 27 deletions src/projects/OSM BADR/02_figures-for-report.R
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Original file line number Diff line number Diff line change
Expand Up @@ -11,10 +11,7 @@
#-----------------------------------------------------------------------------------------------------------------------

# Attach packages
library(readr)
library(dplyr)
library(stringr)
library(tidyr)
library(tidyverse)
library(ggplot2)
library(grid)
library(gridExtra)
Expand All @@ -24,7 +21,7 @@ library(gridExtra)
g_drive <- "G:/Shared drives/ABMI Camera Mammals/"

# Import data
buffer <- read_csv(paste0(g_drive, "results/osm/2021-2022_osm_buffer_treatment_results.csv")) |>
buffer <- read_csv(paste0(g_drive, "Results/OSM BADR/2021-2022_osm_buffer_treatment_results_new.csv")) |>
mutate(fine_scale = str_extract(treatment, "\\d+"),
treatment = str_remove(treatment, "\\d+"),
treatment = str_to_title(str_remove(treatment, " buffer $")),
Expand All @@ -36,7 +33,7 @@ buffer <- read_csv(paste0(g_drive, "results/osm/2021-2022_osm_buffer_treatment_r
vegetation == "treedlow20" ~ "Treed Lowland"
))

on_off <- read_csv(paste0(g_drive, "results/osm/2021-2022_osm-on-off_treatment_results.csv")) |>
on_off <- read_csv(paste0(g_drive, "Results/OSM BADR/2021-2022_osm-on-off_treatment_results_new.csv")) |>
mutate(fine_scale = case_when(
str_detect(treatment, "On") ~ "On",
str_detect(treatment, "Off") ~ "Off",
Expand All @@ -49,7 +46,7 @@ on_off <- read_csv(paste0(g_drive, "results/osm/2021-2022_osm-on-off_treatment_r
vegetation == "treedlow20" ~ "Treed Lowland"
))

on_off_2021 <- read_csv(paste0(g_drive, "results/osm/2021_on-off_treatment_results.csv")) |>
on_off_2021 <- read_csv(paste0(g_drive, "Results/OSM BADR/2021_on-off_treatment_results.csv")) |>
mutate(fine_scale = case_when(
str_detect(treatment, "On") ~ "On",
str_detect(treatment, "Off") ~ "Off",
Expand All @@ -64,7 +61,7 @@ on_off_2021 <- read_csv(paste0(g_drive, "results/osm/2021_on-off_treatment_resul

# JEM means

jem_means <- read_csv(paste0(g_drive, "data/processed/osm/2021-2022_osm_mean_jem_density_values.csv")) |>
jem_means <- read_csv(paste0(g_drive, "data/processed/osm/2021-2022_osm_mean_jem_density_values_new.csv")) |>
filter(!vegetation == "wetland") |>
mutate(Habitat = case_when(
vegetation == "decidmix40" ~ "Deciduous Mixedwood",
Expand All @@ -90,6 +87,19 @@ buffer_jem <- jem_means |>
fine_scale = factor(fine_scale, levels = c("Road 10", "Road 30", "Road 100", "Road 300",
"Plant/Mine 10", "Plant/Mine 30", "Plant/Mine 100", "Plant/Mine 300")))

# Smoothed Results

on_off_smooth <- read_csv(paste0(g_drive, "Results/OSM BADR/OSM mammals 2021 2022 Smoothed On Off HF.csv")) |>
select(common_name = Sp, treatment = Treat, mean_density = Mean, lci_density = q5, uci_density = q95) |>
mutate(fine_scale = case_when(
str_detect(treatment, "On") ~ "On",
str_detect(treatment, "Off") ~ "Off",
TRUE ~ "")) |>
mutate(treatment = str_to_title(str_remove(treatment, " Off$| On$"))) |>
mutate(treatment = factor(treatment,
levels = c("Reference", "Dense Linear Features", "Low Activity Well Pads", "High Activity In Situ")))


#-----------------------------------------------------------------------------------------------------------------------

# Make plots
Expand All @@ -106,25 +116,25 @@ plot_on_off <- on_off |>
geom_linerange(aes(ymin = lci_density, ymax = uci_density, color = treatment),
linewidth = 0.5, position = position_dodge(width = 0.75)) +
geom_point(data = (on_off_jem |>
filter(common_name == "WhitetailedDeer")),
filter(common_name == "White.tailed.Deer")),
#Habitat == "Deciduous Mixedwood")),
aes(x = fine_scale, y = mean_density, color = treatment),
size = 2,
alpha = 0.15,
position = position_jitterdodge(jitter.width = 0.2)) +
geom_point(data = (on_off_2021 |>
filter(common_name == "White-tailed Deer")),
aes(color = treatment),
#color = "blue",
size = 4,
alpha = 0.4,
shape = 17,
position = position_dodge(width = 0.75)) +
#geom_point(data = (on_off_2021 |>
# filter(common_name == "White-tailed Deer")),
# aes(color = treatment),
# #color = "blue",
# size = 4,
# alpha = 0.4,
# shape = 17,
# position = position_dodge(width = 0.75)) +
scale_color_manual(values = c("Dark Green", "#FFC300", "#FF5733", "#C70039")) +
#scale_color_brewer(palette = "Set1") +
scale_y_sqrt() +
theme_minimal() +
coord_cartesian(ylim = c(0, 8)) +
coord_cartesian(ylim = c(0, 20)) +
labs(x = "Placement",
y = expression(Density~(individuals~per~km^2))) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5),
Expand All @@ -144,9 +154,6 @@ plot_on_off <- on_off |>

plot_on_off

ggsave(paste0(g_drive, "results/osm/figures/Presentation/wtd_dm.png"),
plot_on_off, height = 5, width = 7.5, dpi = 500, bg = "white")

ggsave(paste0(g_drive, "results/osm/figures/2022/Presentation/wtd_on-ff_sqrt.png"),
plot_on_off, height = 5, width = 8, dpi = 500, bg = "white")

Expand Down Expand Up @@ -198,6 +205,111 @@ full_plot <- grid.arrange(plot_on_off, plot_buffer)

ggsave(paste0(g_drive, "results/osm/figures/wtd_full_sqrt.png"), full_plot, height = 8, width = 8, dpi = 500, bg = "white")


ref <- on_off_smooth |>
filter(treatment == "Reference") |>
select(-fine_scale) |>
mutate(distance = 51.5)

pm_dist_smooth <- read_csv(paste0(g_drive, "Results/OSM BADR/OSM mammals 2021 2022 Smoothed Plant mine distance.csv")) |>
mutate(treatment = "Plant/Mine") |>
select(common_name = Sp, treatment, distance = Dist, mean_density = Mean, lci_density = q5, uci_density = q95)

dist_smooth <- read_csv(paste0(g_drive, "Results/OSM BADR/OSM mammals 2021 2022 Smoothed Road distance.csv")) |>
mutate(treatment = "Roads") |>
select(common_name = Sp, treatment, distance = Dist, mean_density = Mean, lci_density = q5, uci_density = q95) |>
bind_rows(pm_dist_smooth) |>
mutate(distance = case_when(
distance == "0-20m" ~ 300,
distance == "20-50m" ~ 270,
distance == "50-200m" ~ 220,
distance == ">200m" ~ 130
))

# Plots of Smoothed Results

plot_on_off_smooth <- on_off_smooth |>
filter(common_name == "White-tailed Deer") |>
ggplot(aes(x = fine_scale, y = mean_density)) +
geom_point(aes(color = treatment),
size = 3.5,
position = position_dodge(width = 0.6)) +
geom_linerange(aes(ymin = lci_density, ymax = uci_density, color = treatment),
linewidth = 0.5, position = position_dodge(width = 0.6)) +
scale_color_manual(values = c("Dark Green", "#FFC300", "#FF5733", "#C70039")) +
#scale_color_brewer(palette = "Set1") +
theme_minimal() +
#scale_y_sqrt() +
coord_cartesian(ylim = c(0, 2)) +
labs(x = "",
y = expression(Relative~Density~(Individuals~per~km^2))) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, size = 12),
#axis.title.x = element_text(size = 13, margin = margin(0.4, 0, 0, 0, unit = "cm"), hjust = 0.72),
axis.title.x = element_blank(),
axis.title.y = element_text(size = 10, margin = margin(0, 0.4, 0, 0, unit = "cm")),
#strip.text = element_text(size = 13),
legend.position = "top",
legend.title = element_blank(),
legend.margin = margin(0, 0, 0, 0),
legend.spacing.x = unit(0.05, "cm"),
legend.text = element_text(size = 12),
axis.ticks = element_blank(),
panel.grid.major.y = element_line(linewidth = 0.5, color = "grey80"),
panel.grid.major.x = element_blank())

plot_on_off_smooth

ggsave(paste0(g_drive, "Results/OSM BADR/Figures/2022/White-tailed Deer On Off Smoothed Sqrt.png"),
plot_on_off_smooth, height = 5, width = 8, dpi = 500, bg = "white")

# Smoothed Dist Treatment

plot_dist_smooth <- dist_smooth |>
filter(common_name == "White-tailed Deer") |>
ggplot(aes(x = distance, y = mean_density)) +
geom_point(aes(color = treatment),
size = 3.5) +
geom_linerange(aes(ymin = lci_density, ymax = uci_density, color = treatment),
linewidth = 0.5) +
scale_color_manual(values = c("#80461B", "#CD7F32")) +
scale_x_continuous(breaks = c(130, 220, 270, 300),
labels = c(">200m", "50-200m", "30m", "10m")) +
geom_point(data = ref |> filter(common_name == "White-tailed Deer"),
aes(x = distance, y = mean_density),
color = "darkgreen",
size = 3.5) +
geom_linerange(data = ref |> filter(common_name == "White-tailed Deer"),
aes(ymin = lci_density, ymax = uci_density),
color = "darkgreen",
linewidth = 0.5) +
coord_cartesian(ylim = c(0, 4),
xlim = c(0, 310)) +
theme_minimal() +
labs(x = "",
y = expression(Relative~Density~(Individuals~per~km^2))) +
guides(color = guide_legend(reverse=TRUE)) +
theme(axis.text.x = element_text(angle = 0, hjust = 0.5, size = 12),
#axis.title.x = element_text(size = 15, margin = margin(0.6, 0, 0, 0, unit = "cm"), hjust = 0.72),
axis.title.x = element_blank(),
axis.title.y = element_text(size = 10, margin = margin(0, 0.4, 0, 0, unit = "cm")),
strip.text = element_text(size = 13),
legend.position = "top",
legend.title = element_blank(),
legend.margin = margin(0, 0, 0, 0),
legend.spacing.x = unit(0.05, "cm"),
legend.text = element_text(size = 12),
axis.ticks = element_blank(),
panel.grid.major.y = element_line(linewidth = 0.5, color = "grey80"),
panel.grid.major.x = element_blank(),
panel.grid.minor.x = element_blank())

plot_dist_smooth

# Join together
full_plot <- grid.arrange(plot_on_off_smooth, plot_dist_smooth)

ggsave(paste0(g_drive, "Results/OSM BADR/Figures/2022/WTD Full Smooth.png"), full_plot, height = 8, width = 8, dpi = 500, bg = "white")

#-----------------------------------------------------------------------------------------------------------------------

# Moose
Expand Down Expand Up @@ -292,8 +404,8 @@ ggsave(paste0(g_drive, "results/osm/figures/moose_full_sqrt.png"), full_plot, he
# Canada Lynx

plot_on_off <- on_off |>
filter(common_name == "Canada Lynx",
Habitat == "Treed Lowland") |>
filter(common_name == "Canada Lynx") |>
#Habitat == "Treed Lowland") |>
mutate(lci_density = ifelse(mean_density > 0, lci_density, 0),
uci_density = ifelse(mean_density > 0, uci_density, 0)) |>
filter(common_name == "Canada Lynx") |>
Expand All @@ -306,8 +418,8 @@ plot_on_off <- on_off |>
geom_linerange(aes(ymin = lci_density, ymax = uci_density, color = treatment),
linewidth = 0.5, position = position_dodge(width = 0.75)) +
geom_point(data = (on_off_jem |>
filter(common_name == "CanadaLynx",
Habitat == "Treed Lowland")),
filter(common_name == "Canada.Lynx")),
#Habitat == "Treed Lowland")),
aes(x = fine_scale, y = mean_density, color = treatment),
size = 2,
alpha = 0.15,
Expand All @@ -331,8 +443,8 @@ plot_on_off <- on_off |>
legend.text = element_text(size = 12),
axis.ticks = element_blank(),
panel.grid.major.y = element_line(linewidth = 0.5, color = "grey80"),
panel.grid.major.x = element_blank())
#facet_grid(. ~ Habitat, scales = "free_x", space = "free")
panel.grid.major.x = element_blank()) +
facet_grid(. ~ Habitat, scales = "free_x", space = "free")

ggsave(paste0(g_drive, "results/osm/figures/Presentation/lynx_tl_02.png"),
plot_on_off, height = 5, width = 7.5, dpi = 500, bg = "white")
Expand Down
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