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dicamba_paper_plots.R
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# R scripts used to create plots from my publication doi:10.1017/wsc.2021.76
# FIGURE 2 ---------------------------------------
correlation_plot <- df_pooled %>%
ggplot(aes(x = Biomass, y = area_cm)) +
geom_point(size = 3, aes(color = damage)) +
theme_light() +
theme(legend.position = "bottom",
axis.line = element_line(color = "black", size = .5),
legend.title = element_blank()) +
labs(x = "Biomass (g)", y = expression(" Plant area - cm"^2),
color = "Visual estimation:") +
geom_smooth(method="lm", formula= (y ~ log(x)), se=FALSE, linetype = 1, size = 1) +
ylim(c(0,75)) +
scale_shape_discrete(labels = c("Dead","Alive")) +
scale_color_manual(values = c("#009E73", "#F0E442","#D55E00")) +
theme(
strip.text.x = element_text(size = 14, color = "black", face = "bold"),
strip.text.y = element_text(size = 14, color = "black", face = "bold"),
axis.text = element_text(size = 14),
axis.title = element_text(size = 14),
legend.text = element_text(size = 14),
legend.title = element_text(size = 14, face = "bold"))
bayes_plot <- df_pooled %>%
ggplot(aes(x = Biomass, y = area_cm)) +
geom_point(size = 3, aes(color = Classification)) +
theme_light() +
theme(legend.position = "bottom",
axis.line = element_line(color = "black", size = .5),
legend.title = element_blank()) +
labs(x = "Biomass (g)", y = expression(" Plant area - cm"^2),
color = "Classification:") +
geom_smooth(method="lm", formula= (y ~ log(x)), se=FALSE, linetype = 1, size = 1) +
ylim(c(0,75)) +
scale_color_manual(values = c("#009E73","#D55E00"))+
theme(
strip.text.x = element_text(size = 14, color = "black", face = "bold"),
strip.text.y = element_text(size = 14, color = "black", face = "bold"),
axis.text = element_text(size = 14),
axis.title = element_text(size = 14),
legend.text = element_text(size = 14),
legend.title = element_text(size = 14, face = "bold"))
plot_grid(correlation_plot, bayes_plot, labels = "AUTO")
ggsave("dicamba_bayes.tiff", width = 38, height = 15, units = "cm", dpi = 300)
# FIGURE 3 -------------------------------------
# THIS IS ON A SEPARATE FILE NAMED DR_ANALYSIS.RMD
## PLOT A --------------------------------
dicamba_24D <- tukey_final %>%
ggplot(aes(x = rate_X, y = control, fill = Treatment)) +
geom_col(position = position_dodge(0.5), width = .4) +
geom_errorbar(aes(ymin=Min,ymax=Max),
position = position_dodge(0.5), width = .2) +
theme_light() +
labs(x = "Herbicide rate", y = "Control (%)") +
theme(legend.position = "bottom") +
geom_text(aes(label= groups, y = Max+8), size = 5, position = position_dodge(0.5)) +
ylim(c(0,110)) +
theme(
strip.text.x = element_text(size = 16, color = "black", face = "bold"),
strip.text.y = element_text(size = 16, color = "black", face = "bold"),
axis.text = element_text(size = 16, face = "bold"),
axis.title = element_text(size = 16, face = "bold"),
legend.text = element_text(size = 16),
legend.title = element_text(size = 16, face = "bold"),
text = element_text(family = "Times New Roman")) +
scale_fill_manual(values = c("#D55E00", "#CC79A7", "#E69F00","#F0E442"))
## PLOT B --------------------------------
glufosinate <- tukey_706_18$means %>%
rownames_to_column("Treatment") %>%
full_join(tukey_706_18$groups) %>%
ggplot(aes(x = reorder(Treatment, -Control), y = Control, fill = Treatment)) +
geom_col(width = 0.2) +
theme_light() +
theme(legend.position = "none") +
geom_text(aes(label= groups, y = Control+std+5), size = 5, position = position_dodge(0.5)) +
theme(
strip.text.x = element_text(size = 16, color = "black", face = "bold"),
strip.text.y = element_text(size = 16, color = "black", face = "bold"),
axis.text = element_text(size = 16, face = "bold"),
axis.title = element_text(size = 16, face = "bold"),
legend.text = element_text(size = 16),
legend.title = element_text(size = 16, face = "bold"),
text = element_text(family = "Times New Roman")) +
geom_errorbar(aes(ymin=Control-std,ymax=Control+std),
position = position_dodge(0.5), width = .15) +
labs(y = "Control (%)", x = " Treatment") +
scale_fill_manual(values = c("#E69F00", "#56B4E9", "#009E73",
"#F0E442"))
## COMBINE PLOTS A+B -------------------------
library(patchwork)
dicamba_24D / glufosinate +
plot_annotation(tag_levels = 'A') &
theme(plot.tag = element_text(face = "bold", size = 16))
ggsave("glufosinate_vs_dicamba_2.tiff", width = 16, height = 8, units = "in", dpi = 300)
## PLOT C ------------------------------------
par(mfrow=c(1,1))
tiff("field_dicamba_DR.tiff", width = 10, height = 6, units = 'in', res = 300)
plot(drc_model, bp=.2, bty="l",
ylab="Control (%)",
xlab="Dicamba (g a.e /ha)",
main="Dicamba field dose response",
xlim=c(0,100000),
col = T,
ylim = c(0,110),
broken = F,
pch = 1,
lwd = 2.5,
legendPos = c(100000,60))
arrows(560, 100, 560, -1, code=0, lty=2, col="blue") # field rate line
arrows(361.2035, 50, 361.2035, -1, code=0, lty=1, col="black") # 14 DAT ed50
arrows(0.1, 50, 361.2035, 50, code=0, lty=1, col="black") # 50%
arrows(372.2829, 50, 372.2829, -1, code=0, lty=1, col="red") # 14 DAT ed50
arrows(361.2035, 50, 361.2035, -1, code=0, lty=1, col="black") # 14 DAT ed50
arrows(638.3069, 50, 638.3069, -1, code=0, lty=1, col="green") # 14 DAT ed50
arrows(0.1, 50, 638.3069, 50, code=0, lty=1, col="green") # 50%
arrows(0.1, 50, 372.2829, 50, code=0, lty=1, col="red") # 50%
arrows(0.1, 50, 361.2035, 50, code=0, lty=1, col="black") # 50%
dev.off()
## FIGURE 6 -----------------
#ggridge plots
library(ggridges)
df_plot <- df_pooled %>%
mutate(population = as.character(population),
population = case_when(population == "RxR-2" ~ "Resistant",
population == "CHR" ~ "Resistant",
population == "F1-3" ~ "F1 S♀ x R♂",
population == "F1-1" ~ "F1 R♀ x S♂",
population == "BC-1" ~ "BC-1",
population == "BC-2" ~ "BC-2",
population == "WUS" ~ "Sensitive",
population == "F2" ~ "F2"),
population = factor(population, levels = c("Sensitive", "Resistant", "BC-2", "BC-1", "F1 S♀ x R♂","F1 R♀ x S♂","F2")))
area_ridge <- df_plot %>%
filter(population != "RxR-6") %>%
ggplot(aes(x = log(area_cm), y = population, fill = population)) +
geom_density_ridges(stat="binline",bins = 25, alpha = .5) +
theme_ridges(center_axis_labels = TRUE) +
theme(legend.position = "none", legend.title = element_blank(),
axis.line = element_line(color="black", size = .5),
plot.title = element_text(hjust = 0.5)) +
labs(x = expression ("Log plant area - "~cm^2), y = "Population")
biomass_ridge <- df_plot %>%
filter(population != "RxR-6") %>%
ggplot(aes(x = log(Biomass), y = population, fill = population)) +
geom_density_ridges(stat="binline",bins = 25, alpha = .5) +
theme_ridges(center_axis_labels = TRUE) +
theme(legend.position = "none", legend.title = element_blank(),
axis.line = element_line(color="black", size = .5),
plot.title = element_text(hjust = 0.5),
axis.text.y = element_blank()) +
labs(x = "Log Biomass - g", y = "")
library(patchwork)
area_ridge + biomass_ridge + plot_annotation(tag_levels = 'A') &
theme(plot.tag = element_text(size = 12, face = "bold"),
text = element_text('Times New Roman'))
ggsave("ridge_plot.tiff", units = "in", height = 6, width = 14, dpi = 300)