论文
Meta-analysis reveals less sensitivity of non-native animals than natives to extreme weather worldwide
https://www.nature.com/articles/s41559-023-02235-1
论文中提供作图用到的原始数据，我们可以试着复现一下论文中的图。今天的推文试着复现一下论文中的figure1
image.png
先画一个地图
代码语言：javascript复制library(tidyverse)
library(readxl)
world.dat<-map_data("world")
ggplot()
geom_polygon(data=world.dat,aes(x=long,y=lat,group=group),
fill="#dedede")
theme_bw()
scale_y_continuous(expand = expansion(mult=c(0,0)))
scale_x_continuous(expand = expansion(add=c(0,0)))
theme(panel.border = element_blank(),
panel.grid = element_blank(),
axis.text = element_blank(),
axis.ticks = element_blank())
labs(x=NULL,y=NULL)-> world.map
world.map
figure1a代码添加采样地点
代码语言：javascript复制fig1a.dat<-read_excel("data/20231127/41559_2023_2235_MOESM8_ESM.xlsx",
sheet = "Fig1A")
fig1a.dat
world.map
geom_point(data=fig1a.dat,aes(x=Longitude,y=Latitude,color=sufferedECE))
scale_color_manual(values = c("Cold"="#b7f8ff",
"Drought"="#ae965b",
"Flood"="#4d4dff",
"Heatwave"="#ff6f6f",
"Storm"="#ffa64d"),
name="EWEs")
guides(color=guide_legend(override.aes = list(size=5)))
theme(legend.position = c(0.1,0.3))
image.png
figure1b 代码和1a基本一致
代码语言：javascript复制fig1b.dat<-read_excel("data/20231127/41559_2023_2235_MOESM8_ESM.xlsx",
sheet = "Fig1B")
fig1b.dat
world.map
geom_point(data=fig1b.dat,aes(x=Longitude,y=Latitude,color=sufferedECE))
scale_color_manual(values = c("Cold"="#b7f8ff",
"Drought"="#ae965b",
"Flood"="#4d4dff",
"Heatwave"="#ff6f6f",
"Storm"="#ffa64d"),
name="EWEs")
guides(color=guide_legend(override.aes = list(size=5)))
theme(legend.position = "none")
image.png
figure1c d
代码语言：javascript复制
fig1c.dat<-read_excel("data/20231127/41559_2023_2235_MOESM8_ESM.xlsx",
sheet = "Fig1C") %>%
mutate(sufferedECE=factor(sufferedECE,levels = c("Heatwave","Cold","Storm","Flood","Drought")))
fig1c.dat
pc<-ggplot(data=fig1c.dat,aes(x=sufferedECE,y=number_effct_sizes))
geom_col(aes(fill=sufferedECE))
scale_fill_manual(values = c("Cold"="#b7f8ff",
"Drought"="#ae965b",
"Flood"="#4d4dff",
"Heatwave"="#ff6f6f",
"Storm"="#ffa64d"),
name="EWEs")
theme_bw()
theme(legend.position = "none",
panel.border = element_blank(),
panel.grid = element_blank(),
axis.line = element_line(),
axis.text.x = element_blank(),
axis.ticks.x = element_blank())
scale_y_continuous(limits = c(0,500),
breaks = seq(0,500,by=100),
labels = c(0,100,"",300,"",500),
expand = expansion(mult = c(0,0)))
geom_text(aes(label=c(84,47,31,24,21)),vjust=-1)
annotate(geom = "text",x=2,y=350,label="Number of studies",hjust=0)
annotate(geom = "segment",x=2,y=330,xend = 2,yend=250,
arrow=arrow(angle = 20,type="closed",length = unit(3,'mm')))
labs(x=NULL,y="Number of sampleneffect sizes")
pc
fig1d.dat<-read_excel("data/20231127/41559_2023_2235_MOESM8_ESM.xlsx",
sheet = "Fig1D") %>%
mutate(sufferedECE=factor(sufferedECE,levels = c("Heatwave","Cold","Storm","Flood","Drought")))
fig1d.dat
pd<-ggplot(data=fig1d.dat,aes(x=sufferedECE,y=number_effct_sizes))
geom_col(aes(fill=sufferedECE))
scale_fill_manual(values = c("Cold"="#b7f8ff",
"Drought"="#ae965b",
"Flood"="#4d4dff",
"Heatwave"="#ff6f6f",
"Storm"="#ffa64d"),
name="EWEs")
theme_bw()
theme(legend.position = "none",
panel.border = element_blank(),
panel.grid = element_blank(),
axis.line = element_line(),
axis.text.x = element_blank(),
axis.ticks.x = element_blank())
scale_y_continuous(limits = c(0,2000),
breaks = seq(0,2000,by=500),
labels = c(0,500,"",1500,""),
expand = expansion(mult = c(0,0)))
geom_text(aes(label=c(74,32,129,47,76)),vjust=-1)
labs(x=NULL,y="Number of sampleneffect sizes")
pd
pc pd
image.png
figure1e
代码语言：javascript复制fig1e.dat<-read_excel("data/20231127/41559_2023_2235_MOESM8_ESM.xlsx",
sheet = "Fig1E") %>%
rename("group"="...1") %>%
pivot_longer(!group)
fig1e.dat
pe<-ggplot(data=fig1e.dat,aes(x=name,y=value))
geom_bar(stat="identity",
aes(fill=group),
position = "dodge")
theme_bw()
theme(panel.border = element_blank(),
panel.grid = element_blank(),
axis.line.y = element_line(),
axis.ticks.x = element_blank(),
axis.text.x = element_text(angle=90,hjust=1),
legend.position = c(0.8,0.8))
scale_y_continuous(limits = c(0,36),
expand = expansion(mult=c(0,0)),
breaks = seq(0,35,by=5),
labels = c(0,5,"",15,"",25,"",35))
scale_fill_manual(values = c("nonnative_prop"="#7fb3ff",
"native_prop"="#00008a"),
name="",
labels=c("Native","Non-native"))
labs(x=NULL,y="Proportion of samplen(effect sizes(%)")
pe
image.png
5个图组合到一起
代码语言：javascript复制part1<-pa pc pb pd
plot_layout(ncol = 2,nrow=2,widths = c(3,1))
part1/pe
plot_layout(nrow=2,heights = c(2,1))
plot_annotation(tag_levels = 'a')
image.png
示例数据可以到论文中下载，或者给推文打赏1元获取我整理的示例数据和代码
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