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本節(jié)來復現(xiàn)nature communications上一篇文章中地圖的繪制方法，下面來進行復現(xiàn)過程，由于未找到作者提供的數(shù)據(jù)信息，小編自己構建了繪圖文件因此結果與原圖有出入僅供參考。整張圖均使用R代碼進行繪制

Land-use diversity predicts regional bird taxonomic and functional richness worldwide

論文原圖

復現(xiàn)圖

加載R包

# install.packages("rnaturalearthdata")

# install.packages("tidygeocoder")
library(tidygeocoder)
library(tidyverse)
library(sf)
library(camcorder)
library(scico)
library(rnaturalearth)
library(terra)
library(tidyterra)
library(geodata)
library(cowplot)
library(ggsci)

繪制點圖

df1 <- read_tsv("data.xls") %>% filter(type=="Taxonomic richness") %>% 
  select(5:9) %>% 
  group_by(REALM) %>% 
  slice_head(n=1)

df1$REALM <- factor(df$REALM,levels = c("Nearctic","Palearctic","Indomalayan","Neotropic","Afrotropic","Australasia"))  

plot1 <- df1 %>% ggplot(aes(y = fct_rev(REALM))) +
  theme_bw()+
  geom_errorbarh(aes(xmin=Lower_ci,xmax=Upper_ci),height=0.1) +
  geom_point(aes(x=visregFit,color=REALM),fill="black",size=3,show.legend = F) +
  labs(x="Taxonomic richness",y=NULL)+
  scale_color_npg()+
  theme(axis.ticks.y= element_blank(),
        axis.title.y= element_blank(),
        axis.title.x = element_text(color="black",size=8,face="bold"),
        axis.text.y=element_text(color="black",size=8,face="bold"),
        axis.text.x=element_text(color="black",size=8,face="bold"))


df2 <- read_tsv("data.xls") %>%
  filter(type=="Functional richness") %>% 
  select(5:9) %>% 
  group_by(REALM) %>% 
  slice_head(n=1)

df2$REALM <- factor(df$REALM,levels = c("Nearctic","Palearctic","Indomalayan","Neotropic","Afrotropic","Australasia"))  

plot2 <- df2 %>% ggplot(aes(y = fct_rev(REALM))) +
  theme_bw()+
  geom_errorbarh(aes(xmin=Lower_ci,xmax=Upper_ci),height=0.1) +
  geom_point(aes(x=visregFit,color=REALM),fill="black",size=3,show.legend = F) +
  labs(x="Functional richness",y=NULL)+
  scale_color_npg()+
  theme(axis.ticks.y= element_blank(),
        axis.title.y= element_blank(),
        axis.title.x = element_text(color="black",size=8,face="bold"),
        axis.text.y=element_text(color="black",size=8,face="bold"),
        axis.text.x=element_text(color="black",size=8,face="bold"))

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