Create plot theme.

LGCtheme <- theme(strip.background = element_blank(),
        panel.grid = element_blank(),
        axis.title = element_text(size = 13),
        axis.text = element_text(size = 12), 
        legend.text = element_text(size = 12), 
        strip.text = element_text(size = 12, color = "black"))

Read in data

RR_long<-read_csv("US_RR_long.csv")
## Parsed with column specification:
## cols(
##   data = col_character(),
##   year = col_double(),
##   fishery_age = col_double(),
##   fisheries = col_double(),
##   PCAAwestern_age = col_double(),
##   PCAAwestern_origin = col_double()
## )

Reorganize data structure

total_fishery<-RR_long %>% 
  dplyr::select(data,year,fishery_age, fisheries) %>% 
  mutate(label = "Total Fishery")

western<-RR_long %>% 
  dplyr::select(data,year,PCAAwestern_age, PCAAwestern_origin) %>% 
  dplyr::rename("fishery_age" = "PCAAwestern_age", "fisheries" = "PCAAwestern_origin") %>% 
  mutate(label = "Western Origin")

stacked_long<-bind_rows(total_fishery, western)
stacked_long %>%   #dataset
  filter(data == "US_RR>177") %>%    #select only >177 data
  filter(fisheries > 0) %>%         #remove 0s
ggplot(aes(x=year, y = fishery_age, size = fisheries, fill = label)) +    #create ggplot object
  geom_point(pch = 21, color = "black") + LGCtheme +                      #add point outline and custom theme
  labs(x = "Year", y = "Age", size = "Biomass?", fill = "Type?", title = "US Rod and Reel Fishery (>177 cm)") +  #add titles
  ylim(0,20) +                      #change y axis 
  scale_fill_manual(values = c("white","black")) +     #set colors
  scale_size_continuous(breaks = c(100,300,500,700,900)) +    #set size legend breaks
  guides(fill = guide_legend(order = 1), size = guide_legend(order = 2))   #order legends

stacked_long %>% 
  filter(data == "US_RR_115_144") %>% 
  filter(fisheries > 0) %>% 
ggplot(aes(x=year, y = fishery_age, size = fisheries, fill = label)) + geom_point(pch = 21, color = "black") + LGCtheme + 
  labs(x = "Year", y = "Age", size = "Biomass?", fill = "Type?", title = "US Rod and Reel Fishery (115-144 cm)") +
  ylim(0,20) + scale_fill_manual(values = c("white","black")) + scale_size_continuous(breaks = c(1000,2000,3000,4000,5000)) +
  guides(fill = guide_legend(order = 1), size = guide_legend(order = 2))

stacked_long %>% 
  filter(data == "US_RR_66_114") %>% 
  filter(fisheries > 0) %>% 
ggplot(aes(x=year, y = fishery_age, size = fisheries, fill = label)) + geom_point(pch = 21, color = "black") + LGCtheme + 
  labs(x = "Year", y = "Age", size = "Biomass?", fill = "Type?", title = "US Rod and Reel Fishery (66-114 cm)") +
  ylim(0,20) + scale_fill_manual(values = c("white","black")) + scale_size_continuous(breaks = c(1000,2000,3000,4000,5000)) +
  guides(fill = guide_legend(order = 1), size = guide_legend(order = 2))

toplabs<-as_labeller(c("US_RR_66_114" = "66-114 cm","US_RR_115_144" = "115-144 cm","US_RR>177" = ">177 cm"))

stacked_long %>% 
  mutate(data = fct_relevel(data,"US_RR_66_114","US_RR_115_144","US_RR>177")) %>% 
  filter(fisheries > 0) %>% 
ggplot(aes(x=year, y = fishery_age, size = fisheries, fill = label)) + geom_point(pch = 21, color = "black") + LGCtheme + 
  labs(x = "Year", y = "Age", size = "Biomass?", fill = "Type?") +
  ylim(0,20) + scale_fill_manual(values = c("white","black")) + scale_size_continuous(breaks = c(100,500,1000,2000,4000,6000)) +
  facet_wrap(~data, labeller = toplabs) + guides(fill = guide_legend(order = 1), size = guide_legend(order = 2))