ordered and re-ran figures

code/ms_figures/Fig1_fisheries_results.R

@@ -252,57 +252,3 @@ g <- gridExtra::grid.arrange(g1, g2, g3, g4, layout_matrix=layout_matrix, height
 ggsave(g, filename=file.path(plotdir, "Fig1_fisheries_results.png"), 
        width=6.5, height=8, units="in", dpi=600)
 
-
-
-
-
-
-
-
-
-
-# 
-# Plot national results
-##############################
-# 
-# # National per capita trends
-# cdata_stats <- cdata %>%
-#   # Classify countries as experiencing increasing/descreasing per capita supply
-#   select(rcp, scenario, country, iso3, year, npeople, meat_kg_person) %>% 
-#   filter(year %in% c(2020, 2050, 2100)) %>% 
-#   group_by(rcp, scenario, country, iso3) %>% 
-#   mutate(trend=ifelse(meat_kg_person > meat_kg_person[year==2020], "increase", "decrease")) %>% 
-#   ungroup() %>% 
-#   filter(year!=2020) %>%
-#   # Tally countries experiencing increasing/decreasing per capita supply
-#   group_by(rcp, scenario, year, trend) %>%
-#   summarise(ncountries=n(),
-#             npeople=sum(npeople)) %>% 
-#   ungroup() %>% 
-#   # Reduce to just decreasing counts
-#   filter(trend=="decrease")
-# 
-# # Plot data
-# g3 <- ggplot(cdata_stats, aes(x=year, y=ncountries, fill=rcp)) +
-#   facet_grid(~scenario) +
-#   geom_bar(stat="identity", position = "dodge") +
-#   labs(y="Number of nations\nwith decreased seafood production per capita") +
-#   theme_bw()
-# g3
-# 
-# # Plot data
-# g4 <- ggplot(cdata_stats, aes(x=year, y=npeople/1e9, fill=rcp)) +
-#   facet_grid(~scenario) +
-#   geom_bar(stat="identity", position = "dodge") +   
-#   labs(y="Billions of people\nwith decreased seafood production per capita") +
-#   theme_bw()
-# g4
-# 
-#   
-#   
-# 
-# 
-# 
-# 
-# 
-

code/ms_figures/Fig2_mariculture_results.R

@@ -333,50 +333,3 @@ g
 ggsave(g, filename=file.path(plotdir, "Fig2_mariculture_results.png"), 
        width=6.5, height=3.5, units="in", dpi=600)
 
-
-
-
-
-
-
-
-# # Read forage fish availability data
-# ffdata <- read.csv("data/feed_params/processed/forage_fish_availability.csv", as.is=T)
-
-# # WC/interaction plot
-# ############################################
-# 
-# # Format finfish data
-# ffdata_use <- ffdata %>% 
-#   # Mark big-picture scenarios
-#   mutate(scenario=ifelse(mgmt_scenario=="BAU fisheries management" & feed_scenario=="BAU feed use", "Business-as-usual", NA), 
-#          scenario=ifelse(mgmt_scenario=="BAU fisheries management" & feed_scenario=="Reformed feed use", "Fisheries limiting", scenario),
-#          scenario=ifelse(mgmt_scenario=="Reformed fisheries management" & feed_scenario=="Reformed feed use", "Progressive reforms", scenario)) %>% 
-#   # Reduce
-#   filter(!is.na(scenario)) %>% 
-#   select(rcp, scenario, year, catch_ff_mt_maq) %>% 
-#   # Factor new scenario
-#   mutate(scenario=factor(scenario, levels=c("Business-as-usual", "Fisheries limiting", "Progressive reforms")))
-# 
-# # Plot data
-# g5 <- ggplot(ffdata_use, aes(x=year, y=catch_ff_mt_maq/1e6, color=rcp, linetype=scenario)) +
-#   geom_line() +
-#   # Axis
-#   lims(y=c(0,NA)) +
-#   scale_x_continuous(breaks=c(2012, seq(2020, 2100, 10))) +
-#   # Labels
-#   labs(x="", y="Catch directed to mariculture\nfeed ingredients (millions of mt)", tag="e") +
-#   # Legends
-#   scale_color_manual(name="", values=RColorBrewer::brewer.pal(4, name="RdBu") %>% rev()) +
-#   scale_linetype_manual(name="", values=c(3,2,1)) +
-#   # Theme
-#   theme_bw() + big_plot_theme +
-#   theme(legend.position="bottom", 
-#         legend.box = "vertical",
-#         legend.spacing=unit(0.01, 'cm'),
-#         legend.box.spacing = unit(0.01, 'cm'),
-#         legend.key.size = unit(0.4, 'cm'), 
-#         legend.margin=unit(0, "cm"))
-# g5
-
-

code/ms_figures/Fig4_national_production.R

@@ -151,10 +151,3 @@ ggsave(g, filename=file.path(plotdir, "Fig4_national_production.png"),
 
 
 
-
-
-
-
-
-
-

code/ms_figures/FigS10_species_development.R

@@ -81,7 +81,7 @@ g <- ggplot(data, mapping=aes(x=fao_mt_yr+0.001, y=reorder(comm_name, fao_mt_yr)
 g
 
 # Export plot
-ggsave(g, filename=file.path(plotdir, "FigS5_species_development.png"), 
+ggsave(g, filename=file.path(plotdir, "FigS10_species_development.png"), 
        width=6.5, height=8.5, units="in", dpi=600)
 
 

code/ms_figures/FigS11_harvest_length_linf_perc_boxplots.R

@@ -0,0 +1,59 @@
+
+# Clear workspace
+rm(list = ls())
+
+# Setup
+################################################################################
+
+# Packages
+library(stringr)
+library(readxl)
+library(tidyverse)
+
+# Directories
+plotdir <- "figures"
+datadir <- "data/feed_params/processed"
+
+# Read data
+data <- read.csv(file=file.path(datadir, "FAO_harvest_size_as_prop_of_linf_data.csv"), as.is=T)
+
+# Calculate median
+stats <- data1 %>% 
+  group_by(type) %>% 
+  summarize(n=n(), 
+            harvest_perc_linf=median(harvest_perc_linf))
+
+# Plot data
+################################################################################
+
+# Setup theme
+my_theme <- theme(axis.text=element_text(size=8),
+                  axis.title=element_text(size=10),
+                  plot.title=element_text(size=12),
+                  legend.position = "none",
+                  panel.grid.major = element_blank(), 
+                  panel.grid.minor = element_blank(),
+                  panel.background = element_blank(), 
+                  axis.line = element_line(colour = "black"))
+
+# Plot
+g <- ggplot(data, aes(x=type, y=harvest_perc_linf, fill=type)) +
+  geom_boxplot() +
+  labs(x="", y="Harvest size as a\npercentage of asymptotic length") +
+  geom_hline(yintercept=100, linetype="dotted") +
+  geom_text(data=stats, mapping=aes(x=type, y=harvest_perc_linf,
+                                    label=paste0(round(harvest_perc_linf), "%")), vjust=-0.5) +
+  theme_bw() + my_theme
+g  
+
+# Export
+ggsave(g, filename=file.path(plotdir, "FigS11_harvest_sizes_as_linf_perc.png"), 
+       width=4.5, height=4.5, units="in", dpi=600)
+
+
+
+
+
+
+
+

code/ms_figures/FigS13_S24_fcr_fmfo_trends.R

@@ -227,12 +227,12 @@ g <- ggplot(fifos_g, aes(x=year, y=fifo)) +
 g
 
 # Export plot
-ggsave(g, filename=file.path(plotdir, "figure_fifo_projections.png"), 
+ggsave(g, filename=file.path(plotdir, "FigS24_fifo_trends_projections.png"), 
        width=6.5, height=4, units="in", dpi=600)
 
 # Export data
 fifo_preds <- pred_df1
-save(fifos_g, fifo_proj_g, fifo_preds, file=file.path(feeddir, "FigS24_fifo_trends_projections.Rdata"))
+save(fifos_g, fifo_proj_g, fifo_preds, file=file.path(feeddir, "fifo_trends_projections.Rdata"))
 
 
 # Build output table

code/ms_figures/FigS15_arag_sat_calc_example.R

@@ -174,7 +174,7 @@ g <- grid.arrange(sst_plot, sal_plot, si_plot, po4_plot, alk_plot, dic_plot, ara
              layout_matrix=matrix(c(1:6,7,7), byrow=T, ncol=2), heights=c(rep(0.2,3), 0.4))
 
 # Export
-ggsave(g, filename=file.path(plotdir, "FigS10_arag_sat_calc_example.png"), 
+ggsave(g, filename=file.path(plotdir, "FigS15_arag_sat_calc_example.png"), 
        width=6.5, height=6.5, units="in", dpi=600)
 
 

code/ms_figures/FigS17_eezs_analyzed.R

@@ -72,7 +72,7 @@ g <- ggplot(eezs) +
   scale_fill_discrete(name="") +
   theme_bw() + my_theme + 
   theme(legend.position = "bottom")
-g
+#g
 
 # Plot data (point version)
 # g <- ggplot(eezs_pts) +
@@ -84,7 +84,7 @@ g
 # g
 
 # Export plot
-ggsave(g, filename=file.path(plotdir, "figure_eezs_evaluated.png"), 
+ggsave(g, filename=file.path(plotdir, "FigS17_figure_eezs_evaluated.png"), 
        width=6.5, height=3.75, units="in", dpi=600)
 
 

code/ms_figures/FigS18_use_constraints.R

@@ -121,7 +121,7 @@ g4
 g <- gridExtra::grid.arrange(g1,g2,g3,g4, ncol=2)
 
 # Export
-ggsave(g, filename=file.path(plotdir, "FigS17_use constraints.png"), 
+ggsave(g, filename=file.path(plotdir, "FigS18_use constraints.png"), 
        width=6.5, height=4, units="in", dpi=600)
 
 

code/ms_figures/FigS1_mariculture_results_sens_analysis..R

@@ -309,8 +309,6 @@ g6 <- ggplot(pdata_use, aes(x=period, y=meat_mt/1e6, fill=rcp)) +
 g6
 
 
-
-
 # Merge and export
 ############################################
 
@@ -327,53 +325,6 @@ g <- gridExtra::grid.arrange(g1, g2, g3, g4, g5, g6,
 g
 
 # Export figure
-ggsave(g, filename=file.path(plotdir, "Fig2_mariculture_results_sens_analysis.png"), 
+ggsave(g, filename=file.path(plotdir, "FigS1_mariculture_results_sens_analysis.png"), 
        width=6.5, height=3.5, units="in", dpi=600)
 
-
-
-
-
-
-
-
-# # Read forage fish availability data
-# ffdata <- read.csv("data/feed_params/processed/forage_fish_availability.csv", as.is=T)
-
-# # WC/interaction plot
-# ############################################
-# 
-# # Format finfish data
-# ffdata_use <- ffdata %>% 
-#   # Mark big-picture scenarios
-#   mutate(scenario=ifelse(mgmt_scenario=="BAU fisheries management" & feed_scenario=="BAU feed use", "Business-as-usual", NA), 
-#          scenario=ifelse(mgmt_scenario=="BAU fisheries management" & feed_scenario=="Reformed feed use", "Fisheries limiting", scenario),
-#          scenario=ifelse(mgmt_scenario=="Reformed fisheries management" & feed_scenario=="Reformed feed use", "Progressive reforms", scenario)) %>% 
-#   # Reduce
-#   filter(!is.na(scenario)) %>% 
-#   select(rcp, scenario, year, catch_ff_mt_maq) %>% 
-#   # Factor new scenario
-#   mutate(scenario=factor(scenario, levels=c("Business-as-usual", "Fisheries limiting", "Progressive reforms")))
-# 
-# # Plot data
-# g5 <- ggplot(ffdata_use, aes(x=year, y=catch_ff_mt_maq/1e6, color=rcp, linetype=scenario)) +
-#   geom_line() +
-#   # Axis
-#   lims(y=c(0,NA)) +
-#   scale_x_continuous(breaks=c(2012, seq(2020, 2100, 10))) +
-#   # Labels
-#   labs(x="", y="Catch directed to mariculture\nfeed ingredients (millions of mt)", tag="e") +
-#   # Legends
-#   scale_color_manual(name="", values=RColorBrewer::brewer.pal(4, name="RdBu") %>% rev()) +
-#   scale_linetype_manual(name="", values=c(3,2,1)) +
-#   # Theme
-#   theme_bw() + big_plot_theme +
-#   theme(legend.position="bottom", 
-#         legend.box = "vertical",
-#         legend.spacing=unit(0.01, 'cm'),
-#         legend.box.spacing = unit(0.01, 'cm'),
-#         legend.key.size = unit(0.4, 'cm'), 
-#         legend.margin=unit(0, "cm"))
-# g5
-
-

code/ms_figures/FigS21_dist_shore_wb_data.R

@@ -145,6 +145,6 @@ g2 <- ggplot() +
 g <- grid.arrange(g0, g1, g2, nrow=3)
 
 # Export
-ggsave(g, filename=file.path(plotdir, "figure_costs_cdist_wages_diesel.png"), 
+ggsave(g, filename=file.path(plotdir, "FigS21_costs_cdist_wages_diesel.png"), 
        width=6.5, height=11.25, units="in", dpi=600)
 

code/ms_figures/FigS22_wage_labor_costs.R

@@ -107,6 +107,6 @@ g2 <- ggplot() +
 g <- grid.arrange(g1, g2, nrow=2)
 
 # Export
-ggsave(g, filename=file.path(plotdir, "figure_farm_wage_labor_costs.png"), 
+ggsave(g, filename=file.path(plotdir, "FigS22_farm_wage_labor_costs.png"), 
        width=6.5, height=7.5, units="in", dpi=600)
 

code/ms_figures/FigS23_forage_fish_supply.R

@@ -13,7 +13,7 @@ plotdir <- "figures"
 datadir <- "data/feed_params/processed"
 
 # Export data
-data_orig <- read.csv(file.path(outdir, "forage_fish_availability.csv"), as.is=T)
+data_orig <- read.csv(file.path(datadir, "forage_fish_availability.csv"), as.is=T)
 
 # Reduce
 data <- data_orig %>% 
@@ -58,7 +58,7 @@ g <- ggplot(data, aes(x=year, y=catch_ff_mt_maq/1e6, color=rcp, linetype=mgmt_sc
 g
 
 # Export plot
-ggsave(g, filename=file.path(plotdir, "FigS24_forage_fish_supply.png"), 
+ggsave(g, filename=file.path(plotdir, "FigS23_forage_fish_supply.png"), 
        width=6.5, height=3.5, units="in", dpi=600)
 
 

code/ms_figures/FigS26_bivalve_carrying_capacity.R

@@ -58,6 +58,6 @@ g <- ggplot(data, aes(x=log_ctrt, y=log_ctpt, size=cultured_mt_sqkm, color=impac
 g
 
 # Export plot
-ggsave(g, filename=file.path(plotdir, "FigS19_bivavle_carrying_capacity.png"), 
+ggsave(g, filename=file.path(plotdir, "FigS26_bivavle_carrying_capacity.png"), 
        width=6.5, height=4.5, units="in", dpi=600)
 

code/ms_figures/FigS27_bivalve_meow_analysis.R

@@ -169,7 +169,7 @@ g3 <- ggplot(results, aes(x=biv_mt_sqkm, fill=dev_scenario)) +
 g3
 
 # Export plot
-ggsave(g2, filename=file.path(plotdir, "Fig26_bivalve_meow_analysis.png"), 
+ggsave(g2, filename=file.path(plotdir, "FigS27_bivalve_meow_analysis.png"), 
        width=6.5, height=3.25, units="in", dpi=600)
 
 

code/ms_figures/FigS2_global_production_sens_analysis.R

@@ -118,5 +118,5 @@ g <- gridExtra::grid.arrange(g1, g2, g3, nrow=1, widths=c(0.4, 0.3, 0.3))
 g
 
 # Export plot
-ggsave(g, filename=file.path(plotdir, "FigSX_global_production_sens_analysis.png"), 
+ggsave(g, filename=file.path(plotdir, "FigS2_global_production_sens_analysis.png"), 
        width=6.5, height=2.5, units="in", dpi=600)

code/ms_figures/FigS3_national_production_sens_analysis.R

@@ -146,6 +146,6 @@ g2
 g <- gridExtra::grid.arrange(g1, g2, nrow=2, heights=c(0.48, 0.52))
 
 # Export data
-ggsave(g, filename=file.path(plotdir, "Fig4_national_production_sens_analysis.png"), 
+ggsave(g, filename=file.path(plotdir, "FigS3_national_production_sens_analysis.png"), 
        width=6.5, height=5, units="in", dpi=600)