diff --git a/.DS_Store b/.DS_Store
index 8d7f8ea..b2c14d5 100644
Binary files a/.DS_Store and b/.DS_Store differ
diff --git a/code/.DS_Store b/code/.DS_Store
index b77b6c8..863790d 100644
Binary files a/code/.DS_Store and b/code/.DS_Store differ
diff --git a/code/ms_figures/Fig1_fisheries_results.R b/code/ms_figures/Fig1_fisheries_results.R
index e492471..a1b58be 100644
--- a/code/ms_figures/Fig1_fisheries_results.R
+++ b/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
-# 
-#   
-#   
-# 
-# 
-# 
-# 
-# 
-
diff --git a/code/ms_figures/Fig2_mariculture_results.R b/code/ms_figures/Fig2_mariculture_results.R
index f456c0b..e2b5196 100644
--- a/code/ms_figures/Fig2_mariculture_results.R
+++ b/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
-
-
diff --git a/code/ms_figures/Fig4_national_production.R b/code/ms_figures/Fig4_national_production.R
index 2997d2f..a5ba4c9 100644
--- a/code/ms_figures/Fig4_national_production.R
+++ b/code/ms_figures/Fig4_national_production.R
@@ -151,10 +151,3 @@ ggsave(g, filename=file.path(plotdir, "Fig4_national_production.png"),
 
 
 
-
-
-
-
-
-
-
diff --git a/code/ms_figures/FigS10_species_development.R b/code/ms_figures/FigS10_species_development.R
index 3ee746e..f6bff54 100644
--- a/code/ms_figures/FigS10_species_development.R
+++ b/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)
 
 
diff --git a/code/ms_figures/FigS11_harvest_length_linf_perc_boxplots.R b/code/ms_figures/FigS11_harvest_length_linf_perc_boxplots.R
new file mode 100644
index 0000000..67e920f
--- /dev/null
+++ b/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)
+
+
+
+
+
+
+
+
diff --git a/code/ms_figures/FigS13_S24_fcr_fmfo_trends.R b/code/ms_figures/FigS13_S24_fcr_fmfo_trends.R
index 5adf63a..35bd2bd 100644
--- a/code/ms_figures/FigS13_S24_fcr_fmfo_trends.R
+++ b/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
diff --git a/code/ms_figures/FigS15_arag_sat_calc_example.R b/code/ms_figures/FigS15_arag_sat_calc_example.R
index 8a83c83..01de252 100644
--- a/code/ms_figures/FigS15_arag_sat_calc_example.R
+++ b/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)
 
 
diff --git a/code/ms_figures/FigS17_eezs_analyzed.R b/code/ms_figures/FigS17_eezs_analyzed.R
index 9cc3bb1..43f201f 100644
--- a/code/ms_figures/FigS17_eezs_analyzed.R
+++ b/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)
 
 
diff --git a/code/ms_figures/FigS18_use_constraints.R b/code/ms_figures/FigS18_use_constraints.R
index 41695ee..b688d4a 100644
--- a/code/ms_figures/FigS18_use_constraints.R
+++ b/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)
 
 
diff --git a/code/ms_figures/FigS1_mariculture_results_sens_analysis..R b/code/ms_figures/FigS1_mariculture_results_sens_analysis..R
index e8057ec..4353eb6 100644
--- a/code/ms_figures/FigS1_mariculture_results_sens_analysis..R
+++ b/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
-
-
diff --git a/code/ms_figures/FigS21_dist_shore_wb_data.R b/code/ms_figures/FigS21_dist_shore_wb_data.R
index b672cf7..09c0345 100644
--- a/code/ms_figures/FigS21_dist_shore_wb_data.R
+++ b/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)
 
diff --git a/code/ms_figures/FigS22_wage_labor_costs.R b/code/ms_figures/FigS22_wage_labor_costs.R
index 843a53d..c023af1 100644
--- a/code/ms_figures/FigS22_wage_labor_costs.R
+++ b/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)
 
diff --git a/code/ms_figures/FigS23_forage_fish_supply.R b/code/ms_figures/FigS23_forage_fish_supply.R
index bc6f58f..ecb0d4c 100644
--- a/code/ms_figures/FigS23_forage_fish_supply.R
+++ b/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)
 
 
diff --git a/code/ms_figures/FigS26_bivalve_carrying_capacity.R b/code/ms_figures/FigS26_bivalve_carrying_capacity.R
index f25cbc6..37a3b60 100644
--- a/code/ms_figures/FigS26_bivalve_carrying_capacity.R
+++ b/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)
 
diff --git a/code/ms_figures/FigS27_bivalve_meow_analysis.R b/code/ms_figures/FigS27_bivalve_meow_analysis.R
index a5f3751..7ecbbe8 100644
--- a/code/ms_figures/FigS27_bivalve_meow_analysis.R
+++ b/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)
 
 
diff --git a/code/ms_figures/FigS2_global_production_sens_analysis.R b/code/ms_figures/FigS2_global_production_sens_analysis.R
index 12b55f5..e067491 100644
--- a/code/ms_figures/FigS2_global_production_sens_analysis.R
+++ b/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)
diff --git a/code/ms_figures/FigS3_national_production_sens_analysis.R b/code/ms_figures/FigS3_national_production_sens_analysis.R
index f22ba6f..fb0ea2c 100644
--- a/code/ms_figures/FigS3_national_production_sens_analysis.R
+++ b/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)
 
diff --git a/code/ms_figures/FigS4-S5_global_pop_size_sens_analysis.R b/code/ms_figures/FigS4-S5_global_pop_size_sens_analysis.R
index 68e3cf0..8059ee0 100644
--- a/code/ms_figures/FigS4-S5_global_pop_size_sens_analysis.R
+++ b/code/ms_figures/FigS4-S5_global_pop_size_sens_analysis.R
@@ -69,38 +69,38 @@ my_theme <-  theme(axis.text=element_text(size=6),
 
 
 # Plot three sectors
-g1 <- ggplot(data1, aes(x=period, y=meat_kg_person, fill=sector)) +
+g1 <- ggplot(data2, aes(x=period, y=meat_kg_person, fill=sector)) +
   facet_grid(rcp~pop_size_perc) +
   geom_bar(stat="identity", alpha=0.5) +
   # Add reference line
   geom_hline(yintercept=curr_kg_person, linetype="dashed", color="black", lwd=0.3) +
   # Labels
-  labs(x="Period", y="Seafood production per capita\n(kg of meat per person per year)", title="Progressive reforms") +
+  labs(x="Period", y="Seafood production per capita\n(kg of meat per person per year)", title="Business-as-usual") +
   # Legend
   scale_fill_manual(name="", values=c("darkgreen", "salmon", "navy")) +
   # Theme
   theme_bw() + my_theme
 g1
-
+  
 # Export
-ggsave(g1, filename=file.path(plotdir, "FigSX_global_pop_size_sens_analysis_reforms.png"), 
+ggsave(g1, filename=file.path(plotdir, "FigS4_global_pop_size_sens_analysis_bau.png"), 
        width=6.5, height=4.5, units="in", dpi=600)
 
 # Plot three sectors
-g2 <- ggplot(data2, aes(x=period, y=meat_kg_person, fill=sector)) +
+g2 <- ggplot(data1, aes(x=period, y=meat_kg_person, fill=sector)) +
   facet_grid(rcp~pop_size_perc) +
   geom_bar(stat="identity", alpha=0.5) +
   # Add reference line
   geom_hline(yintercept=curr_kg_person, linetype="dashed", color="black", lwd=0.3) +
   # Labels
-  labs(x="Period", y="Seafood production per capita\n(kg of meat per person per year)", title="Business-as-usual") +
+  labs(x="Period", y="Seafood production per capita\n(kg of meat per person per year)", title="Progressive reforms") +
   # Legend
   scale_fill_manual(name="", values=c("darkgreen", "salmon", "navy")) +
   # Theme
   theme_bw() + my_theme
 g2
-  
+
 # Export
-ggsave(g2, filename=file.path(plotdir, "FigSX_global_pop_size_sens_analysis_bau.png"), 
+ggsave(g2, filename=file.path(plotdir, "FigS5_global_pop_size_sens_analysis_reforms.png"), 
        width=6.5, height=4.5, units="in", dpi=600)
   
diff --git a/code/ms_figures/FigS6_population_growth.R b/code/ms_figures/FigS6_population_growth.R
index 97fd397..c4a2321 100644
--- a/code/ms_figures/FigS6_population_growth.R
+++ b/code/ms_figures/FigS6_population_growth.R
@@ -95,7 +95,7 @@ g2
 g <- gridExtra::grid.arrange(g1, g2, ncol=2, widths=c(0.4,0.6))
 
 # Export
-ggsave(g, filename=file.path(plotdir, "FigS1_population_growth.png"), 
+ggsave(g, filename=file.path(plotdir, "FigS6_population_growth.png"), 
        width=6.5, height=3, units="in", dpi=600)
 
 
diff --git a/code/ms_figures/figure_fcr_fmfo_trends.R b/code/ms_figures/figure_fcr_fmfo_trends.R
deleted file mode 100644
index 1816f2b..0000000
--- a/code/ms_figures/figure_fcr_fmfo_trends.R
+++ /dev/null
@@ -1,255 +0,0 @@
-
-# Clear workspace
-rm(list = ls())
-
-# Turn off scientific notation
-options(scipen=999)
-
-# Setup
-################################################################################
-
-# Packages
-library(tidyverse)
-library(grid)
-library(gridExtra)
-
-# Directories
-datadir <- "data/species/data"
-feeddir <- "data/feed_params/processed"
-plotdir <- "figures"
-tabledir <- "tables"
-
-# Read data
-load(file.path(datadir, "aquaculture_species_key.Rdata"))
-load(file.path(feeddir, "Tacon_Metian_2008_and_2015_fcr_fmfo_data.Rdata"))
-
-
-# Build data
-################################################################################
-
-# Feed groups in analysis
-feed_groups <- sort(unique(data$feed_group))
-
-# Merge T&M 2015 Table 1 and T&M 2008 Table 4
-
-# Groups
-sort(unique(tm08_t4$group))
-sort(unique(tm15_t1$group))
-
-# T&M 2008 Table 4
-tm08_t4_format <- tm08_t4 %>% 
-  spread(key="ingredient", value="value") %>% 
-  rename(fmfo_perc_source=source, fo_perc="Fish oil", fm_perc="Fishmeal") %>% 
-  select(group, year, fm_perc, fo_perc, fmfo_perc_source) %>% 
-  mutate(group=recode(group, 
-                      "Chinese carp species"="Chinese fed carps",
-                      "Milkfish (Chanos chanos)"="Milkfish"))
-
-# T&M 2015 Table 1
-tm15_t1_format <- tm15_t1 %>% 
-  select(group, year, percent_fed, fcr) %>% 
-  mutate(group=recode(group, 
-                      "Catfishes"="Catfish",
-                      "Other freshwater & diadromous fishes"="Freshwater fish"),
-         fcr_source="Tacon & Metian 2015") %>% 
-  select(group, year, percent_fed, fcr, fcr_source)
-  
-# Merge data
-fdata_wide <- tm15_t1_format %>% 
-  full_join(tm08_t4_format) %>% 
-  arrange(group, year) %>% 
-  mutate(fifo=fcr * ( (fm_perc/100+fo_perc/100) / (0.224 + 0.0485) ) )
-  
-
-# Convert to long for plotting
-fdata_long <- fdata_wide %>% 
-  # Remove columns
-  select(-c(fcr_source, fmfo_perc_source)) %>% 
-  # Convert wide to long
-  gather(key="parameter", value="value", 3:ncol(.)) %>% 
-  # Format groups
-  mutate(group=recode(group, 
-                      "Freshwater fish"="Misc freshwater fish",
-                      "Marine fish"="Misc marine fish")) %>% 
-  filter(group %in% feed_groups) %>% 
-  # Format parameter names
-  mutate(parameter_label=recode(parameter, 
-                          "fcr"="Feed conversion\nrate (FCR)",
-                          "fifo"="Fish In, Fish Out\n(FIFO) ratio",
-                          "fm_perc"="Percentage of feed\ncomposed of fishmeal (%)",
-                          "fo_perc"="Percentage of feed\ncomposed of fish oil (%)", 
-                          "percent_fed"="Percentage of\nproduction fed"),
-         parameter_label=factor(parameter_label, levels=c("Percentage of\nproduction fed",
-                                              "Fish In, Fish Out\n(FIFO) ratio", 
-                                              "Feed conversion\nrate (FCR)",
-                                              "Percentage of feed\ncomposed of fishmeal (%)",
-                                              "Percentage of feed\ncomposed of fish oil (%)"))) %>% 
-  # Format values
-  mutate(value_label=ifelse(parameter %in% c("fcr", "fifo"), round(value,2), paste0(round(value,2), "%"))) %>% 
-  # Remove NA values
-  filter(!is.na(value))
-
-# End point
-ts_end <- fdata_long %>% 
-  group_by(group, parameter) %>% 
-  filter(year==max(year))
-
-# Subset FIFO time series
-fifo <- fdata_long %>% 
-  filter(parameter=="fifo")
-
-
-# Plot data
-################################################################################
-
-# Setup theme
-my_theme <- theme(axis.text=element_text(size=5),
-                  # axis.title=element_text(size=9),
-                  strip.text = element_text(size=5),
-                  panel.grid.major = element_blank(), 
-                  panel.grid.minor = element_blank(),
-                  panel.background = element_blank(), 
-                  axis.title = element_blank(),
-                  axis.line = element_line(colour = "black"),
-                  axis.text.x = element_text(angle = 90, hjust = 0.5))
-
-# Plot
-g <- ggplot(fdata_long, aes(x=year, y=value, color=parameter_label)) +
-  # Facetting
-  facet_grid(parameter_label ~ group, scales="free") +
-  # Trend lines
-  geom_line(lwd=0.3) +
-  # Add and label end points
-  geom_point(data=ts_end, mapping=aes(x=year, y=value), size=0.8) +
-  ggrepel::geom_text_repel(data=ts_end, mapping=aes(x=year, y=value, label=value_label), size=2) +
-  # Horizontal line in FIFO
-  geom_hline(data = fifo, aes(yintercept = 1), linetype="dotted", color="grey70") +
-  # Small things
-  labs(x="", y="") +
-  # xlim(c(1995, 2025)) +
-  scale_x_continuous(breaks=seq(1995,2025,5)) +
-  theme_bw() + my_theme +
-  theme(legend.position = "none")
-g  
-
-# Export figure
-ggsave(g, filename=file.path(plotdir, "figure_fcr_fmfo_trends.png"), 
-       width=6.5, height=5.5, units="in", dpi=600)
-
-
-# Plot data
-################################################################################
-
-# Projection year
-proj_years <- c(2030, 2050)
-
-# Subset FIFOs
-fifos <- fdata_long %>% 
-  filter(parameter=="fifo")
-
-# Plotting parameters
-par(mfrow=c(2,4))
-
-# Loop through and fit exponential decline
-groups <- sort(unique(fifos$group))
-fifo_proj <- data.frame(group=groups, fifo2030=NA, fifo2050=NA)
-for(i in 1:length(groups)){
-  
-  # Subset data
-  group_i <- groups[i]
-  sdata <- filter(fifos, group==group_i)
-  
-  # Plot data
-  plot(value ~ year, sdata, xlim=c(2000, max(proj_years)), ylim=c(0, 5),
-       main=group_i, xlab="", ylab="FIFO")
-  abline(h=1)
-  
-  # Fit model
-  lmfit <- lm(log(value) ~ year, sdata)
-  a <- exp(coef(lmfit)[1])
-  b <- coef(lmfit)[2]
-  
-  # Plot fit
-  curve(a*exp(b*x), from=2000, to=max(proj_years), n=100, add=T)
-  
-  # Plot and record prediction
-  pred <- as.numeric(exp(predict(lmfit, data.frame(year=proj_years))))
-  points(x=proj_years, y=pred, pch=16, cex=2)
-  fifo_proj$fifo2030[i] <- pred[1]
-  fifo_proj$fifo2050[i] <- pred[2]
-  
-  # Record predictions for GGPLOT graph
-  yrs <- 2000:2050
-  fifo_preds <- as.numeric(exp(predict(lmfit, data.frame(year=yrs))))
-  pred_df <- data.frame(group=group_i, year=yrs, fifo=fifo_preds)
-  if(i==1){pred_df1 <- pred_df}else{pred_df1 <- rbind(pred_df, pred_df1)}
-  
-}
-
-
-# Build output table
-################################################################################
-
-my_theme <- theme(panel.grid.major = element_blank(), 
-                  panel.grid.minor = element_blank(),
-                  panel.background = element_blank(), 
-                  axis.title.x=element_blank(), 
-                  axis.line = element_line(colour = "black"),
-                  axis.text.x = element_text(angle = 90, vjust = 0.5))
-
-# Reshape for plotting
-fifos_g <- fifos %>%
-  select(group, year, value) %>%
-  rename(fifo=value)
-
-fifo_proj_g <- fifo_proj %>% 
-  gather(key="year", value="fifo", 2:3) %>% 
-  mutate(year=recode(year, "fifo2030"="2030", "fifo2050"="2050") %>% as.numeric(),
-         fifo_label=round(fifo, digits=3))
-
-# Plot data
-g <- ggplot(fifos_g, aes(x=year, y=fifo)) +
-  facet_wrap(~group, ncol=4) +
-  geom_point() +
-  # Add regression lines
-  geom_line(data=pred_df1) +
-  # Add prediction point
-  geom_point(data=fifo_proj_g, col="red") +
-  # Add horizontal line
-  geom_hline(yintercept = 1, linetype="dotted", color="grey40") +
-  ggrepel::geom_text_repel(data=fifo_proj_g, 
-                           mapping=aes(label=fifo_label), 
-                           color="red", size=2.5) +
-  # Little things
-  xlim(2000,2050) +
-  labs(x="", y='"Fish In, Fish Out"\n(FIFO) ratio') +
-  theme_bw() + my_theme
-g
-
-# Export plot
-ggsave(g, filename=file.path(plotdir, "figure_fifo_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, "fifo_trends_projections.Rdata"))
-
-
-# Build output table
-################################################################################
-
-# Buildt table
-out_table <- ts_end %>% 
-  select(group, parameter, value_label) %>% 
-  spread(key="parameter", value="value_label") %>% 
-  select(fcr, fm_perc, fo_perc, fifo) %>% 
-  left_join(fifo_proj)
-
-# Export table
-write.csv(out_table, file=file.path(tabledir, "TableS6_fifo_fcr_fmfo_stats.csv"), row.names=F)
-
-
-
-
-
-
diff --git a/code/ms_figures/FigS25_global_aq_trends.R b/code/ms_figures/old_figures/FigS25_global_aq_trends.R
similarity index 100%
rename from code/ms_figures/FigS25_global_aq_trends.R
rename to code/ms_figures/old_figures/FigS25_global_aq_trends.R
diff --git a/data/.DS_Store b/data/.DS_Store
index 10e65e8..3cd8aee 100644
Binary files a/data/.DS_Store and b/data/.DS_Store differ
diff --git a/data/feed_params/.DS_Store b/data/feed_params/.DS_Store
index 47c3a6a..4d30b8f 100644
Binary files a/data/feed_params/.DS_Store and b/data/feed_params/.DS_Store differ
diff --git a/data/feed_params/Step2_format_harvest_sizes.R b/data/feed_params/Step2_format_harvest_sizes.R
index a267003..2dc8fb4 100644
--- a/data/feed_params/Step2_format_harvest_sizes.R
+++ b/data/feed_params/Step2_format_harvest_sizes.R
@@ -61,8 +61,8 @@ freeR::check_names(data$species)
 fl_vonb <- freeR::fishlife(data$species)
 
 # FishBase
-fb_vonb <- freeR::fishbase(dataset="vonb", species=data$species, level="species")
-fb_lw <- freeR::fishbase(dataset="lw", species=data$species, level="species")
+fb_vonb <- freeR::fishbase(dataset="vonb", species=data$species, level="species", cleaned = T)
+fb_lw <- freeR::fishbase(dataset="lw", species=data$species, level="species", cleaned = T)
 
 # FishBase species medians
 
@@ -109,6 +109,8 @@ data1 <- data %>%
 # Sample size
 table(data1$type)
 
+# Export
+write.csv(data1, file=file.path(outdir, "FAO_harvest_size_as_prop_of_linf_data.csv"), row.names=F)
 
 # Plot data
 ################################################################################
@@ -139,9 +141,7 @@ g <- ggplot(data1, aes(x=type, y=harvest_perc_linf, fill=type)) +
   theme_bw() + my_theme
 g  
 
-# Export
-ggsave(g, filename=file.path(plotdir, "figure_harvest_sizes_as_linf_perc.png"), 
-       width=4.5, height=4.5, units="in", dpi=600)
+
 
 
 
diff --git a/data/feed_params/processed/.DS_Store b/data/feed_params/processed/.DS_Store
new file mode 100644
index 0000000..5008ddf
Binary files /dev/null and b/data/feed_params/processed/.DS_Store differ
diff --git a/data/feed_params/processed/FAO_2013_2017_maq_prod_averages_by_country.csv b/data/feed_params/processed/FAO_2013_2017_maq_prod_averages_by_country.csv
index d43f9a4..30c9688 100644
--- a/data/feed_params/processed/FAO_2013_2017_maq_prod_averages_by_country.csv
+++ b/data/feed_params/processed/FAO_2013_2017_maq_prod_averages_by_country.csv
@@ -59,7 +59,7 @@
 "French Polynesia","PYF","Mollusca",882.12191,38012100.3
 "French Polynesia","PYF","Pisces",6.12,89386.5333333333
 "Gambia","GMB","Mollusca",20,10000
-"Georgia","GEO","Pisces",20,1e+05
+"Georgia","GEO","Pisces",20,100000
 "Germany","DEU","Mollusca",5059.25,8643820.75
 "Germany","DEU","Pisces",21,93318
 "Greece","GRC","Mollusca",8773.33363636364,3959983.81818182
diff --git a/data/feed_params/processed/FAO_harvest_size_as_prop_of_linf_data.csv b/data/feed_params/processed/FAO_harvest_size_as_prop_of_linf_data.csv
new file mode 100644
index 0000000..fe36bc7
--- /dev/null
+++ b/data/feed_params/processed/FAO_harvest_size_as_prop_of_linf_data.csv
@@ -0,0 +1,49 @@
+"type","species_orig","comm_name","species","harvest_size_notes","harvest_kg","harvest_mm","harvest_g","harvest_cm","linf_cm","k","fb_linf_cm","fb_k","fb_a","fb_b","harvest_cm_calc","harvest_cm_final","linf_cm_final","harvest_perc_linf"
+"Bivalves","American cupped oyster (Crassostrea virginica)","American cupped oyster","Crassostrea virginica","7.6 cm (SeaLifeBase)",NA,76,NA,7.6,NA,NA,9.085,0.55,2.001025,2.1776,NA,7.6,9.085,83.6543753439736
+"Finfish","Arapaima (Arapaima gigas)","Arapaima","Arapaima gigas","10-12 kg, 1.2 m tl",11,NA,11000,NA,273.508349761823,0.119579924051373,317,0.1769,0.01663,2.9585,92.7645979548421,92.7645979548421,273.508349761823,33.9165506411865
+"Finfish","Atlantic bluefin tuna (Thunnus thynnus)","Atlantic bluefin tuna","Thunnus thynnus","45-90 kg",67.5,NA,67500,NA,376.096303932282,0.101468923843262,337,0.088,0.0232,2.914,165.269790135899,165.269790135899,376.096303932282,43.9434762873012
+"Finfish","Atlantic cod (Gadus morhua)","Atlantic cod","Gadus morhua","2-4 kg, 24-36 months",3,NA,3000,NA,104.490612388055,0.165194275571593,110,0.1635,0.0068,3.094,66.7380844123577,66.7380844123577,104.490612388055,63.8699332764052
+"Finfish","Atlantic salmon (Salmo salar)","Atlantic salmon","Salmo salar","2 kg",2,NA,2000,NA,123.251890111783,0.274403478828673,120,0.26,0.01072,2.99163,57.7910601338629,57.7910601338629,123.251890111783,46.8885792189064
+"Finfish","Barramundi (Lates calcarifer)","Barramundi","Lates calcarifer","0.35-2.0 kg, 0.75-2 yrs",1.175,NA,1175,NA,110.966976271589,0.205448863803007,143,0.125,0.017,2.969,42.6618871321835,42.6618871321835,110.966976271589,38.4455705342187
+"Finfish","Bighead carp (Hypophthalmichthys nobilis)","Bighead carp","Hypophthalmichthys nobilis","0.75-1.5 kg",1.125,NA,1125,NA,111.327268956708,0.154618009792534,158.85565,0.168,0.012475,2.955,47.5178565376898,47.5178565376898,111.327268956708,42.6830344290293
+"Bivalves","Blue mussel (Mytilus edulis)","Blue mussel","Mytilus edulis","4 cm, 12-15 months",NA,40,NA,4,NA,NA,8.13,0.22,0.00748,2.85,NA,4,8.13,49.20049200492
+"Finfish","Catla (Catla catla)","Catla","Gibelion catla","1-2 kg",1.5,NA,1500,NA,NA,NA,115,0.317,0.03862,3.3255,23.9898073161097,23.9898073161097,115,20.8607020140084
+"Finfish","Cobia (Rachycentron canadum)","Cobia","Rachycentron canadum","6-10 kg, 8-12 months",8,NA,8000,NA,127.529906103023,0.284588832055529,138.03001,0.272,0.00427,3.09,107.148905330401,107.148905330401,127.529906103023,84.0186499030611
+"Finfish","Coho salmon (Oncorhynchus kisutch)","Coho salmon","Oncorhynchus kisutch","2.5-3.5 kg, 10-12 months",3,NA,3000,NA,78.8101685017406,0.485030743323046,80,0.98,0.0112,3,64.4615994694649,64.4615994694649,78.8101685017406,81.7935054510652
+"Finfish","Common sole (Solea spp.)","Common sole","Solea solea","350 g, 18 months",0.35,NA,350,NA,38.3250055264887,0.318889680655936,38.05,0.33,0.00737,3.0725,33.2723269851303,33.2723269851303,38.3250055264887,86.8162353222201
+"Finfish","Crucian carp (Carassius carassius)","Crucian carp","Carassius carassius","150-400 g",0.275,NA,275,NA,35.4916387465186,0.177452313663111,29.8,0.093,0.0163,3.06,24.0668894944381,24.0668894944381,35.4916387465186,67.8100260918463
+"Finfish","European eel (Anguilla anguilla)","European eel","Anguilla anguilla","150-200g (butterflied)",0.175,NA,175,NA,71.2898532719499,0.145864142961333,82,0.131,0.00117,3.139,44.5212264046561,44.5212264046561,71.2898532719499,62.4510001932824
+"Finfish","European seabass (Dicentrarchus labrax)","European seabass","Dicentrarchus labrax","400 g",0.4,NA,400,NA,75.1187565189705,0.171500030938308,76.7,0.16,0.00938,3.039,33.3795495384545,33.3795495384545,75.1187565189705,44.4357056549849
+"Finfish","Flathead grey mullet (Mugil cephalus)","Flathead grey mullet","Mugil cephalus","0.75-1.0 kg",0.875,NA,875,NA,59.8453880810529,0.243490094344597,58.8,0.3,0.015825,2.8952,43.4623148708633,43.4623148708633,59.8453880810529,72.6243345803008
+"Finfish","Giant gourami (Osphronemus goramy)","Giant gourami","Osphronemus goramy","0.7-1.0 kg",0.85,NA,850,NA,25.3820230250994,0.518498178560551,NA,NA,0.017,3.032,35.4643674258315,35.4643674258315,25.3820230250994,139.722383006123
+"Finfish","Gilthead seabream (Sparus aurata)","Gilthead seabream","Sparus aurata","350-400 g",0.375,NA,375,NA,56.2913564206841,0.246296319387648,54.6,0.265,0.0153,2.9956,29.1918978323487,29.1918978323487,56.2913564206841,51.858579520074
+"Finfish","Grass carp (Ctenopharyngodon idellus)","Grass carp","Ctenopharyngodon idella","1.5-2.5 kg",2,NA,2000,NA,115.130938832693,0.11355273446682,138.709,0.1716,0.0121,2.94,59.5543018583067,59.5543018583067,115.130938832693,51.7274526396855
+"Finfish","Greater amberjack (Seriola dumerili)","Greater amberjack","Seriola dumerili","3-5 kg",4,NA,4000,NA,151.519972123109,0.225303248080133,169.3,0.227,0.0225,2.86,68.4891054961171,68.4891054961171,151.519972123109,45.2013715000357
+"Bivalves","Grooved carpet shell (Ruditapes decussatus)","Grooved carpet shell","Ruditapes decussatus","30-40 mm",NA,35,NA,3.5,NA,NA,5.37,0.44,0.19275,3.605,NA,3.5,5.37,65.1769087523277
+"Finfish","Japanese amberjack (Seriola quinqueradiata)","Japanese amberjack","Seriola quinqueradiata","2-3 kg",2.5,NA,2500,NA,106.676959847085,0.256331834312919,113,0.4415,0.00814,3,67.4691441688534,67.4691441688534,106.676959847085,63.2462194887879
+"Bivalves","Japanese carpet shell (Ruditapes philippinarum)","Japanese carpet shell","Ruditapes philippinarum","3.5 cm",NA,35,NA,3.5,NA,NA,5.24,0.33,0.22999,3.0611,NA,3.5,5.24,66.793893129771
+"Finfish","Japanese eel (Anguilla japonica)","Japanese eel","Anguilla japonica","150 g - 2 kg",1.075,NA,1075,NA,97.6400445343534,0.0997023188820683,98.2,0.07,0.0003,3.35,90.4698030009444,90.4698030009444,97.6400445343534,92.6564540526338
+"Finfish","Mandarin fish (Siniperca chuatsi)","Mandarin fish","Siniperca chuatsi","0.5 kg",0.5,NA,500,NA,71.5831697734535,0.175545242924117,64.3,0.16,0.01075,3.087,32.5091550563631,32.5091550563631,71.5831697734535,45.4145229377913
+"Finfish","Meagre (Argyrosomus regius)","Meagre","Argyrosomus regius","800-1200 g",1,NA,1000,NA,133.302237387809,0.116468625835001,171.89999,0.15,0.0182,2.8305,47.2705408427124,47.2705408427124,133.302237387809,35.4611758729831
+"Bivalves","Mediterranean mussel (Mytilus galloprovincialis)","Mediterranean mussel","Mytilus galloprovincialis","8-10 cm",NA,90,NA,9,NA,NA,6.14,0.325,NA,NA,NA,9,6.14,146.579804560261
+"Finfish","Milkfish (Chanos chanos)","Milkfish","Chanos chanos","250-500 g, 20-40 cm",0.375,NA,375,NA,40.972118307771,0.544992690695047,43.8,0.865,0.0069,3.024,36.801635708008,36.801635708008,40.972118307771,89.8211691950232
+"Finfish","Mrigal carp (Cirrhinus mrigala)","Mrigal carp","Cirrhinus mrigala","600-700 g",0.65,NA,650,NA,61.3674027583041,0.175932213458094,99.8,1.339,0.0077,3.355,29.4023676986811,29.4023676986811,61.3674027583041,47.9120288249488
+"Finfish","Mud carp (Cirrhinus molitorella)","Mud carp","Cirrhinus molitorella","125-500 g",0.3125,NA,312.5,NA,65.2063756099285,0.158327892728871,60.1,0.117,0.00767,3.133,29.6108297299255,29.6108297299255,65.2063756099285,45.4109424928946
+"Bivalves","New Zealand mussel (Perna canaliculus)","New Zealand mussel","Perna canaliculus","90-120 mm",NA,105,NA,10.5,NA,NA,17.235,0.6,0.13502,2.8,NA,10.5,17.235,60.9225413402959
+"Finfish","Nile tilapia (Oreochromis niloticus)","Nile tilapia","Oreochromis niloticus","500 g",0.5,NA,500,NA,29.7517303924761,1.97741970688712,26.1,2.9905,0.02081,2.99,29.1820879880761,29.1820879880761,29.7517303924761,98.0853469802077
+"Finfish","North African catfish (Clarias gariepinus)","North African catfish","Clarias gariepinus","200-300 g",0.25,NA,250,NA,118.628131852763,0.13557762239993,116,0.14,0.008,2.98,32.2358356897082,32.2358356897082,118.628131852763,27.1738542841744
+"Bivalves","Northern quahog (Mercenaria mercenaria)","Northern quahog","Mercenaria mercenaria",">25 mm",NA,30,NA,3,NA,NA,8.18,0.5,0.06151,3.09,NA,3,8.18,36.6748166259169
+"Finfish","Orange-spotted grouper (Epinephelus coioides)","Orange-spotted grouper","Epinephelus coioides","350-400 g",0.375,NA,375,NA,93.0919629789621,0.144231230738564,95.45,0.1535,0.0105,3.051,31.0631726689465,31.0631726689465,93.0919629789621,33.3682647512401
+"Bivalves","Pacific cupped oyster (Crassostrea gigas)","Pacific cupped oyster","Crassostrea gigas","70-100 g, >75 mm",0.085,NA,85,NA,NA,NA,10.14,2.52,0.1452,2.2446,17.097706394377,17.097706394377,10.14,168.616433869596
+"Finfish","Pike-perch (Sander lucioperca)","Pike-perch","Sander lucioperca","1-2 kg",1.5,NA,1500,NA,82.9827661700725,0.163411710757459,89.8,0.14,0.00546,3.114,55.7950374798458,55.7950374798458,82.9827661700725,67.2368975571317
+"Finfish","Pompanos nei (Trachinotus spp)","Pompanos nei","Trachinotus blochii","453 g",0.453,NA,453,NA,49.7580392527311,0.431065675945423,NA,NA,0.088,2.572,27.738652107088,27.738652107088,49.7580392527311,55.7470762989631
+"Finfish","Rainbow trout (Oncorhynchus mykiss)","Rainbow trout","Oncorhynchus mykiss","450-600 g (USA), 1-2 kg (Europe), 3-5 kg (Scandanavia, Canada, Chile), 30-40 cm (USA?)",3.5,NA,3500,NA,62.671991857935,0.48112071045701,67,0.461,0.01285,2.9995,64.86697459338,64.86697459338,62.671991857935,103.502334408679
+"Finfish","Red drum (Sciaenops ocellatus)","Red drum","Sciaenops ocellatus","1 kg",1,NA,1000,NA,94.491800586301,0.350275010538659,95,0.418,0.00846,3.028,47.3413854371641,47.3413854371641,94.491800586301,50.1010512482788
+"Finfish","Roho labeo (Labeo rohita)","Roho labeo","Labeo rohita","1-1.5 kg",1.25,NA,1250,NA,87.9836513642361,0.231019146097232,96.6,0.329,0.00866,3.193,41.2899824315139,41.2899824315139,87.9836513642361,46.9291530770654
+"Finfish","Sea trout (Salmo trutta)","Sea trout","Salmo trutta","2-3 kg",2.5,NA,2500,NA,52.3172117286902,0.245395056543089,44.7,0.273,0.008065,3.08,60.6598288779701,60.6598288779701,52.3172117286902,115.946218985338
+"Finfish","Siberian sturgeon (Acipenser baerii)","Siberian sturgeon","Acipenser baerii","1-2 kg",1.5,NA,1500,NA,160.630393807753,0.0621508393869201,149,0.06,0.0015,3.2563,69.5956462051647,69.5956462051647,160.630393807753,43.3265738540481
+"Finfish","Silver carp (Hypophthalmichthys molitrix)","Silver carp","Hypophthalmichthys molitrix","0.75-1.5 kg",1.125,NA,1125,NA,87.7758726196837,0.204386324742559,103,0.2046,0.00838,3.093,45.4891368288036,45.4891368288036,87.7758726196837,51.8241920828283
+"Finfish","Striped bass, hybrid (Morone hybrid)","Striped bass, hybrid","Morone saxatilis","0.5-1.0 kg",0.75,NA,750,NA,96.8966821177613,0.169181403509746,100.35,0.194,0.00614,3.153,41.053492429012,41.053492429012,96.8966821177613,42.3683159544291
+"Finfish","Striped catfish (Pangasius hypophthalmus)","Striped catfish","Pangasianodon hypophthalmus","2.7-3.3 kg",3,NA,3000,NA,70.0317283905263,0.197021698719602,NA,NA,0.01895,2.875,64.3466478380297,64.3466478380297,70.0317283905263,91.8821358787632
+"Finfish","Turbot (Psetta maxima)","Turbot","Scophthalmus maximus","1.5-2 kg",1.75,NA,1750,NA,56.1916598355709,0.252554121928771,54.75,0.2835,0.013,3.11,44.58888274731,44.58888274731,56.1916598355709,79.3514248872285
+"Bivalves","Yesso scallop (Patinopecten yessoensis)","Yesso scallop","Mizuhopecten yessoensis","100 mm",NA,100,NA,10,NA,NA,13.35,0.925,0.14439,2.98,NA,10,13.35,74.9063670411985
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