exploratory code for catch limits

SEFSC · Jan 24, 2025 · cf8bdcf · cf8bdcf
1 parent 68541fe
commit cf8bdcf
Showing 1 changed file with 143 additions and 0 deletions.
diff --git a/Examples/Gulf_reef_fish_CatchLimits_EDA.R b/Examples/Gulf_reef_fish_CatchLimits_EDA.R
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+
+library(tidyverse)
+library(RColorBrewer)
+
+# MH dataset 
+mh <- readRDS("C:/Users/sarina.atkinson/Documents/GitHub/SEFSC/SEFSC-ODM-Management-History/ODM-MH-Data_log/data/results/MH_DL_2024Apr30.RDS")
+
+# Catch limits for Gulf Reef
+mh2 <- mh %>% filter(MANAGEMENT_CATEGORY == 'CATCH LIMITS',
+                    FMP == "REEF FISH RESOURCES OF THE GULF OF MEXICO")
+
+chk <- filter(mh, MANAGEMENT_TYPE == 'DEFINITION', 
+              FMP == "REEF FISH RESOURCES OF THE GULF OF MEXICO") %>% ungroup() %>% select(VALUE, FR_CITATION) %>% distinct()
+
+# Summarize management types by sector 
+plot1 <- ggplot(mh2 %>%
+                  group_by(SECTOR_USE, MANAGEMENT_TYPE_USE) %>%
+                  summarise(nrecs = n_distinct(REGULATION_ID)) %>%
+                  group_by(SECTOR_USE) %>% 
+                  mutate(tot = sum(nrecs), perc = nrecs/tot, labels = paste0(round(perc * 100,1), "%")), aes(x = "" , y = perc, fill = MANAGEMENT_TYPE_USE)) +
+  geom_col(width = 1, color = 1) +
+  coord_polar(theta = "y") +
+  #geom_text(aes(x = 1.7, label = labels), size=4.5, 
+  #          position = position_stack(vjust = 0.5))+
+  facet_wrap(~SECTOR_USE) +
+  scale_fill_brewer(palette = "Set3") +
+  guides(fill = guide_legend(title = "Management Type")) +
+  theme_void()
+
+# ACLs by species
+plot2 <- ggplot(mh2 %>%
+                  filter(MANAGEMENT_TYPE == 'ACL') %>%
+                  group_by(SECTOR_USE, SPP_NAME) %>%
+                  summarise(nrecs = n_distinct(REGULATION_ID)) %>%
+                  group_by(SECTOR_USE) %>% 
+                  mutate(tot = sum(nrecs), perc = nrecs/tot, labels = paste0(round(perc * 100,1), "%")), aes(x = "" , y = perc, fill = SPP_NAME)) +
+  geom_col(width = 1, color = 1) +
+  coord_polar(theta = "y") +
+  #geom_text(aes(x = 1.7, label = labels), size=4.5, 
+  #          position = position_stack(vjust = 0.5))+
+  facet_wrap(~SECTOR_USE) +
+  #scale_fill_brewer(palette = "Set3") +
+  guides(fill = guide_legend(title = "Species")) +
+  theme_void()
+
+unique(mh2$SPP_NAME)
+
+# DWG ACLS
+acl_dwg <- mh2 %>% ungroup() %>%
+  filter(SPP_NAME == 'ACL/ACT:  DEEP-WATER GROUPER (DWG) COMBINED') %>%
+  select(REGULATION_ID, MANAGEMENT_TYPE_USE, SECTOR, SECTOR_USE, FR_CITATION, 
+         EFFECTIVE_DATE, START_YEAR, START_DATE2, END_DATE2,
+         VALUE, VALUE_TYPE, VALUE_UNITS, VALUE_RATE) %>% distinct() %>%
+  arrange(START_YEAR, FR_CITATION)
+
+chk <- filter(mh2, MANAGEMENT_TYPE_USE == 'QUOTA', SPP_NAME == 'QUOTA: DEEP-WATER GROUPERS (DWG)')
+# SWG ACLS
+acl_swg <- mh2 %>% ungroup() %>%
+  filter(SPP_NAME == 'ACL/ACT:  OTHER SHALLOW-WATER GROUPER (OTHER SWG)') %>%
+  select(REGULATION_ID, MANAGEMENT_TYPE_USE, SECTOR, SECTOR_USE, FR_CITATION, 
+         EFFECTIVE_DATE, START_YEAR, START_DATE2, END_DATE2,
+         VALUE, VALUE_TYPE, VALUE_UNITS, VALUE_RATE) %>% distinct() %>%
+  arrange(START_YEAR, FR_CITATION)
+
+filter(mh2, SPP_NAME == 'ACL/ACT: SHALLOW-WATER GROUPER (SWG) COMBINED') %>% ungroup() %>% 
+  select(COMMON_NAME_USE) %>% distinct() %>% pull()
+
+# FRs for ACLS
+chk <- mh2 %>%
+  filter(MANAGEMENT_TYPE == 'ACL') %>%
+  group_by(FR_CITATION, SPP_NAME) %>%
+  summarise(nrecs = n_distinct(REGULATION_ID))
+
+filter(mh2, FR_CITATION == '73 FR 38139') %>% ungroup() %>% select(FR_URL) %>% distinct() %>% pull()
+
+# Gray Snapper ACLS
+acl_gs <- mh2 %>% ungroup() %>%
+  filter(SPP_NAME == 'SNAPPER, GRAY') %>%
+  select(REGULATION_ID, MANAGEMENT_TYPE_USE, SECTOR, SECTOR_USE, FR_CITATION, 
+         EFFECTIVE_DATE, START_YEAR, START_DATE2, END_DATE2,
+         VALUE, VALUE_TYPE, VALUE_UNITS, VALUE_RATE) %>% distinct() %>%
+  arrange(START_YEAR, FR_CITATION)
+
+# Tilefish ACLS
+acl_tile <- mh2 %>% ungroup() %>%
+  filter(SPP_NAME == 'ACL/ACT: TILEFISHES COMBINED') %>%
+  select(REGULATION_ID, MANAGEMENT_TYPE_USE, SECTOR, SECTOR_USE, FR_CITATION, 
+         EFFECTIVE_DATE, START_YEAR, START_DATE2, END_DATE2,
+         VALUE, VALUE_TYPE, VALUE_UNITS, VALUE_RATE) %>% distinct() %>%
+  arrange(START_YEAR, FR_CITATION)
+
+# Vermilion Snapper ACLS
+acl_vs <- mh2 %>% ungroup() %>%
+  filter(SPP_NAME == 'SNAPPER, VERMILION') %>%
+  select(REGULATION_ID, MANAGEMENT_TYPE_USE, SECTOR, SECTOR_USE, FR_CITATION, 
+         EFFECTIVE_DATE, START_YEAR, START_DATE2, END_DATE2,
+         VALUE, VALUE_TYPE, VALUE_UNITS, VALUE_RATE) %>% distinct() %>%
+  arrange(START_YEAR, FR_CITATION)
+
+# Mutton Snapper ACLS
+acl_ms <- mh2 %>% ungroup() %>%
+  filter(SPP_NAME == 'SNAPPER, MUTTON') %>%
+  select(REGULATION_ID, MANAGEMENT_TYPE_USE, SECTOR, SECTOR_USE, FR_CITATION, 
+         EFFECTIVE_DATE, START_YEAR, START_DATE2, END_DATE2,
+         VALUE, VALUE_TYPE, VALUE_UNITS, VALUE_RATE) %>% distinct() %>%
+  arrange(START_YEAR, FR_CITATION)
+
+# Yellowtail Snapper ACLS
+acl_ys <- mh2 %>% ungroup() %>%
+  filter(SPP_NAME == 'SNAPPER, YELLOWTAIL') %>%
+  select(REGULATION_ID, MANAGEMENT_TYPE_USE, SECTOR, SECTOR_USE, FR_CITATION, 
+         EFFECTIVE_DATE, START_YEAR, START_DATE2, END_DATE2,
+         VALUE, VALUE_TYPE, VALUE_UNITS, VALUE_RATE) %>% distinct() %>%
+  arrange(START_YEAR, FR_CITATION)
+
+# HOgfish ACLS
+acl_hog <- mh2 %>% ungroup() %>%
+  filter(SPP_NAME == 'HOGFISH') %>%
+  select(REGULATION_ID, MANAGEMENT_TYPE_USE, SECTOR, SECTOR_USE, FR_CITATION, 
+         EFFECTIVE_DATE, START_YEAR, START_DATE2, END_DATE2,
+         VALUE, VALUE_TYPE, VALUE_UNITS, VALUE_RATE, NEVER_IMPLEMENTED) %>% distinct() %>%
+  arrange(START_YEAR, FR_CITATION)
+
+# Catch limits for Gulf Reef
+mh3 <- mh %>% filter(MANAGEMENT_CATEGORY == 'CATCH LIMITS',
+                     FMP == "COASTAL MIGRATORY PELAGIC RESOURCES")
+# Cobia ACLS
+acl_cobia <- mh3 %>% ungroup() %>%
+  filter(SPP_NAME == 'COBIA', MANAGEMENT_TYPE_USE == 'ACL') %>%
+  select(REGULATION_ID, MANAGEMENT_TYPE_USE, SECTOR, SECTOR_USE, FR_CITATION, ZONE_USE,
+         EFFECTIVE_DATE, START_YEAR, START_DATE2, END_DATE2,
+         VALUE, VALUE_TYPE, VALUE_UNITS, VALUE_RATE) %>% distinct() %>%
+  arrange(START_YEAR, FR_CITATION, REGULATION_ID)
+
+# Spanish Mackerel ACLS
+acl_sm <- mh3 %>% ungroup() %>%
+  filter(SPP_NAME == 'MACKEREL, SPANISH', ZONE_USE == 'GULF MIGRATORY GROUP SPANISH MACKEREL', MANAGEMENT_TYPE_USE == 'ACL') %>%
+  select(REGULATION_ID, MANAGEMENT_TYPE_USE, SECTOR, SECTOR_USE, FR_CITATION, ZONE_USE,
+         EFFECTIVE_DATE, START_YEAR, START_DATE2, END_DATE2,
+         VALUE, VALUE_TYPE, VALUE_UNITS, VALUE_RATE) %>% distinct() %>%
+  arrange(START_YEAR, FR_CITATION, REGULATION_ID)
+
+