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23 changes: 16 additions & 7 deletions ODM-MH-Analysis_ready/Catch Limits/CatchLimits.R
Original file line number Diff line number Diff line change
Expand Up @@ -8,17 +8,17 @@ librarian::shelf(here, tidyverse, gt, flextable, officer, dplyr, gt, officer, lu
# Load the MH Data Log
mh <- readRDS(here("ODM-MH-Data_log", "data", "results", "MH_DL_2025Sep10.RDS"))

#### Define species and region of interest ####
#### Define species, region, and sector of interest ####
species = c('SNAPPER, CUBERA', 'AMBERJACK, GREATER', 'AMBERJACK, LESSER', 'JACK, ALMACO', 'SNAPPER, SILK', 'SNAPPER, QUEEN', 'SNAPPER, BLACKFIN', 'WENCHMAN',
'DRUM, RED', 'COBIA', 'GROUPER, GAG', 'SNAPPER, GRAY', 'MACKEREL, KING', 'GROUPER, YELLOWEDGE', 'SNAPPER, LANE', 'GROUPER, RED', 'SNAPPER, RED',
'SCAMP', 'MACKEREL, SPANISH','HOGFISH', 'SNAPPER, MUTTON', 'SNAPPER, YELLOWTAIL', 'SNAPPER, VERMILION', 'TRIGGERFISH, GRAY', 'TRIGGERFISH, QUEEN')
region = 'GULF OF MEXICO'
sector = 'RECREATIONAL'

#### ACLs ####
# Filter to species and region of interest
# Remove non-detailed regulations and those that were never implemented
# Filter to only include records that apply to the entire region (ZONE_USE = ALL) and sector of interest
# Filter to species, region, and sector of interest
# Remove non-detailed regulations, those that were never implemented, and those that removed a regulation
# Adjust variable titles and format
ACLs <- mh %>%
filter(COMMON_NAME_USE %in% species,
REGION %in% region,
Expand Down Expand Up @@ -53,7 +53,10 @@ ACLs <- mh %>%
`FR Reference`, `FR URL`, `Amendment Number or Rule Type`) %>%
arrange(Species, CLUSTER, `First Year in Effect`)

# Quota
#### Quotas ####
# Filter to species, region, and sector of interest
# Remove non-detailed regulations, those that were never implemented, and those that removed a regulation
# Adjust variable titles and format
Quotas <- mh %>%
filter(COMMON_NAME_USE %in% species,
REGION %in% region,
Expand Down Expand Up @@ -88,7 +91,10 @@ Quotas <- mh %>%
`FR Reference`, `FR URL`, `Amendment Number or Rule Type`) %>%
arrange(Species, CLUSTER, `First Year in Effect`)

# ACT
#### ACTs ####
# Filter to species, region, and sector of interest
# Remove non-detailed regulations, those that were never implemented, and those that removed a regulation
# Adjust variable titles and format
ACTs <- mh %>%
filter(COMMON_NAME_USE %in% species,
REGION %in% region,
Expand Down Expand Up @@ -122,7 +128,10 @@ ACTs <- mh %>%
`FR Reference`, `FR URL`, `Amendment Number or Rule Type`) %>%
arrange(Species, CLUSTER, `First Year in Effect`)

# TAC
#### TACs ####
# Filter to species, region, and sector of interest
# Remove non-detailed regulations, those that were never implemented, and those that removed a regulation
# Adjust variable titles and format
TACs <- mh %>%
filter(COMMON_NAME_USE %in% species,
REGION %in% region,
Expand Down
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