knitr::opts_chunk$set(echo=FALSE, warning = FALSE, message = FALSE, cache = FALSE, progress = TRUE, verbose = FALSE, comment = F , error = FALSE, dev = 'png', dpi = 200) options(knitr.kable.NA = '')
Exploration of discard estimates from calendar year module
pull all merged trips from CAMS_OBS_CATCH
Set stratification variables for all trips
# FULL Stratification variables stratvars = c('SPECIES_STOCK' ,'CAMS_GEAR_GROUP' , 'MESHGROUP' , 'TRIPCATEGORY' , 'ACCESSAREA')
- SPECIES_STOCK is taken from CAMS support table `MAPS.CAMS_STATAREA_STOCK` - CAMS_GEAR_GROUP is derived from a support table (`MAPS.CAMS_GEARCODE_STRATA`) - MESHGROUP is hardcoded for all trips according to decisions made by the mesh subgroup (see summary when available)
discaRd
# Assumed Stratification variables stratvars = c('SPECIES_STOCK' , 'CAMS_GEAR_GROUP', ,'MESHGROUP')
The discaRd functions allow for an assumed rate to be calculated. This assumed rate is relative to the stratification used in the functions. Here, the stratification is coarsened to 'SPECIES_STOCK', 'CAMS_GEAR_GROUP' and 'MESHGROUP'.
A transition rate is calculated between year t and year t-1. This rate determines how much, if any, information is used from previous years.
A broad stock/gear stratification is applied to subtrips that do not meet the requirements for the full or assumed stratification. This broad stock/gear stratification utilizes observed coverage from both the focal year and the previous year as it includes gear types with low observer coverage.
Rates and DISCARD_SOURCE
(in parentheses) are assigned for each trip according to:
(O) Observed values used from observed rate trips; discard rate is NOT USED.
CV calculations are available for (I), (T), (GM) and (G).
Discard pounds per trip are calculated according to
mutate(DISC_MORT_RATIO = coalesce(DISC_MORT_RATIO, 1)) %>% mutate(DISCARD = case_when(!is.na(LINK1) ~ DISC_MORT_RATIO*OBS_DISCARD , is.na(LINK1) ~ DISC_MORT_RATIO*COAL_RATE*LIVE_POUNDS) # COAL_RATE is the final discard rate used. It is 'coalesced' from the (I), (T), (GM) and (G) rates
By assigning SPECIES_STOCK
as a stratification variable, the computation time is reduced. Each subtrip may only occur in a single statistical area so it should never cross stock boundaries.
Once the full table (CAMS_OBS_CATCH) is loaded, each species takes ~X seconds to process on the server.
Output tables are produced for each species. These can easily be recombined. Preliminary species tables have been shared on MAPS
and CAMS_GARFO
.
MAPS.CAMS_DISCARD_BLACKSEA_BASS_2019 CAMS_GARFO.CAMS_DISCARD_BLACKSEA_BASS_2019 MAPS.CAMS_DISCARD_BLUEFISH_2019 CAMS_GARFO.CAMS_DISCARD_BLUEFISH_2019 MAPS.CAMS_DISCARD_BUTTERFISH_2019 CAMS_GARFO.CAMS_DISCARD_BUTTERFISH_2019 MAPS.CAMS_DISCARD_SQUIDATLLONG_FIN_2019 CAMS_GARFO.CAMS_DISCARD_SQUIDATLLONG_FIN_2019 MAPS.CAMS_DISCARD_SQUIDSHORT_FIN_2019 CAMS_GARFO.CAMS_DISCARD_SQUIDSHORT_FIN_2019 MAPS.CAMS_DISCARD_MACKERELATLANTIC_2019 CAMS_GARFO.CAMS_DISCARD_MACKERELATLANTIC_2019 MAPS.CAMS_DISCARD_MACKERELCHUB_2019 CAMS_GARFO.CAMS_DISCARD_MACKERELCHUB_2019 MAPS.CAMS_DISCARD_FLUKE_2019 CAMS_GARFO.CAMS_DISCARD_FLUKE_2019 MAPS.CAMS_DISCARD_SCUP_2019 CAMS_GARFO.CAMS_DISCARD_SCUP_2019 MAPS.CAMS_DISCARD_SURFCLAM_2019 CAMS_GARFO.CAMS_DISCARD_SURFCLAM_2019 MAPS.CAMS_DISCARD_OCEANQUAHOG_2019 CAMS_GARFO.CAMS_DISCARD_OCEANQUAHOG_2019 MAPS.CAMS_DISCARD_ALEWIFE_2019 CAMS_GARFO.CAMS_DISCARD_ALEWIFE_2019 MAPS.CAMS_DISCARD_AMSHAD_2019 CAMS_GARFO.CAMS_DISCARD_AMSHAD_2019
# library(odbc) # library(dplyr, warn.conflicts = FALSE) # # library(dbplyr) library(ggplot2) # # library(config) # library(stringr) # library(discaRd) # library(knitr) # library(kableExtra) devtools::load_all() options(scipen = 999) discard <- read.csv("~/discaRd/CAMS/MODULES/CALENDAR/January_comparisons.csv") '%ni%' <- Negate("%in%") discard %>% filter(Source == 'Federal') %>% pivot_wider(id_cols = !Source, names_from = Method,values_from = c(Discards, kall)) %>% mutate(diff = Discards_CAMS-Discards_QM, perc_diff = 100 * (Discards_QM - Discards_CAMS)/(Discards_CAMS)) %>% dplyr::select(Species, Discards_CAMS, Discards_QM, diff, perc_diff) %>%dplyr::mutate(across(where(is.numeric), round, 2))%>% DT::datatable(caption = 'Comparison of total federal discards in FY 2019 by species and source')
discard <- read.csv("~/discaRd/CAMS/MODULES/CALENDAR/January_comparisons.csv") '%ni%' <- Negate("%in%") discard %>% filter(Source %in% c("State")) %>% dplyr::select(Species, Discards) %>% DT::datatable(caption = 'Total discards by species for state trips')
```{bring in species tables}
dw_maps <- config::get(config = "maps", file = "~/config_group.yml")
connectString <- paste( "(DESCRIPTION=", "(ADDRESS=(PROTOCOL=tcp)(HOST=", dw_maps$host, ")(PORT=", dw_maps$port, "))", "(CONNECT_DATA=(SERVICE_NAME=",dw_maps$svc, ")))", sep = "" )
bcon <- ROracle::dbConnect( drv = ROracle::Oracle(), username = dw_maps$uid, password = dw_maps$pwd, dbname = connectString )
db_blackseabass = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_BLACKSEA_BASS_2019")) %>% collect
db_blackseabass$SPECIES <- "BLACKSEABASS"
db_bluefish = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_BLUEFISH_2019")) %>% collect
db_bluefish$SPECIES <- "BLUEFISH"
db_butterfish = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_BUTTERFISH_2019")) %>% collect
db_butterfish$SPECIES <- "BUTTERFISH"
db_longfinsquid = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_SQUIDATLLONG_FIN_2019")) %>% collect
db_longfinsquid$SPECIES <- "LONGFINSQUID"
db_shortfinsquid = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_SQUIDSHORT_FIN_2019")) %>% collect
db_shortfinsquid$SPECIES <- "SHORTFINSQUID"
db_mackerel = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_MACKERELATLANTIC_2019")) %>% collect
db_mackerel$SPECIES <- "MACKEREL"
db_chubmackerel = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_CHUBMACKEREL_2019")) %>% collect
db_chubmackerel$SPECIES <- "CHUB MACKEREL"
db_fluke = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_FLUKE_2019")) %>% collect
db_fluke$SPECIES <- "FLUKE"
db_scup = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_SCUP_2019")) %>% collect
db_scup$SPECIES <- "SCUP"
db_surfclam = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_CLAMSURF_2019")) %>% collect
db_surfclam$SPECIES <- "SURFCLAM"
db_oceanquahog = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_QUAHOGOCEANBLACK_CLAM_2019")) %>% collect
db_oceanquahog$SPECIES <- "OCEANQUAHOG"
db_alewife = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_ALEWIFE_2019")) %>% collect
db_alewife$SPECIES <- "ALEWIFE"
db_final <- rbind(db_blackseabass, db_bluefish, db_butterfish, db_longfinsquid, db_shortfinsquid, db_mackerel, db_chubmackerel, db_fluke, db_scup, db_surfclam, db_oceanquahog, db_alewife)
db_final %>%
filter(DISCARD_SOURCE != 'O') %>%
dplyr::group_by(FED_OR_STATE) %>%
dplyr::summarise(DISCARD_Total = round(sum(CAMS_DISCARD, na.rm=TRUE))) %>%
dplyr::arrange(desc(DISCARD_Total)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard Totals QM and non QM')
```r dw_maps <- config::get(config = "maps", file = "~/config_group.yml") # Connect to database - move this to config file in the future - quick addition for server connectString <- paste( "(DESCRIPTION=", "(ADDRESS=(PROTOCOL=tcp)(HOST=", dw_maps$host, ")(PORT=", dw_maps$port, "))", "(CONNECT_DATA=(SERVICE_NAME=",dw_maps$svc, ")))", sep = "" ) # Connect to oracle each loop in case of timeouts bcon <- ROracle::dbConnect( drv = ROracle::Oracle(), username = dw_maps$uid, password = dw_maps$pwd, dbname = connectString ) db_blackseabass = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_BLACKSEA_BASS_2019")) %>% collect db_blackseabass$SPECIES <- "BLACKSEABASS" db_bluefish = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_BLUEFISH_2019")) %>% collect db_bluefish$SPECIES <- "BLUEFISH" db_butterfish = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_BUTTERFISH_2019")) %>% collect db_butterfish$SPECIES <- "BUTTERFISH" db_longfinsquid = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_SQUIDATLLONG_FIN_2019")) %>% collect db_longfinsquid$SPECIES <- "LONGFINSQUID" db_shortfinsquid = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_SQUIDSHORT_FIN_2019")) %>% collect db_shortfinsquid$SPECIES <- "SHORTFINSQUID" db_mackerel = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_MACKERELATLANTIC_2019")) %>% collect db_mackerel$SPECIES <- "MACKEREL" db_chubmackerel = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_CHUBMACKEREL_2019")) %>% collect db_chubmackerel$SPECIES <- "CHUB MACKEREL" db_fluke = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_FLUKE_2019")) %>% collect db_fluke$SPECIES <- "FLUKE" db_scup = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_SCUP_2019")) %>% collect db_scup$SPECIES <- "SCUP" db_surfclam = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_CLAMSURF_2019")) %>% collect db_surfclam$SPECIES <- "SURFCLAM" db_oceanquahog = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_QUAHOGOCEANBLACK_CLAM_2019")) %>% collect db_oceanquahog$SPECIES <- "OCEANQUAHOG" db_alewife = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_ALEWIFE_2019")) %>% collect db_alewife$SPECIES <- "ALEWIFE" db_final <- rbind(db_blackseabass, db_bluefish, db_butterfish, db_longfinsquid, db_shortfinsquid, db_mackerel, db_chubmackerel, db_fluke, db_scup, db_surfclam, db_oceanquahog, db_alewife) strat_blackseabass <- db_blackseabass %>% dplyr::group_by(SPECIES, STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% dplyr::select( SPECIES ,STRATA_FULL # STRATA # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD ,DISCARD_SOURCE ,FED_OR_STATE) strat_bluefish <- db_bluefish %>% dplyr::group_by(SPECIES, STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% dplyr::select( SPECIES ,STRATA_FULL # STRATA # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD ,DISCARD_SOURCE ,FED_OR_STATE) strat_butterfish <- db_butterfish %>% dplyr::group_by(SPECIES, STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% dplyr::select( SPECIES ,STRATA_FULL # STRATA # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD ,DISCARD_SOURCE ,FED_OR_STATE) strat_longfinsquid <- db_longfinsquid %>% dplyr::group_by(SPECIES, STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% dplyr::select( SPECIES ,STRATA_FULL # STRATA # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD ,DISCARD_SOURCE ,FED_OR_STATE) strat_shortfinsquid <- db_shortfinsquid %>% dplyr::group_by(SPECIES, STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% dplyr::select( SPECIES ,STRATA_FULL # STRATA # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD ,DISCARD_SOURCE ,FED_OR_STATE) strat_mackerel <- db_mackerel %>% dplyr::group_by(SPECIES, STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% dplyr::select( SPECIES ,STRATA_FULL # STRATA # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD ,DISCARD_SOURCE ,FED_OR_STATE) strat_chubmackerel <- db_chubmackerel %>% dplyr::group_by(SPECIES, STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% dplyr::select( SPECIES ,STRATA_FULL # STRATA # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD ,DISCARD_SOURCE ,FED_OR_STATE) strat_fluke <- db_fluke %>% dplyr::group_by(SPECIES, STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% dplyr::select( SPECIES ,STRATA_FULL # STRATA # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD ,DISCARD_SOURCE ,FED_OR_STATE) strat_scup <- db_scup %>% dplyr::group_by(SPECIES, STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% dplyr::select( SPECIES ,STRATA_FULL # STRATA # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD ,DISCARD_SOURCE ,FED_OR_STATE) strat_surfclam <- db_surfclam %>% dplyr::group_by(SPECIES, STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% dplyr::select( SPECIES ,STRATA_FULL # STRATA # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD ,DISCARD_SOURCE ,FED_OR_STATE) strat_oceanquahog <- db_oceanquahog %>% dplyr::group_by(SPECIES, STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% dplyr::select( SPECIES ,STRATA_FULL # STRATA # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD ,DISCARD_SOURCE ,FED_OR_STATE) strat_alewife <- db_alewife %>% dplyr::group_by(SPECIES, STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% dplyr::select( SPECIES ,STRATA_FULL # STRATA # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD ,DISCARD_SOURCE ,FED_OR_STATE) strat_final <- rbind(strat_blackseabass, strat_bluefish, strat_butterfish, strat_longfinsquid, strat_shortfinsquid, strat_mackerel, strat_chubmackerel, strat_fluke, strat_scup, strat_surfclam, strat_oceanquahog, strat_alewife) strat_final %>% filter(FED_OR_STATE=='FED') %>% # dplyr::group_by(SPECIES, STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% #slice(1) %>% ggplot()+ geom_histogram(aes(x = CAMS_DISCARD_RATE, fill = DISCARD_SOURCE), bins=60, position = "dodge") + facet_wrap(~SPECIES)+ theme_light()
strat_final %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=='STATE') %>% #dplyr::group_by(SPECIES, STRATA, DISCARD_SOURCE, FED_OR_STATE) %>% #slice(1) %>% ggplot()+ geom_histogram(aes(x = CAMS_DISCARD_RATE, fill = DISCARD_SOURCE), bins=60, position = "dodge") + facet_wrap(~SPECIES)+ theme_light()
db_final %>% # filter(DISCARD_SOURCE != 'O')& filter(FED_OR_STATE=='FED') %>% group_by(SPECIES, SPECIES_ITIS, DISCARD_SOURCE,SPECIES_STOCK) %>% dplyr::summarise(DSUM = sum(CAMS_DISCARD, na.rm = T)) %>% # slice(1) %>% ggplot()+ geom_bar(aes(x = SPECIES_STOCK, y = DSUM, fill = DISCARD_SOURCE), stat = 'identity', position = 'dodge')+ facet_wrap(~SPECIES, scales = 'free')+ theme_light()
db_final %>% # filter(DISCARD_SOURCE != 'O')& filter(FED_OR_STATE=='STATE') %>% group_by(SPECIES, SPECIES_ITIS, DISCARD_SOURCE,SPECIES_STOCK) %>% dplyr::summarise(DSUM = sum(CAMS_DISCARD, na.rm = T)) %>% # slice(1) %>% ggplot()+ geom_bar(aes(x = SPECIES_STOCK, y = DSUM, fill = DISCARD_SOURCE), stat = 'identity', position = 'dodge')+ facet_wrap(~SPECIES, scales = 'free')+ theme_light()
db_blackseabass %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="FED") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for federal trips by strata for Blackseabass')
db_blackseabass %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="STATE") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for state trips by strata for Blackseabass')
db_bluefish %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="FED") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates by Strata for Bluefish')
db_bluefish %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="STATE") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates by Strata for Bluefish')
db_butterfish %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="FED") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for federal trips by strata for Butterfish')
db_butterfish %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="STATE") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for state trips by strata for Butterfish')
db_longfinsquid %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="FED") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for federal trips by strata for Longfinsquid')
db_longfinsquid %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="STATE") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for state trips by strata for Longfinsquid')
db_shortfinsquid %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="FED") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for federal trips by strata for Shortfinsquid')
db_shortfinsquid %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="STATE") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for state trips by Strata for Shortfinsquid')
db_mackerel %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="FED") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for federal trips by strata for Mackerel')
db_mackerel %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="STATE") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for state trips by Strata for Mackerel')
db_chubmackerel %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="FED") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for federal trips by strata for Chub Mackerel')
db_chubmackerel %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="STATE") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for state trips by Strata for Chub Mackerel')
db_fluke %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="FED") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for federal trips by strata for Fluke')
db_fluke %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="STATE") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for state trips by Strata for Fluke')
db_scup %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="FED") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for federal trips by strata for Scup')
db_scup %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="STATE") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for state trips by Strata for Scup')
db_surfclam %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="FED") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for federal trips by strata for Surfclam')
db_surfclam %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="STATE") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for state trips by Strata for Surfclam')
db_oceanquahog %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="FED") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for federal trips by strata for Ocean Quahog')
db_oceanquahog %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="STATE") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for state trips by Strata for Ocean Quahog')
db_alewife %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="FED") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for federal trips by strata for Alewife')
db_alewife %>% filter(DISCARD_SOURCE != 'O' & FED_OR_STATE=="STATE") %>% group_by(STRATA_FULL, DISCARD_SOURCE, FED_OR_STATE) %>% dplyr::summarise(SUBTRIP_KALL = sum(SUBTRIP_KALL) , CAMS_DISCARD_RATE = round(mean(CAMS_DISCARD_RATE), digits=5) , DISC_MORT_RATIO = mean(DISC_MORT_RATIO) # , CV = mean(CV, na.rm=TRUE) , DISCARD = round(sum(CAMS_DISCARD))) %>% # , N_OBS_TRIPS_F = mean(N_OBS_TRIPS_F)) %>% ungroup() %>% dplyr::select(STRATA_FULL, DISCARD_SOURCE # ,N_OBS_TRIPS_F ,CAMS_DISCARD_RATE ,SUBTRIP_KALL ,DISC_MORT_RATIO ,DISCARD) %>% # ,CV) dplyr::arrange(desc(DISCARD)) %>%# top_n(10) %>% DT::datatable(caption = 'Discard rates for state trips by Strata for Alewife')
db_blackseabass %>% filter(FED_OR_STATE == 'FED') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for federal trips by stock, gear and discard source for Blackseabass')
db_blackseabass %>% filter(FED_OR_STATE == 'STATE') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for state trips by stock, gear and discard source for Blackseabass')
db_bluefish %>% filter(FED_OR_STATE == 'FED') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for federal trips by stock, gear and discard source for Bluefish')
db_bluefish %>% filter(FED_OR_STATE == 'STATE') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for state trips by stock, gear and discard source for Bluefish')
db_butterfish %>% filter(FED_OR_STATE == 'FED') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for federal trips by stock, gear and discard source for Butterfish')
db_butterfish %>% filter(FED_OR_STATE == 'STATE') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for state trips by stock, gear and discard source for Butterfish')
db_longfinsquid %>% filter(FED_OR_STATE == 'FED') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for federal trips by stock, gear and discard source for Longfinsquid')
db_longfinsquid %>% filter(FED_OR_STATE == 'STATE') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for state trips by stock, gear and discard source for Longfinsquid')
db_shortfinsquid %>% filter(FED_OR_STATE == 'FED') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for federal trips by stock, gear and discard source for Shortfinsquid')
db_shortfinsquid%>% filter(FED_OR_STATE == 'STATE') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for state trips by stock, gear and discard source for Shortfinsquid')
db_mackerel %>% filter(FED_OR_STATE == 'FED') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for federal trips by stock, gear and discard source for Mackerel')
db_mackerel %>% filter(FED_OR_STATE == 'STATE') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for state trips by stock, gear and discard source for Mackerel')
db_chubmackerel %>% filter(FED_OR_STATE == 'FED') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for federal trips by stock, gear and discard source for Chub Mackerel')
db_chubmackerel %>% filter(FED_OR_STATE == 'STATE') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for state trips by stock, gear and discard source for Chub Mackerel')
db_fluke %>% filter(FED_OR_STATE == 'FED') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for federal trips by stock, gear and discard source for Fluke')
db_fluke %>% filter(FED_OR_STATE == 'STATE') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for state trips by stock, gear and discard source for Fluke')
db_scup %>% filter(FED_OR_STATE == 'FED') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for federal trips by stock, gear and discard source for Scup')
db_scup %>% filter(FED_OR_STATE == 'STATE') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for state trips by stock, gear and discard source for Scup')
db_surfclam %>% filter(FED_OR_STATE == 'FED') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for federal trips by stock, gear and discard source for Surf Clam')
db_surfclam %>% filter(FED_OR_STATE == 'STATE') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for state trips by stock, gear and discard source for Surfclam')
db_oceanquahog %>% filter(FED_OR_STATE == 'FED') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for federal trips by stock, gear and discard source for Ocean Quahog')
db_oceanquahog %>% filter(FED_OR_STATE == 'STATE') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for state trips by stock, gear and discard source for Ocean Quahog')
db_alewife %>% filter(FED_OR_STATE == 'FED') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for federal trips by stock, gear and discard source for Alewife')
db_alewife %>% filter(FED_OR_STATE == 'STATE') %>% group_by(DISCARD_SOURCE, CAMS_GEAR_GROUP, SPECIES_STOCK) %>% dplyr::summarise(D = sum(CAMS_DISCARD), K = sum(SUBTRIP_KALL), Drate = mean(CAMS_DISCARD_RATE), Dmort = mean(DISC_MORT_RATIO)) %>% arrange(desc(D))%>% top_n(10) %>% dplyr::mutate(across(where(is.numeric), round, 4)) %>% mutate(across(ends_with("D"), round, 0))%>% DT::datatable(caption = 'Discard totals for state trips by stock, gear and discard source for Alewife')
For more information regarding stratification variables and discard rates by species see
MAPS.CAMS_STATAREA_STOCK MAPS.CAMS_DISCARD_MORTALITY_STOCK MAPS.CAMS_GEARCODE_STRATA MAPS.CAMS_MASTER_GEAR MAPS.CAMS_OBS_CATCH
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