noaa-garfo/discaRd
Cochran bycatch estimation

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In noaa-garfo/discaRd: Cochran bycatch estimation 

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 = '')

Background

Exploration of discard estimates from may year module

Steps

  1. pull all merged trips from CAMS_OBS_CATCH

  2. 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)
- SECTID comes from a CAMS matching table (`MAPS.MATCH_MULT_SECTID`)
  1. Run discaRd
    • there are sub-passes for year t and year t-1
# Assumed Stratification variables

stratvars = c('SPECIES_STOCK'
              , 'CAMS_GEAR_GROUP',
              ,'MESHGROUP')

  1. 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'.

  2. 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.

  3. 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.

  4. Rates and DISCARD_SOURCE (in parentheses) are assigned for each trip according to:

  5. (I) in season rate; >= 5 trips in Full Stratification
  6. (T) Transition in season rate; < 5 trips in Full Stratification, year t, AND >= 5 trips in year t-1
  7. (A) Assumed rate. This is the rate when there were <5 trips in season and <5 in previous season.
  8. (G) Broad stock/gear rate <5 trips in season and <5 trips in previous season
  9. (N) No coverage in focal season and previous season; discard rate is not possible to estimate.

  10. (O) Observed values used from observed rate trips; discard rate is NOT USED.

  11. CV calculations are available for (I), (T), (A) and (G).

  12. 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), (A) 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_BARNDOORSKATE_2019
    CAMS_GARFO.CAMS_DISCARD_BARNDOORSKATE_2019

    MAPS.CAMS_DISCARD_SKATECLEARNOSE_2019
    CAMS_GARFO.CAMS_DISCARD_SKATECLEARNOSE_2019

    MAPS.CAMS_DISCARD_SKATELITTLE_2019
    CAMS_GARFO.CAMS_DISCARD_SKATELITTLE_2019

    MAPS.CAMS_DISCARD_SKATEROSETTE_2019
    CAMS_GARFO.CAMS_DISCARD_SKATEROSETTE_2019

    MAPS.CAMS_DISCARD_SKATESMOOTH_2019
    CAMS_GARFO.CAMS_DISCARD_SKATESMOOTH_2019

    MAPS.CAMS_DISCARD_SKATEWINTER_2019
    CAMS_GARFO.CAMS_DISCARD_SKATEWINTER_2019

Diagnostic Plots/Tables

# 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/MAY/Skate_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')

Combined skate discard estimates are much higher for the seven skate species included in the MAPS discard mortality support table (ITIS: 564139, 160855, 564130, 564130, 564136, 564151, 564149 and 564145) compared to the 11 used for QM (160845, 160846, 160848, 160855, 564037, 564130, 564136, 564139, 564145, 564149, 564151).

Probably due to differences in gear types and discard mortality rates which I believe are just one value across skates for QM.

discard <- read.csv("~/discaRd/CAMS/MODULES/MAY/Skate_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')

 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_barndoorskate = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_SKATEBARNDOOR_2019")) %>% 
    collect

db_barndoorskate$SPECIES <- "BARNDOORSKATE"

db_clearnoseskate = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_SKATECLEARNOSE_2019")) %>% 
    collect

db_clearnoseskate$SPECIES <- "CLEARNOSESKATE"

db_littleskate= tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_SKATELITTLE_2019")) %>% 
    collect

db_littleskate$SPECIES <- "LITTLESKATE"

db_rosetteskate = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_SKATEROSETTE_2019")) %>% 
    collect

db_rosetteskate$SPECIES <- "ROSETTESKATE"

db_smoothskate = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_SKATESMOOTH_2019")) %>%
    collect

db_smoothskate$SPECIES <- "SMOOTHSKATE"

db_winterskate = tbl(bcon, sql("select * from MAPS.CAMS_DISCARD_SKATEWINTER_2019")) %>%
    collect

db_winterskate$SPECIES <- "WINTERSKATE"


db_final <- rbind(db_barndoorskate, db_clearnoseskate, db_littleskate, 
                  db_rosetteskate, db_smoothskate, db_winterskate)

strat_barndoorskate <- db_barndoorskate %>%     
   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_clearnoseskate <- db_clearnoseskate %>%   
    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_littleskate <- db_littleskate %>%     
  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_rosetteskate <- db_rosetteskate %>%   
 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_smoothskate <- db_smoothskate%>%
  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_winterskate <- db_winterskate%>%
  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_barndoorskate, strat_clearnoseskate, strat_littleskate,
                     strat_rosetteskate, strat_smoothskate, strat_winterskate)


  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_barndoorskate %>%    
  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 Barndoor Skate')

db_barndoorskate %>%    
  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 Barndoor Skate')

db_clearnoseskate %>%   
   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 Clearnose Skate')

db_clearnoseskate %>%   
   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 Clearnose Skate')

db_littleskate %>%  
  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 Little Skate')

db_littleskate %>%  
  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 Little Skate')

db_rosetteskate %>%     
  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 Rosette Skate')

db_rosetteskate %>%     
  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 Rosette Skate')

db_smoothskate %>%  
  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 Smooth Skate')

db_smoothskate %>%  
  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 Smooth Skate')

db_winterskate %>%  
  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 Winter Skate')

db_winterskate %>%  
  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 Winter Skate')

db_barndoorskate %>% 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 Barndoorskate')

db_barndoorskate %>% 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 Barndoorskate')

db_clearnoseskate %>% 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 Clearnoseskate')

db_clearnoseskate %>% 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 Clearnoseskate')

db_littleskate %>% 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 Littleskate')

db_littleskate %>% 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 Littleskate')

db_rosetteskate %>% 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 Rosetteskate')

db_rosetteskate %>% 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 Rosetteskate')

db_smoothskate %>% 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 Smoothskate')

db_smoothskate %>% 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 Smoothskate')

db_winterskate %>% 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 Winterskate')

db_winterskate %>% 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 Winterskate')

Appendix

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



noaa-garfo/discaRd documentation built on April 17, 2025, 10:32 p.m.

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