post 12/1 data update. Add STAR panel report.

docs/data_summary_doc.qmd

@@ -25,7 +25,7 @@ This documents data streams for use in the Northern Yellowtail Rockfish stock as
 Some summary figures:
 
 ```{r pacfin-catch, cache=TRUE}
-load(here('data/confidential/commercial/PacFIN.YTRK.CompFT.09.Oct.2024.RData'))
+load(here('data/confidential/commercial/pacfin_12-09-2024/PacFIN.YTRK.CompFT.09.Dec.2024.RData'))
 # I have checked and LANDING_YEAR = PACFIN_YEAR for all rows.
 
 yt_n_catch_pacfin <- catch.pacfin |>
@@ -43,7 +43,7 @@ or_comm_catch <- read.csv(here("Data/Confidential/commercial/Oregon Commercial l
 comm_draft_landings <- yt_n_catch_pacfin |> 
   filter(AGENCY_CODE != 'O') |> 
   group_by(PACFIN_YEAR, AGENCY_CODE)|>
-  summarise(catch_mt = sum(LANDED_WEIGHT_MTONS)) |>
+  summarise(catch_mt = sum(ROUND_WEIGHT_MTONS)) |>
   rename(YEAR = PACFIN_YEAR) |>
   bind_rows(
     mutate(or_comm_catch, AGENCY_CODE = 'O')
@@ -73,7 +73,7 @@ comm_draft_landings |>
 # landings by gear type
 yt_n_catch_pacfin |>
   group_by(PACFIN_GROUP_GEAR_CODE, LANDING_YEAR) |>
-  summarise(landings_mt = sum(LANDED_WEIGHT_MTONS)) |>
+  summarise(landings_mt = sum(ROUND_WEIGHT_MTONS)) |>
   ggplot() +
   geom_col(aes(x = LANDING_YEAR, y = landings_mt, fill = factor(PACFIN_GROUP_GEAR_CODE, levels = c('TWL', 'MSC', 'NET', 'POT', 'TLS', 'TWS', 'HKL')))) +
   ggtitle('Commercial landings through 2023 by gear') +
@@ -84,7 +84,7 @@ yt_n_catch_pacfin |>
 yt_n_catch_pacfin |>
   mutate(geargroup2 = ifelse(PACFIN_GEAR_CODE == "MDT", yes = "MDT", no = PACFIN_GROUP_GEAR_CODE)) |> # split midwater trawl as MDT
   group_by(geargroup2, LANDING_YEAR) |>
-  summarise(catch_mt = sum(LANDED_WEIGHT_MTONS)) |>
+  summarise(catch_mt = sum(ROUND_WEIGHT_MTONS)) |>
   ggplot() +
   geom_col(aes(x = LANDING_YEAR, y = catch_mt, fill = factor(geargroup2, levels = c("TWL", "MDT", "MSC", "NET", "POT", "TLS", "TWS", "HKL")))) +
   ggtitle("Commercial landings through 2023 by gear with midwater trawl separated") +
@@ -136,8 +136,8 @@ ashop_catch |>
 # WASHINGTON
 wa_modern <- read.csv(here('Data/Raw_not_confidential/RecFIN_WA_catch_to_2023.csv')) |>
   filter(RECFIN_WATER_AREA_NAME != 'Canada', RECFIN_YEAR <= 2023) |>
-  tibble::as_tibble() |>
-  group_by(RECFIN_YEAR) |>
+  tibble::as_tibble() |> filter(RECFIN_YEAR == 2023) |> 
+  group_by(RECFIN_YEAR) |> 
   summarise(Dead_Catch = sum(SUM_TOTAL_MORTALITY_MT)) |>
   mutate(State = 'WA (mt)')
 
@@ -209,9 +209,10 @@ crfs_ratios <- read.csv(here('Data/Raw_not_confidential/RecFIN_CA_catch_to_2023.
   filter(grepl('Redwood', DISTRICT_NAME))
 
 # This is pre-filtered to N. CA MRFSS only
-ca_mrfss_catch <- read.csv(here('Data/Confidential/Rec/RecFIN_CA_MRFSS.csv')) |> 
+ca_mrfss_catch <- read.csv(here('Data/Confidential/Rec/RecFIN_CA_MRFSS.csv')) |>
+  arrange(desc(WGT_AB1)) |> 
   group_by(YEAR) |>
-  summarise(n_ca_catch_mt = sum(WGT_AB1, na.rm = TRUE)/1000) |>
+  summarise(n_ca_catch_mt = sum(WGT_AB1, na.rm = TRUE)/1000) |> 
   # for MRFSS phase 2, calculate ratio above 40-10 by weighted average of Albin and CRFS ratios
   # weights are the inverse of time to last Albin year, first CRFS year
   mutate(weighted_ratio = (albin$pct / (YEAR - 1986) + crfs_ratios$pct / (2005 - YEAR)) / (1/(YEAR - 1986) + 1/(2005 - YEAR)),
@@ -242,8 +243,8 @@ bind_rows(or_rec_catch, wa_modern, wa_historical, ca_modern, ca_mrfss_catch, ca_
 #### Outstanding issues for WA:
 
 1.  There are three values for `RECFIN_WATER_AREA_NAME`: Estuary, Ocean, and Canada. Which should be included? Above table excludes Canada.
-2.  2023 has a number of instances where `RECFIN_WEEK` is zero, and one instance where is it missing. In the instance where it is missing, there is no estimate of catch in mt.
-3.  Will likely convert the numbers in the historical sport landings to weight in mt. On the to do list.
+2.  2023 has a number of instances where `RECFIN_WEEK` is zero, ~~and one instance where is it missing. In the instance where it is missing, there is no estimate of catch in mt.~~ Is `RECFIN_WEEK` of zero any cause for concern?
+3.  Will likely convert the numbers in the historical sport landings to weight in mt. Waiting for rec biodata before this is possible.
 
 #### Method for CA MRFSS catches:
 
@@ -262,7 +263,7 @@ For CA rec catch estimates for the assessment:
 -   1993-2004: Multiply total N. CA catch by weighted average of Albin ratio (1) and CRFS ratio. Weights are inverse of time to last Albin year or first CRFS year.
 -   1990-1992: Interpolate between average of 1987-1989 and 1993-1995
 
-**Concern**: Catches for 1980-1989 look somewhat high. They exceed rec catches in OR in 1982 and 1983.
+**Concern**: Catches for 1980-1989 look somewhat high. They exceed rec catches in OR in 1982 and 1983. 1982, in particular, has much higher MRFSS catches in N. CA than any other year.
 
 ## Comp Data
 
@@ -271,7 +272,7 @@ For CA rec catch estimates for the assessment:
 Initial length sample sizes after running `PacFIN.Utilities::cleanPacFIN()`:
 
 ```{r comm-bio, cache=TRUE}
-load(here('Data/Confidential/Commercial/PacFIN.YTRK.bds.09.Oct.2024.RData'))
+load(here('Data/Confidential/Commercial/pacfin_12-09-2024/PacFIN.YTRK.bds.09.Dec.2024.RData'))
 bds_clean <- PacFIN.Utilities::cleanPacFIN(bds.pacfin, verbose = FALSE) 
 bds_clean |>
   filter(state == 'WA' | state == 'OR' | PACFIN_GROUP_PORT_CODE == 'CCA' |
@@ -477,6 +478,11 @@ yt_survey_bio <- nwfscSurvey::pull_bio(common_name = 'yellowtail rockfish', surv
 
 yt_n_survey_bio <- filter(yt_survey_bio, Latitude_dd > 40 + 1/6)
 
+yt_tri_bio <- yt_survey_bio <- nwfscSurvey::pull_bio(common_name = 'yellowtail rockfish', survey = 'Triennial') 
+
+yt_n_tri_bio <- purrr::map(yt_tri_bio, \(dat) filter(dat, Latitude_dd > 40 + 1/6))
+
+
 # looking at how growth varies over space and time
 # clear break point in selectivity between age 5 and 6.
 filter(yt_n_survey_bio, Age_years <= 20, Age_years >= 6) |>