diff --git a/docs/data_summary_doc.qmd b/docs/data_summary_doc.qmd
index 1240901..55ffe30 100644
--- a/docs/data_summary_doc.qmd
+++ b/docs/data_summary_doc.qmd
@@ -52,7 +52,8 @@ WDFW has alerted the STAT these do not include all tribal catches in recent year
The following values were provided directly to the STAT:
```{r}
-or_comm_catch <- readr::read_csv(here("Data/Confidential/Oregon Commercial landings_433_2023.csv"))
+or_comm_catch <- read.csv(here("Data/Confidential/Oregon Commercial landings_433_2023.csv")) |>
+ tibble::as_tibble()
or_comm_catch |>
group_by(YEAR) |>
summarise(catch_mt = sum(TOTAL)) |>
@@ -74,8 +75,9 @@ Note this is for catch landed into Del Norte and Humboldt counties only.
## At-Sea landings
```{r}
-ashop_catch <- readxl::read_excel(here("Data/Confidential/Oken_YLT_Catch data_1976-2023_102824.xlsx"),
- sheet = 'Catch Summary Table')
+ashop_catch <- readxl::read_excel(
+ here("Data/Confidential/Oken_YLT_Catch data_1976-2023_102824_ASHOP.xlsx"),
+ sheet = 'Catch Summary Table')
ashop_catch |>
mutate(catch_mt = EXPANDED_SumOfEXTRAPOLATED_2SECTOR_WEIGHT_KG / 1000) |>
select(YEAR, catch_mt) |>
@@ -90,8 +92,9 @@ ashop_catch |>
Modern catches:
```{r}
-wa_modern <- readr::read_csv(here('Data/Raw_not_confidential/RecFIN_WA_catch_to_2023.csv')) |>
- filter(RECFIN_WATER_AREA_NAME != 'Canada', RECFIN_YEAR < 2023)
+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()
wa_modern |> group_by(RECFIN_YEAR) |>
summarise(Dead_Catch_mt = sum(SUM_TOTAL_MORTALITY_MT)) |>
knitr::kable(align = 'l', digits = 1)
@@ -105,7 +108,8 @@ Questions:
Historical catches:
```{r}
-wa_historical <- readr::read_csv(here('Data/Raw_not_confidential/WA_historical_rec.csv'))
+wa_historical <- read.csv(here('Data/Raw_not_confidential/WA_historical_rec.csv')) |>
+ tibble::as_tibble()
wa_historical |>
group_by(RECFIN_YEAR) |>
@@ -117,7 +121,8 @@ wa_historical |>
The following values were provided directly to the STAT:
```{r}
-or_rec_catch <- readr::read_csv(here("Data/Confidential/Oregon Recreational landings_433_2023.csv"))
+or_rec_catch <- read.csv(here("Data/Confidential/Oregon Recreational landings_433_2023.csv")) |>
+ tibble::as_tibble()
or_rec_catch |>
select(Year, Total_MT) |>
knitr::kable(align = 'l', digits = 1)
@@ -127,18 +132,19 @@ or_rec_catch |>
### California
```{r}
-ca_modern <- readr::read_csv(here('Data/Raw_not_confidential/RecFIN_CA_catch_to_2023.csv')) |>
- filter(DISTRICT_NAME == "Redwood (Humboldt County, Except Shelter Cover Area, And Del Norte County)" )
+ca_modern <- read.csv(here('Data/Raw_not_confidential/RecFIN_CA_catch_to_2023.csv')) |>
+ filter(grepl("Redwood", DISTRICT_NAME)) |>
+ tibble::as_tibble()
ca_modern |>
group_by(RECFIN_YEAR) |>
summarise(Dead_Catch_mt = sum(SUM_TOTAL_MORTALITY_MT)) |>
knitr::kable(align = 'l', digits = 1)
-
-
```
Note that 2020 proxy catches are missing, and we will need historical recreational catches that are not on RecFIN.
+MRFSS data (1981-2004) does not have an obvious way to determine whether catches should be assigned to the northern or southern stock.
+
## Length Data
### Commercial
@@ -166,14 +172,41 @@ While running `PacFIN.Utilities::cleanPacFIN()`, it noted that 20 Washington age
### Recreational
-STAT is working on it!
+VERY tentative length sample sizes. I anticipate this is biased high as I have done no filtering.
+
+```{r}
+rec_bio <- read.csv(here("Data/Confidential/RecFIN_Lengths.csv")) |>
+ tibble::as_tibble() |>
+ filter(STATE_NAME == "OREGON" | STATE_NAME == "WASHINGTON" | grepl("REDWOOD", RECFIN_PORT_NAME))
+
+or_mrfss <- read.csv(here("Data/Confidential/MRFSS_BIO_2025 CYCLE_433.csv")) |>
+ tibble::as_tibble()
+
+or_mrfss_smry <- or_mrfss |>
+ filter(Length_Flag == 'measured') |>
+ group_by(Year) |>
+ summarise(n_length = n()) |>
+ mutate(STATE_NAME = 'OREGON')
+
+rec_bio |>
+ filter(!is.na(RECFIN_LENGTH_MM), STATE_NAME != 'OREGON' | !(RECFIN_YEAR %in% or_mrfss_smry$Year)) |>
+ group_by(RECFIN_YEAR, STATE_NAME) |>
+ summarize(n_length = n()) |>
+ rename(Year = RECFIN_YEAR) |>
+ bind_rows(or_mrfss_smry) |>
+ tidyr::pivot_wider(names_from = STATE_NAME, values_from = n_length, values_fill = 0) |>
+ arrange(Year) |>
+ knitr::kable(align = 'l')
+```
+From Oregon MRFSS data (provided directly to the STAT, covering `r min(or_mrfss_smry$Year)` to `r max(or_mrfss_smry$Year)`) this only includes counts of samples with `Length_Flag == "measured"`. I was not sure of recommendations for how to filter the data.
### At-Sea
```{r}
-ashop_lengths_old <- readxl::read_excel(here("Data/Confidential/Oken_YLT_Length data_1976-2023_102824.xlsx"),
- sheet = "YLT_Length data 1976-1989")
+ashop_lengths_old <- readxl::read_excel(
+ here("Data/Confidential/Oken_YLT_Length data_1976-2023_102824_ASHOP.xlsx"),
+ sheet = "YLT_Length data 1976-1989")
ashop_lengths_new <- suppressWarnings(
- readxl::read_excel(here("Data/Confidential/Oken_YLT_Length data_1976-2023_102824.xlsx"),
+ readxl::read_excel(here("Data/Confidential/Oken_YLT_Length data_1976-2023_102824_ASHOP.xlsx"),
sheet = "YLT_Length data1990-2023") # warning is about converting text to numeric
)
diff --git a/docs/index.html b/docs/index.html
index a5805fc..e5b3ef4 100644
--- a/docs/index.html
+++ b/docs/index.html
@@ -6,7 +6,7 @@
-
+
Data summary