update with 7.24 pull 5 year average

2024/safe/01-summary.Rmd

@@ -6,7 +6,7 @@ Flathead sole is assessed using an age-structured model and Tier 3 determination
 
 ## Summary of Changes in Assessment Inputs
 
-Changes in input data: The updated information for this harvest projection includes replacing the estimated `r this_year-1` catch with the final catch value from the Alaska Regional Office (https://www.fisheries.noaa.gov/sites/default/files/akro/car110_goa2023.html) (`r prettyNum(round(as.numeric(catchvec[2,2]),0),big.mark = ',')` t), and estimating the `r this_year`-`r this_year+2`  catches. The `r this_year` projected catch was calculated as the current catch as of `r pull_date` added to the average `r format(as.Date(pull_date), "%d %B")` – December 31 catches over the previous 5 years. The `r this_year+1`  and `r this_year+2`  projected catches were calculated as the average catch over the previous 5 years (`r prettyNum(c2,big.mark = ',')` t). These estimated catches for the present and two future years are input in place of *maxABC* for projections, which is appropriate given that recent catches are much less than the maximum ABC for this stock.
+Changes in input data: The updated information for this harvest projection includes replacing the estimated `r this_year-1` catch with the final catch value from the Alaska Regional Office (https://www.fisheries.noaa.gov/sites/default/files/akro/car110_goa2023.html) (`r prettyNum(round(as.numeric(catchvec[2,2]),0),big.mark = ',')` t), and estimating the `r this_year`-`r this_year+2`  catches. The `r this_year` projected catch was calculated as the current catch as of `r pull_date` added to the average `r format(as.Date(pull_date), "%d %B")` – December 31 catches over the previous `r average_window` years. The `r this_year+1`  and `r this_year+2`  projected catches were calculated as the average catch over the previous `r average_window` years (`r prettyNum(c2,big.mark = ',')` t). These estimated catches for the present and two future years are input in place of *maxABC* for projections, which is appropriate given that recent catches are much less than the maximum ABC for this stock.
 
 ## Summary of Results
 

2024/safe/01a-main_table.Rmd

@@ -8,7 +8,7 @@ safe_2023 <- read.csv(here::here(this_year,'safe','static_tables','safe_2023.csv
 
 ## load base safe values, made using fAK_SCENARIOS.R
 # safe0 <- read.csv(here::here(this_year,'projection', '2024-06-06-exec_summ.csv')) %>% 
-  safe0 <- read.csv(here::here(this_year,'projection', '2024-07-24-exec_summ_3yavg.csv')) %>% 
+  safe0 <- read.csv(here::here(this_year,'projection', '2024-07-24-exec_summ_5yavg.csv')) %>% 
   # t()  %>% 
   data.frame() %>%
   bind_cols(safe_2023[4:14,],.) %>%

2024/safe/01b-apportionment.Rmd

@@ -7,7 +7,7 @@ The following table shows the recommended ABC apportionment for `r this_year+1`
 
 
 ```{r}
-appo <- read.csv(here::here(this_year,'apportionment','2024-07-24-AreaApportionment-3yavg.csv'))
+appo <- read.csv(here::here(this_year,'apportionment','2024-07-24-AreaApportionment-5yavg.csv'))
 appo[2:3,4:7] <-  round(appo[2:3,4:7],0)
 appo[1,8] <- 100
 appo$Year <- as.character(appo$Year)

2024/safe/goa-fhs-2024.Rmd

@@ -61,11 +61,12 @@ library(dplyr)
 # globals
 species = 'Flathead sole'
 this_year = 2024
+average_window = 5
 date = 'October 22, 2024'
-pull_date <- lubridate::date('2024-06-04')
+pull_date <- lubridate::date('2024-07-24')
 model = "base"
 end_proj = this_year + 15 
-execsumm <- read.csv(here::here(this_year,'projection', '2024-06-06-exec_summ.csv'))[,2:3]
+execsumm <- read.csv(here::here(this_year,'projection', '2024-07-24-exec_summ_5yavg.csv'))[,2:3]
 ofl_25 <- round(execsumm[9,1]) ## ofl in mt
 ofl_26 <- round(execsumm[9,2]) ## ofl in mt
 Fofl_25 <- round(execsumm[6,1],2)
@@ -78,7 +79,7 @@ tb_25 <- execsumm[1,1] # 2025 total biomass
 abc_25 <- round(execsumm[10,1]) ## this year's ABC for 2025 
 abc_26 <- round(execsumm[10,2]) ## this year's ABC for 2025 
 # catchvec<- read.csv(here::here(this_year,'data', 'output','2024-06-04-catch_for_spm.csv'))
-catchvec<- read.csv(here::here(this_year,'data', 'output','2024-07-24-catch_for_spm-3y.csv'))
+catchvec<- read.csv(here::here(this_year,'data', 'output','2024-07-24-catch_for_spm-5y.csv'))
 c1 <- round(as.numeric(catchvec[3,2]),0) # estimated catch in current year
 c2 <- round(as.numeric(catchvec[4,2]),0)# proj catch year + 1
 c3 <- round(as.numeric(catchvec[5,2]),0) # proj catch year + 2