Update SR text

doc-sr/01_context.Rmd

@@ -3,18 +3,14 @@
 ```{r para-1-context-en, eval = !fr(), results = 'asis'}
 cat("# Context
 
-`r sp` (*`r sp_science`*) stock status on the West Coast of `r bc` was assessed using data from 1996--2021 and examined at a CSAS review meeting on October 19 and 20, 2022.
+`r sp` (*`r sp_science`*) stock status on the West Coast of `r bc` was assessed using data from 1996--2021 and examined at a CSAS review meeting on October 19 and 20, 2022. The biomass of this stock has been declining since 2012, and an assessment was requested by the Pacific Groundfish Management Unit (GMU) in 2022. In the `r ca`, the stock was estimated slightly below the Upper Stock Reference (USR) in the base model and close to the Limit Reference Point (LRP) under one sensitivity model with higher recruitment variation. The model also showed declining estimated spawning stock biomass, declining survey indices, and declining estimated recruitment. Due to all of these issues, a two-year update on the stock was requested by the GMU. Two years was chosen because it it a relatively short amount of time, but long enough that all of the surveys included in the model would have another data point added to their indices.
 
-The model used to assess this stock was the Inegrated Statistic Catch-at-Age Model (`r iscam`) and was tuned to five fishery-independent trawl survey series covering `r start_catch_yr`--2021. In addition, a Discard CPUE series was used as an index of abundance. This series was created using discards from fishery trawl catch as a proxy for CPUE.
+The `r ca` estimated a median stock size at the beginning of 2022 (or end of 2021) of 67.95 kilotonnes (kt) with a credible interval of 56.14--83.83 kt. When divided by the estimated unfished biomass ($B_0$), the median relative biomass for 2022 was estimated to be 0.37 with a credible interval of 0.26--0.51. The estimated median relative biomass for 2011, was estimated to be 0.77 with a credible interval of 0.53--1.09. The estimated biomass declined each year from 2011--2021.
 
-A two-sex, two-fleet base model was selected and implemented in a Bayesian context using Markov chain Monte Carlo (MCMC) methods.
-
-The 2021 assessment estimated a median stock size at the beginning of 2022 of 67.95 kilotonnes (kt) with a credible interval of 56.14--83.83 kt. When divided by the estimated initial or virgin biomass ($B_0$), the median relative biomass for 2022 was estimated to be 0.37 with a credible interval of 0.26--0.51. The esimated median relative biomass for 2011 (10 years prior), was estimated to be 0.77 with a credible interval of 0.53--0.1.09. The estimated biomass declined each year from 2011--2021.
-
-A summary of the 2021 stock assessment can be found in the [Science Advisory Report 2023/042](https://www.dfo-mpo.gc.ca/csas-sccs/Publications/SAR-AS/2023/2023_042-eng.html).
+A summary of the `r ca` can be found in the [Science Advisory Report 2023/042](https://www.dfo-mpo.gc.ca/csas-sccs/Publications/SAR-AS/2023/2023_042-eng.html).
 
 This Science Response results from the Science Response Process of October 2, 2024 on the
-Stock Assessment Update of `r sp` (`r sp_science`) for `r bc` in 2024.
+Stock Assessment Update of `r sp` (*`r sp_science`*) in `r bc` in 2024.
 ")
 ```
 

doc-sr/02_background.Rmd

@@ -3,11 +3,11 @@ cat("# Background
 
 ## Description of the Fishery and Management
 
-The commercial fishery for `r sp` has been active for decades. Prior to 2006 there were no limits on the amount of `r sp` that could be caught. In 2006 a TAC of 15,000 t was established and it remained at this level until 2017. In 2017, the TAC was increased to 17,500 t and remained there for two years until it was reduced to 14,000 t in 2019 as a precautionary measure to address concerns raised by the commercial trawl fleet about their oberved reduction in abundance of Arrowtooth Flounder. In 2020 the TAC was decreased to 5,000 t to address industry concerns regarding declining `r sp` abundance on traditional fishing grounds (DFO 2020).
+The commercial fishery for `r sp` has been active for decades. Prior to 2006 there were no limits on the amount of `r sp` that could be caught. In 2006 a Total Allowable Catch (TAC) of 15 kt was established and it remained at this level until 2017. In 2017, the TAC was increased to 17.5 kt and remained there for two years until it was reduced to 14 kt in 2019 as a precautionary measure to address concerns raised by the commercial trawl fleet about their oberved reduction in abundance of Arrowtooth Flounder. In 2020 the TAC was decreased to its current level of 5 kt to address industry concerns regarding declining `r sp` abundance on traditional fishing grounds (@dfomemo2020).
 
 Before the introduction of 100% at-sea observer coverage in the `r bc` groundfish fleets in 1996, reporting of `r sp` discards in fishery logbooks was mandatory, but since `r sp` were not given a TAC until 2005, there was little incentive for skippers to record discards accurately until at-sea observers were present aboard vessels starting in 1996.
 
-The assessment model has been updated by adding new catch for 2022 and 2023. This can be seen in Table \@ref(tab:overall-catch-table) and Figure \@ref(fig:fig-catch-fleet). The Discard CPUE series was also updated.
+Since the `r ca`, there have been two years of new `r sp` commercial catch (2022 and 2023). These values are presented in Table \@ref(tab:fleet-catch-table) and Figure \@ref(fig:fig-catch-fleet). The catch for the Freezer Trawler fleet increased by `r perc_inc_ft_2021_2022`% from 2021 to 2022, but then decreased by `r perc_dec_ft_2022_2023`% from 2022 to 2023. The Shoreside fleet decreased for both years, by `r perc_dec_ss_2021_2022`% from 2021 to 2022, and by `r perc_dec_ss_2022_2023`% from 2022 to 2023.
 
 ")
 ```
@@ -34,7 +34,7 @@ plot_catch_fleet(list(catch_ft, catch_ss),
 
 ```
 
-```{r ft-catch-table, results = "asis"}
+```{r fleet-catch-table, results = "asis"}
 cap <- paste0("Recent coastwide commercial fishery landings and discards ",
  "(t) of ", sp, " by fleet.")
 if(fr()){
@@ -48,5 +48,6 @@ table_catch_fleet(list(catch_ft, catch_ss),
  caption = cap,
  start_yr = 1996,
  font_size = 8,
+ longtable = FALSE,
  gear_col_widths = "6em")
 ```

doc-sr/03_analysis.Rmd

@@ -1,9 +1,23 @@
-```{r analysis-and-response-survey-en, eval = !fr(), results = 'asis'}
+```{r analysis-and-response-model-en, eval = !fr(), results = 'asis'}
 cat("# Analysis and Response
 
-## Survey Indices and Catch
+## Stock assessment model
 
-For each survey index included in the assessment, there was one new index point added for this Science Response. For the `r wcviss` there was a new index point for 2022. For the `r qcsss` and the `r hsss`, there was a new index point for 2023. For the Discard CPUE, two new index points were estimated and added, for 2022 and 2023. Since the Discard CPUE is a Generalized Linear Mixed Model (GLMM), all the indices in the time series were slightly different than those used in the 2022 assessment. Figure \@ref(fig:fig-base-index-fits) shows the index fits. The 2022 point for the `r dcpue` and the 2023 point for the `r qcsss` were not fit very well by the model, however the overall trends of those indices and the others follow those seen in the 2022 stock assessment.
+The model used to assess this stock was the Integrated Statistical Catch-at-Age Model (`r iscam`). It was tuned to four fishery-independent trawl survey series covering `r start_catch_yr`--2021, a Discard CPUE series as an index of abundance, annual estimates of commercial catch from two fleets (Freezer Trawlers and Shoreside), and age composition data from the two fleets in the commercial fishery and the four surveys. A two-sex, two-fleet base model was selected and implemented in a Bayesian context using Markov Chain Monte Carlo (MCMC) methods. Leading parameters estimated included $R_0$, initial recruitment, $h$, steepness of the stock-recruitment relationship, $\bar{R}$, average recruitment, and $q_k, k=1,2,3,4,5$, catchability of the four surveys and the Discard CPUE index. Selectivity parameters were also estimated for each sex, fleet, and survey.
+
+")
+```
+
+```{r analysis-and-response-model-fr, eval = fr(), results = 'asis', needs_trans = TRUE}
+<<analysis-and-response-model-en>>
+```
+
+```{r analysis-and-response-survey-en, eval = !fr(), results = 'asis'}
+cat("## Survey Indices and Catch
+
+Since the `r ca`, there has been one new year added for each survey index included (Figure \@ref(fig:fig-base-index-fits)), except for the `r hsmas` which has a terminal year of 2003. The `r wcviss` took place in 2022, and the `r qcsss` and the `r hsss` both took place in 2023. The `r dcpue` had two new index points estimated and added, for 2022 and 2023. The `r dcpue` is created using a Generalized Linear Mixed Model (GLMM), and as such all the indices in the time series are estimated each time new data are added. The estimated values for each year in the `r dcpue` were therefore slightly different than those used in the `r ca` (the light grey points and bars in Figure \@ref(fig:fig-base-index-fits)).
+
+The 2022 point for the `r dcpue` and the 2023 point for the `r qcsss` were not fit well by the model, however the median posterior estimates are within the 95% index confidence intervals for those years. Overall trends of all indices follow those seen in the `r ca`, with the `r qcsss` and `r hsss` indices being fit slightly better in the 2005--2012 time period than in the 2022 assessment.
 
 ")
 ```
@@ -15,15 +29,15 @@ For each survey index included in the assessment, there was one new index point
 ```{r analysis-and-response-growth-en, eval = !fr(), results = 'asis'}
 cat("## Growth
 
-Growth parameters were estimated outside the `r iscam` model and the only differences when compared to the 2022 assessment were in the scalar in length-weight allometry ($\alpha$) parameter for males which went from $0.0000095$ in the 2022 assessment to $`r base_model$dat$lw.alpha[2]`$, the power in length-weight allometry ($\beta$) parameter for females which went from $3.0515274$ in the 2022 assessment to $`r base_model$dat$lw.beta[1]`$, and the power in length-weight allometry ($\beta$) parameter for males which went from $2.9741834$ in the 2022 assessment to $`r base_model$dat$lw.beta[2]`$. Table \@ref(tab:growth-params-table) shows all the values input into the model for this update.
+Growth parameters were estimated outside the `r iscam` model and the only differences when compared to the `r ca` were in the scalar in length-weight allometry ($\alpha$) parameter for males which went from $0.0000095$ in the 2022 assessment to $`r base_model$dat$lw.alpha[2]`$, the power in length-weight allometry ($\beta$) parameter for females which went from $3.0515274$ in the 2022 assessment to $`r base_model$dat$lw.beta[1]`$, and the power in length-weight allometry ($\beta$) parameter for males which went from $2.9741834$ in the 2022 assessment to $`r base_model$dat$lw.beta[2]`$. Table \@ref(tab:growth-params-table) shows all the values input into the model for this update.
 
 ")
 ```
 
 ```{r analysis-and-response-loengths-en, eval = !fr(), results = 'asis'}
 cat("## Length and Age data
 
-Length data have continued to be recorded for the surveys, but have deteriorated in the fishery. Figure \@ref(fig:fig-lengths) shows the lack of commercial lengths since 2019, except for a small amounts in 2019 and 2023 for the Freezer Trawler fleet. Recent survey data show a simliar trend to previous years, with more large females than males in the stock. In 2023, the Freezer Trawler fleet saw a larger proportion of males.
+Sex-specific length data have continued to be recorded for the surveys, but have been almost non-existent in the fishery after 2019. Figure \@ref(fig:fig-lengths) shows the lack of commercial lengths since 2019, except for a small amount in 2019 and moderate amount in 2023 for the Freezer Trawler fleet. Recent survey data show a simliar trend to previous years, with more large females than males in the stock. In 2023, the Freezer Trawler fleet saw a larger proportion of males.
 
 Samples from 2022 and 2023 were not aged for this update, and therefore not included in the update model.
 
@@ -76,6 +90,17 @@ plot_vuln_mcmc(base_model,
  leg_loc = c(0.05, 0.05))
 ```
 
+(ref:fig-base-recr-en) Recruitment of `r sp` for the base model. The black points are the medians of the posteriors, the vertical black lines are the 95% CIs for the posteriors, the point at $R_0$ is the median estimate for the initial recruitment parameter $R_0$, and the vertical line over that point and shaded ribbon across the time series is the 95% CI for $R_0$.
+
+(ref:fig-base-recr-fr) Recrutement de `r sp` pour le modèle de base. Les points noirs sont les médianes des valeurs postérieures, les lignes noires verticales sont les IC à 95% des valeurs postérieures, le point à $R_0$ est l'estimation médiane du paramètre de recrutement initial $R_0$, et la ligne verticale au-dessus de ce point et le ruban ombré à travers la série temporelle est l'IC à 95% pour $R_0$.
+
+```{r fig-base-recr, fig.cap = ifelse(fr(), "(ref:fig-base-recr-fr)", "(ref:fig-base-recr-en)")}
+plot_recr_mcmc(base_model,
+ angle_x_labels = TRUE,
+ text_title_size = NULL,
+ leg_loc = NULL)
+```
+
 (ref:fig-base-index-fits-en) Index fits for the base model. The light grey points and vertical lines show the index values and 95% CIs; the black points show the medians of the posteriors; the black solid vertical lines show the 95% CIs of the posteriors.
 
 <!-- The 2014 WCHG Synoptic index point is shown but was not included in the model. -->
@@ -211,7 +236,7 @@ Typically, DFO's reference points of $0.4B_{MSY}$ for the LRP and $0.8B_{MSY}$ f
 
 Harvest decision tables are provided as advice to managers (Tables \@ref(tab:decision-table-02bo)--\@ref(tab:decision-table-decreasing-biomass)) with constant catch policies ranging from 0 to 8 kilotonnes, from `r base_model$dat$end.yr + 1` to `r base_model$dat$end.yr + base_model$proj$num.projyrs + 1`. To interpret the decision tables with respect to the LPR ($0.2B_0$) and USR ($0.4B_0$), the probability of being above the USR is $P(B_t > USR)$, the probability of being above the LRP but below the USR is $P(B_t > LRP) - P(B_t > USR)$, and the probability of being below the LRP is $1 - P(B_t > LRP)$.
 
-During the review meeting for the 2022 stock assessment, participants deliberated about the validity of the USR being set to $0.4B_0$ and requested an 'alternative USR' of $0.35B_0$. This was included in the 2022 Research Document and is included here as well.
+During the review meeting for the `r ca`, participants deliberated about the validity of the USR being set to $0.4B_0$ and requested an 'alternative USR' of $0.35B_0$. This was included in the 2022 Research Document and is included here as well.
 
 Harvest decision tables provided in this document include:
 
@@ -364,4 +389,4 @@ table_decision(base_model,
 ### Comparison with previous assessment
 
 , and output similar fits to the
-survey indices and the discard CPUE index as it did in the 2022 stock assessment.
+survey indices and the discard CPUE index as it did in the `r ca`.

doc-sr/_bookdown.yml

@@ -1,12 +1,13 @@
 book_filename: "sr"
 rmd_files: ["index.Rmd",
+ #"test.Rmd"
  "01_context.Rmd",
  "02_background.Rmd"
- #"03_analysis.Rmd",
+ "03_analysis.Rmd",
  #"04_conclusions.Rmd",
  #"05_contributors.Rmd",
  #"06_approval.Rmd",
  #"07_bibliography.Rmd",
- #"08_appendix.Rmd"]
- ]
+ #"08_appendix.Rmd",
+ "999-blank.Rmd"]
 delete_merged_file: true

doc-sr/index.Rmd

@@ -30,17 +30,18 @@ cat_no: "Cat-Number-Here"
 # with `csas_table()` that cross page boundaries. If `false`, these will
 # both be absent from all tables. If it is missing or any other value than
 # `false`, it will be assumed to be `true`
-show_continued_text: true
+show_continued_text: false
 output:
  csasdown::sr_pdf:
+ #latex_engine: lualatex
  french: false
  prepub: false
  # copy_sty is a toggle to copy the style file from the csasdown package every time you compile
  # the document. If false, any changes you have made to the style file in your project
  # will remain between compilations. If true, your changes will be lost when you compile
  copy_sty: true
  # line_nums is a toggle to show line numbers on the left side of the page. 
- line_nums: true
+ line_nums: false
  # line_nums_mod represents showing every Nth line if line_nums is true
  line_nums_mod: 1
  # draft_watermark is a toggle to show/not show a DRAFT watermark across every page
@@ -138,6 +139,7 @@ options(knitr.graphics.rel_path = FALSE)
 library(devtools)
 library(dplyr)
 if(as.logical(length(grep("grandin", user)))){
+ load_all("~/github/kableExtra")
  load_all("~/github/pbs-assess/gfiscamutils")
  load_all("~/github/pbs-assess/gfplot")
  load_all("~/github/pbs-assess/csasdown")
@@ -157,7 +159,7 @@ library(gfutilities)
 library(ggplot2)
 library(gridExtra)
 library(here)
-library(kableExtra)
+#library(kableExtra)
 library(purrr)
 library(rosettafish)
 library(tidylog, warn.conflicts = FALSE)
@@ -679,6 +681,21 @@ if(vuln_ratio_yr %in% colnames(models$sens_grps[[4]][[2]]$mcmccalcs$vbt_quants[[
  sel_eq_mat_vuln_ratio <- sel_eq_mat_vuln_bio / sel_eq_mat_bio
 }
 
+ct_ft_2021 <- catch_ft |> filter(year == 2021) |> summarize(value = sum(value))
+ct_ft_2022 <- catch_ft |> filter(year == 2022) |> summarize(value = sum(value))
+perc_inc_ft_2021_2022 <- f(ct_ft_2022 / ct_ft_2021 * 100 - 100, 1)
+
+ct_ft_2023 <- catch_ft |> filter(year == 2023) |> summarize(value = sum(value))
+perc_dec_ft_2022_2023 <- f(100 - ct_ft_2023 / ct_ft_2022 * 100, 1)
+
+ct_ss_2021 <- catch_ss |> filter(year == 2021) |> summarize(value = sum(value))
+ct_ss_2022 <- catch_ss |> filter(year == 2022) |> summarize(value = sum(value))
+ct_ss_2023 <- catch_ss |> filter(year == 2023) |> summarize(value = sum(value))
+perc_dec_ss_2021_2022 <- f(100 - ct_ss_2022 / ct_ss_2021 * 100, 1)
+perc_dec_ss_2022_2023 <- f(100 - ct_ss_2023 / ct_ss_2022 * 100, 1)
+
+# Current assessment text
+ca <- "2022 stock assessment"
 ```
 
 ```{r removal-rate-calcs}

doc/bib/refs.bib

@@ -1369,17 +1369,13 @@ @article{starr2018
 }
 
 
-@Article{ forrest2020pcod,
- author = {Forrest, R. E. and Anderson, S. C. and Grandin, C. J. and
- Starr P. J.},
- year = {2020},
- title = {Assessment of {Pacific Cod} ({\emph{Gadus macrocephalus}})
- for {Hecate Strait} and {Queen Charlotte Sound} ({Area
- 5ABCD}), and {West Coast Vancouver Island} ({Area 3CD}) in
- 2018},
- journal = {DFO Can. Sci. Advis. Sec. Res. Doc.},
- volume = {2020/070},
- pages = {v + 215~p}
+@Article{forrest2020pcod,
+ author = {Forrest, R. E. and Anderson, S. C. and Grandin, C. J. and Starr P. J.},
+ year = {2020},
+ title = {Assessment of {Pacific Cod} ({\emph{Gadus macrocephalus}}) for {Hecate Strait} and {Queen Charlotte Sound} ({Area 5ABCD}), and {West Coast Vancouver Island} ({Area 3CD}) in 2018},
+ journal = {DFO Can. Sci. Advis. Sec. Res. Doc.},
+ volume = {2020/070},
+ pages = {v + 215~p}
 }
 %https://waves-vagues.dfo-mpo.gc.ca/Library/40952290.pdf