Move dynamic B0 text

doc/030-statistical-catch-at-age-model.Rmd

@@ -104,6 +104,18 @@ Although the PA Policy recommends $F_\mathrm{MSY}$ as a provisional reference re
 ")
 ```
 
+```{r dynamic-bo-fr, eval = fr(), results = 'asis', needs_trans = FALSE}
+cat("## DYNAMIQUE $B_0$ {#dynamic-bo}
+
+Un $B_0$ dynamique a été calculé dans R à l'aide des valeurs moyennes des paramètres et étendu pour inclure le modèle de capture par âge à deux flottes et deux sexes. La mortalité par pêche a été fixée à zéro et toutes les estimations moyennes des paramètres ont été incluses. La figure \@ref(fig:fig-dynamic-b-zero) montre les trajectoires de biomasse estimées pour ce cas.
+
+La biomasse calculée en utilisant une approche dynamique $B_0$ est significativement plus élevée pour toutes les années qu'en utilisant une approche non dynamique $B_0$.
+
+Ce travail a été réalisé à la demande des participants à la réunion d'examen, après la première version de cette évaluation du stock.")
+```
+
+```
+
 ```{r scam-fishery-reference-points-fr, eval = fr(), results = 'asis', needs_trans = FALSE}
 cat("## POINTS DE RÉFÉRENCE DE LA PÊCHE {#scam-ref-points}
 

doc/035-base-model-results.Rmd

@@ -120,7 +120,11 @@ L'estimation médiane a posteriori de $B_\mathrm{MSY}$ (et de l'IC à 95%), cond
 cat("### Biomass {#scam-biomass}
 The base model estimates the spawning biomass to have been on a decreasing trajectory since 2012 (Figure \@ref(fig:fig-base-sb), Table \@ref(tab:biomass-table)). The posterior median (and 95% CI) spawning biomass in `r assess_yr` is projected to be `r f(proj_bio[2] * 1000)` t (`r f(proj_bio[1] * 1000)`--`r f(proj_bio[3] * 1000)`) (Table \@ref(tab:reference-points-table)). The median projected beginning-of-year `r assess_yr` spawning biomass, which incorporates fishing mortality arising from the observed `r end_yr` catch, is considerably higher than median estimates of both the default USR of $0.8B_\mathrm{MSY}$ and the default LRP of $0.4B_\mathrm{MSY}$ (Figure \@ref(fig:fig-base-sb), Table \@ref(tab:reference-points-table)). The `r assess_yr` spawning biomass was projected to be slightly below the USR $0.4B_0$ and above the LRP $0.2B_0$ (Figure \@ref(fig:fig-base-depletion), Table \@ref(tab:reference-points-table)).
 
-For comparison, posterior estimates of vulnerable biomass and spawning biomass are shown together in Figure \@ref(fig:fig-base-sb-vuln-compare). The two estimated vulnerable biomasses are considerably smaller than the spawning biomass, due to the relatively early age at maturity compared to the estimated age-at-50%-harvest, discussed in Sections \@ref(scam-ref-points) and \@ref(fishery-ref-points).")
+For comparison, posterior estimates of vulnerable biomass and spawning biomass are shown together in Figure \@ref(fig:fig-base-sb-vuln-compare). The two estimated vulnerable biomasses are considerably smaller than the spawning biomass, due to the relatively early age at maturity compared to the estimated age-at-50%-harvest, discussed in Sections \@ref(scam-ref-points) and \@ref(fishery-ref-points).
+
+Given the choice to base reference points on $B_0$, some participants at the regional peer review meeting expressed interest in comparing biomass to a dynamic $B_0$ that reconstructs what biomass would be expected through time without fishing mortality. A dynamic $B_0$ was calculated by recreating the population dynamics model in R with parameter estimates from the fitted base model. The fishing mortality was set to zero but estimated recruitment deviations were included. Figure \@ref(fig:fig-dynamic-b-zero) shows the estimated dynamic $B_0$ from this exercise.
+This figure illustrates that the model explains a portion of the recent decline by a sequence of poor recruitment.
+")
 ```
 
 ```{r scam-results-biomass-fr, eval = fr(), results = 'asis', needs_trans = FALSE}