The SRG requests sensitivities on fishery selectivity parameterization (in the base model) by increasing the maximum age beyond which selectivity is held constant to ages 8, 10, and 12. Present the resulting fishery selectivity (2024 with uncertainty and MCMC traces and individual years with uncertainty), spawning biomass trajectories, fits to the acoustic survey index, and recruitment deviation estimates.
model_age_8 <- request_models[[1]][[1]] model_age_10 <- request_models[[1]][[2]] model_age_12 <- request_models[[1]][[3]] plot_selex_posteriors(base_model, type = "fishery", n_posts = 1000, age_range = c(1, 13), glow = TRUE)
plot_selex_posteriors(model_age_8, type = "fishery", n_posts = 1000, age_range = c(1, 13), glow = TRUE)
plot_selex_posteriors(model_age_10, type = "fishery", n_posts = 1000, age_range = c(1, 13), glow = TRUE)
plot_selex_posteriors(model_age_12, type = "fishery", n_posts = 1000, age_range = c(1, 13), glow = TRUE)
plot_selex_uncertainty(base_model, n_col = 2, ages = 1:13, pad_top = TRUE, pad_bottom = TRUE, label_loc = c(1, 0.65), label_font_size = 3)
plot_selex_uncertainty(model_age_8, n_col = 2, ages = 1:13, pad_top = TRUE, pad_bottom = TRUE, label_loc = c(1, 0.65), label_font_size = 3)
plot_selex_uncertainty(model_age_10, n_col = 2, ages = 1:13, pad_top = TRUE, pad_bottom = TRUE, label_loc = c(1, 0.65), label_font_size = 3)
plot_selex_uncertainty(model_age_12, n_col = 2, ages = 1:13, pad_top = TRUE, pad_bottom = TRUE, label_loc = c(1, 0.65), label_font_size = 3)
:::::: {.columns} ::: {.column width="50%"}
# Left plot_biomass(list(base_model, model_age_8, model_age_10, model_age_12), c("base model", request_models_names[[1]]), ylim = c(0, 5), point_shape = ts_single_model_pointshape, leg_pos = c(0.75, 0.80))
:::
::: {.column width="50%"}
# Right plot_rel_biomass(list(base_model, model_age_8, model_age_10, model_age_12), c("base model", request_models_names[[1]]), ylim = c(0, 2.5), alpha = 0.2, leg_pos = c(0.75, 0.80)) |> suppressWarnings()
::: ::::::
plot_survey_fit_mcmc(base_model, type = "acoustic", n_posts = 1000, glow = TRUE, glow_color = "black", glow_offset = 0.5, leg_ymax = 4.8, leg_sep = 0.65, x_lim = c(survey_start_yr, survey_end_yr), y_lim = c(0, 6), x_labs_mod = 5, y_labs_by = 0.5, tick_prop = 1, vjust_x_labels = -2, remove_yr_labels = NULL)
plot_survey_fit_mcmc(model_age_8, type = "acoustic", n_posts = 1000, glow = TRUE, glow_color = "black", glow_offset = 0.5, leg_ymax = 4.8, leg_sep = 0.65, x_lim = c(survey_start_yr, survey_end_yr), y_lim = c(0, 6), x_labs_mod = 5, y_labs_by = 0.5, tick_prop = 1, vjust_x_labels = -2, remove_yr_labels = NULL)
plot_survey_fit_mcmc(model_age_10, type = "acoustic", n_posts = 1000, glow = TRUE, glow_color = "black", glow_offset = 0.5, leg_ymax = 4.8, leg_sep = 0.65, x_lim = c(survey_start_yr, survey_end_yr), y_lim = c(0, 6), x_labs_mod = 5, y_labs_by = 0.5, tick_prop = 1, vjust_x_labels = -2, remove_yr_labels = NULL)
plot_survey_fit_mcmc(model_age_12, type = "acoustic", n_posts = 1000, glow = TRUE, glow_color = "black", glow_offset = 0.5, leg_ymax = 4.8, leg_sep = 0.65, x_lim = c(survey_start_yr, survey_end_yr), y_lim = c(0, 6), x_labs_mod = 5, y_labs_by = 0.5, tick_prop = 1, vjust_x_labels = -2, remove_yr_labels = NULL)
plot_recdevs(list(base_model, model_age_8, model_age_10, model_age_12), c("base model", request_models_names[[1]]), line_color = ts_single_line_color, leg_ncol = 2, leg_pos = c(0.30, 0.90))
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.