inst/markdown/archive/bycatch.md
In jae0/bio.snowcrab: Snow crab assessment suite using aegis* and associated projects and data streams.
title: "By catch estimation"
author: "Jae S. Choi"
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Approach: estimate bycatch from at seas observed data and project onto marfis data
First set up environment. Can be made more efficient by doing intermediate saves (to do).
#| eval: true
#| output: false
require(aegis)
year.assessment = 2023
p = bio.snowcrab::load.environment( year.assessment=year.assessment )
require(gt) # table formatting
require(ggplot2)
bycatch_dir = file.path( p$annual.results, "bycatch")
years = as.character(1996: year.assessment)
if (0) {
loadfunctions( "aegis")
loadfunctions( "bio.snowcrab") # in case of local edits
require(data.table)
obs = observer.db( DS="bycatch_clean_data", p=p, yrs=p$yrs ) # At sea observed data is created on the fly, to access it directly
}
Naive estimation: directly from observations
We estimate bycatch using at-sea-observed effort and catch and re-scaling these naively to total snow crab fishery effort associated with the observations by year:
All Maritimes
#| eval: true
#| output: false
#| warning: false
#| error: false
region="cfaall"
o = observer.db( DS="bycatch_summary", p=p, yrs=p$yrs, region=region )
o$bycatch_table[ o$bycatch_table==0 ] = NA
o$bycatch_table[ is.na(o$bycatch_table) ] = "."
o$bycatch_table_catch[ o$bycatch_table_catch==0 ] = NA
o$bycatch_table_catch[ is.na(o$bycatch_table_catch) ] = "."
Discard rates of snow crab, by weight
#| label: figure-discard_maritimes
#| fig-cap: "At sea observed rate of snow crab discards relative to total catch (discard + kept), all Maritimes."
#| fig-dpi: 144
#| fig-height: 4
pl = ggplot( o$eff_summ, aes(x=fishyr, y=discard_rate, ymin=discard_rate-discard_rate_sd, ymax=discard_rate+discard_rate_sd) ) +
geom_pointrange() + # Vertical line with point in the middle
geom_errorbar(width = 0.1, col="brown") + # Standard error bars
geom_point(size = 1.5, col="darkred") +
labs(x="Year", y="Discard rate of snow crab (At sea observed, by weight)" )
(pl)
Bycatch catch rates
#| label: bycatch_rates_all
#| tbl-cap: "At sea observed bycatch rates in Maritimes"
#| fig-dpi: 144
#| fig-height: 15
plot( o$spec ~ o$bct, xlab = "At sea observed catch rate in snow crab fishery (kg/trap)", ylab="Species", type="p", cex=1.1, pch=19, col="darkorange", xlim=c(0, max(o$bct, na.rm=TRUE)*1.4), yaxt="n" )
text( o$bct, o$spec, labels=o$species, pos=4, srt=0 , cex=0.8, col="darkslateblue")
text( max(o$bct, na.rm=TRUE)*0.88, 2.5, labels=paste( "Snow crab CPUE (At sea obs., mean): ", o$bct_sc, " kg/trap"), col="darkred", cex=0.9 )
Bycatch table from effort
#| label: bycatch_all
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon effort rescaling of Maritimes Region snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt(o$bycatch_table) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
Bycatch table from catch
#| label: bycatch_all_catch
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon catch rescaling of Maritimes Region snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt(o$bycatch_table_catch) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
Entanglements of large megafauna
#| warning: false
#| error: false
#| tbl-cap: "Entanglements Maritimes"
#| label: bycatch_entanglements_all
oss = o$oss # subset for region of interest
print("whale entaglements:")
whales = oss[ grep("whale", common, ignore.case=TRUE), ]
print(whales[, .N, by=.(yr)] )
print("leatherback entaglements:")
leatherback = oss[ grep("LEATHERBACK", common, ignore.case=TRUE), ]
print(leatherback[, .N, by=.(yr)])
print("basking sharks entaglements:")
basking_shark = oss[ grep("BASKING SHARK", common, ignore.case=TRUE), ]
print(basking_shark[, .N, by=.(yr)])
Map of locations of entanglements:
#| warning: false
#| error: false
#| fig-cap: "Entanglement locations in Maritimes. Whales (red), Leatherback turtles (green), Basking shark (blue)."
#| label: bycatch_entanglements_map_all
#| fig-dpi: 144
#| fig-height: 5
plot(lat~-lon, oss, pch=".", col="lightgray", xlim=c(-65.2, -57), ylim=c(42.9,47) )
points(lat~-lon, whales, pch=19, cex=1.5, col="darkred" )
points(lat~-lon, leatherback, pch=18, cex=1.5, col="darkgreen" )
points(lat~-lon, basking_shark, pch=17, cex=1.5, col="slateblue" )
NENS
#| eval: true
#| output: false
#| warning: false
#| error: false
region="cfanorth"
o = observer.db( DS="bycatch_summary", p=p, yrs=p$yrs, region=region )
o$bycatch_table[ o$bycatch_table==0 ] = NA
o$bycatch_table[ is.na(o$bycatch_table) ] = "."
o$bycatch_table_catch[ o$bycatch_table_catch==0 ] = NA
o$bycatch_table_catch[ is.na(o$bycatch_table_catch) ] = "."
Discard rates of snow crab, by weight
#| label: figure-discard_nens
#| fig-cap: "At sea observed rate of snow crab discards relative to total catch (discard + kept), NENS."
#| fig-dpi: 144
#| fig-height: 4
pl = ggplot( o$eff_summ, aes(x=fishyr, y=discard_rate, ymin=discard_rate-discard_rate_sd, ymax=discard_rate+discard_rate_sd) ) +
geom_pointrange() + # Vertical line with point in the middle
geom_errorbar(width = 0.1, col="brown") + # Standard error bars
geom_point(size = 1.5, col="darkred") +
labs(x="Year", y="Discard rate of snow crab (At sea observed, by weight)" )
(pl)
Bycatch catch rates
#| label: bycatch_rates_nens
#| tbl-cap: "At sea observed bycatch rates in NENS"
#| fig-dpi: 144
#| fig-height: 6
plot( o$spec ~ o$bct, xlab = "At sea observed catch rate in snow crab fishery (kg/trap)", ylab="Species", type="p", cex=1.1, pch=19, col="darkorange", xlim=c(0, max(o$bct, na.rm=TRUE)*1.4), yaxt="n" )
text( o$bct, o$spec, labels=o$species, pos=4, srt=0 , cex=0.8, col="darkslateblue")
text( max(o$bct, na.rm=TRUE)*0.88, 2.5, labels=paste( "Snow crab CPUE (At sea obs., mean): ", o$bct_sc, " kg/trap"), col="darkred", cex=0.9 )
Bycatch table from effort
#| label: bycatch_NENS
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon effort rescaling of NENS snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt(o$bycatch_table) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
Bycatch table from catch
#| label: bycatch_NENS_catch
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon catch rescaling of NENS snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt(o$bycatch_table_catch) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
Entanglements of large megafauna
#| warning: false
#| error: false
#| label: bycatch_entanglements_ens
#| tbl-cap: "Entanglements NENS"
oss = o$oss # subset for region of interst
whales = oss[ grep("whale", common, ignore.case=TRUE), ]
print(whales[, .(yr, lon, lat, uid, est_discard_wt)] )
leatherback = oss[ grep("LEATHERBACK", common, ignore.case=TRUE), ]
print(leatherback[, .(yr, lon, lat, uid, est_discard_wt)])
basking_shark = oss[ grep("BASKING SHARK", common, ignore.case=TRUE), ]
print(basking_shark[, .(yr, lon, lat, uid, est_discard_wt)])
SENS
#| eval: true
#| output: false
#| warning: false
#| error: false
region="cfasouth"
o = observer.db( DS="bycatch_summary", p=p, yrs=p$yrs, region=region )
o$bycatch_table[ o$bycatch_table==0 ] = NA
o$bycatch_table[ is.na(o$bycatch_table) ] = "."
o$bycatch_table_catch[ o$bycatch_table_catch==0 ] = NA
o$bycatch_table_catch[ is.na(o$bycatch_table_catch) ] = "."
Discard rates of snow crab, by weight
#| label: figure-discard_sens
#| fig-cap: "At sea observed rate of snow crab discards relative to total catch (discard + kept), SENS."
#| fig-dpi: 144
#| fig-height: 4
pl = ggplot( o$eff_summ, aes(x=fishyr, y=discard_rate, ymin=discard_rate-discard_rate_sd, ymax=discard_rate+discard_rate_sd) ) +
geom_pointrange() + # Vertical line with point in the middle
geom_errorbar(width = 0.1, col="brown") + # Standard error bars
geom_point(size = 1.5, col="darkred") +
labs(x="Year", y="Discard rate of snow crab (At sea observed, by weight)" )
(pl)
Bycatch catch rates
#| label: bycatch_rates_sens
#| tbl-cap: "At sea observed bycatch rates in SENS"
#| fig-dpi: 144
#| fig-height: 14
plot( o$spec ~ o$bct, xlab = "At sea observed catch rate in snow crab fishery (kg/trap)", ylab="Species", type="p", cex=1.1, pch=19, col="darkorange", xlim=c(0, max(o$bct, na.rm=TRUE)*1.4), yaxt="n" )
text( o$bct, o$spec, labels=o$species, pos=4, srt=0 , cex=0.8, col="darkslateblue")
text( max(o$bct, na.rm=TRUE)*0.88, 2.5, labels=paste( "Snow crab CPUE (At sea obs., mean): ", o$bct_sc, " kg/trap"), col="darkred", cex=0.8 )
Bycatch table from effort
#| label: bycatch_SENS
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon effort rescaling of SENS snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt( o$bycatch_table ) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
Bycatch table from catch
#| label: bycatch_SENS_catch
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon catch rescaling of SENS snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt( o$bycatch_table_catch ) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
#| warning: false
#| error: false
#| label: entanglements_SENS
#| tbl-cap: "Entanglements SENS"
# get large megafauna:
oss = o$oss # subset for region of interst
whales = oss[ grep("whale", common, ignore.case=TRUE), ]
print(whales[, .(yr, lon, lat, uid, est_discard_wt)] )
leatherback = oss[ grep("LEATHERBACK", common, ignore.case=TRUE), ]
print(leatherback[, .(yr, lon, lat, uid, est_discard_wt)])
basking_shark = oss[ grep("BASKING SHARK", common, ignore.case=TRUE), ]
print(basking_shark[, .(yr, lon, lat, uid, est_discard_wt)])
4X
#| eval: true
#| output: false
#| warning: false
#| error: false
region="cfa4x"
o = observer.db( DS="bycatch_summary", p=p, yrs=p$yrs, region=region )
o$bycatch_table[ o$bycatch_table==0 ] = NA
o$bycatch_table[ is.na(o$bycatch_table) ] = "."
o$bycatch_table_catch[ o$bycatch_table_catch==0 ] = NA
o$bycatch_table_catch[ is.na(o$bycatch_table_catch) ] = "."
Discard rates of snow crab, by weight
#| label: figure-discard_4x
#| fig-cap: "At sea observed rate of snow crab discards relative to total catch (discard + kept), 4X."
#| fig-dpi: 144
#| fig-height: 4
pl = ggplot( o$eff_summ, aes(x=fishyr, y=discard_rate, ymin=discard_rate-discard_rate_sd, ymax=discard_rate+discard_rate_sd) ) +
geom_pointrange() + # Vertical line with point in the middle
geom_errorbar(width = 0.1, col="brown") + # Standard error bars
geom_point(size = 1.5, col="darkred") +
labs(x="Year", y="Discard rate of snow crab (At sea observed, by weight)" )
(pl)
Bycatch catch rates
#| label: bycatch_rates_4x
#| tbl-cap: "At sea observed bycatch rates in 4X"
#| fig-dpi: 144
#| fig-height: 6
plot( o$spec ~ o$bct, xlab = "At sea observed catch rate in snow crab fishery (kg/trap)", ylab="Species", type="p", cex=1.1, pch=19, col="darkorange", xlim=c(0, max(o$bct, na.rm=TRUE)*1.4), yaxt="n" )
text( o$bct, o$spec, labels=o$species, pos=4, srt=0 , cex=0.8, col="darkslateblue")
text( max(o$bct, na.rm=TRUE)*0.88, 2.5, labels=paste( "Snow crab CPUE (At sea obs., mean): ", o$bct_sc, " kg/trap"), col="darkred", cex=0.9 )
Bycatch table from effort
#| label: bycatch_4X
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon effort rescaling of 4X snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt(o$bycatch_table) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
Bycatch table from catch
#| label: bycatch_4X_catch
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon catch rescaling of 4X snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt(o$bycatch_table_catch) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
Entanglements of large megafauna
#| warning: false
#| error: false
#| label: bycatch_entanglements_e4x
#| tbl-cap: "Entanglements 4X"
oss = o$oss # subset for region of interst
whales = oss[ grep("whale", common, ignore.case=TRUE), ]
print(whales[, .(yr, lon, lat, uid, est_discard_wt)] )
leatherback = oss[ grep("LEATHERBACK", common, ignore.case=TRUE), ]
print(leatherback[, .(yr, lon, lat, uid, est_discard_wt)])
basking_shark = oss[ grep("BASKING SHARK", common, ignore.case=TRUE), ]
print(basking_shark[, .(yr, lon, lat, uid, est_discard_wt)])
To do next:
Estimate via carstm: requires a Poisson model of each species of catch (number) with offset of landings and covariates ... soon, ever?
END
jae0/bio.snowcrab documentation built on Nov. 6, 2024, 10:10 p.m.
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title: "By catch estimation" author: "Jae S. Choi" toc: true number-sections: true highlight-style: pygments editor: render-on-save: true format: html: code-fold: true html-math-method: katex embed-resources: true pdf: pdf-engine: lualatex docx: default
Approach: estimate bycatch from at seas observed data and project onto marfis data
First set up environment. Can be made more efficient by doing intermediate saves (to do).
#| eval: true
#| output: false
require(aegis)
year.assessment = 2023
p = bio.snowcrab::load.environment( year.assessment=year.assessment )
require(gt) # table formatting
require(ggplot2)
bycatch_dir = file.path( p$annual.results, "bycatch")
years = as.character(1996: year.assessment)
if (0) {
loadfunctions( "aegis")
loadfunctions( "bio.snowcrab") # in case of local edits
require(data.table)
obs = observer.db( DS="bycatch_clean_data", p=p, yrs=p$yrs ) # At sea observed data is created on the fly, to access it directly
}
Naive estimation: directly from observations
We estimate bycatch using at-sea-observed effort and catch and re-scaling these naively to total snow crab fishery effort associated with the observations by year:
All Maritimes
#| eval: true
#| output: false
#| warning: false
#| error: false
region="cfaall"
o = observer.db( DS="bycatch_summary", p=p, yrs=p$yrs, region=region )
o$bycatch_table[ o$bycatch_table==0 ] = NA
o$bycatch_table[ is.na(o$bycatch_table) ] = "."
o$bycatch_table_catch[ o$bycatch_table_catch==0 ] = NA
o$bycatch_table_catch[ is.na(o$bycatch_table_catch) ] = "."
Discard rates of snow crab, by weight
#| label: figure-discard_maritimes
#| fig-cap: "At sea observed rate of snow crab discards relative to total catch (discard + kept), all Maritimes."
#| fig-dpi: 144
#| fig-height: 4
pl = ggplot( o$eff_summ, aes(x=fishyr, y=discard_rate, ymin=discard_rate-discard_rate_sd, ymax=discard_rate+discard_rate_sd) ) +
geom_pointrange() + # Vertical line with point in the middle
geom_errorbar(width = 0.1, col="brown") + # Standard error bars
geom_point(size = 1.5, col="darkred") +
labs(x="Year", y="Discard rate of snow crab (At sea observed, by weight)" )
(pl)
Bycatch catch rates
#| label: bycatch_rates_all
#| tbl-cap: "At sea observed bycatch rates in Maritimes"
#| fig-dpi: 144
#| fig-height: 15
plot( o$spec ~ o$bct, xlab = "At sea observed catch rate in snow crab fishery (kg/trap)", ylab="Species", type="p", cex=1.1, pch=19, col="darkorange", xlim=c(0, max(o$bct, na.rm=TRUE)*1.4), yaxt="n" )
text( o$bct, o$spec, labels=o$species, pos=4, srt=0 , cex=0.8, col="darkslateblue")
text( max(o$bct, na.rm=TRUE)*0.88, 2.5, labels=paste( "Snow crab CPUE (At sea obs., mean): ", o$bct_sc, " kg/trap"), col="darkred", cex=0.9 )
Bycatch table from effort
#| label: bycatch_all
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon effort rescaling of Maritimes Region snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt(o$bycatch_table) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
Bycatch table from catch
#| label: bycatch_all_catch
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon catch rescaling of Maritimes Region snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt(o$bycatch_table_catch) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
Entanglements of large megafauna
#| warning: false
#| error: false
#| tbl-cap: "Entanglements Maritimes"
#| label: bycatch_entanglements_all
oss = o$oss # subset for region of interest
print("whale entaglements:")
whales = oss[ grep("whale", common, ignore.case=TRUE), ]
print(whales[, .N, by=.(yr)] )
print("leatherback entaglements:")
leatherback = oss[ grep("LEATHERBACK", common, ignore.case=TRUE), ]
print(leatherback[, .N, by=.(yr)])
print("basking sharks entaglements:")
basking_shark = oss[ grep("BASKING SHARK", common, ignore.case=TRUE), ]
print(basking_shark[, .N, by=.(yr)])
Map of locations of entanglements:
#| warning: false
#| error: false
#| fig-cap: "Entanglement locations in Maritimes. Whales (red), Leatherback turtles (green), Basking shark (blue)."
#| label: bycatch_entanglements_map_all
#| fig-dpi: 144
#| fig-height: 5
plot(lat~-lon, oss, pch=".", col="lightgray", xlim=c(-65.2, -57), ylim=c(42.9,47) )
points(lat~-lon, whales, pch=19, cex=1.5, col="darkred" )
points(lat~-lon, leatherback, pch=18, cex=1.5, col="darkgreen" )
points(lat~-lon, basking_shark, pch=17, cex=1.5, col="slateblue" )
NENS
#| eval: true
#| output: false
#| warning: false
#| error: false
region="cfanorth"
o = observer.db( DS="bycatch_summary", p=p, yrs=p$yrs, region=region )
o$bycatch_table[ o$bycatch_table==0 ] = NA
o$bycatch_table[ is.na(o$bycatch_table) ] = "."
o$bycatch_table_catch[ o$bycatch_table_catch==0 ] = NA
o$bycatch_table_catch[ is.na(o$bycatch_table_catch) ] = "."
Discard rates of snow crab, by weight
#| label: figure-discard_nens
#| fig-cap: "At sea observed rate of snow crab discards relative to total catch (discard + kept), NENS."
#| fig-dpi: 144
#| fig-height: 4
pl = ggplot( o$eff_summ, aes(x=fishyr, y=discard_rate, ymin=discard_rate-discard_rate_sd, ymax=discard_rate+discard_rate_sd) ) +
geom_pointrange() + # Vertical line with point in the middle
geom_errorbar(width = 0.1, col="brown") + # Standard error bars
geom_point(size = 1.5, col="darkred") +
labs(x="Year", y="Discard rate of snow crab (At sea observed, by weight)" )
(pl)
Bycatch catch rates
#| label: bycatch_rates_nens
#| tbl-cap: "At sea observed bycatch rates in NENS"
#| fig-dpi: 144
#| fig-height: 6
plot( o$spec ~ o$bct, xlab = "At sea observed catch rate in snow crab fishery (kg/trap)", ylab="Species", type="p", cex=1.1, pch=19, col="darkorange", xlim=c(0, max(o$bct, na.rm=TRUE)*1.4), yaxt="n" )
text( o$bct, o$spec, labels=o$species, pos=4, srt=0 , cex=0.8, col="darkslateblue")
text( max(o$bct, na.rm=TRUE)*0.88, 2.5, labels=paste( "Snow crab CPUE (At sea obs., mean): ", o$bct_sc, " kg/trap"), col="darkred", cex=0.9 )
Bycatch table from effort
#| label: bycatch_NENS
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon effort rescaling of NENS snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt(o$bycatch_table) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
Bycatch table from catch
#| label: bycatch_NENS_catch
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon catch rescaling of NENS snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt(o$bycatch_table_catch) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
Entanglements of large megafauna
#| warning: false
#| error: false
#| label: bycatch_entanglements_ens
#| tbl-cap: "Entanglements NENS"
oss = o$oss # subset for region of interst
whales = oss[ grep("whale", common, ignore.case=TRUE), ]
print(whales[, .(yr, lon, lat, uid, est_discard_wt)] )
leatherback = oss[ grep("LEATHERBACK", common, ignore.case=TRUE), ]
print(leatherback[, .(yr, lon, lat, uid, est_discard_wt)])
basking_shark = oss[ grep("BASKING SHARK", common, ignore.case=TRUE), ]
print(basking_shark[, .(yr, lon, lat, uid, est_discard_wt)])
SENS
#| eval: true
#| output: false
#| warning: false
#| error: false
region="cfasouth"
o = observer.db( DS="bycatch_summary", p=p, yrs=p$yrs, region=region )
o$bycatch_table[ o$bycatch_table==0 ] = NA
o$bycatch_table[ is.na(o$bycatch_table) ] = "."
o$bycatch_table_catch[ o$bycatch_table_catch==0 ] = NA
o$bycatch_table_catch[ is.na(o$bycatch_table_catch) ] = "."
Discard rates of snow crab, by weight
#| label: figure-discard_sens
#| fig-cap: "At sea observed rate of snow crab discards relative to total catch (discard + kept), SENS."
#| fig-dpi: 144
#| fig-height: 4
pl = ggplot( o$eff_summ, aes(x=fishyr, y=discard_rate, ymin=discard_rate-discard_rate_sd, ymax=discard_rate+discard_rate_sd) ) +
geom_pointrange() + # Vertical line with point in the middle
geom_errorbar(width = 0.1, col="brown") + # Standard error bars
geom_point(size = 1.5, col="darkred") +
labs(x="Year", y="Discard rate of snow crab (At sea observed, by weight)" )
(pl)
Bycatch catch rates
#| label: bycatch_rates_sens
#| tbl-cap: "At sea observed bycatch rates in SENS"
#| fig-dpi: 144
#| fig-height: 14
plot( o$spec ~ o$bct, xlab = "At sea observed catch rate in snow crab fishery (kg/trap)", ylab="Species", type="p", cex=1.1, pch=19, col="darkorange", xlim=c(0, max(o$bct, na.rm=TRUE)*1.4), yaxt="n" )
text( o$bct, o$spec, labels=o$species, pos=4, srt=0 , cex=0.8, col="darkslateblue")
text( max(o$bct, na.rm=TRUE)*0.88, 2.5, labels=paste( "Snow crab CPUE (At sea obs., mean): ", o$bct_sc, " kg/trap"), col="darkred", cex=0.8 )
Bycatch table from effort
#| label: bycatch_SENS
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon effort rescaling of SENS snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt( o$bycatch_table ) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
Bycatch table from catch
#| label: bycatch_SENS_catch
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon catch rescaling of SENS snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt( o$bycatch_table_catch ) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
#| warning: false
#| error: false
#| label: entanglements_SENS
#| tbl-cap: "Entanglements SENS"
# get large megafauna:
oss = o$oss # subset for region of interst
whales = oss[ grep("whale", common, ignore.case=TRUE), ]
print(whales[, .(yr, lon, lat, uid, est_discard_wt)] )
leatherback = oss[ grep("LEATHERBACK", common, ignore.case=TRUE), ]
print(leatherback[, .(yr, lon, lat, uid, est_discard_wt)])
basking_shark = oss[ grep("BASKING SHARK", common, ignore.case=TRUE), ]
print(basking_shark[, .(yr, lon, lat, uid, est_discard_wt)])
4X
#| eval: true
#| output: false
#| warning: false
#| error: false
region="cfa4x"
o = observer.db( DS="bycatch_summary", p=p, yrs=p$yrs, region=region )
o$bycatch_table[ o$bycatch_table==0 ] = NA
o$bycatch_table[ is.na(o$bycatch_table) ] = "."
o$bycatch_table_catch[ o$bycatch_table_catch==0 ] = NA
o$bycatch_table_catch[ is.na(o$bycatch_table_catch) ] = "."
Discard rates of snow crab, by weight
#| label: figure-discard_4x
#| fig-cap: "At sea observed rate of snow crab discards relative to total catch (discard + kept), 4X."
#| fig-dpi: 144
#| fig-height: 4
pl = ggplot( o$eff_summ, aes(x=fishyr, y=discard_rate, ymin=discard_rate-discard_rate_sd, ymax=discard_rate+discard_rate_sd) ) +
geom_pointrange() + # Vertical line with point in the middle
geom_errorbar(width = 0.1, col="brown") + # Standard error bars
geom_point(size = 1.5, col="darkred") +
labs(x="Year", y="Discard rate of snow crab (At sea observed, by weight)" )
(pl)
Bycatch catch rates
#| label: bycatch_rates_4x
#| tbl-cap: "At sea observed bycatch rates in 4X"
#| fig-dpi: 144
#| fig-height: 6
plot( o$spec ~ o$bct, xlab = "At sea observed catch rate in snow crab fishery (kg/trap)", ylab="Species", type="p", cex=1.1, pch=19, col="darkorange", xlim=c(0, max(o$bct, na.rm=TRUE)*1.4), yaxt="n" )
text( o$bct, o$spec, labels=o$species, pos=4, srt=0 , cex=0.8, col="darkslateblue")
text( max(o$bct, na.rm=TRUE)*0.88, 2.5, labels=paste( "Snow crab CPUE (At sea obs., mean): ", o$bct_sc, " kg/trap"), col="darkred", cex=0.9 )
Bycatch table from effort
#| label: bycatch_4X
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon effort rescaling of 4X snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt(o$bycatch_table) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
Bycatch table from catch
#| label: bycatch_4X_catch
#| tbl-cap: "At sea observed bycatch estimates (kg) based upon catch rescaling of 4X snow crab fishery. Dots indicated low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The average is only for the years shown."
gt::gt(o$bycatch_table_catch) |>
gt::tab_options(table.font.size = 12, data_row.padding = gt::px(1),
summary_row.padding = gt::px(1), grand_summary_row.padding = gt::px(1),
footnotes.padding = gt::px(1), source_notes.padding = gt::px(1),
row_group.padding = gt::px(1))
Entanglements of large megafauna
#| warning: false
#| error: false
#| label: bycatch_entanglements_e4x
#| tbl-cap: "Entanglements 4X"
oss = o$oss # subset for region of interst
whales = oss[ grep("whale", common, ignore.case=TRUE), ]
print(whales[, .(yr, lon, lat, uid, est_discard_wt)] )
leatherback = oss[ grep("LEATHERBACK", common, ignore.case=TRUE), ]
print(leatherback[, .(yr, lon, lat, uid, est_discard_wt)])
basking_shark = oss[ grep("BASKING SHARK", common, ignore.case=TRUE), ]
print(basking_shark[, .(yr, lon, lat, uid, est_discard_wt)])
To do next:
Estimate via carstm: requires a Poisson model of each species of catch (number) with offset of landings and covariates ... soon, ever?
END
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