inst/markdown/02_fishery_summary.md
In jae0/snowcrab: Snow crab assessment suite using aegis* and associated projects and data streams.
title: "Snow crab fishery summary"
keywords:
- snow crab trawl survey results
- basic tables and figures
abstract: |
Details of 2024 snow crab fishery performance.
fontsize: 12pt
metadata-files:
- _metadata.yml
params:
year_assessment: 2024
year_start: 1999
data_loc: "~/bio.data/bio.snowcrab"
sens: 1
debugging: FALSE
model_variation: logistic_discrete_historical
#| eval: true
#| output: false
#| echo: false
#| label: setup
require(knitr)
knitr::opts_chunk$set(
root.dir = data_root,
echo = FALSE,
out.width="6.2in",
fig.retina = 2,
dpi=192
)
# things to load into memory (in next step) via _load_results.qmd
toget = c( "fishery_results" )
{{< include _load_results.qmd >}}
Fishing locations
Fishing locations recorded in logbooks
#| label: fig-map-logbook-locations
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 4
#| echo: false
#| layout-ncol: 2
#| fig-cap: "Snow Crab logbook locations."
#| fig-subcap:
#| - ""
#| - ""
#| - ""
#| - ""
loc = file.path( data_loc, "output", "maps", "logbook.locations" )
yrsplot = year_assessment + c(0:-3)
fns = paste( "logbook.locations", yrsplot, "png", sep="." )
fn = file.path( loc, fns )
include_graphics( fn )
$~$
Fishing locations recorded in logbooks: a closer look
#| label: fig-map-logbook-locations-two-years
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 5
#| echo: false
#| layout-ncol: 1
#| fig-cap: "Snow Crab logbook locations in the past two years."
#| fig-subcap:
#| - "N-ENS"
#| - "S-ENS"
#| - "4X"
fns = file.path( media_supplementary, c(
"nens_past_two_years_fishing_positions.png",
"sens_past_two_years_fishing_positions.png",
"cfa4x_past_two_years_fishing_positions.png"
))
include_graphics( fns )
Fishery performance
Fishery performance: Summary
#| label: tbl-fishery-performance
#| echo: false
#| results: asis
#| eval: true
#| output: true
#| tbl-cap: "Fishery performance statistics. Note: 4X years represent the starting year."
#| tbl-subcap:
#| - ""
#| - ""
#| - ""
#| - ""
for (r in 1:nregions) {
reg = regions[r]
REG = reg_labels[r]
cat(REG, "\n")
oo = dt[ which(dt$Region==reg), c("Year", "Licenses", "TAC", "Landings", "Effort", "CPUE")]
names(oo) = c( "Year", "Licenses", "TAC (t)", "Landings (t)", "Effort (1000 th)", "CPUE (kg/th)" )
out = gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
print(out)
cat("\n\n")
}
$~$
Landings
Landings: annual
#| label: fig-landings-timeseries
#| eval: true
#| output: true
#| fig-cap: "Landings (t) of Snow Crab on the SSE. For 4X, the year refers to the starting year of the season. Inset is a closeup view of the timeseries for N-ENS and 4X."
#| fig-dpi: 144
#| fig-height: 8
if (params$sens==1) {
ts_dir = file.path( data_loc, "assessments", year_assessment, "timeseries", "fishery" )
} else if (params$sens==2) {
ts_dir = file.path( data_loc, "assessments", year_assessment, "timeseries", "fishery", "split" )
}
include_graphics( file.path( ts_dir, "landings.ts.png" ) )
$~$
Landings: close-up
#| label: fig-landings-decomposed
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 5
#| echo: false
#| layout-ncol: 1
#| fig-cap: "Landings decomposed"
#| fig-subcap:
#| - "Fraction of landings in Spring"
#| - "Fraction of landings in Summer"
#| - "Fraction of landings in Winter"
#| - "Cummulative landings"
fns = c(
"percent_spring_landings.png",
"percent_summer_landings.png",
"percent_winter_landings.png",
"weekly_landing.png"
)
include_graphics( file.path( media_supplementary, fns ) )
$~$
Landings: spatial
#| label: fig-landings-map
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 4
#| echo: false
#| layout-ncol: 2
#| fig-cap: "Snow Crab landings from fisheries logbook data for previous and current years (tons per 10 km x 10 km grid)."
#| fig-subcap:
#| - ""
#| - ""
#| - ""
#| - ""
loc0 = file.path( data_loc, "output", "maps", "logbook", "snowcrab", "annual", "landings" )
yrsplot = year_assessment + c(0:-3)
fn = file.path( loc0, paste( "landings", yrsplot, "png", sep=".") )
include_graphics( fn )
$~$
Effort
Effort: annual
#| label: fig-effort-timeseries
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 8
#| fig-cap: "Temporal variations in fishing effort."
if (params$sens==1) {
ts_dir = file.path( data_loc, "assessments", year_assessment, "timeseries", "fishery" )
} else if (params$sens==2) {
ts_dir = file.path( data_loc, "assessments", year_assessment, "timeseries", "fishery", "split" )
}
include_graphics( file.path( ts_dir, "effort.ts.png" ) )
$~$
Effort: spatial
#| label: fig-effort-map
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 8
#| echo: false
#| layout-ncol: 2
#| fig-cap: "Snow Crab fishing effort from fisheries logbook data for previous and current years (no X 10$^3$ per 10 km X 10 km grid)."
#| fig-subcap:
#| - ""
#| - ""
#| - ""
#| - ""
loc0 = file.path( data_loc, "output", "maps", "logbook", "snowcrab", "annual", "effort" )
yrsplot = year_assessment + c(0:-3)
fn = file.path( loc0, paste( "effort", yrsplot, "png", sep=".") )
include_graphics( fn )
$~$
Catch rates
Catch rates: annual
#| label: fig-cpue-timeseries
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 4
#| fig-cap: "Temporal variations in crude catch rates of Snow Crab (kg/trap haul)."
if (params$sens==1) {
ts_dir = file.path( data_loc, "assessments", year_assessment, "timeseries", "fishery" )
} else if (params$sens==2) {
ts_dir = file.path( data_loc, "assessments", year_assessment, "timeseries", "fishery", "split" )
}
include_graphics( file.path( ts_dir, "cpue.ts.png" ) )
$~$
Catch rates: close up
#| label: fig-cpue-weekly
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 5
#| echo: false
#| layout-ncol: 1
#| fig-cap: "CPUE (kg/trap haul) on a weekly basis"
fns = c(
"weekly_cpue_smoothed2.png"
)
include_graphics( file.path( media_supplementary, fns ) )
$~$
Catch rates: spatial
#| label: fig-cpue-map
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 4
#| echo: false
#| layout-ncol: 2
#| fig-cap: "Snow Crab crude catch rates on the Scotian Shelf for previous and current years. Units are kg/trap haul per 10 km x 10 km grid."
#| fig-subcap:
#| - ""
#| - ""
#| - ""
#| - ""
loc0= file.path( data_loc, "output", "maps", "logbook", "snowcrab", "annual", "cpue" )
yrsplot = year_assessment + c(0:-3)
fn = file.path( loc0, paste( "cpue", yrsplot, "png", sep=".") )
include_graphics( fn )
$~$
At-sea Observed Data
At-sea Observed Data: Summary
#| label: tbl-observed-summary
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 5
#| echo: false
#| layout-ncol: 1
#| tbl-cap: "Table of observed data coverage"
fns = c(
"observersummary2.png"
)
include_graphics( file.path( media_supplementary, fns ) )
At-sea Observed fishing locations
#| label: fig-map-observer-locations
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 4
#| echo: false
#| layout-ncol: 2
#| fig-cap: "Snow Crab At-sea-observer locations."
#| fig-subcap:
#| - ""
#| - ""
#| - ""
#| - ""
loc = file.path( data_loc, "output", "maps", "observer.locations" )
yrsplot = year_assessment + c(0:-3)
fns = paste( "observer.locations", yrsplot, "png", sep="." )
fn = file.path( loc, fns )
include_graphics( fn )
$~$
At-sea-observed effort: no. trips
#| label: tbl-observer-number-trips
#| eval: true
#| output: true
#| tbl-cap: "Number of at-sea observed trips."
oo = dcast( odb0[ fishyr>=2004,.(N=length(unique(tripset))), by=c(vnr, "fishyr")],
fishyr ~ get(vnr), value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
if ( "NA" %in% names(oo) ) oo$"NA" = NULL
keep = c("fishyr", regions)
oo = oo[,..keep]
names(oo) = c("Year", reg_labels )
oo$Total = rowSums( oo[, 2:nregions ], na.rm=TRUE)
gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
$~$
At-sea-observed effort: trap hauls
#| label: tbl-observer-number-traphauls
#| eval: true
#| output: true
#| tbl-cap: "Number of at-sea observed trap hauls."
odb0$th = paste(odb0$tripset, odb0$lat, odb0$lon) ## <<< NOTE: needs a re-think
oo = dcast( odb0[ fishyr>=2004,.(N=length(unique(th))), by=c(vnr, "fishyr")],
fishyr ~ get(vnr), value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
if ( "NA" %in% names(oo) ) oo$"NA" = NULL
keep = c("fishyr", regions)
oo = oo[,..keep]
names(oo) = c("Year", reg_labels )
oo$Total = rowSums( oo[, 2:nregions ], na.rm=TRUE)
gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
$~$
At-sea-observed number of crab
#| label: tbl-observer-number-crab
#| eval: true
#| output: true
#| tbl-cap: "Number of at-sea observed crab."
oo = dcast( odb0[ fishyr>=2004,.(N=.N), by=c(vnr, "fishyr")],
fishyr ~ get(vnr), value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
if ( "NA" %in% names(oo) ) oo$"NA" = NULL
keep = c("fishyr", regions)
oo = oo[,..keep]
names(oo) = c("Year", reg_labels )
oo[, 2:nregions] = round( oo[, 2:nregions] )
oo$Total = rowSums( oo[, 2:nregions ], na.rm=TRUE)
gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
$~$
At-sea-observed weight of crab
#| label: tbl-observer-weight-crab
#| eval: true
#| output: true
#| tbl-cap: "Total weight of at-sea observed crab (kg)."
oo = dcast( odb0[ fishyr>=2004,.(N=sum( mass, na.rm=TRUE)/1000 ), by=c(vnr, "fishyr")],
fishyr ~ get(vnr), value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
if ( "NA" %in% names(oo) ) oo$"NA" = NULL
keep = c("fishyr", regions)
oo = oo[,..keep]
names(oo) = c("Year", reg_labels )
oo[, 2:nregions] = round( oo[, 2:nregions] )
oo$Total = rowSums( oo[, 2:nregions ], na.rm=TRUE)
gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
Carapace condition from observed data: \< 95mm CW
#| label: tbl-observer-sublegal
#| echo: false
#| results: asis
#| eval: true
#| output: true
#| layout-ncol: 1
#| tbl-cap: "Fishery performance statistics: Distribution of at sea observations of males less than 95 mm CW by year and shell condition."
#| tbl-subcap:
#| - "(a)"
#| - "(b)"
#| - "(c)"
#| - "(d)"
odb = odb0[ cw < 95 & prodcd_id==0 & shell %in% c(1:5) & get(vnr) %in% regions & sex==0, ] # male
for (r in 1:nregions){
reg = regions[r]
REG = reg_labels[r]
cat( REG, "\n")
oo = dcast( odb0[ get(vnr)==reg, .(N=.N), by=.(fishyr, shell) ], fishyr ~ shell, value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
if ( "NA" %in% names(oo) ) oo$"NA" = NULL
keep = c("fishyr", "1", "2", "3", "4", "5" )
oo = oo[,..keep]
names(oo) = c("Year", "CC1", "CC2", "CC3", "CC4", "CC5" )
oo$Total = rowSums( oo[, 2:6 ], na.rm=TRUE)
oo[, 2:6 ] = round(oo[, 2:6 ] / oo$Total * 100, digits=1)
out = gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
print(out)
cat("\n\n")
}
$~$
Carapace condition from observed data: >= 95mm CW
#| label: tbl-observer-legal
#| echo: false
#| results: asis
#| eval: true
#| output: true
#| layout-ncol: 1
#| tbl-cap: "Fishery performance statistics: Distribution of at sea observations of males greater than 95 mm CW by year and shell condition."
#| tbl-subcap:
#| - "(a)"
#| - "(b)"
#| - "(c)"
#| - "(d)"
odb = odb0[ cw >= 95 & cw < 170 & prodcd_id==0 & shell %in% c(1:5) & get(vnr) %in% regions & sex==0, ] # male
for (r in 1:nregions){
reg = regions[r]
REG = reg_labels[r]
cat( REG, "\n")
oo = dcast( odb0[ get(vnr)==reg, .(N=.N), by=.(fishyr, shell) ], fishyr ~ shell, value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
if ( "NA" %in% names(oo) ) oo$"NA" = NULL
keep = c("fishyr", "1", "2", "3", "4", "5" )
oo = oo[,..keep]
names(oo) = c("Year", "CC1", "CC2", "CC3", "CC4", "CC5" )
oo$Total = rowSums( oo[, 2:6 ], na.rm=TRUE)
oo[, 2:6 ] = round(oo[, 2:6 ] / oo$Total * 100, digits=1)
out = gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
print(out)
cat("\n\n")
}
$~$
Soft-shell
There are two possible definitions:
- durometer \< 68 (D)
- carapace conditions 1 and 2 (CC)
#| label: tbl-observer-softgt95
#| eval: true
#| output: true
#| echo: false
#| results: asis
#| layout-ncol: 1
#| tbl-cap: "Soft-shell incidence. There are two possible definitions of soft-shelled crab: (D) based on durometer measurements < 68 on the hardness scale; and (CC) based upon classification as carapace conditions 1 and 2."
#| tbl-subcap:
#| - "(a)"
#| - "(b)"
#| - "(c)"
#| - "(d)"
odb = odb0[ cw >= 95 & cw < 170 & prodcd_id==0 & shell %in% c(1:5) & get(vnr) %in% regions & sex==0, ] # male
shell_condition = odb[ !is.na(get(vnr)), .N, by=c(vnr, "fishyr", "shell") ]
shell_condition[, total:=sum(N, na.rm=TRUE), by=c(vnr, "fishyr")]
shell_condition$percent = round(shell_condition$N / shell_condition$total, 3) * 100
shell_condition$Year = shell_condition$fishyr
for (r in 1:nregions){
reg = regions[r]
REG = reg_labels[r]
cat( REG, "\n")
soft = odb[ get(vnr)==reg & durometer < 68, .(Soft=.N), by=.(fishyr ) ]
total = odb[ get(vnr)==reg & is.finite(durometer) , .(Total=.N), by=.(fishyr) ]
oo = soft[total, on="fishyr"]
oo = oo[, .(Year=fishyr, Soft=round(Soft/Total*100, 1), Total=Total) ]
scond = shell_condition[ get(vnr)==reg & shell %in% c(1,2), .(SoftSC=sum(percent), TotalSC=unique(total)[1]), by=.(Year)]
oo = oo[scond, on="Year"]
names(oo) = c( "Year", "Soft (D)", "Total (D)", "Soft (CC)", "Total (CC)" )
out = gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
print(out)
cat("\n\n")
}
Soft shell locations
#| label: fig-observed-softshell-map
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 5
#| echo: false
#| layout-ncol: 1
#| fig-cap: "Map of observed soft shell locations."
#| fig-subcap:
#| - "N-ENS"
#| - "CFA23"
#| - "CFA24"
fns = c(
"nens_soft_crab_positions_68.png",
"cfa23_soft_crab_positions_68.png",
"cfa24_soft_crab_positions_68.png"
)
include_graphics( file.path( media_supplementary, fns ) )
$~$
At-sea-observed size
#| label: fig-observed-size
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 5
#| echo: false
#| fig-cap: "At sea observed crab size"
fns = c(
"mean_cw_observed.png"
)
include_graphics( file.path( media_supplementary, fns ) )
$~$
Size frequency distributions by carapace condition
#| label: fig-size-frequency-carapace-condition-observer
#| echo: false
#| results: asis
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 6
#| layout-ncol: 2
#! fig-cap: "Size frequency distribution of Snow Crab sampled by At-sea-observers, broken down by Carapace Condition (CC). Vertical lines indicate 95 mm Carapace Width, the minimum legal commercial size."
#| fig-subcap:
#| - ""
#| - ""
#| - ""
#| - ""
odir = file.path( data_loc, "assessments", year_assessment, "figures", "size.freq", "observer" )
years = year_assessment + c(0:-3)
for (r in 1:nregions) {
reg = regions[r]
REG = reg_labels[r]
cat( REG, "\n" )
fns = paste( "size.freq", reg, years, "png", sep="." )
fn = check_file_exists(file.path( odir, fns ) )
for (ff in fn) show_image(ff)
cat("\n\n")
}
$~$
Total discards of snow crab, by weight
#| label: tbl-fishery-discard-total
#| eval: true
#| output: true
#| echo: false
#| results: asis
#| layout-ncol: 2
#| tbl-cap: "Average by-catch discard rate by weight observed (kg/trap haul; and standard deviation, SD)."
#| tbl-subcap:
#| - "(a)"
#| - "(b)"
#| - "(c)"
#| - "(d)"
for (r in 1:nregions){
reg = regions[r]
REG = reg_labels[r]
cat( REG, "\n")
o = BC[[reg]]
oo = o$eff_summ[ order(fishyr), ]
names(oo) = c("Year", "Discards", "SD")
oo$Discards = round( oo$Discards*100, 1)
oo$SD = round( oo$SD*100, 1)
names(oo) = c("Year", "Discard mean", "Discard SD")
out = gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
print(out)
cat("\n\n")
}
$~$
#| label: fig-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: 6
oo = NULL
for (reg in regions) {
o = BC[[reg]][["eff_summ"]]
o$region = reg
oo = rbind(oo, o)
}
oo$fishyr = jitter(oo$fishyr, amount=0.02)
color_map = c("#E69F00", "#56B4E9", "#CC79A7" , "#D55E00", "#F0E442")[1:length(regions)]
shapes = c(15, 17, 19, 21, 23)[1:length(regions)]
pl = ggplot( oo, aes(x=fishyr, y=discard_rate, ymin=discard_rate-discard_rate_sd, ymax=discard_rate+discard_rate_sd, fill=region, colour=region) ) +
geom_line( alpha=0.9, linewidth=1 ) +
geom_point(aes(shape=region), size=5, alpha=0.7 )+
geom_pointrange() + # Vertical line with point in the middle
geom_errorbar(width = 0.1, col="brown") + # Standard error bars
geom_point(size = 1.5, col="darkred") +
scale_colour_manual(values=color_map) +
scale_fill_manual(values=color_map) +
scale_shape_manual(values = shapes) +
theme_light( base_size = 18) +
labs(x="Year", y="Discard rate of snow crab (Observed, by weight)" ) +
theme( legend.position="inside", legend.position.inside=c(0.2, 0.8), legend.title=element_blank() )
(pl)
Bycatch of non-target species
General approach: estimate bycatch from at sea observed data and project
onto marfis data
Bycatch of non-target species: estimates based on fisheries effort
Bycatch comes from at-sea-observed effort and catch. Rescale these
naively to total snow crab fishery effort.
#| label: tbl-fishery-discard-effort
#| eval: true
#| output: true
#| echo: false
#| results: asis
#| layout-ncol: 1
#| tbl-cap: "By-catch (kg) estimated from fisheries effort. Dots indicate low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The overall average is only for the years shown."
#| tbl-subcap:
#| - "(a)"
#| - "(b)"
#| - "(c)"
#| - "(d)"
for (r in 1:nregions){
reg = regions[r]
REG = reg_labels[r]
cat( REG, "\n")
o = BC[[reg]]
oo = o$bycatch_table_effort
oo[ oo==0 ] = NA
oo[ is.na(oo) ] = "."
out = gt::gt(oo) |> 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))
print(out)
cat("\n\n")
}
Bycatch of non-target species: estimates based on fisheries catch
Bycatch comes from at-sea-observed effort and catch. Rescale these
naively to total snow crab fishery catch.
#| label: tbl-fishery-discard-catch
#| eval: true
#| output: true
#| echo: false
#| results: asis
#| layout-ncol: 1
#| tbl-cap: "By-catch (kg) estimated from landings. Dots indicate low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The overall average is only for the years shown."
#| tbl-subcap:
#| - "(a)"
#| - "(b)"
#| - "(c)"
#| - "(d)"
for (r in 1:nregions){
reg = regions[r]
REG = reg_labels[r]
cat( REG, "\n")
o = BC[[reg]]
oo = o$bycatch_table_catch
oo[ oo==0 ] = NA
oo[ is.na(oo) ] = "."
out = gt::gt(oo) |> 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))
print(out)
cat("\n\n")
}
$~$
#| label: fig-bycatch_rates_all
#| eval: false
#| tbl-cap: "At sea observed bycatch rates in Maritimes"
#| fig-dpi: 144
#| fig-height: 15
reg = "cfaall"
o = BC[[reg]]
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 )
Entanglements of megafauna
#| label: tbl-bycatch_entanglements_all
#| warning: false
#| error: false
#| tbl-cap: "Entanglements of megafauna in Maritimes"
#| eval: true
#| output: true
region = "cfaall"
# observer data .. extra care needed as there are duplicated records, etc
oss = observer.db( DS="bycatch_clean_data", p=p, yrs=yrs_observer ) # Prepare at sea observed data
i = polygon_inside( oss[, c("lon", "lat")], region=region )
oss = oss[i,]
whales = oss[grep("whale", common, ignore.case=TRUE), .(whales=.N), by=.(yr)]
leatherback = oss[grep("leatherback", common, ignore.case=TRUE), .(leatherback=.N), by=.(yr)]
basking_shark = oss[ grep("BASKING SHARK", common, ignore.case=TRUE), .(basking_shark=.N), by=.(yr)]
out = data.table( yr=yrs_observer )
out = whales[out, on="yr"]
out = leatherback[out, on="yr"]
out = basking_shark[out, on="yr"]
out[ is.na(out) ] = 0
colnames(out) = c("Year", "Whale", "Leatherback turtle", "Basking shark")
gt::gt(out) |> 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))
Map of locations of megafauna entanglements:
#| label: fig-bycatch_entanglements_map_all
#| warning: false
#| error: false
#| fig-cap: "Entanglement locations in Maritimes of megafauna since 2000. Whales (red), Leatherback turtles (green), Basking shark (blue)."
#| fig-dpi: 144
#| fig-height: 5
loc = file.path( data_loc, "output", "maps", "observer.entanglements" )
fn = file.path( loc, "observed_bycatch_entanglements.png" )
include_graphics( fn )
```{=html}
<!--
To do next:
Estimate via carstm: requires a Poisson model of each species of catch (number) with offset of landings and covariates ... soon, ever?
-->
```
jae0/snowcrab documentation built on Feb. 20, 2025, 2:27 p.m.
R Package Documentation
Browse R Packages
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Note that we can't provide technical support on individual packages. You should contact the package authors for that.
title: "Snow crab fishery summary" keywords: - snow crab trawl survey results - basic tables and figures abstract: | Details of 2024 snow crab fishery performance. fontsize: 12pt metadata-files: - _metadata.yml params: year_assessment: 2024 year_start: 1999 data_loc: "~/bio.data/bio.snowcrab" sens: 1 debugging: FALSE model_variation: logistic_discrete_historical
#| eval: true
#| output: false
#| echo: false
#| label: setup
require(knitr)
knitr::opts_chunk$set(
root.dir = data_root,
echo = FALSE,
out.width="6.2in",
fig.retina = 2,
dpi=192
)
# things to load into memory (in next step) via _load_results.qmd
toget = c( "fishery_results" )
{{< include _load_results.qmd >}}
Fishing locations
Fishing locations recorded in logbooks
#| label: fig-map-logbook-locations
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 4
#| echo: false
#| layout-ncol: 2
#| fig-cap: "Snow Crab logbook locations."
#| fig-subcap:
#| - ""
#| - ""
#| - ""
#| - ""
loc = file.path( data_loc, "output", "maps", "logbook.locations" )
yrsplot = year_assessment + c(0:-3)
fns = paste( "logbook.locations", yrsplot, "png", sep="." )
fn = file.path( loc, fns )
include_graphics( fn )
$~$
Fishing locations recorded in logbooks: a closer look
#| label: fig-map-logbook-locations-two-years
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 5
#| echo: false
#| layout-ncol: 1
#| fig-cap: "Snow Crab logbook locations in the past two years."
#| fig-subcap:
#| - "N-ENS"
#| - "S-ENS"
#| - "4X"
fns = file.path( media_supplementary, c(
"nens_past_two_years_fishing_positions.png",
"sens_past_two_years_fishing_positions.png",
"cfa4x_past_two_years_fishing_positions.png"
))
include_graphics( fns )
Fishery performance
Fishery performance: Summary
#| label: tbl-fishery-performance
#| echo: false
#| results: asis
#| eval: true
#| output: true
#| tbl-cap: "Fishery performance statistics. Note: 4X years represent the starting year."
#| tbl-subcap:
#| - ""
#| - ""
#| - ""
#| - ""
for (r in 1:nregions) {
reg = regions[r]
REG = reg_labels[r]
cat(REG, "\n")
oo = dt[ which(dt$Region==reg), c("Year", "Licenses", "TAC", "Landings", "Effort", "CPUE")]
names(oo) = c( "Year", "Licenses", "TAC (t)", "Landings (t)", "Effort (1000 th)", "CPUE (kg/th)" )
out = gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
print(out)
cat("\n\n")
}
$~$
Landings
Landings: annual
#| label: fig-landings-timeseries
#| eval: true
#| output: true
#| fig-cap: "Landings (t) of Snow Crab on the SSE. For 4X, the year refers to the starting year of the season. Inset is a closeup view of the timeseries for N-ENS and 4X."
#| fig-dpi: 144
#| fig-height: 8
if (params$sens==1) {
ts_dir = file.path( data_loc, "assessments", year_assessment, "timeseries", "fishery" )
} else if (params$sens==2) {
ts_dir = file.path( data_loc, "assessments", year_assessment, "timeseries", "fishery", "split" )
}
include_graphics( file.path( ts_dir, "landings.ts.png" ) )
$~$
Landings: close-up
#| label: fig-landings-decomposed
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 5
#| echo: false
#| layout-ncol: 1
#| fig-cap: "Landings decomposed"
#| fig-subcap:
#| - "Fraction of landings in Spring"
#| - "Fraction of landings in Summer"
#| - "Fraction of landings in Winter"
#| - "Cummulative landings"
fns = c(
"percent_spring_landings.png",
"percent_summer_landings.png",
"percent_winter_landings.png",
"weekly_landing.png"
)
include_graphics( file.path( media_supplementary, fns ) )
$~$
Landings: spatial
#| label: fig-landings-map
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 4
#| echo: false
#| layout-ncol: 2
#| fig-cap: "Snow Crab landings from fisheries logbook data for previous and current years (tons per 10 km x 10 km grid)."
#| fig-subcap:
#| - ""
#| - ""
#| - ""
#| - ""
loc0 = file.path( data_loc, "output", "maps", "logbook", "snowcrab", "annual", "landings" )
yrsplot = year_assessment + c(0:-3)
fn = file.path( loc0, paste( "landings", yrsplot, "png", sep=".") )
include_graphics( fn )
$~$
Effort
Effort: annual
#| label: fig-effort-timeseries
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 8
#| fig-cap: "Temporal variations in fishing effort."
if (params$sens==1) {
ts_dir = file.path( data_loc, "assessments", year_assessment, "timeseries", "fishery" )
} else if (params$sens==2) {
ts_dir = file.path( data_loc, "assessments", year_assessment, "timeseries", "fishery", "split" )
}
include_graphics( file.path( ts_dir, "effort.ts.png" ) )
$~$
Effort: spatial
#| label: fig-effort-map
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 8
#| echo: false
#| layout-ncol: 2
#| fig-cap: "Snow Crab fishing effort from fisheries logbook data for previous and current years (no X 10$^3$ per 10 km X 10 km grid)."
#| fig-subcap:
#| - ""
#| - ""
#| - ""
#| - ""
loc0 = file.path( data_loc, "output", "maps", "logbook", "snowcrab", "annual", "effort" )
yrsplot = year_assessment + c(0:-3)
fn = file.path( loc0, paste( "effort", yrsplot, "png", sep=".") )
include_graphics( fn )
$~$
Catch rates
Catch rates: annual
#| label: fig-cpue-timeseries
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 4
#| fig-cap: "Temporal variations in crude catch rates of Snow Crab (kg/trap haul)."
if (params$sens==1) {
ts_dir = file.path( data_loc, "assessments", year_assessment, "timeseries", "fishery" )
} else if (params$sens==2) {
ts_dir = file.path( data_loc, "assessments", year_assessment, "timeseries", "fishery", "split" )
}
include_graphics( file.path( ts_dir, "cpue.ts.png" ) )
$~$
Catch rates: close up
#| label: fig-cpue-weekly
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 5
#| echo: false
#| layout-ncol: 1
#| fig-cap: "CPUE (kg/trap haul) on a weekly basis"
fns = c(
"weekly_cpue_smoothed2.png"
)
include_graphics( file.path( media_supplementary, fns ) )
$~$
Catch rates: spatial
#| label: fig-cpue-map
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 4
#| echo: false
#| layout-ncol: 2
#| fig-cap: "Snow Crab crude catch rates on the Scotian Shelf for previous and current years. Units are kg/trap haul per 10 km x 10 km grid."
#| fig-subcap:
#| - ""
#| - ""
#| - ""
#| - ""
loc0= file.path( data_loc, "output", "maps", "logbook", "snowcrab", "annual", "cpue" )
yrsplot = year_assessment + c(0:-3)
fn = file.path( loc0, paste( "cpue", yrsplot, "png", sep=".") )
include_graphics( fn )
$~$
At-sea Observed Data
At-sea Observed Data: Summary
#| label: tbl-observed-summary
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 5
#| echo: false
#| layout-ncol: 1
#| tbl-cap: "Table of observed data coverage"
fns = c(
"observersummary2.png"
)
include_graphics( file.path( media_supplementary, fns ) )
At-sea Observed fishing locations
#| label: fig-map-observer-locations
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 4
#| echo: false
#| layout-ncol: 2
#| fig-cap: "Snow Crab At-sea-observer locations."
#| fig-subcap:
#| - ""
#| - ""
#| - ""
#| - ""
loc = file.path( data_loc, "output", "maps", "observer.locations" )
yrsplot = year_assessment + c(0:-3)
fns = paste( "observer.locations", yrsplot, "png", sep="." )
fn = file.path( loc, fns )
include_graphics( fn )
$~$
At-sea-observed effort: no. trips
#| label: tbl-observer-number-trips
#| eval: true
#| output: true
#| tbl-cap: "Number of at-sea observed trips."
oo = dcast( odb0[ fishyr>=2004,.(N=length(unique(tripset))), by=c(vnr, "fishyr")],
fishyr ~ get(vnr), value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
if ( "NA" %in% names(oo) ) oo$"NA" = NULL
keep = c("fishyr", regions)
oo = oo[,..keep]
names(oo) = c("Year", reg_labels )
oo$Total = rowSums( oo[, 2:nregions ], na.rm=TRUE)
gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
$~$
At-sea-observed effort: trap hauls
#| label: tbl-observer-number-traphauls
#| eval: true
#| output: true
#| tbl-cap: "Number of at-sea observed trap hauls."
odb0$th = paste(odb0$tripset, odb0$lat, odb0$lon) ## <<< NOTE: needs a re-think
oo = dcast( odb0[ fishyr>=2004,.(N=length(unique(th))), by=c(vnr, "fishyr")],
fishyr ~ get(vnr), value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
if ( "NA" %in% names(oo) ) oo$"NA" = NULL
keep = c("fishyr", regions)
oo = oo[,..keep]
names(oo) = c("Year", reg_labels )
oo$Total = rowSums( oo[, 2:nregions ], na.rm=TRUE)
gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
$~$
At-sea-observed number of crab
#| label: tbl-observer-number-crab
#| eval: true
#| output: true
#| tbl-cap: "Number of at-sea observed crab."
oo = dcast( odb0[ fishyr>=2004,.(N=.N), by=c(vnr, "fishyr")],
fishyr ~ get(vnr), value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
if ( "NA" %in% names(oo) ) oo$"NA" = NULL
keep = c("fishyr", regions)
oo = oo[,..keep]
names(oo) = c("Year", reg_labels )
oo[, 2:nregions] = round( oo[, 2:nregions] )
oo$Total = rowSums( oo[, 2:nregions ], na.rm=TRUE)
gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
$~$
At-sea-observed weight of crab
#| label: tbl-observer-weight-crab
#| eval: true
#| output: true
#| tbl-cap: "Total weight of at-sea observed crab (kg)."
oo = dcast( odb0[ fishyr>=2004,.(N=sum( mass, na.rm=TRUE)/1000 ), by=c(vnr, "fishyr")],
fishyr ~ get(vnr), value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
if ( "NA" %in% names(oo) ) oo$"NA" = NULL
keep = c("fishyr", regions)
oo = oo[,..keep]
names(oo) = c("Year", reg_labels )
oo[, 2:nregions] = round( oo[, 2:nregions] )
oo$Total = rowSums( oo[, 2:nregions ], na.rm=TRUE)
gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
Carapace condition from observed data: \< 95mm CW
#| label: tbl-observer-sublegal
#| echo: false
#| results: asis
#| eval: true
#| output: true
#| layout-ncol: 1
#| tbl-cap: "Fishery performance statistics: Distribution of at sea observations of males less than 95 mm CW by year and shell condition."
#| tbl-subcap:
#| - "(a)"
#| - "(b)"
#| - "(c)"
#| - "(d)"
odb = odb0[ cw < 95 & prodcd_id==0 & shell %in% c(1:5) & get(vnr) %in% regions & sex==0, ] # male
for (r in 1:nregions){
reg = regions[r]
REG = reg_labels[r]
cat( REG, "\n")
oo = dcast( odb0[ get(vnr)==reg, .(N=.N), by=.(fishyr, shell) ], fishyr ~ shell, value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
if ( "NA" %in% names(oo) ) oo$"NA" = NULL
keep = c("fishyr", "1", "2", "3", "4", "5" )
oo = oo[,..keep]
names(oo) = c("Year", "CC1", "CC2", "CC3", "CC4", "CC5" )
oo$Total = rowSums( oo[, 2:6 ], na.rm=TRUE)
oo[, 2:6 ] = round(oo[, 2:6 ] / oo$Total * 100, digits=1)
out = gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
print(out)
cat("\n\n")
}
$~$
Carapace condition from observed data: >= 95mm CW
#| label: tbl-observer-legal
#| echo: false
#| results: asis
#| eval: true
#| output: true
#| layout-ncol: 1
#| tbl-cap: "Fishery performance statistics: Distribution of at sea observations of males greater than 95 mm CW by year and shell condition."
#| tbl-subcap:
#| - "(a)"
#| - "(b)"
#| - "(c)"
#| - "(d)"
odb = odb0[ cw >= 95 & cw < 170 & prodcd_id==0 & shell %in% c(1:5) & get(vnr) %in% regions & sex==0, ] # male
for (r in 1:nregions){
reg = regions[r]
REG = reg_labels[r]
cat( REG, "\n")
oo = dcast( odb0[ get(vnr)==reg, .(N=.N), by=.(fishyr, shell) ], fishyr ~ shell, value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
if ( "NA" %in% names(oo) ) oo$"NA" = NULL
keep = c("fishyr", "1", "2", "3", "4", "5" )
oo = oo[,..keep]
names(oo) = c("Year", "CC1", "CC2", "CC3", "CC4", "CC5" )
oo$Total = rowSums( oo[, 2:6 ], na.rm=TRUE)
oo[, 2:6 ] = round(oo[, 2:6 ] / oo$Total * 100, digits=1)
out = gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
print(out)
cat("\n\n")
}
$~$
Soft-shell
There are two possible definitions:
- durometer \< 68 (D)
- carapace conditions 1 and 2 (CC)
#| label: tbl-observer-softgt95
#| eval: true
#| output: true
#| echo: false
#| results: asis
#| layout-ncol: 1
#| tbl-cap: "Soft-shell incidence. There are two possible definitions of soft-shelled crab: (D) based on durometer measurements < 68 on the hardness scale; and (CC) based upon classification as carapace conditions 1 and 2."
#| tbl-subcap:
#| - "(a)"
#| - "(b)"
#| - "(c)"
#| - "(d)"
odb = odb0[ cw >= 95 & cw < 170 & prodcd_id==0 & shell %in% c(1:5) & get(vnr) %in% regions & sex==0, ] # male
shell_condition = odb[ !is.na(get(vnr)), .N, by=c(vnr, "fishyr", "shell") ]
shell_condition[, total:=sum(N, na.rm=TRUE), by=c(vnr, "fishyr")]
shell_condition$percent = round(shell_condition$N / shell_condition$total, 3) * 100
shell_condition$Year = shell_condition$fishyr
for (r in 1:nregions){
reg = regions[r]
REG = reg_labels[r]
cat( REG, "\n")
soft = odb[ get(vnr)==reg & durometer < 68, .(Soft=.N), by=.(fishyr ) ]
total = odb[ get(vnr)==reg & is.finite(durometer) , .(Total=.N), by=.(fishyr) ]
oo = soft[total, on="fishyr"]
oo = oo[, .(Year=fishyr, Soft=round(Soft/Total*100, 1), Total=Total) ]
scond = shell_condition[ get(vnr)==reg & shell %in% c(1,2), .(SoftSC=sum(percent), TotalSC=unique(total)[1]), by=.(Year)]
oo = oo[scond, on="Year"]
names(oo) = c( "Year", "Soft (D)", "Total (D)", "Soft (CC)", "Total (CC)" )
out = gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
print(out)
cat("\n\n")
}
Soft shell locations
#| label: fig-observed-softshell-map
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 5
#| echo: false
#| layout-ncol: 1
#| fig-cap: "Map of observed soft shell locations."
#| fig-subcap:
#| - "N-ENS"
#| - "CFA23"
#| - "CFA24"
fns = c(
"nens_soft_crab_positions_68.png",
"cfa23_soft_crab_positions_68.png",
"cfa24_soft_crab_positions_68.png"
)
include_graphics( file.path( media_supplementary, fns ) )
$~$
At-sea-observed size
#| label: fig-observed-size
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 5
#| echo: false
#| fig-cap: "At sea observed crab size"
fns = c(
"mean_cw_observed.png"
)
include_graphics( file.path( media_supplementary, fns ) )
$~$
Size frequency distributions by carapace condition
#| label: fig-size-frequency-carapace-condition-observer
#| echo: false
#| results: asis
#| eval: true
#| output: true
#| fig-dpi: 144
#| fig-height: 6
#| layout-ncol: 2
#! fig-cap: "Size frequency distribution of Snow Crab sampled by At-sea-observers, broken down by Carapace Condition (CC). Vertical lines indicate 95 mm Carapace Width, the minimum legal commercial size."
#| fig-subcap:
#| - ""
#| - ""
#| - ""
#| - ""
odir = file.path( data_loc, "assessments", year_assessment, "figures", "size.freq", "observer" )
years = year_assessment + c(0:-3)
for (r in 1:nregions) {
reg = regions[r]
REG = reg_labels[r]
cat( REG, "\n" )
fns = paste( "size.freq", reg, years, "png", sep="." )
fn = check_file_exists(file.path( odir, fns ) )
for (ff in fn) show_image(ff)
cat("\n\n")
}
$~$
Total discards of snow crab, by weight
#| label: tbl-fishery-discard-total
#| eval: true
#| output: true
#| echo: false
#| results: asis
#| layout-ncol: 2
#| tbl-cap: "Average by-catch discard rate by weight observed (kg/trap haul; and standard deviation, SD)."
#| tbl-subcap:
#| - "(a)"
#| - "(b)"
#| - "(c)"
#| - "(d)"
for (r in 1:nregions){
reg = regions[r]
REG = reg_labels[r]
cat( REG, "\n")
o = BC[[reg]]
oo = o$eff_summ[ order(fishyr), ]
names(oo) = c("Year", "Discards", "SD")
oo$Discards = round( oo$Discards*100, 1)
oo$SD = round( oo$SD*100, 1)
names(oo) = c("Year", "Discard mean", "Discard SD")
out = gt::gt(oo) |> gt::tab_options(table.font.size = 14, 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))
print(out)
cat("\n\n")
}
$~$
#| label: fig-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: 6
oo = NULL
for (reg in regions) {
o = BC[[reg]][["eff_summ"]]
o$region = reg
oo = rbind(oo, o)
}
oo$fishyr = jitter(oo$fishyr, amount=0.02)
color_map = c("#E69F00", "#56B4E9", "#CC79A7" , "#D55E00", "#F0E442")[1:length(regions)]
shapes = c(15, 17, 19, 21, 23)[1:length(regions)]
pl = ggplot( oo, aes(x=fishyr, y=discard_rate, ymin=discard_rate-discard_rate_sd, ymax=discard_rate+discard_rate_sd, fill=region, colour=region) ) +
geom_line( alpha=0.9, linewidth=1 ) +
geom_point(aes(shape=region), size=5, alpha=0.7 )+
geom_pointrange() + # Vertical line with point in the middle
geom_errorbar(width = 0.1, col="brown") + # Standard error bars
geom_point(size = 1.5, col="darkred") +
scale_colour_manual(values=color_map) +
scale_fill_manual(values=color_map) +
scale_shape_manual(values = shapes) +
theme_light( base_size = 18) +
labs(x="Year", y="Discard rate of snow crab (Observed, by weight)" ) +
theme( legend.position="inside", legend.position.inside=c(0.2, 0.8), legend.title=element_blank() )
(pl)
Bycatch of non-target species
General approach: estimate bycatch from at sea observed data and project onto marfis data
Bycatch of non-target species: estimates based on fisheries effort
Bycatch comes from at-sea-observed effort and catch. Rescale these naively to total snow crab fishery effort.
#| label: tbl-fishery-discard-effort
#| eval: true
#| output: true
#| echo: false
#| results: asis
#| layout-ncol: 1
#| tbl-cap: "By-catch (kg) estimated from fisheries effort. Dots indicate low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The overall average is only for the years shown."
#| tbl-subcap:
#| - "(a)"
#| - "(b)"
#| - "(c)"
#| - "(d)"
for (r in 1:nregions){
reg = regions[r]
REG = reg_labels[r]
cat( REG, "\n")
o = BC[[reg]]
oo = o$bycatch_table_effort
oo[ oo==0 ] = NA
oo[ is.na(oo) ] = "."
out = gt::gt(oo) |> 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))
print(out)
cat("\n\n")
}
Bycatch of non-target species: estimates based on fisheries catch
Bycatch comes from at-sea-observed effort and catch. Rescale these naively to total snow crab fishery catch.
#| label: tbl-fishery-discard-catch
#| eval: true
#| output: true
#| echo: false
#| results: asis
#| layout-ncol: 1
#| tbl-cap: "By-catch (kg) estimated from landings. Dots indicate low values. Where species exist in a list but there is no data, this indicates some historical bycatch. The overall average is only for the years shown."
#| tbl-subcap:
#| - "(a)"
#| - "(b)"
#| - "(c)"
#| - "(d)"
for (r in 1:nregions){
reg = regions[r]
REG = reg_labels[r]
cat( REG, "\n")
o = BC[[reg]]
oo = o$bycatch_table_catch
oo[ oo==0 ] = NA
oo[ is.na(oo) ] = "."
out = gt::gt(oo) |> 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))
print(out)
cat("\n\n")
}
$~$
#| label: fig-bycatch_rates_all
#| eval: false
#| tbl-cap: "At sea observed bycatch rates in Maritimes"
#| fig-dpi: 144
#| fig-height: 15
reg = "cfaall"
o = BC[[reg]]
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 )
Entanglements of megafauna
#| label: tbl-bycatch_entanglements_all
#| warning: false
#| error: false
#| tbl-cap: "Entanglements of megafauna in Maritimes"
#| eval: true
#| output: true
region = "cfaall"
# observer data .. extra care needed as there are duplicated records, etc
oss = observer.db( DS="bycatch_clean_data", p=p, yrs=yrs_observer ) # Prepare at sea observed data
i = polygon_inside( oss[, c("lon", "lat")], region=region )
oss = oss[i,]
whales = oss[grep("whale", common, ignore.case=TRUE), .(whales=.N), by=.(yr)]
leatherback = oss[grep("leatherback", common, ignore.case=TRUE), .(leatherback=.N), by=.(yr)]
basking_shark = oss[ grep("BASKING SHARK", common, ignore.case=TRUE), .(basking_shark=.N), by=.(yr)]
out = data.table( yr=yrs_observer )
out = whales[out, on="yr"]
out = leatherback[out, on="yr"]
out = basking_shark[out, on="yr"]
out[ is.na(out) ] = 0
colnames(out) = c("Year", "Whale", "Leatherback turtle", "Basking shark")
gt::gt(out) |> 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))
Map of locations of megafauna entanglements:
#| label: fig-bycatch_entanglements_map_all
#| warning: false
#| error: false
#| fig-cap: "Entanglement locations in Maritimes of megafauna since 2000. Whales (red), Leatherback turtles (green), Basking shark (blue)."
#| fig-dpi: 144
#| fig-height: 5
loc = file.path( data_loc, "output", "maps", "observer.entanglements" )
fn = file.path( loc, "observed_bycatch_entanglements.png" )
include_graphics( fn )
```{=html} <!--
To do next:
Estimate via carstm: requires a Poisson model of each species of catch (number) with offset of landings and covariates ... soon, ever?
--> ```
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