inst/markdown/archive/02.tables.md

title: "Snow crab tables" author: "Jae S. Choi" toc: true number-sections: true highlight-style: pygments editor: render-on-save: false format: html: code-fold: true html-math-method: katex embed-resources: true pdf: pdf-engine: lualatex docx: default

Set up environment

First set up environment. Data comes from:

These are mostly imported and formatted in 01_snowcrab.R

#| eval: true
#| output: false
    require(aegis)

    # Get data and format based upon parameters:
    year.assessment = 2023
    p = bio.snowcrab::load.environment( year.assessment=year.assessment )

    # loadfunctions( "aegis")
    # loadfunctions( "bio.snowcrab")  # in case of local edits

    # require(ggplot2)
    # require(data.table)

    require(gt)  # table formatting

    outtabledir = file.path( p$annual.results, "tables" )

    years = as.character(1996: year.assessment)

    regions = c("cfanorth", "cfasouth", "cfa4x")
    nregions = length(regions)

    FD = fishery_data()  # mass in tonnes
    fda = FD$summary_annual
    dt = as.data.frame( fda[ which(fda$yr %in% c(year.assessment - c(0:10))),] )
    dt =  dt[,c("region", "yr", "Licenses", "TAC", "landings", "effort", "cpue")] 
    names(dt) = c("Region", "Year", "Licenses", "TAC", "Landings", "Effort", "CPUE") 
    rownames(dt) = NULL
    odb0 = setDT(observer.db("odb"))
    odb0$region = NA
    for ( reg in regions) {
      r = polygon_inside(x = odb0, region = aegis.polygons::polygon_internal_code(reg), planar=FALSE)
      odb0$region[r] = reg
    }


Fishery statistics from at sea observations

NENS:

#| eval: true
#| output: true
#| label: table-fishery-nens-perf
#| tbl-cap: "Fishery performance statistics in NENS. Units are: TACs and Landings (tons, t), Effort ($\\times 10^3$ trap hauls, th) and CPUE (kg/th)."

ii = which(dt$Region=="cfanorth")
oo = dt[ii, c("Year", "Licenses", "TAC", "Landings", "Effort", "CPUE")] 
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))

SENS:

#| eval: true
#| output: true
#| label: table-fishery-sens-perf
#| tbl-cap: "Fishery performance statistics in SENS. Units are: TACs and Landings (tons, t), Effort ($\\times 10^3$ trap hauls, th) and CPUE (kg/th)."
ii = which(dt$Region=="cfasouth")
oo = dt[ii, c("Year", "Licenses", "TAC", "Landings", "Effort", "CPUE")] 
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))

4X:

#| eval: true
#| output: true
#| label: table-fishery-4x-perf
#| tbl-cap: "Fishery performance statistics in 4X. Units are: TACs and Landings (tons, t), Effort ($\\times 10^3$ trap hauls, th) and CPUE (kg/th). There were no landings or TACs in 2018/2019 due to indications of low abundance. The 2022 season is ongoing."
ii = which(dt$Region=="cfa4x")
oo = dt[ii, c("Year", "Licenses", "TAC", "Landings", "Effort", "CPUE")] 
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))

At sea observed data

Carapace condition from observed data < 95mm CW

#| eval: true
#| output: false
  odb = odb0[ cw < 95 & prodcd_id==0 & shell %in% c(1:5) & region %in% regions & sex==0, ]  # male

NENS:

#| eval: true
#| output: true
#| label: table-fishery-nens-sublegal
#| tbl-cap: "Fishery performance statistics in NENS. Distribution of at sea observations of males less than 95 mm CW by year and shell condition."
resN = dcast( odb0[ region=="cfanorth", .(N=.N), by=.(fishyr, shell) ], fishyr  ~ shell, value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
if ( "NA" %in% names(resN) ) resN$"NA" = NULL
names(resN) = c("Year", "CC1", "CC2", "CC3", "CC4", "CC5" )
resN$Total = rowSums( resN[, 2:6 ], na.rm=TRUE)
resN[, 2:6 ] = round(resN[, 2:6 ] / resN$Total * 100, digits=2)
gt::gt(resN) |> 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))

SENS:

#| eval: true
#| output: true
#| label: table-fishery-sens-sublegal
#| tbl-cap: "Fishery performance statistics in SENS. Distribution of at sea observations of males less than 95 mm CW by year and shell condition."
resS = dcast( odb0[ region=="cfasouth", .(N=.N), by=.(fishyr, shell) ], fishyr  ~ shell, value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
if ( "NA" %in%  names(resS)) resS$"NA" = NULL
names(resS) = c("Year", "CC1", "CC2", "CC3", "CC4", "CC5" )
resS$Total = rowSums( resS[, 2:6 ], na.rm=TRUE)
resS[, 2:6 ] = round(resS[, 2:6 ] / resS$Total * 100, digits=2)
gt::gt(resS) |> 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))

4X:

#| eval: true
#| output: true
#| label: table-fishery-4x-sublegal
#| tbl-cap: "Fishery performance statistics in 4X. Distribution of at sea observations of males less than 95 mm CW by year and shell condition."
resX = dcast( odb0[ region=="cfa4x", .(N=.N), by=.(fishyr, shell) ], fishyr  ~ shell, value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
if ("NA" %in% names(resX)) resX$"NA" = NULL
names(resX) = c("Year", "CC1", "CC2", "CC3", "CC4", "CC5" )
resX$Total = rowSums( resX[, 2:6 ], na.rm=TRUE)
resX[, 2:6 ] = round(resX[, 2:6 ] / resX$Total * 100, digits=2)
gt::gt(resX) |> 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))

Carapace condition from observed data >= 95mm CW

#| eval: true
#| output: false
odb = odb0[ cw >= 95 & cw < 170  & prodcd_id==0 & shell %in% c(1:5) & region %in% regions & sex==0, ]  # male

NENS:

#| eval: true
#| output: true
#| label: table-fishery-nens-comm
#| tbl-cap: "Fishery performance statistics in NENS. Distribution of at sea observations of males greater than 95 mm CW by year and shell condition."
resN = dcast( odb[ region=="cfanorth", .(N=.N), by=.(fishyr, shell) ], fishyr  ~ shell, value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
names(resN) = c("Year", "CC1", "CC2", "CC3", "CC4", "CC5" )
resN$Total = rowSums( resN[, 2:6 ], na.rm=TRUE)
resN[, 2:6 ] = round(resN[, 2:6 ] / resN$Total * 100, digits=2)
gt::gt(resN) |> 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))

SENS:

#| eval: true
#| output: true
#| label: table-fishery-sens-comm
#| tbl-cap: "Fishery performance statistics in SENS. Distribution of at sea observations of males greater than 95 mm CW by year and shell condition."
resS = dcast( odb[ region=="cfasouth", .(N=.N), by=.(fishyr, shell) ], fishyr  ~ shell, value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
names(resS) = c("Year", "CC1", "CC2", "CC3", "CC4", "CC5" )
resS$Total = rowSums( resS[, 2:6 ], na.rm=TRUE)
resS[, 2:6 ] = round(resS[, 2:6 ] / resS$Total * 100, digits=2)
gt::gt(resS) |> 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))

4X:

#| eval: true
#| output: true
#| label: table-fishery-4x-comm
#| tbl-cap: "Fishery performance statistics in 4X. Distribution of at sea observations of males greater than 95 mm CW by year and shell condition."
resX = dcast( odb[ region=="cfa4x", .(N=.N), by=.(fishyr, shell) ], fishyr  ~ shell, value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
names(resX) = c("Year", "CC1", "CC2", "CC3", "CC4", "CC5" )
resX$Total = rowSums( resX[, 2:6 ], na.rm=TRUE)
resX[, 2:6 ] = round(resX[, 2:6 ] / resX$Total * 100, digits=2)
gt::gt(resX) |> 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))

Percent soft from observed data

There are two possible definitions:

#| eval: true
#| output: true
odb = odb0[ cw >= 95 & cw < 170  & prodcd_id==0 & shell %in% c(1:5) & region %in% regions & sex==0, ]  # male
shell_condition = odb[ !is.na(odb$region), .N, by=.(region, fishyr, shell) ]
shell_condition[, total:=sum(N, na.rm=TRUE), by=.(region, fishyr)]
shell_condition$percent = round(shell_condition$N / shell_condition$total, 3) * 100
shell_condition$Year = shell_condition$fishyr

NENS:

#| eval: true
#| output: true
#| label: table-fishery-nens-soft-durometer
#| tbl-cap: "Fishery performance statistics in NENS. Distribution of at sea observations of males soft-shelled based on durometer (<68) and shell condition (1 and 2, SC)."
softN  = odb[ region=="cfanorth" & durometer <  68, .(Soft=.N), by=.(fishyr ) ] 
totalN = odb[ region=="cfanorth" & is.finite(durometer) , .(Total=.N), by=.(fishyr) ] 
resN = softN[totalN, on="fishyr"]
resN = resN[, .(Year=fishyr, Soft=round(Soft/Total*100,2), Total=Total) ]  
ssN = shell_condition[ region=="cfanorth" & shell %in% c(1,2), .(SoftSC=sum(percent), TotalSC=unique(total)[1]), by=.(Year)]
resN = resN[ssN, on="Year"]
gt::gt(resN) |> 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))

SENS:

#| eval: true
#| output: true
#| label: table-fishery-sens-soft-durometer
#| tbl-cap: "Fishery performance statistics in SENS. Distribution of at sea observations of males soft-shelled  based on durometer (<68) and shell condition (1 and 2, SC)."
softS  = odb[ region=="cfasouth" & durometer <  68, .(Soft=.N), by=.(fishyr ) ] 
totalS = odb[ region=="cfasouth" & is.finite(durometer) , .(Total=.N), by=.(fishyr) ] 
resS = softS[totalS, on="fishyr"]
resS = resS[, .(Year=fishyr, Soft=round(Soft/Total*100,2), Total=Total) ]  
ssS = shell_condition[ region=="cfasouth" & shell %in% c(1,2), .(SoftSC=sum(percent), TotalSC=unique(total)[1]), by=.(Year)]
resS = resS[ssS, on="Year"]
gt::gt(resS) |> 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))

4X:

#| eval: true
#| output: true
#| label: table-fishery-4x-soft-durometer
#| tbl-cap: "Fishery performance statistics in 4X. Distribution of at sea observations of males soft-shelled  based on durometer (<68) and shell condition (1 and 2, SC)."
softX  = odb[ region=="cfa4x" & durometer <  68, .(Soft=.N), by=.(fishyr ) ] 
totalX = odb[ region=="cfa4x" & is.finite(durometer) , .(Total=.N), by=.(fishyr) ] 
resX = softX[totalX, on="fishyr"]
resX = resX[, .(Year=fishyr, Soft=round(Soft/Total*100,2), Total=Total) ]  
ssX = shell_condition[ region=="cfa4x" & shell %in% c(1,2), .(SoftSC=sum(percent), TotalSC=unique(total)[1]), by=.(Year)]
resX = resX[ssX, on="Year"]
gt::gt(resX) |> 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))

Compare discard rates Maritimes:

NENS:discard

#| eval: true
#| output: true
#| warning: false
#| error: false 
#| label: table-fishery-nens-discard
#| tbl-cap: "Fishery performance statistics in NENS. Average by-catch discard rate by weight observed (kg/trap haul; and standard deviation, SD)."
region="cfanorth"
o = observer.db( DS="bycatch_summary", p=p,  yrs=p$yrs, region=region )   
resN = o$eff_summ[ order(fishyr), ]
names(resN) = c("Year", "Discards", "SD")
resN$Discards = round( resN$Discards*100, 2)
resN$SD = round( resN$SD*100, 2)
gt::gt(resN) |> 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))

SENS:

#| eval: true
#| output: true
#| warning: false
#| error: false 
#| label: table-fishery-sens-discard
#| tbl-cap: "Fishery performance statistics in SENS. Average by-catch discard rate by weight observed (kg/trap haul; and standard deviation, SD)."
region="cfasouth"
o = observer.db( DS="bycatch_summary", p=p,  yrs=p$yrs, region=region )   
resS = o$eff_summ[ order(fishyr), ]
names(resS) = c("Year", "Discards", "SD")
resS$Discards = round( resS$Discards*100, 2)
resS$SD = round( resS$SD*100, 2)
gt::gt(resS) |> 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))

4X:

#| eval: true
#| output: true
#| warning: false
#| error: false 
#| label: table-fishery-4x-discard
#| tbl-cap: "Fishery performance statistics in 4X. Average by-catch discard rate by weight observed (kg/trap haul; and standard deviation, SD)."
region="cfa4x"
o = observer.db( DS="bycatch_summary", p=p,  yrs=p$yrs, region=region )   
resX = o$eff_summ[ order(fishyr), ]
names(resX) = c("Year", "Discards", "SD")
resX$Discards = round( resX$Discards*100, 2)
resX$SD = round( resX$SD*100, 2)
gt::gt(resX) |> 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))

Survey-based tables

Carapace condition from trawl data >= 95mm CW

#| eval: true
#| output: false
det = snowcrab.db( p=p, DS="det.georeferenced" )
setDT(det)
det$fishyr = det$yr  ## the counting routine expectes this variable
det = det[ cw >= 95 ,]  # commerical sized crab only
years = sort( unique( det$yr ) )
det$region = NA
for ( reg in regions) {
  r = polygon_inside(x = det, region = aegis.polygons::polygon_internal_code(reg), planar=FALSE)
  det$region[r] = reg
}

NENS:

#| eval: true
#| output: true
#| label: table-survey-nens-comm
#| tbl-cap: "Distribution of NENS survey: males less than 95 mm CW by year and shell condition."
resN = dcast( det[ region=="cfanorth" & !is.na(shell), .(N=.N), by=.(fishyr, shell) ], fishyr  ~ shell, value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
names(resN) = c("Year", "CC1", "CC2", "CC3", "CC4", "CC5" )
resN$Total = rowSums( resN[, 2:6 ], na.rm=TRUE)
resN[, 2:6 ] = round(resN[, 2:6 ] / resN$Total * 100, digits=2)
gt::gt(resN) |> 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))

SENS:

#| eval: true
#| output: true
#| label: table-survey-sens-comm
#| tbl-cap: "Distribution of SENS survey: males less than 95 mm CW by year and shell condition."
resS = dcast( det[ region=="cfasouth" & !is.na(shell), .(N=.N), by=.(fishyr, shell) ], fishyr  ~ shell, value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
names(resS) = c("Year", "CC1", "CC2", "CC3", "CC4", "CC5" )
resS$Total = rowSums( resS[, 2:6 ], na.rm=TRUE)
resS[, 2:6 ] = round(resS[, 2:6 ] / resS$Total * 100, digits=2)
gt::gt(resS) |> 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))

4X:

#| eval: true
#| output: true
#| label: table-survey-4X-comm
#| tbl-cap: "Distribution of 4X survey: males less than 95 mm CW by year and shell condition."
resX = dcast( det[ region=="cfa4x" & !is.na(shell), .(N=.N), by=.(fishyr, shell) ], fishyr  ~ shell, value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
names(resX) = c("Year", "CC1", "CC2", "CC3", "CC4", "CC5" )
resX$Total = rowSums( resX[, 2:6 ], na.rm=TRUE)
resX[, 2:6 ] = round(resX[, 2:6 ] / resX$Total * 100, digits=2)
gt::gt(resX) |> 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))

Counts of stations in each area

#| eval: true
#| output: true
#| label: table-survey-station-count
#| tbl-cap: "Survey station counts"
set = snowcrab.db(p=p, DS="set.clean")
setDT(set)
# check towquality .. this should always == 1
if (length( unique( set$towquality) ) != 1 ) print("error -- not good tows")
set$region = NA
for (reg in c( "cfanorth", "cfasouth", "cfa4x"  ) ) {
  d = polygon_inside(set[,c("lon","lat")], reg)
  set$region[d] = reg 
}
out = dcast( set[, .(N=.N), by=.(region, yr)], yr~region, value.var="N", fill=0, drop=FALSE, na.rm=TRUE )
out[,Total:=sum(cfanorth,cfasouth,cfa4x, na.rm=TRUE)]
out = out[, .(yr, cfanorth, cfasouth, cfa4x)]
names(out) = c("Year", "NENS", "SENS", "4X")
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))


jae0/snowcrab documentation built on Nov. 6, 2024, 10:13 p.m.