In pacific-hake/hakedataUSA: Extract USA Data for Pacific Hake

Please do NOT share this document given that information summarized in at least one of the included figures shows summary statistics for groups containing less than three vessels.

Data from NORPAC is used to calculate monthly, fishery-specific bycatch rates for each year (Figure \@ref(fig:catch-rates)). These are used to extrapolate the amount of bycatch there might have been in unsampled tows of Pacific Hake. The hypothesized amount of bycatch is then subtracted from the total weight of the unsampled tow to generate a total weight of Pacific Hake.

library(dplyr)
library(devtools)
load_all()
options(scipen = 999)
knitr::opts_chunk$set(
  echo = FALSE, results = "hide", cache = TRUE,
  message = FALSE, error = FALSE, warning = FALSE
)
load("../hake-assessment/data/extractedData/norpac_catch.Rdat")
species <- 206
current_year <- as.numeric(format(Sys.Date(), "%Y")) - 1

ncatch_formatted <- ncatch %>%
  dplyr::mutate(
    Date = f_date(RETRIEVAL_DATE, format = "%Y-%m-%d"),
    month = f_date(RETRIEVAL_DATE, format = "%m"),
    Month = f_date(RETRIEVAL_DATE, format = "%b", factor = TRUE),
    year = f_date(RETRIEVAL_DATE, "%Y"),
    # Create catch rate in mt/hr
    crate = EXTRAPOLATED_WEIGHT / 1000 / HRS,
    FISHING_DEPTH_M = FISHING_DEPTH_FATHOMS * fathom_to_meter,
    BOTTOM_DEPTH_M = BOTTOM_DEPTH_FATHOMS * fathom_to_meter,
    vesseltype = f_vessel_type(VESSEL_TYPE),
    Sector = "DomesticAtSea",
    sampled = ifelse(is.na(HAUL_SAMPLED_BY) | HAUL_SAMPLED_BY == 0, 0, 1),
    # Unsampled hauls will have a SPECIES == NA and EXTRAPOLATED_WEIGHT == NA
    SPECIES = ifelse(sampled == 0, species, SPECIES),
    OFFICIAL_TOTAL_CATCHkg = OFFICIAL_TOTAL_CATCH * 1000,
    # ByCatch (kg)
    ByCatch = OFFICIAL_TOTAL_CATCHkg - EXTRAPOLATED_WEIGHT
  )

entries_dont_match <- ncatch_formatted %>%
  dplyr::group_by(VESSEL, Date, HAUL, year, month, vesseltype) %>%
  dplyr::summarize(
    sum = sum(EXTRAPOLATED_WEIGHT),
    total = unique(OFFICIAL_TOTAL_CATCH) * 1000,
    diff = total - sum
  ) %>%
  dplyr::filter(abs(diff) > 0.1)

catch_rates <- ncatch_formatted %>%
  dplyr::filter(
    SPECIES == species,
    sampled == 1
  ) %>%
  dplyr::group_by(vesseltype, VESSEL, HAUL, HAUL_DATE, CRUISE, PERMIT) %>%
  dplyr::mutate(
    bycatch_kg = OFFICIAL_TOTAL_CATCH * 1000 - EXTRAPOLATED_WEIGHT
  ) %>%
  dplyr::group_by(year, month, vesseltype) %>%
  dplyr::summarize(
    bycatch_kg = sum(bycatch_kg),
    OFFICIAL_TOTAL_CATCHkg = sum(OFFICIAL_TOTAL_CATCH) * 1000,
    bycatchrate = bycatch_kg / OFFICIAL_TOTAL_CATCHkg
  ) %>%
  dplyr::full_join(
    ncatch_formatted %>%
      dplyr::filter(sampled == 0, OFFICIAL_TOTAL_CATCH > 0) %>%
      dplyr::group_by(year, month, vesseltype) %>%
      dplyr::summarize(
        n = n(),
        unsampled_mt = sum(OFFICIAL_TOTAL_CATCH)
      ),
    by = c("year", "month", "vesseltype")
  )

ncatch_bycatch <- dplyr::full_join(
  ncatch_formatted %>%
    dplyr::filter(SPECIES == species, sampled == 1) %>%
    dplyr::group_by(year, month, vesseltype) %>%
    dplyr::summarize(
      catch_sampled = sum(EXTRAPOLATED_WEIGHT, na.rm = TRUE),
      catch_bycatch = sum(OFFICIAL_TOTAL_CATCH * 1000 - EXTRAPOLATED_WEIGHT, na.rm = TRUE)
    ),
  ncatch_formatted %>%
    dplyr::group_by(year, month, vesseltype) %>%
    dplyr::filter(SPECIES != species, sampled == 1) %>%
    dplyr::summarize(
      catch_bycatch_other = sum(EXTRAPOLATED_WEIGHT)
    ),
  by = c("year", "month", "vesseltype")
) %>%
  dplyr::mutate(
    bycatchrate = catch_bycatch / catch_sampled,
    test = catch_bycatch - catch_bycatch_other,
    sampled = 0
  )
test <- dplyr::left_join(
  ncatch_formatted,
  ncatch_bycatch,
  by = c("year", "month", "vesseltype", "sampled")
)

In r current_year, the total landings (mt) brought on board and NOT sampled was estimated to sum to r dplyr::filter(catch_rates, year == current_year, vesseltype == "CP") %>% dplyr::pull(unsampled_mt) %>% sum(na.rm = TRUE) and r dplyr::filter(catch_rates, year == current_year, vesseltype == "MS") %>% dplyr::pull(unsampled_mt) %>% sum(na.rm = TRUE) (mt) for Catcher-Processors and Motherships, respectively. The total landings of Pacific Hake in the Catcher-Processor fleet for r current_year was estimated to be 126,247.03 (mt). The total landings of Pacific Hake in the Mothership fleet for r current_year was estimated to be 59,152.31 (mt). Which, makes for r round(126247.03/126287*100, 2) and r round(59152.31/89144*100, 2) percent attainment, respectively. These estimates are known to be different than the information provided in the Commercial At-Sea Pacific Whiting Fishery and Shoreside Targeted Whiting Fishery Summary . Approximately, 126,246.74 and 59,157.13 (mt) were landed in by Catcher- Processors and Motherships, respectively.

I found that the estimates of bycatch rates changed depending on how landing of non-target species is calculated. That is, adding EXTRAPOLATED_WEIGHT of non-target species is not the same as subtracting EXTRAPOLATED_WEIGHT of Pacific Hake from the OFFICIAL_TOTAL_CATCH after accounting for differences in units. There are many records where these two numbers do not add up after accounting for what I consider to be rounding errors, i.e., differences of less than 0.1. Beyond not knowing exactly how to calculate the total amount of bycatch in sampled tows, there will always be differences between numbers reported in PacFIN and those reported in the stock assessment because the JTC is using monthly-specific bycatch rates for each vessel type instead of bycatch rates from like tows that are calculated in season.

The goal is to best estimate the amount of Pacific Hake that was removed from U.S. waters and I am uncertain which method accomplishes that. Though it is clear that that amount of bycatch differs by fishery, month, and year (Figures \@ref(fig:catch-rates) and \@ref(fig:total-bycatch)).

```rBycatch (kg) / total catch (kg) by month (x axis), year (panel), and fishery (color). Size of the points indicates the amount of unsampled landings (mt)."} ggplot2::ggplot( data = catch_rates %>% dplyr::filter(vesseltype != 3), ggplot2::aes(x = month, y = bycatchrate, group = vesseltype, colour = vesseltype) ) + ggplot2::geom_point(alpha = .5, ggplot2::aes(size = unsampled_mt)) + ggplot2::geom_line() + ggplot2::facet_wrap("year", scales = "fixed") + ggplot2::theme_bw() + ggplot2::ylab("bycatch (kg) / total catch (kg)")

```rWeight (kg) of bycatch by year (x axis), month (color), and vessel type (panel) in the at-sea fishery."}
ncatch_formatted %>%
  dplyr::filter(SPECIES != species, VESSEL_TYPE != 3, !is.na(EXTRAPOLATED_WEIGHT)) %>%
  dplyr::group_by(year, Month = factor(month), vesseltype) %>%
  dplyr::summarize(EXTRAPOLATED_WEIGHT = sum(EXTRAPOLATED_WEIGHT)) %>%
  ggplot2::ggplot(ggplot2::aes(
    x = year,
    y = EXTRAPOLATED_WEIGHT,
    colour = Month,
    group = Month
  )) +
  ggplot2::geom_line() +
  ggplot2::geom_point() +
  ggplot2::facet_grid(. ~ vesseltype, scales = "fixed") +
  ggplot2::ylab("Extrapolated weight (kg) of sampled bycatch") +
  ggplot2::theme_bw()

pacific-hake/hakedataUSA documentation built on June 2, 2025, 4:05 a.m.