In commfish/scallopr: Analyze ADF&G weathervane scallop survey data

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%",
  eval = FALSE
)

scallopr

The goal of scallopr is to provide a suite of functions for analyzing ADF&G weathervane scallop survey data.

Installation

You can install the released version of scallopr from the commercial fisheries github site with:

# install.packages("devtools")
devtools::install_github("commfish/scallopr")

Example

This is a basic example which shows how to setup and run each function independently. Note that this is based around using an R-project format that has the following folder structure:

data
figs
output
analysis
text

library(scallopr)
theme_set(FNGr::theme_sleek())

# Constants for 2019 survey ----
YEAR <- 2019
Q <- 0.83

# data ----
events_data <- read_csv(paste0('data/', YEAR, '/HaulTableData_Cruise1901.csv')) 
catch_data <- read_csv(paste0('data/', YEAR, '/CatchTableData_Cruise1901.csv'))
awl_data <- read_csv(paste0('data/', YEAR, '/ScalMeatTableData_Cruise1901.csv'))
shell_data <- read_csv(paste0('data/', YEAR, '/ScalShellTableData_Cruise1901.csv'))
set.seed(8456)

# clean data ----
tows <- clean_tow(events_data)
beds <- clean_bed(tows)
scal_catch <- clean_catch(catch_data, tows, YEAR)
scal_awl <- clean_awl(awl_data, tows)

# table of catch results
tbl_catch <- tbl_catch(scal_catch, beds)
abund_est <- scallop_est(scal_catch, beds, Q = Q, abundance = TRUE, boot = TRUE)
biom_est <- scallop_est(scal_catch, beds, Q = Q, abundance = TRUE, boot = TRUE)
meat_wt_est(scal_awl, scal_catch, Q = Q, beds, boot = TRUE)
tbl_sex(scal_awl, tows)
tbl_worm(scal_awl, tows)
tbl_gonad(scal_awl, tows)


# figures ----
plot_catch_rate(scal_catch, tows, YEAR)

# Function for plotting abundance (abundance = TRUE) or biomass estimates
plot_scal_est(abund_est, abundance = TRUE, YEAR)
plot_scal_est(biom_est, abundance = FALSE, YEAR)

plot_size_dist(scal_awl, scal_catch, tows, YEAR)
plot_mw_rw(scal_awl, tows, Districts, YEAR)
plot_mw_sh(scal_awl, tows, Districts, YEAR)