cod-2532.Rmd

---
title: "Using s6model to assess the status of Eastern Baltic cod (cod-2532)"
author: "Alexandros Kokkalis"
date: "`r Sys.Date()`"
output: 
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    fig_caption: yes
# bibliography: bib.bibtex
vignette: >
  %\VignetteIndexEntry{Using s6model to assess the status of Eastern Baltic cod (cod-2532)}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

## Introduction

The Eastern Baltic cod (_Gadus morhua_) is assessed in this example using only survey data from the BITS survey. The data can be downloaded from the [DATRAS](http:https://datras.ices.dk) database. 

## Downloading and pre-processing of the data

The data are downloaded using the `DATRAS` package which can be installed using:
```{r, eval=FALSE, echo = TRUE}
install.packages('DATRAS',repos='http:https://www.rforge.net/',type='source')
```

The package contains functions to download, read and subset survey data. Shape files for ICES regions can be downloaded from [ICES spatial facility](http:https://geo.ices.dk/).

```{r, echo = TRUE, eval = FALSE}
library(DATRAS)
## Download the survey data for the years 1991 to 2014
downloadExchange("BITS", 1991:2014)
## Read in all data
bits <- readExchangeDir()
## Select only cod
ebcod <- subset(bits, Species == "Gadus morhua")
```

Select only the relevant areas for the Eastern Baltic cod
```{r, echo=TRUE, eval = FALSE}
## Add area information
ebcod <- addSpatialData(ebcod, shape = "ices_areas.shp")
ebcod <- subset(ebcod, ICES_area %in% c("25", "26", "27", "28-1", 
                                        "28-2", "29", "30", "31", "32"))
```

Then using the `s6model` package we can extract the yearly weight frequencies using the function `getDFYears`. This function extracts the length distributions from an object of class `DATRASraw`, fits the weight length relationship, transforms the length to weight and returns a `list` of `data.frames`, one for each year. The bin size is set to 100 g (`binsize` argument) and the weight-length relationship is fitted using weight and length data in the survey for each year (`estWL` argument).
```{r, echo = TRUE, eval = FALSE}
library(s6model)
ebcoddat <- getDfYears(ebcod, binsize = 100, estWL = TRUE)
```

Now the data are in a format that can be used to assess the stock status. The data are provided with the package (saved as `ebcoddat`).

## Assessment of the stock

Now the data are in the correct format the assessment can be done using the `makeAssessment` function. It has many arguments and only a subset of them are presented here. There are default values for most of them, so that a preliminary assessment can be done using `makeAssessment(dat)`, where `dat` has the data in the correct format. The results are saved after a successful run of the function so that they can accessed at a later point to make plots and reports.

Since it is an assessment using only survey data, we are using `isSurvey = TRUE` and we make the assumption that all sizes are selected by the gear by setting the relative selectivity parameter ($\eta_S$, argument `eta_S`) of the gear very small.
```{r, echo = TRUE, eval = FALSE}
res <- makeAssessment(ebcoddat, fnout = NULL, isSurvey = TRUE, nsample = 10, eta_S = 1e-10, a.mean = 0.5, a.sd = 0.2)
plot(res, addMedian = TRUE, ylim = c(1/40,40), log = "y")
addIces("cod-2532")
```