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 database.
The data are downloaded using the DATRAS
package which can be installed using:
install.packages('DATRAS',repos='http://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.
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
## 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).
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
).
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.
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")
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