Utility functions for the Stox Project. R package, updated 2021-10-11.

This package contains utility functions for the Institute of Marine Research's (IMR) Stox Project. The package has two purposes: 1) To function as a showcase and developmental platform for functions that may be included in the future releases of the Stox Project. 2) To provide a collection of functions needed in the internal workflow of the Deep-sea species group at IMR.

The package requires RstoxData Stox project packages to function. These packages can be installed by following the links for each package or using the devtools package. The RstoxUtils package can be installed using devtools once all Stox project packages are installed correctly.

devtools::install_github("MikkoVihtakari/RstoxUtils", upgrade = "never")

The RstoxUtils uses multiple GIS packages developed for R. You may have to update these (Packages -> Update -> Select all -> Install updates in R Studio).

If the installation of a dependency fails, try installing those packages manually (using RStudio or install.packages).

Each numbered section below demonstrates a separate functionality in the RstoxUtils package.

The IMR database data are distributed as .xml files of a certain structure. The RstoxData::readXmlFile function reads these files, but due to the data architecture, information is spread across multiple data frames in the standard format. The RstoxUtils::processBioticFile function combines the data in station-based (stnall element in the list architecture) and individual fish-based (indall) formats. The RstoxUtils::processBioticFiles function does the same for multiple .xml files.

xml.example <- system.file("extdata", "example.xml", package = "RstoxUtils")

standard.format <- RstoxData::readXmlFile(xml.example)

## The data are as a list organized under multiple data.frames
names(standard.format)
#>  [1] "missions"                       "mission"                       
#>  [3] "fishstation"                    "catchsample"                   
#>  [5] "individual"                     "prey"                          
#>  [7] "agedetermination"               "preylengthfrequencytable"      
#>  [9] "copepodedevstagefrequencytable" "tag"                           
#> [11] "metadata"
## Station-based data are organized under 3 data frames
dim(standard.format$mission)
#> [1]  6 11
dim(standard.format$fishstation)
#> [1] 59 74
dim(standard.format$catchsample)
#> [1] 84 36
## Individual-based data have 2 additional data frames
dim(standard.format$individual)
#> [1] 446  56
dim(standard.format$agedetermination)
#> [1] 52 39
## The user has to merge these data frames to work with the data
## RstoxUtils addresses this issue and merges the data

library(RstoxUtils)

Utils.format <- RstoxUtils::processBioticFile(xml.example)

## Station-based data can now be found from 1 data frame

dim(Utils.format$stnall)
#> [1] 84 56
## The same applies for individual-based-data 
dim(Utils.format$indall)
#> [1] 498  64
## The uniting ID tags in the Utils format are
# missionid, startyear, serialno, catchsampleid and sometimes cruise for station based format
# The abovementioned and specimenid

NOTE: The RstoxUtils::processBioticFile function have not been modified to use the improvements made to the 0.6.3 version of the RstoxData::readXmlFile function yet. The modifications will make the processBioticFile quicker as some corrections from this function were implemented in the master function. Also, the ID tags have not been proofed yet. This note will disappear once the fixes have been made.

Moved to the RstoxStrata package.

The detailed electronic logbook data can be read using the extractLogbook() function. These data are confidential and require a special access to the folder on the server where they are located. If you need such access (and work at IMR), take contact with the data people at your group. Those who have the access, know where the data are located. The path argument should point to the folder of interest on the server (elFangstdagbok_detaljert for all data). The path can be defined on Mac (and Linux) as path = "/Volumes/.../elFangstdagbok_detaljert" and as path = Q:/.../elFangstdagbok_detaljert on Windows, where ... represents the entire folder path that cannot be shown here. You can copy the folder location as path to your clip-board and past it the extractLogbook() function. Remember to use quotes (i.e. " ").

The function is slow especially in Tromsø (prepare for 30 min to 1 h). It filters species out of the logbook data based on codes listed in the table under. For example, all Atlantic halibut can be extracted as follows:

extractLogbook(path, species = "HAL")

Or as:

extractLogbook(path, species = 2311) # Excluding farmed fish

The species name will be returned in Norwegian, English or Latin depending on the language argument.

Gear names are translated based on the table under:

The codes have been extracted from the Norwegian Directorate of Fisheries website.

Any contributions to the package are more than welcome. Please contact the package creator Mikko Vihtakari ([email protected]) to discuss your ideas on improving the package or place a request in the issues section.

2021-10-11 Strata making scripts moved to a separate package.

2020-05-19 Added logbook data extraction.

2019-12-16 The first version of the package online. Bugged as life, but available. Please excuse me for not having double-checked all references to other people's work. The references will come in future releases.