Chapter 3 Data
There are many data resources necessary to run the full bifrost capelin assessment. We will split this data chapter into the data needed for maturity parameter estimation and the consumption.
3.1 Maturity data
For the maturity part of bifrost, we need data from the acoustic survey in the Barents sea, processed by StoX. By running the StoX projects, a file called “2_EstimateByPopulation_Category_Reports_Abundance.txt” is produced. At the bottom of this file, you find the following table (example from 2016 survey):
##
## ______________________________________________________________________________________________________
## Variable: Abundance
## EstLayer: 1
## Stratum: TOTAL
## species: 162035
## ______________________________________________________________________________________________________
## age
## LenGrp 0 1 2 3 4 Number Biomass Mean W
## (1E3) (1E3kg) (g)
## ______________________________________________________________________________________________________
## 7.5-8.0 | 108413 3196550 - - - 3304964 5109.9 1.55
## 8.0-8.5 | - 2217823 - - - 2217823 3783.9 1.71
## 8.5-9.0 | - 2823284 - - - 2823284 5647.8 2.00
## 9.0-9.5 | - 3281410 - - - 3281410 8391.2 2.56
## 9.5-10.0 | - 6291983 - - - 6291983 19246.9 3.06
## 10.0-10.5 | - 3159791 - - - 3159791 11534.3 3.65
## 10.5-11.0 | - 1931237 13811 - - 1945048 8259.7 4.25
## 11.0-11.5 | - 2290788 - - - 2290788 12006.9 5.24
## 11.5-12.0 | - 2248815 82271 - - 2331085 14483.6 6.21
## 12.0-12.5 | - 4699161 357024 - - 5056185 36801.5 7.28
## 12.5-13.0 | - 1340294 268462 - - 1608756 13458.5 8.37
## 13.0-13.5 | - 706850 763254 - - 1470104 14119.9 9.60
## 13.5-14.0 | - 331121 994703 11299 - 1337122 14680.7 10.98
## 14.0-14.5 | - 37247 1871252 169922 - 2078422 28255.4 13.59
## 14.5-15.0 | - 29063 1054995 90411 - 1174470 18218.4 15.51
## 15.0-15.5 | - 10750 1084263 89633 34848 1219495 21461.7 17.60
## 15.5-16.0 | - - 580099 429271 - 1009370 20859.0 20.67
## 16.0-16.5 | - - 629549 420717 74734 1125000 25230.4 22.43
## 16.5-17.0 | - - 170522 310787 8881 490190 12514.5 25.53
## 17.0-17.5 | - - 55086 531150 5792 592027 17443.1 29.46
## 17.5-18.0 | - - 4998 155824 30239 191061 6166.7 32.28
## 18.0-18.5 | - - - 96756 - 96756 3606.3 37.27
## 18.5-19.0 | - - 9115 44474 - 53589 1960.2 36.58
## 19.0-19.5 | - - - 7286 - 7286 324.9 44.59
## ______________________________________________________________________________________________________
## TSN(1000) | 108413 34596168 7939404 2357530 154495 45156010 - -
## TSB(1000 kg) | 128.6 144667.9 115752.5 59107.0 3909.2 - 323565.2 -
## Mean length (cm) | 7.50 10.00 14.23 16.19 16.14 - - -
## Mean weight (g) | 1.19 4.18 14.58 25.07 25.30 - - 7.17
## ______________________________________________________________________________________________________This is the information we have stored in the example data cap for the years 1972-2019, which you can load by running the following code:
data(cap, package = "bifrost")
head(dplyr::filter(cap, year == 2016), n = 10)## length.group 1 2 3 4 5 sum(10e9) biomass(10e3t) meanweight(g) meanlength(cm) year
## 1 1 0.000 0 0 0 0 0.000 0.000 0.0 5.25 2016
## 2 2 0.000 0 0 0 0 0.000 0.000 0.0 5.75 2016
## 3 3 0.000 0 0 0 0 0.000 0.000 0.0 6.25 2016
## 4 4 0.000 0 0 0 0 0.000 0.000 0.0 6.75 2016
## 5 5 0.000 0 0 0 0 0.000 0.000 0.0 7.25 2016
## 6 6 2.753 0 0 0 0 2.753 4.405 1.6 7.75 2016
## 7 7 2.247 0 0 0 0 2.247 3.820 1.7 8.25 2016
## 8 8 3.005 0 0 0 0 3.005 6.010 2.0 8.75 2016
## 9 9 3.501 0 0 0 0 3.501 9.103 2.6 9.25 2016
## 10 10 5.956 0 0 0 0 5.956 17.868 3.0 9.75 2016