The provision of stock assessment advice requires

• The assessment of stock status relative to reference points,
• The prediction of the response of a stock to management,
  
• Checking that predictions are consistent with reality.

The tRFMOs share a common advice framework, with two main tools

Phase Plot

To summarise current status relevant to reference points

Strategy Matrix

To allow managers to choose options that will meet their objectives, such as setting a TAC to recover an overfished stock and to prevent overfishing.

The biggest form of uncertainty is the difference between models and reality.

The five main types of error

• Estimation arising when estimating parameters of the models used in the assessment procedure
• Model related to the ability of the model structure to capture the core system dynamics
• Process caused by disregarding variability, temporal and spatial, in dynamic population and fisheries processes
• Observation sampling and measurement error
• Implementation where the management plan is not fully executed as intended

Main forms of Stock Assessment Error

• Estimation Error in model parameters
• Model Error does the model structure capture the core system dynamics

Model uncertainty can further be sub-divided into

• Structural Uncertainty due to inadequate models, incomplete or competing conceptual frameworks, or where significant processes or relationships are wrongly specified or not considered.
• Value Uncertainty due to missing or inaccurate data or poorly known parameters.

Based on SCRS Paper

kobe R package

install.packages("kobe")

library(kobe)

Vignette

Provides a overview of the package and examples

??kobe

https://cran.r-project.org/web/packages/kobe/index.html

Analysis/vpa
├── east
│   ├── inflated
│   │   ├── high
│   │   ├── low
│   │   └── med
│   └── reported
│       ├── high
│       ├── low
│       └── med
└── west
    └── cont
        ├── 2line
        └── bevholt

13 directories

Projections and estimates of stock status relative to reference

Output files

BENCH-1.OUT
BENCH-1.STA

SSBIO-1.OUT

Read using kobe

dirVPA="/home/laurie/ownCloud/GVYP_VPA/BFTAss"

rep.med=kobe.2box(file.path(dirVPA,"Analysis/vpa/east/reported/med"))
rep.med=transform(rep.med,year=year+1949)

Sanity check

colnames(rep.med)

[1] "tac"     "iter"    "f0.1"    "ssb0.1"  "year"    "stock"   "harvest"

     tac      2014      2015      2016      2017      2018       2019
1      0 0.3686314 0.3268398 0.2725608 0.1983017 0.1173826 0.06043956
2   2000 0.3686314 0.3273393 0.2742258 0.2027972 0.1233766 0.06376956
3   4000 0.3686314 0.3280053 0.2772228 0.2074592 0.1292041 0.06943057
4   6000 0.3686314 0.3283383 0.2792208 0.2136197 0.1360306 0.07492507
5   8000 0.3686314 0.3286713 0.2802198 0.2152847 0.1430236 0.08108558
6  10000 0.3686314 0.3290043 0.2822178 0.2194472 0.1478521 0.08691309
7  12000 0.3686314 0.3293373 0.2855478 0.2242757 0.1541792 0.09257409
8  13500 0.3686314 0.3296703 0.2872128 0.2269397 0.1600067 0.09706960
9  14000 0.3686314 0.3296703 0.2873793 0.2277722 0.1616717 0.09890110
10 15000 0.3686314 0.3298368 0.2878788 0.2299367 0.1648352 0.10123210
11 16000 0.3686314 0.3300033 0.2893773 0.2321012 0.1674992 0.10572761
12 18000 0.3686314 0.3311688 0.2915418 0.2364302 0.1751582 0.11255411
13 20000 0.3686314 0.3320013 0.2943723 0.2405927 0.1798202 0.12154512
14 22000 0.3686314 0.3325008 0.2968698 0.2452547 0.1844822 0.12770563
15 24000 0.3686314 0.3333333 0.2993673 0.2482517 0.1909757 0.13536464
16 26000 0.3686314 0.3334998 0.3011988 0.2515818 0.1981352 0.14285714
17 28000 0.3686314 0.3339993 0.3031968 0.2554113 0.2061272 0.15118215
18 30000 0.3686314 0.3348318 0.3053613 0.2600733 0.2124542 0.15900766
         2020        2021        2022        2023         2024
1  0.02480852 0.008325008 0.003496503 0.001498501 0.0011655012
2  0.02797203 0.009657010 0.003496503 0.001332001 0.0008325008
3  0.03296703 0.012154512 0.003996004 0.001665002 0.0008325008
4  0.03546454 0.014485514 0.005494505 0.002664003 0.0011655012
5  0.04045954 0.018148518 0.006493506 0.003163503 0.0013320013
6  0.04612055 0.020979021 0.008491508 0.003496503 0.0016650017
7  0.05211455 0.024142524 0.010989011 0.004329004 0.0019980020
8  0.05627706 0.027472527 0.012654013 0.005494505 0.0026640027
9  0.05744256 0.028305028 0.013153513 0.005494505 0.0026640027
10 0.06077256 0.030136530 0.014818515 0.006327006 0.0028305028
11 0.06260406 0.033466533 0.016150516 0.007492507 0.0034965035
12 0.06959707 0.037962038 0.019147519 0.008824509 0.0046620047
13 0.07525808 0.043956044 0.022977023 0.010489510 0.0061605062
14 0.08225108 0.051781552 0.027805528 0.014985015 0.0076590077
15 0.09057609 0.058608059 0.034965035 0.019480519 0.0089910090
16 0.10073260 0.064269064 0.039627040 0.023143523 0.0124875125
17 0.10789211 0.071928072 0.046120546 0.028138528 0.0186480186
18 0.11588412 0.080419580 0.053946054 0.033799534 0.0226440226
           2025
1  0.0011655012
2  0.0008325008
3  0.0008325008
4  0.0009990010
5  0.0009990010
6  0.0009990010
7  0.0011655012
8  0.0014985015
9  0.0016650017
10 0.0019980020
11 0.0019980020
12 0.0023310023
13 0.0033300033
14 0.0038295038
15 0.0049950050
16 0.0069930070
17 0.0099900100
18 0.0146520147

     tac 2014         2015         2016         2017         2018
1      0    0 0.0000000000 0.0000000000 0.0000000000 0.0000000000
2   2000    0 0.0000000000 0.0000000000 0.0000000000 0.0000000000
3   4000    0 0.0000000000 0.0000000000 0.0000000000 0.0000000000
4   6000    0 0.0000000000 0.0000000000 0.0000000000 0.0000000000
5   8000    0 0.0000000000 0.0000000000 0.0000000000 0.0000000000
6  10000    0 0.0000000000 0.0000000000 0.0000000000 0.0000000000
7  12000    0 0.0000000000 0.0000000000 0.0000000000 0.0000000000
8  13500    0 0.0000000000 0.0000000000 0.0000000000 0.0000000000
9  14000    0 0.0000000000 0.0000000000 0.0000000000 0.0000000000
10 15000    0 0.0000000000 0.0000000000 0.0000000000 0.0000000000
11 16000    0 0.0000000000 0.0000000000 0.0000000000 0.0000000000
12 18000    0 0.0000000000 0.0000000000 0.0000000000 0.0000000000
13 20000    0 0.0000000000 0.0000000000 0.0000000000 0.0000000000
14 22000    0 0.0000000000 0.0000000000 0.0000000000 0.0000000000
15 24000    0 0.0000000000 0.0000000000 0.0000000000 0.0000000000
16 26000    0 0.0003330003 0.0001665002 0.0001665002 0.0000000000
17 28000    0 0.0008325008 0.0004995005 0.0003330003 0.0001665002
18 30000    0 0.0041625042 0.0019980020 0.0011655012 0.0009990010
           2019         2020         2021         2022         2023
1  0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
2  0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
3  0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
4  0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
5  0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
6  0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
7  0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
8  0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
9  0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
10 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
11 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
12 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
13 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
14 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
15 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
16 0.0000000000 0.0000000000 0.0000000000 0.0000000000 0.0000000000
17 0.0001665002 0.0001665002 0.0003330003 0.0004995005 0.0006660007
18 0.0009990010 0.0011655012 0.0021645022 0.0026640027 0.0038295038
           2024         2025
1  0.0000000000 0.0000000000
2  0.0000000000 0.0000000000
3  0.0000000000 0.0000000000
4  0.0000000000 0.0000000000
5  0.0000000000 0.0000000000
6  0.0000000000 0.0000000000
7  0.0000000000 0.0000000000
8  0.0000000000 0.0000000000
9  0.0000000000 0.0000000000
10 0.0000000000 0.0000000000
11 0.0000000000 0.0000000000
12 0.0000000000 0.0000000000
13 0.0000000000 0.0000000000
14 0.0000000000 0.0000000000
15 0.0000000000 0.0000000000
16 0.0000000000 0.0001665002
17 0.0008325008 0.0011655012
18 0.0053280053 0.0066600067

     tac      2014      2015      2016      2017      2018      2019
1      0 0.6313686 0.6731602 0.7274392 0.8016983 0.8826174 0.9395604
2   2000 0.6313686 0.6726607 0.7257742 0.7972028 0.8766234 0.9362304
3   4000 0.6313686 0.6719947 0.7227772 0.7925408 0.8707959 0.9305694
4   6000 0.6313686 0.6716617 0.7207792 0.7863803 0.8639694 0.9250749
5   8000 0.6313686 0.6713287 0.7197802 0.7847153 0.8569764 0.9189144
6  10000 0.6313686 0.6709957 0.7177822 0.7805528 0.8521479 0.9130869
7  12000 0.6313686 0.6706627 0.7144522 0.7757243 0.8458208 0.9074259
8  13500 0.6313686 0.6703297 0.7127872 0.7730603 0.8399933 0.9029304
9  14000 0.6313686 0.6703297 0.7126207 0.7722278 0.8383283 0.9010989
10 15000 0.6313686 0.6701632 0.7121212 0.7700633 0.8351648 0.8987679
11 16000 0.6313686 0.6699967 0.7106227 0.7678988 0.8325008 0.8942724
12 18000 0.6313686 0.6688312 0.7084582 0.7635698 0.8248418 0.8874459
13 20000 0.6313686 0.6679987 0.7056277 0.7594073 0.8201798 0.8784549
14 22000 0.6313686 0.6674992 0.7031302 0.7547453 0.8155178 0.8722944
15 24000 0.6313686 0.6666667 0.7006327 0.7517483 0.8090243 0.8646354
16 26000 0.6313686 0.6663337 0.6986347 0.7482517 0.8018648 0.8571429
17 28000 0.6313686 0.6656677 0.6964702 0.7444222 0.7937063 0.8486513
18 30000 0.6313686 0.6626707 0.6934732 0.7390942 0.7867133 0.8401598
        2020      2021      2022      2023      2024      2025
1  0.9751915 0.9916750 0.9965035 0.9985015 0.9988345 0.9988345
2  0.9720280 0.9903430 0.9965035 0.9986680 0.9991675 0.9991675
3  0.9670330 0.9878455 0.9960040 0.9983350 0.9991675 0.9991675
4  0.9645355 0.9855145 0.9945055 0.9973360 0.9988345 0.9990010
5  0.9595405 0.9818515 0.9935065 0.9968365 0.9986680 0.9990010
6  0.9538795 0.9790210 0.9915085 0.9965035 0.9983350 0.9990010
7  0.9478854 0.9758575 0.9890110 0.9956710 0.9980020 0.9988345
8  0.9437229 0.9725275 0.9873460 0.9945055 0.9973360 0.9985015
9  0.9425574 0.9716950 0.9868465 0.9945055 0.9973360 0.9983350
10 0.9392274 0.9698635 0.9851815 0.9936730 0.9971695 0.9980020
11 0.9373959 0.9665335 0.9838495 0.9925075 0.9965035 0.9980020
12 0.9304029 0.9620380 0.9808525 0.9911755 0.9953380 0.9976690
13 0.9247419 0.9560440 0.9770230 0.9895105 0.9938395 0.9966700
14 0.9177489 0.9482184 0.9721945 0.9850150 0.9923410 0.9961705
15 0.9094239 0.9413919 0.9650350 0.9805195 0.9910090 0.9950050
16 0.8992674 0.9357309 0.9603730 0.9768565 0.9875125 0.9928405
17 0.8919414 0.9277389 0.9533800 0.9711955 0.9805195 0.9888445
18 0.8829504 0.9174159 0.9433899 0.9625375 0.9720280 0.9788545

If you want to recover the stock with 90% chance by 2020 what should the quota be?