R/data.R
TOA_simulations_inputs_1region.Rd1 region simulations of TOA from SPM OM.
data(TOA_simulations_inputs_1region)A list object.
data(TOA_simulations_inputs_1region)
head(realised.catches)
#> [[1]]
#> # A tibble: 594 × 4
#> cell year catch region
#> <chr> <chr> <dbl> <dbl>
#> 1 r10-c5 1998 353. 2
#> 2 r12-c9 1998 76.3 2
#> 3 r5-c11 1998 15987. 1
#> 4 r6-c11 1998 4629. 1
#> 5 r6-c9 1998 1727. 4
#> 6 r7-c11 1998 9744. 1
#> 7 r8-c11 1998 379. 4
#> 8 r8-c7 1998 2362. 4
#> 9 r8-c8 1998 51.7 4
#> 10 r9-c11 1998 3515. 4
#> # … with 584 more rows
#>
#> [[2]]
#> # A tibble: 594 × 4
#> cell year catch region
#> <chr> <chr> <dbl> <dbl>
#> 1 r10-c5 1998 353. 2
#> 2 r12-c9 1998 76.3 2
#> 3 r5-c11 1998 15986. 1
#> 4 r6-c11 1998 4630. 1
#> 5 r6-c9 1998 1727. 4
#> 6 r7-c11 1998 9744. 1
#> 7 r8-c11 1998 379. 4
#> 8 r8-c7 1998 2363. 4
#> 9 r8-c8 1998 51.6 4
#> 10 r9-c11 1998 3514. 4
#> # … with 584 more rows
#>
#> [[3]]
#> # A tibble: 594 × 4
#> cell year catch region
#> <chr> <chr> <dbl> <dbl>
#> 1 r10-c5 1998 353. 2
#> 2 r12-c9 1998 76.3 2
#> 3 r5-c11 1998 15987. 1
#> 4 r6-c11 1998 4629. 1
#> 5 r6-c9 1998 1727. 4
#> 6 r7-c11 1998 9744. 1
#> 7 r8-c11 1998 379. 4
#> 8 r8-c7 1998 2363. 4
#> 9 r8-c8 1998 51.6 4
#> 10 r9-c11 1998 3514. 4
#> # … with 584 more rows
#>
#> [[4]]
#> # A tibble: 594 × 4
#> cell year catch region
#> <chr> <chr> <dbl> <dbl>
#> 1 r10-c5 1998 353. 2
#> 2 r12-c9 1998 76.3 2
#> 3 r5-c11 1998 15986. 1
#> 4 r6-c11 1998 4628. 1
#> 5 r6-c9 1998 1727. 4
#> 6 r7-c11 1998 9744. 1
#> 7 r8-c11 1998 379. 4
#> 8 r8-c7 1998 2362. 4
#> 9 r8-c8 1998 51.6 4
#> 10 r9-c11 1998 3515. 4
#> # … with 584 more rows
#>
#> [[5]]
#> # A tibble: 594 × 4
#> cell year catch region
#> <chr> <chr> <dbl> <dbl>
#> 1 r10-c5 1998 353. 2
#> 2 r12-c9 1998 76.3 2
#> 3 r5-c11 1998 15987. 1
#> 4 r6-c11 1998 4628. 1
#> 5 r6-c9 1998 1727. 4
#> 6 r7-c11 1998 9744. 1
#> 7 r8-c11 1998 379. 4
#> 8 r8-c7 1998 2362. 4
#> 9 r8-c8 1998 51.6 4
#> 10 r9-c11 1998 3515. 4
#> # … with 584 more rows
#>
#> [[6]]
#> # A tibble: 594 × 4
#> cell year catch region
#> <chr> <chr> <dbl> <dbl>
#> 1 r10-c5 1998 353. 2
#> 2 r12-c9 1998 76.3 2
#> 3 r5-c11 1998 15987. 1
#> 4 r6-c11 1998 4629. 1
#> 5 r6-c9 1998 1727. 4
#> 6 r7-c11 1998 9744. 1
#> 7 r8-c11 1998 379. 4
#> 8 r8-c7 1998 2363. 4
#> 9 r8-c8 1998 51.6 4
#> 10 r9-c11 1998 3515. 4
#> # … with 584 more rows
#>
head(realised.tags)
#> [[1]]
#> # A tibble: 464 × 33
#> cell age[2…¹ age[3…² age[4…³ age[5…⁴ age[6…⁵ age[7…⁶ age[8…⁷ age[9…⁸ age[1…⁹
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 r2-c… 0 0 0 0.124 0.314 0.381 0.133 0.0286 0.0190
#> 2 r2-c… 0 0.0909 6.17 39.2 54.8 47.6 22.9 7.39 2.68
#> 3 r2-c… 0 0 0.0520 0.954 2.21 1.96 1.01 0.582 0.147
#> 4 r2-c9 0 0 0.435 0.836 1.10 1.85 1.53 0.714 0.322
#> 5 r4-c9 0 0 0 0.139 0.587 0.788 0.370 0.0694 0.0309
#> 6 r5-c… 0 0 0.617 1.54 0.677 0.657 0.327 0.142 0.0236
#> 7 r5-c9 0 0 0.0267 1.48 3.04 2.61 1.21 0.359 0.203
#> 8 r6-c… 0 0 0 0.0620 0.552 1.34 2.48 2.89 1.90
#> 9 r6-c… 0 0.610 2.59 2.91 1.52 0.971 0.299 0.0341 0.0579
#> 10 r7-c… 0 0 1.41 2.69 1.62 1.13 2.02 2.15 1.69
#> # … with 454 more rows, 23 more variables: `age[11]` <dbl>, `age[12]` <dbl>,
#> # `age[13]` <dbl>, `age[14]` <dbl>, `age[15]` <dbl>, `age[16]` <dbl>,
#> # `age[17]` <dbl>, `age[18]` <dbl>, `age[19]` <dbl>, `age[20]` <dbl>,
#> # `age[21]` <dbl>, `age[22]` <dbl>, `age[23]` <dbl>, `age[24]` <dbl>,
#> # `age[25]` <dbl>, `age[26]` <dbl>, `age[27]` <dbl>, `age[28]` <dbl>,
#> # `age[29]` <dbl>, `age[30]` <dbl>, year <chr>, total <dbl>, region <dbl>,
#> # and abbreviated variable names ¹`age[2]`, ²`age[3]`, ³`age[4]`, …
#>
#> [[2]]
#> # A tibble: 464 × 33
#> cell age[2…¹ age[3…² age[4…³ age[5…⁴ age[6…⁵ age[7…⁶ age[8…⁷ age[9…⁸ age[1…⁹
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 r2-c… 0 0 0 0.124 0.314 0.381 0.133 0.0286 0.0190
#> 2 r2-c… 0 0.0909 6.17 39.2 54.8 47.6 22.9 7.39 2.68
#> 3 r2-c… 0 0 0.0520 0.954 2.21 1.96 1.01 0.582 0.147
#> 4 r2-c9 0 0 0.435 0.836 1.10 1.85 1.53 0.714 0.322
#> 5 r4-c9 0 0 0 0.139 0.587 0.788 0.370 0.0694 0.0309
#> 6 r5-c… 0 0 0.617 1.54 0.677 0.657 0.327 0.142 0.0236
#> 7 r5-c9 0 0 0.0267 1.48 3.04 2.61 1.21 0.359 0.203
#> 8 r6-c… 0 0 0 0.0620 0.552 1.34 2.48 2.89 1.90
#> 9 r6-c… 0 0.610 2.59 2.91 1.52 0.971 0.299 0.0341 0.0579
#> 10 r7-c… 0 0 1.41 2.69 1.62 1.13 2.02 2.15 1.69
#> # … with 454 more rows, 23 more variables: `age[11]` <dbl>, `age[12]` <dbl>,
#> # `age[13]` <dbl>, `age[14]` <dbl>, `age[15]` <dbl>, `age[16]` <dbl>,
#> # `age[17]` <dbl>, `age[18]` <dbl>, `age[19]` <dbl>, `age[20]` <dbl>,
#> # `age[21]` <dbl>, `age[22]` <dbl>, `age[23]` <dbl>, `age[24]` <dbl>,
#> # `age[25]` <dbl>, `age[26]` <dbl>, `age[27]` <dbl>, `age[28]` <dbl>,
#> # `age[29]` <dbl>, `age[30]` <dbl>, year <chr>, total <dbl>, region <dbl>,
#> # and abbreviated variable names ¹`age[2]`, ²`age[3]`, ³`age[4]`, …
#>
#> [[3]]
#> # A tibble: 464 × 33
#> cell age[2…¹ age[3…² age[4…³ age[5…⁴ age[6…⁵ age[7…⁶ age[8…⁷ age[9…⁸ age[1…⁹
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 r2-c… 0 0 0 0.124 0.314 0.381 0.133 0.0286 0.0190
#> 2 r2-c… 0 0.0909 6.17 39.2 54.8 47.6 22.9 7.39 2.68
#> 3 r2-c… 0 0 0.0520 0.954 2.21 1.96 1.01 0.582 0.147
#> 4 r2-c9 0 0 0.435 0.836 1.10 1.85 1.53 0.714 0.322
#> 5 r4-c9 0 0 0 0.139 0.587 0.788 0.370 0.0694 0.0309
#> 6 r5-c… 0 0 0.617 1.54 0.677 0.657 0.327 0.142 0.0236
#> 7 r5-c9 0 0 0.0267 1.48 3.04 2.61 1.21 0.359 0.203
#> 8 r6-c… 0 0 0 0.0620 0.552 1.34 2.48 2.89 1.90
#> 9 r6-c… 0 0.610 2.59 2.91 1.52 0.971 0.299 0.0341 0.0579
#> 10 r7-c… 0 0 1.41 2.69 1.62 1.13 2.02 2.15 1.69
#> # … with 454 more rows, 23 more variables: `age[11]` <dbl>, `age[12]` <dbl>,
#> # `age[13]` <dbl>, `age[14]` <dbl>, `age[15]` <dbl>, `age[16]` <dbl>,
#> # `age[17]` <dbl>, `age[18]` <dbl>, `age[19]` <dbl>, `age[20]` <dbl>,
#> # `age[21]` <dbl>, `age[22]` <dbl>, `age[23]` <dbl>, `age[24]` <dbl>,
#> # `age[25]` <dbl>, `age[26]` <dbl>, `age[27]` <dbl>, `age[28]` <dbl>,
#> # `age[29]` <dbl>, `age[30]` <dbl>, year <chr>, total <dbl>, region <dbl>,
#> # and abbreviated variable names ¹`age[2]`, ²`age[3]`, ³`age[4]`, …
#>
#> [[4]]
#> # A tibble: 464 × 33
#> cell age[2…¹ age[3…² age[4…³ age[5…⁴ age[6…⁵ age[7…⁶ age[8…⁷ age[9…⁸ age[1…⁹
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 r2-c… 0 0 0 0.124 0.314 0.381 0.133 0.0286 0.0190
#> 2 r2-c… 0 0.0909 6.17 39.2 54.8 47.6 22.9 7.39 2.68
#> 3 r2-c… 0 0 0.0520 0.954 2.21 1.96 1.01 0.582 0.147
#> 4 r2-c9 0 0 0.435 0.836 1.10 1.85 1.53 0.714 0.322
#> 5 r4-c9 0 0 0 0.139 0.587 0.788 0.370 0.0694 0.0309
#> 6 r5-c… 0 0 0.617 1.54 0.677 0.657 0.327 0.142 0.0236
#> 7 r5-c9 0 0 0.0267 1.48 3.04 2.61 1.21 0.359 0.203
#> 8 r6-c… 0 0 0 0.0620 0.552 1.34 2.48 2.89 1.90
#> 9 r6-c… 0 0.610 2.59 2.91 1.52 0.971 0.299 0.0341 0.0579
#> 10 r7-c… 0 0 1.41 2.69 1.62 1.13 2.02 2.15 1.69
#> # … with 454 more rows, 23 more variables: `age[11]` <dbl>, `age[12]` <dbl>,
#> # `age[13]` <dbl>, `age[14]` <dbl>, `age[15]` <dbl>, `age[16]` <dbl>,
#> # `age[17]` <dbl>, `age[18]` <dbl>, `age[19]` <dbl>, `age[20]` <dbl>,
#> # `age[21]` <dbl>, `age[22]` <dbl>, `age[23]` <dbl>, `age[24]` <dbl>,
#> # `age[25]` <dbl>, `age[26]` <dbl>, `age[27]` <dbl>, `age[28]` <dbl>,
#> # `age[29]` <dbl>, `age[30]` <dbl>, year <chr>, total <dbl>, region <dbl>,
#> # and abbreviated variable names ¹`age[2]`, ²`age[3]`, ³`age[4]`, …
#>
#> [[5]]
#> # A tibble: 464 × 33
#> cell age[2…¹ age[3…² age[4…³ age[5…⁴ age[6…⁵ age[7…⁶ age[8…⁷ age[9…⁸ age[1…⁹
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 r2-c… 0 0 0 0.124 0.314 0.381 0.133 0.0286 0.0190
#> 2 r2-c… 0 0.0909 6.17 39.2 54.8 47.6 22.9 7.39 2.68
#> 3 r2-c… 0 0 0.0520 0.954 2.21 1.96 1.01 0.582 0.147
#> 4 r2-c9 0 0 0.435 0.836 1.10 1.85 1.53 0.714 0.322
#> 5 r4-c9 0 0 0 0.139 0.587 0.788 0.370 0.0694 0.0309
#> 6 r5-c… 0 0 0.617 1.54 0.677 0.657 0.327 0.142 0.0236
#> 7 r5-c9 0 0 0.0267 1.48 3.04 2.61 1.21 0.359 0.203
#> 8 r6-c… 0 0 0 0.0620 0.552 1.34 2.48 2.89 1.90
#> 9 r6-c… 0 0.610 2.59 2.91 1.52 0.971 0.299 0.0341 0.0579
#> 10 r7-c… 0 0 1.41 2.69 1.62 1.13 2.02 2.15 1.69
#> # … with 454 more rows, 23 more variables: `age[11]` <dbl>, `age[12]` <dbl>,
#> # `age[13]` <dbl>, `age[14]` <dbl>, `age[15]` <dbl>, `age[16]` <dbl>,
#> # `age[17]` <dbl>, `age[18]` <dbl>, `age[19]` <dbl>, `age[20]` <dbl>,
#> # `age[21]` <dbl>, `age[22]` <dbl>, `age[23]` <dbl>, `age[24]` <dbl>,
#> # `age[25]` <dbl>, `age[26]` <dbl>, `age[27]` <dbl>, `age[28]` <dbl>,
#> # `age[29]` <dbl>, `age[30]` <dbl>, year <chr>, total <dbl>, region <dbl>,
#> # and abbreviated variable names ¹`age[2]`, ²`age[3]`, ³`age[4]`, …
#>
#> [[6]]
#> # A tibble: 464 × 33
#> cell age[2…¹ age[3…² age[4…³ age[5…⁴ age[6…⁵ age[7…⁶ age[8…⁷ age[9…⁸ age[1…⁹
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 r2-c… 0 0 0 0.124 0.314 0.381 0.133 0.0286 0.0190
#> 2 r2-c… 0 0.0909 6.17 39.2 54.8 47.6 22.9 7.39 2.68
#> 3 r2-c… 0 0 0.0520 0.954 2.21 1.96 1.01 0.582 0.147
#> 4 r2-c9 0 0 0.435 0.836 1.10 1.85 1.53 0.714 0.322
#> 5 r4-c9 0 0 0 0.139 0.587 0.788 0.370 0.0694 0.0309
#> 6 r5-c… 0 0 0.617 1.54 0.677 0.657 0.327 0.142 0.0236
#> 7 r5-c9 0 0 0.0267 1.48 3.04 2.61 1.21 0.359 0.203
#> 8 r6-c… 0 0 0 0.0620 0.552 1.34 2.48 2.89 1.90
#> 9 r6-c… 0 0.610 2.59 2.91 1.52 0.971 0.299 0.0341 0.0579
#> 10 r7-c… 0 0 1.41 2.69 1.62 1.13 2.02 2.15 1.69
#> # … with 454 more rows, 23 more variables: `age[11]` <dbl>, `age[12]` <dbl>,
#> # `age[13]` <dbl>, `age[14]` <dbl>, `age[15]` <dbl>, `age[16]` <dbl>,
#> # `age[17]` <dbl>, `age[18]` <dbl>, `age[19]` <dbl>, `age[20]` <dbl>,
#> # `age[21]` <dbl>, `age[22]` <dbl>, `age[23]` <dbl>, `age[24]` <dbl>,
#> # `age[25]` <dbl>, `age[26]` <dbl>, `age[27]` <dbl>, `age[28]` <dbl>,
#> # `age[29]` <dbl>, `age[30]` <dbl>, year <chr>, total <dbl>, region <dbl>,
#> # and abbreviated variable names ¹`age[2]`, ²`age[3]`, ³`age[4]`, …
#>