MVLN
North Atlantic Blue Shark
L Kell
07 September, 2023
Historical Status
Figure 1. Historical trends in \(SSB/B_{MSY}\) with marginal plot of current status, ribbons show inter-quartiles and \(90_{th}\) percentile, relative to median.
Figure 2. Historical trends in \(F/F_{MSY}\) with marginal plot of current status, ribbons show inter-quartiles and \(90_{th}\) percentile, relative to median.
Current Status
Figure 3. Kobe phase plot for \(SSB/B_{MSY}\) in 2021 and \(F/F_{MSY}\) in 2020
Figure 4. Kobe phase plot for \(SSB/B_{MSY}\) in 2022 and \(F/F_{MSY}\) in 2022
Figure 5. Kobe phase plots for historical and \(F/F_{MSY}\) forecasts, with correlations.
Projections
Figure 6. Recent historical and future trends in \(SSB/B_{MSY}\) and projection for \(F_{MSY}\), marginal plot of status in 2032, ribbons show inter-quartiles and \(90_{th}\) percentile, relative to median.
Figure 7. Recent historical and future trends in \(F/F_{MSY}\) and projection for \(F_{MSY}\), marginal plot of status in 2032, ribbons show inter-quartiles and \(90_{th}\) percentile, relative to median.
Figure 8. Deterministic values of \(SSB/B_{MSY}\) for projections
Figure 9. Deterministic values of \(F/F_{MSY}\) for projections.
Figure 10. Median estimates of \(B/SSB_{MSY}\) for projections.
Figure 11. Median estimates of \(F/SSB_{MSY}\) for projections.
Figure 12. Plot of \(B/SSB_{MSY}\) & \(F/F_{MSY}\) with sample Monte Carlo simulations.
Figure 13. Comparison of MVLN and MCMC historical a trends in \(SSB/B_{MSY}\), ribbons show inter-quartiles and \(90_{th}\) percentile, relative to median.
Figure 14. Comparison of MVLN and MCMC simulations for Kobe Phase Plot of of \(B/SSB_{MSY}\) & \(F/F_{MSY}\).
Figure 15. Kobe phase plots for MCMC, with correlations between years
Table 1. Covariances from SS
Bratio_2020 Bratio_2021 Bratio_2022 F_2020 F_2021 F_2022
Bratio_2020 1.000 0.976 0.93 -0.74 -0.56 0.083
Bratio_2021 0.976 1.000 0.98 -0.78 -0.60 0.093
Bratio_2022 0.926 0.976 1.00 -0.82 -0.63 0.106
F_2020 -0.736 -0.779 -0.82 1.00 0.60 -0.171
F_2021 -0.564 -0.600 -0.63 0.60 1.00 -0.210
F_2022 0.083 0.093 0.11 -0.17 -0.21 1.000Table 2. Covariances simulated by MVLN
Bratio_2020 Bratio_2021 Bratio_2022 F_2020 F_2021 F_2022
Bratio_2020 1.00 0.98 0.93 -0.72 -0.57 -0.48
Bratio_2021 0.98 1.00 0.98 -0.77 -0.61 -0.52
Bratio_2022 0.93 0.98 1.00 -0.81 -0.64 -0.55
F_2020 -0.72 -0.77 -0.81 1.00 0.60 0.55
F_2021 -0.57 -0.61 -0.64 0.60 1.00 0.47
F_2022 -0.48 -0.52 -0.55 0.55 0.47 1.00Table 3. Estimates of \(SSB/B_{MSY}\) and \(F/F_{MSY}\)
$ stock
An object of class "FLQuant"
, , unit = unique, season = all, area = unique
year
quant 2020 2021 2022 2023
all 1.06319 1.05728 1.03286 0.99326
units: NA
$ harvest
An object of class "FLQuant"
, , unit = unique, season = all, area = unique
year
quant 2020 2021 2022 2023
all 0.77501 0.73481 0.75819 0.76533
units: NA Table 4. Summary of MVLN terminal estimates of \(SSB/B_{MSY}\)
iter 2020 2021 2022
1 15% 0.95 0.95 0.92
2 50% 1.06 1.06 1.03Table 5. Summary of MVLN terminal estimates of \(F/F_{MSY}\)
iter 2020 2021 2022
1 35% 0.74 0.70 0.71
2 50% 0.77 0.74 0.76Table 6. Probability of being in green quadrant.
year
Run 2023 2024 2025 2026 2027 2028 2029 2030
0 "47%" "38%" "53%" "67%" "90%" "99%" "100%" "100%"
150 "47%" "37%" "35%" "31%" "43%" "70%" "88%" "95%"
175 "47%" "37%" "32%" "26%" "35%" "59%" "79%" "90%"
200 "47%" "37%" "30%" "22%" "27%" "49%" "68%" "82%"
225 "47%" "37%" "27%" "18%" "21%" "39%" "55%" "69%"
250 "47%" "37%" "24%" "15%" "16%" "29%" "44%" "56%"
275 "47%" "37%" "22%" "11%" "12%" "20%" "35%" "42%"
300 "47%" "32%" "19%" "8%" "8%" "14%" "24%" "29%"
325 "47%" "23%" "13%" "7%" "6%" "9%" "14%" "17%"
350 "46%" "12%" "7%" "3%" "3%" "5%" "7%" "8%"
375 "47%" "6%" "3%" "1%" "1%" "3%" "3%" "4%"
400 "45%" "2%" "1%" "0%" "0%" "1%" "1%" "1%" Table 7. Probability of being over fished.
year
Run 2023 2024 2025 2026 2027 2028 2029 2030
0 "52%" "61%" "46%" "32%" "9%" "0%" "0%" "0%"
150 "52%" "62%" "64%" "68%" "56%" "29%" "11%" "4%"
175 "52%" "62%" "67%" "73%" "64%" "40%" "20%" "9%"
200 "52%" "62%" "69%" "77%" "72%" "50%" "31%" "17%"
225 "52%" "62%" "72%" "81%" "78%" "60%" "44%" "30%"
250 "52%" "61%" "74%" "84%" "83%" "70%" "55%" "43%"
275 "52%" "61%" "76%" "88%" "87%" "79%" "64%" "57%"
300 "52%" "61%" "78%" "90%" "91%" "84%" "74%" "69%"
325 "52%" "62%" "81%" "92%" "92%" "89%" "83%" "78%"
350 "53%" "63%" "85%" "94%" "95%" "92%" "88%" "86%"
375 "52%" "63%" "86%" "95%" "96%" "94%" "92%" "90%"
400 "54%" "64%" "87%" "96%" "97%" "96%" "95%" "93%"Table 8. Probability of overfishing.
year
Run 2023 2024 2025 2026 2027 2028 2029 2030
0 "3%" "0%" "0%" "0%" "0%" "0%" "0%" "0%"
150 "3%" "0%" "0%" "0%" "0%" "0%" "0%" "0%"
175 "3%" "0%" "0%" "0%" "0%" "0%" "0%" "0%"
200 "3%" "0%" "0%" "0%" "0%" "0%" "0%" "0%"
225 "3%" "2%" "1%" "1%" "0%" "0%" "0%" "0%"
250 "3%" "9%" "8%" "7%" "5%" "4%" "3%" "2%"
275 "3%" "23%" "24%" "23%" "21%" "19%" "17%" "14%"
300 "3%" "44%" "46%" "47%" "46%" "43%" "40%" "39%"
325 "3%" "65%" "68%" "70%" "70%" "68%" "67%" "68%"
350 "3%" "83%" "86%" "86%" "87%" "86%" "86%" "86%"
375 "5%" "92%" "94%" "95%" "94%" "94%" "93%" "93%"
400 "3%" "97%" "98%" "98%" "98%" "98%" "97%" "98%"Table 9. Covariances simulated by MCMC
Bratio_2020 Bratio_2021 Bratio_2022 F_2020 F_2021 F_2022
Bratio_2020 1.000 0.982 0.94 -0.80 -0.60 -0.019
Bratio_2021 0.982 1.000 0.98 -0.84 -0.61 0.047
Bratio_2022 0.937 0.980 1.00 -0.87 -0.61 0.103
F_2020 -0.802 -0.842 -0.87 1.00 0.61 -0.176
F_2021 -0.597 -0.614 -0.61 0.61 1.00 -0.245
F_2022 -0.019 0.047 0.10 -0.18 -0.25 1.000