T90 Codends Improve the Size Selectivity and Catch Efficiency of Shrimp Trawl Fisheries for Southern Velvet Shrimp (Metapenaeopsis palmensis) in the South China Sea
Abstract
:1. Introduction
- (1)
- How would the size selectivity and exploitation pattern change when substituting the T0 codends to T90 codends with the same mesh sizes?
- (2)
- How would the size selectivity and exploitation pattern change when substituting the T0 codends to T90 codends with larger mesh sizes?
- (3)
- Would these potential differences be length-dependent or not?
2. Materials and Methods
2.1. Sea Trials
2.2. Experimental Setup
2.3. Estimation of Size Selectivity
2.4. Estimation of Delta Selectivity between Different Codends Tested
2.5. Estimation of Exploitation Pattern Indicators
3. Results
3.1. Experimental Data
3.2. Size Selectivity
3.3. Delta Selectivity
3.4. Exploitation Pattern Indicators
3.5. Comparison with Previous Diamond-Mesh Codends Selectivity Study
4. Discussion
5. Conclusions
- (1)
- The T0_30 codend had poor size selectivity and exploitation patterns for southern velvet shrimp and, thus, did not mitigate the bycatch issue of juvenile southern velvet shrimp. The implication for fishery management is that the present 25 mm MMS regulation should be revised.
- (2)
- Compared with the T0_30 codend, the T0_35 and T90_30 codends had significantly better size selectivity and exploitation patterns for the target species. These two options provide excellent revision for the existing 25 mm MMS codend regulation in the fishery management, in order to obtain sustainable fishing for southern velvet shrimp in the SCS.
- (3)
- The T90_35 codend performed the best in size selectivity and exploitation for the studied species. However, the loss of individuals with marketable size was of concern.
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Codend | Mesh Opening ± SE (mm) | Twine Diameter ± SE (mm) | Number of Meshes in Circumference | Number of Meshes in Length |
---|---|---|---|---|
T0_30 | 29.79 ± 0.65 | 1.24 ± 0.12 | 183 | 160 |
T90_30 | 29.79 ± 0.65 | 1.24 ± 0.12 | 122 | 208 |
T0_35 | 35.66 ± 1.06 | 1.29 ± 0.08 | 157 | 137 |
T90_35 | 35.66 ± 1.06 | 1.29 ± 0.08 | 105 | 178 |
Cover | 12.51 ± 0.78 | 1.18 ± 0.10 | 550 | 480 |
Codend | Haul ID | Duration (min) | Depth (m) | nR | qR | nE | qE |
---|---|---|---|---|---|---|---|
T0_30 | H1 | 158 | 20 | 28 | 0.33 | 129 | 1.00 |
T0_30 | H2 | 115 | 21 | 24 | 0.33 | 156 | 1.00 |
T0_30 | H3 | 137 | 20 | 63 | 0.33 | 114 | 1.00 |
T0_30 | H4 | 123 | 22 | 24 | 0.50 | 65 | 1.00 |
T0_30 | H5 | 127 | 26 | 25 | 0.50 | 25 | 1.00 |
T0_30 | H6 | 132 | 22 | 26 | 0.50 | 15 | 1.00 |
T0_30 | H7 | 129 | 20 | 31 | 0.33 | 12 | 1.00 |
T0_30 | H8 | 124 | 21 | 23 | 0.50 | 17 | 1.00 |
T0_30 | H9 | 144 | 26 | 80 | 0.50 | 15 | 1.00 |
T0_35 | H1 | 124 | 32 | 119 | 0.50 | 58 | 0.50 |
T0_35 | H2 | 124 | 34 | 44 | 0.50 | 34 | 0.50 |
T0_35 | H3 | 125 | 39 | 32 | 0.50 | 54 | 0.33 |
T0_35 | H4 | 130 | 30 | 15 | 0.50 | 27 | 0.33 |
T0_35 | H5 | 139 | 26 | 43 | 0.33 | 138 | 0.25 |
T0_35 | H6 | 134 | 22 | 26 | 0.50 | 92 | 0.25 |
T0_35 | H7 | 141 | 21 | 83 | 0.50 | 97 | 0.33 |
T0_35 | H8 | 134 | 18 | 17 | 0.50 | 144 | 0.25 |
T0_35 | H9 | 127 | 20 | 71 | 0.50 | 198 | 0.33 |
T90_30 | H1 | 158 | 20 | 51 | 0.33 | 213 | 1.00 |
T90_30 | H2 | 115 | 21 | 44 | 0.33 | 188 | 1.00 |
T90_30 | H3 | 137 | 20 | 22 | 0.33 | 90 | 1.00 |
T90_30 | H4 | 123 | 22 | 11 | 0.50 | 51 | 0.50 |
T90_30 | H5 | 127 | 26 | 20 | 0.50 | 24 | 0.50 |
T90_30 | H6 | 132 | 22 | 44 | 0.50 | 63 | 1.00 |
T90_30 | H7 | 129 | 20 | 46 | 0.33 | 67 | 1.00 |
T90_30 | H8 | 124 | 21 | 13 | 0.50 | 61 | 1.00 |
T90_30 | H9 | 144 | 26 | 45 | 0.50 | 62 | 0.50 |
T90_35 | H1 | 124 | 32 | 52 | 0.50 | 62 | 0.50 |
T90_35 | H2 | 124 | 34 | 33 | 0.50 | 42 | 0.50 |
T90_35 | H3 | 125 | 39 | 79 | 0.50 | 49 | 0.25 |
T90_35 | H4 | 130 | 30 | 66 | 0.50 | 60 | 0.25 |
T90_35 | H5 | 139 | 26 | 121 | 0.33 | 205 | 0.25 |
T90_35 | H6 | 134 | 22 | 13 | 0.50 | 144 | 0.25 |
T90_35 | H7 | 141 | 21 | 13 | 0.50 | 108 | 0.33 |
T90_35 | H8 | 134 | 18 | 16 | 0.50 | 89 | 0.25 |
T90_35 | H9 | 127 | 20 | 55 | 0.50 | 116 | 0.33 |
Model | ||||
---|---|---|---|---|
Codend | Logit | Probit | Gompertz | Richards |
T0_30 | 1099.31 | 1096.08 | 1094.62 | 1096.01 |
T0_35 | 2667.4 | 2657.4 | 2671.97 | 2661.47 |
T90_30 | 1906.4 | 1900.9 | 1908.27 | 1908.33 |
T90_35 | 3748.02 | 3740.33 | 3706.04 | 3709.79 |
Parameters | ||||||
---|---|---|---|---|---|---|
Codends | Model | L50 (cm) | SR (cm) | p-Value | Deviance | DOF |
T0_30 | Gompertz | 5.33 (4.99–5.63) | 0.98 (0.74–1.23) | 0.8970 | 6.36 | 12 |
T0_35 | Probit | 6.35 (6.11–6.66) | 1.26 (1.06–1.47) | 0.4846 | 10.52 | 11 |
T90_30 | Probit | 6.11 (5.91–6.40) | 1.48 (1.17–1.85) | 0.0473 | 18.49 | 10 |
T90_35 | Gompertz | 7.07 (6.73–7.69) | 2.15 (1.73–2.93) | 0.0115 | 24.32 | 11 |
D25 | 5.47 (5.20–5.67) | 0.89 (0.62–1.14) | ||||
D30 | 5.85 (5.47–6.18) | 0.81 (0.61–1.04) | ||||
D35 | 6.22 (4.99–7.01) | 1.90 (1.37–3.47) | ||||
D40 | 6.92 (5.77–7.62) | 2.05 (1.38–4.21) | ||||
D45 | 7.49 (7.09–8.71) | 2.37 (1.45–9.36) | ||||
D54 | 7.72 (6.63–12.93) | 4.01 (1.96–19.68) |
Population | Codend | nP− (%) | nP+ (%) | dnRatio (%) |
---|---|---|---|---|
2017 | T0_30 | 79.56 (69.55–89.19) | 99.42 (98.13–99.90) | 69.36 (63.59–74.07) |
T0_35 | 54.24 (44.17–64.68) | 97.87 (94.58–99.27) | 61.06 (54.84–65.88) | |
T90_30 | 60.33 (51.15–68.64) | 97.64 (93.72–99.34) | 63.61 (58.05–68.33) | |
T90_35 | 35.12 (24.00–44.26) | 77.24 (63.51–85.41) | 56.26 (49.26–61.52) | |
2018 | T0_30 | 52.84 (41.04–67.34) | 99.08 (97.22–99.83) | 98.39 (97.06–99.76) |
T0_35 | 24.77 (17.92–32.39) | 96.22 (90.94–98.66) | 96.73 (93.96–99.48) | |
T90_30 | 32.95 (24.77–39.37) | 95.97 (90.01–98.80) | 97.53 (95.55–99.58) | |
T90_35 | 15.50 (9.15–20.86) | 70.91 (56.24–80.35) | 96.17 (93.32–99.40) | |
2019a | T0_30 | 81.66 (72.47–89.98) | 99.36 (97.97–99.89) | 81.94 (78.93–84.92) |
T0_35 | 52.41 (42.58–60.96) | 97.64 (93.91–99.21) | 74.76 (70.14–78.70) | |
T90_30 | 59.43 (50.73–66.13) | 97.40 (93.00–99.24) | 77.10 (73.08–80.49) | |
T90_35 | 33.59 (22.96–40.84) | 76.12 (62.30–84.55) | 70.89 (65.57–75.45) | |
2019b | T0_30 | 69.95 (59.64–80.28) | 99.32 (97.83–99.88) | 80.78 (75.51–86.16) |
T0_35 | 41.38 (32.59–49.75) | 97.47 (93.62–99.13) | 71.70 (65.60–78.04) | |
T90_30 | 48.80 (40.05–56.13) | 97.21 (92.63–99.20) | 74.97 (69.31–80.46) | |
T90_35 | 26.41 (17.98–33.23) | 75.22 (61.30–83.83) | 67.70 (60.65–74.77) | |
2020 | T0_30 | 60.55 (49.37–72.61) | 99.22 (97.52–99.85) | 95.25 (92.98–96.97) |
T0_35 | 32.28 (24.06–40.54) | 96.93 (92.44–98.92) | 91.62 (88.34–94.39) | |
T90_30 | 40.06 (31.62–46.88) | 96.67 (91.56–99.05) | 93.15 (90.36–95.49) | |
T90_35 | 20.35 (12.85–26.48) | 73.29 (59.07–81.99) | 90.11 (86.31–93.61) |
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Yang, B.; Herrmann, B. T90 Codends Improve the Size Selectivity and Catch Efficiency of Shrimp Trawl Fisheries for Southern Velvet Shrimp (Metapenaeopsis palmensis) in the South China Sea. Sustainability 2022, 14, 12208. https://doi.org/10.3390/su141912208
Yang B, Herrmann B. T90 Codends Improve the Size Selectivity and Catch Efficiency of Shrimp Trawl Fisheries for Southern Velvet Shrimp (Metapenaeopsis palmensis) in the South China Sea. Sustainability. 2022; 14(19):12208. https://doi.org/10.3390/su141912208
Chicago/Turabian StyleYang, Bingzhong, and Bent Herrmann. 2022. "T90 Codends Improve the Size Selectivity and Catch Efficiency of Shrimp Trawl Fisheries for Southern Velvet Shrimp (Metapenaeopsis palmensis) in the South China Sea" Sustainability 14, no. 19: 12208. https://doi.org/10.3390/su141912208
APA StyleYang, B., & Herrmann, B. (2022). T90 Codends Improve the Size Selectivity and Catch Efficiency of Shrimp Trawl Fisheries for Southern Velvet Shrimp (Metapenaeopsis palmensis) in the South China Sea. Sustainability, 14(19), 12208. https://doi.org/10.3390/su141912208