Limits...
Size selection of Antarctic krill (Euphausia superba) in trawls.

Krag LA, Herrmann B, Iversen SA, Engås A, Nordrum S, Krafft BA - PLoS ONE (2014)

Bottom Line: However, our results indicated that size selectivity of krill is a well-defined process in which individuals encounter meshes at an optimal orientation for escapement.The simulation-based results were supported by data from experimental trawl hauls and underwater video images of the mesh geometry during fishing.The methods developed and results described are important tools for selecting optimal trawl designs for krill fishing.

View Article: PubMed Central - PubMed

Affiliation: DTU Aqua, Technical University of Denmark, Hirtshals, Denmark.

ABSTRACT
Trawlers involved in the Antarctic krill (Euphausia superba) fishery use different trawl designs, and very little is known about the size selectivity of the various gears. Size selectivity quantifies a given trawl's ability to catch different sizes of a harvested entity, and this information is crucial for the management of a sustainable fishery. We established a morphological description of krill and used it in a mathematical model (FISHSELECT) to predict the selective potential of diamond meshes measuring 5-40 mm with mesh opening angles (oa) ranging from 10 to 90°. We expected the majority of krill to encounter the trawl netting in random orientations due to high towing speeds and the assumed swimming capabilities of krill. However, our results indicated that size selectivity of krill is a well-defined process in which individuals encounter meshes at an optimal orientation for escapement. The simulation-based results were supported by data from experimental trawl hauls and underwater video images of the mesh geometry during fishing. Herein we present predictions for the size selectivity of a range of netting configurations relevant to the krill fishery. The methods developed and results described are important tools for selecting optimal trawl designs for krill fishing.

Show MeSH

Related in: MedlinePlus

Experimentally obtained data (black line) with 95% confidence limits (broken line).Thick line (gray) is the predicted selectivity curve based on morphological based measurements (FISHSELECT) and the distribution of opening angle (oa)-values given in table 8.
© Copyright Policy
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4126659&req=5

pone-0102168-g013: Experimentally obtained data (black line) with 95% confidence limits (broken line).Thick line (gray) is the predicted selectivity curve based on morphological based measurements (FISHSELECT) and the distribution of opening angle (oa)-values given in table 8.

Mentions: In Figure 13, the experimentally obtained selectivity results are indicated by the black curve, and the dashed lines show the 95% confidence limits. The thick grey curve shows the optimal FISHSELECT-based predictions for CS1_CS2 at optimal orientation and attack angle using the relative contributions of oa values according to Table 8. The similarity of the two curves indicates that it is possible to obtain a modeled size selection curve that is very similar to the one obtained experimentally by using realistic oa values. Table 8 also shows that this curve is reproduced nearly exclusively by contributions of meshes with oa values of 25, 30, and 35°, with contributions of 39.9, 45.33, and 14.74%, respectively. These results also indicate that less open meshes are more common than what would be expected based on the underwater recordings. This might be due to the effect of non-optimal rotation and/or the effect of attack angle. However, the size selection for krill seems to be well approximated by the FISHSELECT optimal mode, as was previously found to be the case for a number of fish species. Thus, it makes sense to make predictions based on the FISHSELECT optimal mode. This premise is validated by the similarity between the experimental and predicted selectivity curves shown in Figure 13. Figure 14 and Table 9 shows the predictions of size selectivity for krill using the oa distribution in Table 8 for the optimal orientation of CS1_CS2 for the range of mesh sizes from 6 to 28 mm. This figure shows the size selectivity consequences of using different mesh sizes in the krill trawl fishery, and it is valid under the assumption that trawls with these mesh sizes have a similar distribution of oas during fishing.


Size selection of Antarctic krill (Euphausia superba) in trawls.

Krag LA, Herrmann B, Iversen SA, Engås A, Nordrum S, Krafft BA - PLoS ONE (2014)

Experimentally obtained data (black line) with 95% confidence limits (broken line).Thick line (gray) is the predicted selectivity curve based on morphological based measurements (FISHSELECT) and the distribution of opening angle (oa)-values given in table 8.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4126659&req=5

pone-0102168-g013: Experimentally obtained data (black line) with 95% confidence limits (broken line).Thick line (gray) is the predicted selectivity curve based on morphological based measurements (FISHSELECT) and the distribution of opening angle (oa)-values given in table 8.
Mentions: In Figure 13, the experimentally obtained selectivity results are indicated by the black curve, and the dashed lines show the 95% confidence limits. The thick grey curve shows the optimal FISHSELECT-based predictions for CS1_CS2 at optimal orientation and attack angle using the relative contributions of oa values according to Table 8. The similarity of the two curves indicates that it is possible to obtain a modeled size selection curve that is very similar to the one obtained experimentally by using realistic oa values. Table 8 also shows that this curve is reproduced nearly exclusively by contributions of meshes with oa values of 25, 30, and 35°, with contributions of 39.9, 45.33, and 14.74%, respectively. These results also indicate that less open meshes are more common than what would be expected based on the underwater recordings. This might be due to the effect of non-optimal rotation and/or the effect of attack angle. However, the size selection for krill seems to be well approximated by the FISHSELECT optimal mode, as was previously found to be the case for a number of fish species. Thus, it makes sense to make predictions based on the FISHSELECT optimal mode. This premise is validated by the similarity between the experimental and predicted selectivity curves shown in Figure 13. Figure 14 and Table 9 shows the predictions of size selectivity for krill using the oa distribution in Table 8 for the optimal orientation of CS1_CS2 for the range of mesh sizes from 6 to 28 mm. This figure shows the size selectivity consequences of using different mesh sizes in the krill trawl fishery, and it is valid under the assumption that trawls with these mesh sizes have a similar distribution of oas during fishing.

Bottom Line: However, our results indicated that size selectivity of krill is a well-defined process in which individuals encounter meshes at an optimal orientation for escapement.The simulation-based results were supported by data from experimental trawl hauls and underwater video images of the mesh geometry during fishing.The methods developed and results described are important tools for selecting optimal trawl designs for krill fishing.

View Article: PubMed Central - PubMed

Affiliation: DTU Aqua, Technical University of Denmark, Hirtshals, Denmark.

ABSTRACT
Trawlers involved in the Antarctic krill (Euphausia superba) fishery use different trawl designs, and very little is known about the size selectivity of the various gears. Size selectivity quantifies a given trawl's ability to catch different sizes of a harvested entity, and this information is crucial for the management of a sustainable fishery. We established a morphological description of krill and used it in a mathematical model (FISHSELECT) to predict the selective potential of diamond meshes measuring 5-40 mm with mesh opening angles (oa) ranging from 10 to 90°. We expected the majority of krill to encounter the trawl netting in random orientations due to high towing speeds and the assumed swimming capabilities of krill. However, our results indicated that size selectivity of krill is a well-defined process in which individuals encounter meshes at an optimal orientation for escapement. The simulation-based results were supported by data from experimental trawl hauls and underwater video images of the mesh geometry during fishing. Herein we present predictions for the size selectivity of a range of netting configurations relevant to the krill fishery. The methods developed and results described are important tools for selecting optimal trawl designs for krill fishing.

Show MeSH
Related in: MedlinePlus