An approach to map and quantify the fishing effort of polyvalent passive gear fishing fleets using geospatial data

被引:4
|
作者
Henriques, Nuno [1 ,2 ]
Russo, Tommaso [3 ,4 ]
Bentes, Luis [1 ]
Monteiro, Pedro [1 ]
Parisi, Antonio [3 ]
Magno, Ramiro [5 ]
Oliveira, Frederico [1 ]
Erzini, Karim [1 ,2 ]
Goncalves, Jorge M. S. [1 ]
机构
[1] Ctr Ciencias Mar, P-8005139 Faro, Portugal
[2] Univ Algarve, P-8005139 Faro, Portugal
[3] Univ Roma Tor Vergata, I-00133 Rome, Lazio, Italy
[4] CoNISMa, Rome, Lazio, Italy
[5] Pattern Inst, P-8005222 Faro, Portugal
关键词
AIS; fisheries mapping; fishing effort; passive fishing gears; polyvalent fishing fleet; soak time; vessel tracking data; MONITORING SYSTEMS VMS; SOAK TIME; LANDINGS PROFILES; GILL-NET; VESSEL; FISHERIES; TRACKING; CATCH; IDENTIFICATION; CONSERVATION;
D O I
10.1093/icesjms/fsad092
中图分类号
S9 [水产、渔业];
学科分类号
0908 ;
摘要
The use of tracking devices, such as vessel monitoring systems or automatic identification system, enabled us to expand our knowledge on the distribution and quantification of fishing activities. However, methods and models based on vessel tracking data are mostly devised to be applied to towed gears, whereas applications to multi-gear and passive fisheries have been underrepresented. Here, we propose a methodology to deal with geospatial data to map and quantify the fishing effort, as soak time, of passive fishing gears used by a multi-gear fishing fleet. This approach can be adapted to other passive multi-or single-gear fisheries, since it requires only three variables that can be extracted from a pre-classified dataset, to identify the beginning (gear deployment) and the end (hauling) of passive fishing events. As far as we are aware, this is the first time a methodology that allows quantifying the soak time of static passive fishing events, within a polyvalent fishery context, is presented. We argue that the information that can be extracted from such approaches could contribute to improved management of multi-gear and static-gear fisheries and the ecosystem-based approach.
引用
收藏
页码:1658 / 1669
页数:12
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