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一种基于访谈的方法来评估意大利海域海龟误捕情况。

An interview-based approach to assess sea turtle bycatch in Italian waters.

作者信息

Lucchetti Alessandro, Vasapollo Claudio, Virgili Massimo

机构信息

Institute of Marine Sciences (ISMAR), National Research Council (CNR), Ancona, Italy.

出版信息

PeerJ. 2017 Apr 26;5:e3151. doi: 10.7717/peerj.3151. eCollection 2017.

Abstract

The loggerhead sea turtle (, Linnaeus, 1758) is the most abundant sea turtle species in the Mediterranean Sea, where commercial fishing appears to be the main driver of mortality. So far, information on sea turtle bycatch in Italy is limited both in space and time due to logistical problems in data collected through onboard observations and on a limited number of vessels involved. In the present study, sea turtle bycatch in Italian waters was examined by collecting fishermen's information on turtle bycatch through an interview-based approach. Their replies enabled the identification of bycatch hotspots in relation to area, season and to the main gear types. The most harmful fishing gears resulted to be trawl nets, showing the highest probabilities of turtle bycatch with a hotspot in the Adriatic Sea, followed by longlines in the Ionian Sea and in the Sicily Channel. Estimates obtained by the present results showed that more than 52,000 capture events and 10,000 deaths occurred in Italian waters in 2014, highlighting a more alarming scenario than earlier studies. The work shows that in case of poor data from other sources, direct questioning of fishermen and stakeholders could represent a useful and cost-effective approach capable of providing sufficient data to estimate annual bycatch rates and identify high-risk gear/location/season combinations.

摘要

蠵龟(, 林奈,1758年)是地中海中数量最多的海龟物种,商业捕鱼似乎是其死亡的主要原因。到目前为止,由于通过船上观测收集数据存在后勤问题,且涉及的船只数量有限,意大利海龟误捕的信息在空间和时间上都很有限。在本研究中,通过基于访谈的方法收集渔民关于海龟误捕的信息,对意大利海域的海龟误捕情况进行了调查。他们的回答有助于确定与区域、季节和主要渔具类型相关的误捕热点。最具危害性的渔具是拖网,在亚得里亚海出现误捕海龟的概率最高,其次是爱奥尼亚海和西西里海峡的延绳钓。根据目前的结果估算,2014年意大利海域发生了超过5.2万次捕获事件和1万起死亡事件,这一情况比早期研究更为惊人。这项工作表明,在其他来源数据不足的情况下,直接询问渔民和利益相关者可能是一种有用且具有成本效益的方法,能够提供足够的数据来估算年度误捕率,并识别高风险的渔具/地点/季节组合。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0167/5408728/ebcd2f163a30/peerj-05-3151-g001.jpg

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