Effects of mesh size and towing speed on the multispecies catch rates of historical swept area surveys

Fisheries Research(2015)

引用 3|浏览13
暂无评分
摘要
The use of different trawl nets is a factor to be considered when analysing historical swept-area research surveys aimed to characterize temporal variations in the relative abundance of demersal resources. If factors that may affect the performance of the bottom trawls were considered, more reliable temporal trends could be established. Due to the high species diversity that characterizes tropical areas, this kind of analysis is often carried out at the multispecies level. Therefore, the objective of this study was to establish the effect of two technical factors, mesh size and towing speed on the multispecies catch rates obtained in different demersal surveys carried out in the Colombian Caribbean Sea between 1988 and 2001, using two generalized linear models: one covering the entire study area and another restricted to one eco-region. For the global model, the effect of the mesh size on the multispecies catch rates was marginally significant (p<0.10), unlike the towing speed, whose effect was not significant (p>0.10). In contrast, for the eco-region model, the effect of mesh size was not significant (p>0.10), while towing speed had a significant effect (p<0.05). Size structure analysis showed escapement mainly through the codend meshes for the larger mesh size evaluated (50.8mm), confirming the appropriateness of considering mesh size when analyzing historical data of swept area surveys. The effect of the towing speed, beyond the clear incidence on the area actually swept, point to the complexity of the relationship between speed and catch rates. In brief, the results showed that, when assessing historical databases, indices of relative abundance of tropical demersal resources can be improved by including mesh size and towing speed factors.
更多
查看译文
关键词
Bottom trawl,Catch per unit effort,Demersal,Standardization,Generalized linear models
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要