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智利南部养殖鲑鱼中桡足类 Caligus rogercresseyi 水平的风险因素分析。

Risk factor analysis for sea lice, Caligus rogercresseyi, levels in farmed salmonids in southern Chile.

机构信息

Faculty of Veterinary Science, Preventive Veterinary Medicine Department, University of Chile, Santiago, Chile.

出版信息

J Fish Dis. 2011 May;34(5):345-54. doi: 10.1111/j.1365-2761.2011.01238.x.

Abstract

Sea lice, Caligus rogercresseyi, are ectoparasitic copepods, which severely affect the salmon farming industry in southern Chile, reducing the health status of fish and producing both direct and indirect economic losses. Local farmers have reported increasing infestation levels since 2004, reaching a peak in 2007. In response to this situation, the Chilean Fisheries Service (Sernapesca) developed a surveillance programme; the first step of which consisted of a general survey of salmon farms. This survey included documenting counts of parasite burdens on fish and measurements of several husbandry and environmental factors providing an evaluation of risk factors for the observed infestation levels. The information collected was analysed using a linear mixed model technique, which takes into account the clustered structure of data, decomposing the unexplained variation and assigning it to different aggregation levels of the productive system. Geographical zones, fish species, treatment against sea lice performed 1 month before sampling, stocking density, fish weight and water salinity were the variables significantly associated with sea lice burdens. In contrast, treatments performed 2-3 months before sampling, use of photoperiod in sea cages and water temperature, were not significant. There was significant unexplained variation at all aggregation levels, i.e. sub-zone, fish farm and cage level, with the fish farm level showing the greatest variation.

摘要

海虱(Caligus rogercresseyi)是一种寄生在鱼类体表的桡足类寄生虫,严重影响智利南部的鲑鱼养殖业,降低鱼类健康状况,并造成直接和间接的经济损失。自 2004 年以来,当地农民报告海虱感染水平不断上升,2007 年达到峰值。为应对这种情况,智利渔业服务局(Sernapesca)制定了一项监测计划;该计划的第一步是对鲑鱼养殖场进行全面调查。这项调查包括记录鱼类寄生虫负担的数量,并测量几项养殖和环境因素,以评估观察到的感染水平的风险因素。使用线性混合模型技术分析收集到的信息,该技术考虑了数据的聚类结构,分解未解释的变异并将其分配到生产系统的不同聚合水平。地理区域、鱼类物种、采样前 1 个月进行的海虱防治、放养密度、鱼体重和水盐度是与海虱负担显著相关的变量。相比之下,采样前 2-3 个月进行的处理、在海上围网中使用光周期和水温和无显著相关性。在所有聚合水平(即分区、养殖场和网箱水平)都存在显著的未解释变异,其中养殖场水平的变异最大。

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