Multi-model approach for growth analysis of Evibacus princeps Smith, 1869 (Decapoda, Scyllaridae) in the Gulf of California

IF 0.6 4区 生物学 Q4 MARINE & FRESHWATER BIOLOGY
Alma L. León-Valdez, E. Aragón-Noriega, J. A. Félix-Ortiz, J. Arzola-González, Jorge Payan-Alejo, W. Valenzuela-Quiñónez, Alejo A. Valdez-Camacho
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引用次数: 0

Abstract

In Mexico, the spiny lobster fishery is well established but this is not the case with the slipper lobster fishery. For a sustainable fishery, many biological traits must be known, one of which is growth. The objective of the present study was to probe the multi-model approach to identify the curve that best describes the growth of Evibacus princeps from the Gulf of California. Specimens were collected aboard commercial trawlers during the industrial shrimp fishing season (October 2021-March 2022) at depths ranging from 10 to 55 m. Five versions of the Schnute model (including the Von Bertalanffy model) were applied and the best model was selected using the Bayesian information criterion. The estimation of an average model was performed because no model obtained 90% of the evidence. E. princeps from the Gulf of California exhibit an indeterminate growth pattern.
加利福尼亚湾王子Evibacus princeps Smith(Decapoda,Scyllaridae)1869年生长分析的多模型方法
在墨西哥,多刺龙虾渔业已经建立起来,但拖鞋龙虾渔业却并非如此。为了实现可持续渔业,必须了解许多生物学特征,其中之一就是生长。本研究的目的是探索多模型方法,以确定最能描述加利福尼亚湾Evibacus princeps生长的曲线。在工业捕虾季节(2021年10月至2022年3月),在10至55米的深度范围内,在商业拖网渔船上采集了样本。应用了五个版本的Schnute模型(包括Von-Bertalanffy模型),并使用贝叶斯信息准则选择了最佳模型。进行平均模型的估计是因为没有模型获得90%的证据。来自加利福尼亚湾的E.princeps表现出不确定的生长模式。
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来源期刊
Crustaceana
Crustaceana 生物-海洋与淡水生物学
CiteScore
1.30
自引率
33.30%
发文量
52
审稿时长
3 months
期刊介绍: Crustaceana is a leading journal in the world on crustacean research, including the latest papers from all branches of zoology. It provides up-to-date information on aspects such as taxonomy, zoogeography, ecology, physiology, anatomy, genetics, palaeontology, and biometry, and covers all groups of Crustacea. Boasting a large international circulation, Crustaceana provides its readers with an abstract for each article.
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