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首页> 外文期刊>Estuarine Coastal and Shelf Science >Otolith reading and multi-model inference for improved estimation of age and growth in the gilthead seabream Spams aurata (L)
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Otolith reading and multi-model inference for improved estimation of age and growth in the gilthead seabream Spams aurata (L)

机译:耳石读取和多模型推理可改善对金头鲷的垃圾邮件年龄(S)的年龄和生长的估计

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摘要

Accurate knowledge of fish age and growth is crucial for species conservation and management of exploited marine stocks. In exploited species, age estimation based on otolith reading is routinely used for building growth curves that are used to implement fishery management models. However, the universal fit of the von Bertalanffy growth function (VBGF) on data from commercial landings can lead to uncertainty in growth parameter inference, preventing accurate comparison of growth-based history traits between fish populations. In the present paper, we used a comprehensive annual sample of wild gilthead seabream (Spams aurata L.) in the Gulf of Lions (France, NW Mediterranean) to test a method ology improving growth modelling for exploited fish populations. After validating the timing for otolith annual increment formation for all life stages, a comprehensive set of growth models (including VBGF) were fitted to the obtained age-length data, used as a whole or sub-divided between group 0 individuals and those coming from commercial landings (ages 1-6). Comparisons in growth model accuracy based on Akaike Information Criterion allowed assessment of the best model for each dataset and, when no model correctly fitted the data, a multi-model inference (MM1) based on model averaging was carried out. The results provided evidence that growth parameters inferred with VBGF must be used with high caution. Hence, VBGF turned to be among the less accurate for growth prediction irrespective of the dataset and its fit to the whole population, the juvenile or the adult datasets provided different growth parameters. The best models for growth prediction were the Tanaka model, for group 0 juveniles, and the MMI, for the older fish, confirming that growth differs substantially between juveniles and adults. All asymptotic models failed to correctly describe the growth of adult S, aurata, probably because of the poor representation of old individuals in the dataset. Multi-model inference associated with separate analysis of juveniles and adult fish is then advised to obtain objective estimations of growth parameters when sampling cannot be corrected towards older fish.
机译:对鱼类年龄和生长的准确了解对于物种保护和海洋鱼类资源的管理至关重要。在被开发物种中,基于耳石读取的年龄估计通常用于建立生长曲线,用于实施渔业管理模型。但是,von Bertalanffy生长函数(VBGF)在商业登陆数据上的通用拟合会导致生长参数推断的不确定性,从而无法准确比较鱼类种群之间基于生长的历史特征。在本文中,我们使用了狮子湾(法国,西北地中海)的野生金头鲷(Spams aurata L.)的年度综合样本,来测试一种方法,以改善被开发鱼类种群的生长模型。在验证了所有生命阶段耳石年增量形成的时间后,将一套完整的生长模型(包括VBGF)拟合到获得的年龄长度数据,将其整体使用或细分为第0组个体和来自商业降落(1-6岁)。根据Akaike信息准则对生长模型准确性进行比较,可以评估每个数据集的最佳模型,并且当没有模型正确拟合数据时,将基于模型平均进行多模型推断(MM1)。结果提供了证据,必须谨慎使用VBGF推断的生长参数。因此,无论数据集及其对整个人群的适合程度如何,VBGF都无法用于增长预测,无论是青少年数据集还是成人数据集都提供了不同的生长参数。预测生长的最佳模型是第0组幼鱼的田中模型和年长鱼类的MMI,这证实了幼鱼和成年鱼的生长差异很大。所有渐近模型均未能正确描述成年S的光环的生长,这可能是因为数据集中老年个体的代表性较差。当不能对成年鱼进行抽样校正时,建议对幼鱼和成年鱼分别进行分析的多模型推论获得生长参数的客观估计。

著录项

  • 来源
    《Estuarine Coastal and Shelf Science》 |2011年第4期|p.534-545|共12页
  • 作者单位

    UMR 5119 UM2-CNRS-lRD-!FREMER-Umt ECOSYM, Place Eugene Bataillon, 34095 Montpettier Cedex 5, France;

    UMR 5119 UM2-CNRS-lRD-!FREMER-Umt ECOSYM, Place Eugene Bataillon, 34095 Montpettier Cedex 5, France,UMR 5119 UM2-CNRS-1RD-1FREMER-UM1 ECOSYM, IRD B.P. J386,18524 Dakar, Senegal;

    UMR 5119 UM2-CNRS-lRD-!FREMER-Umt ECOSYM, Place Eugene Bataillon, 34095 Montpettier Cedex 5, France;

    UMR 5119 UM2-CNRS-lRD-!FREMER-Umt ECOSYM, Place Eugene Bataillon, 34095 Montpettier Cedex 5, France,UMR 5119 UM2-CNRS-1RD-1FREMER-UM1 ECOSYM, IRD B.P. J386,18524 Dakar, Senegal;

    UMR 5119 UM2-CNRS-lRD-!FREMER-Umt ECOSYM, Place Eugene Bataillon, 34095 Montpettier Cedex 5, France;

    UMR 5119 UM2-CNRS-lRD-!FREMER-Umt ECOSYM, Place Eugene Bataillon, 34095 Montpettier Cedex 5, France;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    gilthead seabream; von bertalanfry growth function; multi-model inference; aic weights; mediterranean sea; gulf of lions;

    机译:金头鲷von bertalanfry的生长功能;多模型推理;体重地中海狮子湾;

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