Consejo Superior de Investigaciones Científicas (CSIC), Instituto de Investigaciones Marinas (IIM), C/Eduardo Cabello 6, Vigo, Spain.
PLoS One. 2018 Oct 18;13(10):e0205981. doi: 10.1371/journal.pone.0205981. eCollection 2018.
Determining the magnitude and causes of intrinsic variability is a main issue in the analysis of bivalve growth. Inter-individual variability in bivalve growth has been attributed to differences in the physiological performance. This hypothesis has been commonly tested comparing the physiological rates of fast and slow growers after size differentiation has occurred. This experimental design may detect a link between growth and physiological performance, but we cannot interpret the posterior physiological performance as a driver for the prior growth variability. Considering these limitations, this work introduces a new methodological framework for the analysis of bivalve growth variability. We have conducted sequential measurements of size and physiological performance (feeding, digestion and metabolic rates) in even-sized mussels growing under homogeneous environmental conditions. This experimental design allows us to distinguish between changes over time within individuals, i.e. growth and trends in the physiological rates, from differences between individuals with respect to a baseline level. In addition, Functional Data Analysis provides powerful tools to summarize all the information obtained in the exhaustive sampling scheme and to test whether differences in the physiological performance enhance growth dispersion. Our results report an increasing dispersion in both size and physiological performance over time. Although mussels grew during the experiment, it is difficult to detect any increasing or decreasing temporal pattern in their feeding, digestion and metabolic rates due to the large inter-individual variability. Comparison between the growth and physiological patterns of mussels with final size above (fast growers) and below (slow growers) the median found that fast growers had larger feeding and digestion rates and lower metabolic expenditures during the experimental culture than mussels with slow growth, which agrees with the hypothesis of a physiological basis for bivalve growth variability.
确定内在变异性的大小和原因是贝类生长分析中的一个主要问题。贝类生长的个体间变异性归因于生理性能的差异。这种假设通常通过比较大小分化后快速生长和慢速生长贝类的生理速率来检验。这种实验设计可以检测生长与生理性能之间的联系,但我们不能将后期的生理性能解释为前期生长变异性的驱动因素。考虑到这些局限性,本工作为贝类生长变异性分析引入了一种新的方法框架。我们在同质环境条件下对大小和生理性能(摄食、消化和代谢率)进行了均匀大小的贻贝的连续测量。这种实验设计允许我们区分个体内部随时间的变化,即生长和生理速率的趋势,以及相对于基线水平的个体之间的差异。此外,功能数据分析为总结详尽采样方案中获得的所有信息提供了强大的工具,并检验生理性能的差异是否增强了生长的离散性。我们的结果报告了大小和生理性能随时间的增加而增加的离散度。尽管贻贝在实验期间生长,但由于个体间的巨大差异,很难检测到它们的摄食、消化和代谢率随时间的任何增加或减少的趋势。将最终大小大于(快速生长者)和小于(慢速生长者)中位数的贻贝的生长和生理模式进行比较发现,快速生长者在实验培养期间的摄食和消化率较高,代谢支出较低,这与贝类生长变异性具有生理基础的假设一致。