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基于调和函数的生长增量时间周期性建模。

Modeling the temporal periodicity of growth increments based on harmonic functions.

机构信息

Centro de Investigaciones Biológicas del Noroeste (CIBNOR), La Paz, B.C.S., México.

Posgrado en Ciencias Marinas y Costeras, Departamento de Ciencias Marinas y Costeras, Universidad Autónoma de Baja California Sur, La Paz, BCS, México.

出版信息

PLoS One. 2018 Apr 25;13(4):e0196189. doi: 10.1371/journal.pone.0196189. eCollection 2018.

DOI:10.1371/journal.pone.0196189
PMID:29694381
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC5919015/
Abstract

Age estimation methods based on hard structures require a process of validation to confirm the periodical pattern of growth marks. Among such processes, one of the most used is the marginal increment ratio (MIR), which was stated to follow a sinusoidal cycle in a population. Despite its utility, in most cases, its implementation has lacked robust statistical analysis. Accordingly, we propose a modeling approach for the temporal periodicity of growth increments based on single and second order harmonic functions. For illustrative purposes, the MIR periodicities for two geoduck species (Panopea generosa and Panopea globosa) were modeled to identify the periodical pattern of growth increments in the shell. This model identified an annual periodicity for both species but described different temporal patterns. The proposed procedure can be broadly used to objectively define the timing of the peak, the degree of symmetry, and therefore, the synchrony of band deposition of different species on the basis of MIR data.

摘要

基于硬组织的年龄估计方法需要经过验证过程来确认生长标记的周期性模式。在这些过程中,最常用的方法之一是边缘增量比(MIR),它在人群中被认为遵循正弦周期。尽管它很有用,但在大多数情况下,它的实施缺乏稳健的统计分析。因此,我们提出了一种基于单调和二次谐波函数的生长增量时间周期性建模方法。为了说明问题,对两种象拔蚌(Panopea generosa 和 Panopea globosa)的 MIR 周期性进行了建模,以确定贝壳中生长增量的周期性模式。该模型确定了这两个物种的年度周期性,但描述了不同的时间模式。所提出的程序可以广泛用于根据 MIR 数据客观地定义不同物种的峰值时间、对称性程度,因此,带沉积的同步性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3226/5919015/f3b1d8e75be7/pone.0196189.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3226/5919015/1655779f8da1/pone.0196189.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3226/5919015/3bef3279a18a/pone.0196189.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3226/5919015/93ac5906816e/pone.0196189.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3226/5919015/f3b1d8e75be7/pone.0196189.g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3226/5919015/1655779f8da1/pone.0196189.g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3226/5919015/3bef3279a18a/pone.0196189.g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3226/5919015/93ac5906816e/pone.0196189.g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3226/5919015/f3b1d8e75be7/pone.0196189.g004.jpg

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