首页> 美国卫生研究院文献>Biology Letters >Partially incorrect fossil data augment analyses of discrete trait evolution in living species
【2h】

Partially incorrect fossil data augment analyses of discrete trait evolution in living species

机译:部分不正确的化石数据增强了对生物物种离散性状进化的分析

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Ancestral state reconstruction of discrete character traits is often vital when attempting to understand the origins and homology of traits in living species. The addition of fossils has been shown to alter our understanding of trait evolution in extant taxa, but researchers may avoid using fossils alongside extant species if only few are known, or if the designation of the trait of interest is uncertain. Here, I investigate the impacts of fossils and incorrectly coded fossils in the ancestral state reconstruction of discrete morphological characters under a likelihood model. Under simulated phylogenies and data, likelihood-based models are generally accurate when estimating ancestral node values. Analyses with combined fossil and extant data always outperform analyses with extant species alone, even when around one quarter of the fossil information is incorrect. These results are especially pronounced when model assumptions are violated, such as when there is a trend away from the root value. Fossil data are of particular importance when attempting to estimate the root node character state. Attempts should be made to include fossils in analysis of discrete traits under likelihood, even if there is uncertainty in the fossil trait data.
机译:当试图了解生物物种性状的起源和同源性时,离散性状的祖先状态重建通常至关重要。矿物的添加已显示出改变了我们对现存生物分类中性状进化的理解,但是如果只知道很少的话,或者如果不确定性状的指定是不确定的,研究人员可能会避免将化石与现存物种一起使用。在这里,我研究了在似然模型下化石和编码错误的化石对离散形态特征的祖先状态重建的影响。在模拟的系统发育和数据下,当估计祖先节点值时,基于似然的模型通常是准确的。即使在大约四分之一的化石信息不正确的情况下,使用化石和现存数据相结合的分析也总是优于仅使用现存物种进行的分析。当违反模型假设时,例如当趋势远离根值时,这些结果尤其明显。化石数据在尝试估计根节点字符状态时特别重要。即使化石特征数据不确定,也应尝试在可能的情况下将化石包括在离散特征的分析中。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号