Age-Dependent Speciation Can Explain the Shape of Empirical Phylogenies

作者
Oskar Hagen,Klaas Hartmann,Mike Steel,Tanja Stadler
出处
期刊:Systematic Biology [Oxford University Press]
卷期号:64 (3): 432-440 被引量:81
标识
DOI:10.1093/sysbio/syv001
摘要

Tens of thousands of phylogenetic trees, describing the evolutionary relationships between hundreds of thousands of taxa, are readily obtainable from various databases. From such trees, inferences can be made about the underlying macroevolutionary processes, yet remarkably these processes are still poorly understood. Simple and widely used evolutionary null models are problematic: Empirical trees show very different imbalance between the sizes of the daughter clades of ancestral taxa compared to what models predict. Obtaining a simple evolutionary model that is both biologically plausible and produces the imbalance seen in empirical trees is a challenging problem, to which none of the existing models provide a satisfying answer. Here we propose a simple, biologically plausible macroevolutionary model in which the rate of speciation decreases with species age, whereas extinction rates can vary quite generally. We show that this model provides a remarkable fit to the thousands of trees stored in the online database TreeBase. The biological motivation for the identified age-dependent speciation process may be that recently evolved taxa often colonize new regions or niches and may initially experience little competition. These new taxa are thus more likely to give rise to further new taxa than a taxon that has remained largely unchanged and is, therefore, well adapted to its niche. We show that age-dependent speciation may also be the result of different within-species populations following the same laws of lineage splitting to produce new species. As the fit of our model to the tree database shows, this simple biological motivation provides an explanation for a long standing problem in macroevolution.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
好好好发布了新的文献求助30
刚刚
刚刚
刚刚
鹿呦发布了新的文献求助10
刚刚
韩琳发布了新的文献求助10
刚刚
Lucas完成签到,获得积分10
1秒前
韩琳发布了新的文献求助30
1秒前
韩琳发布了新的文献求助10
1秒前
韩琳发布了新的文献求助80
1秒前
李hk发布了新的文献求助10
1秒前
韩琳发布了新的文献求助10
2秒前
文静紫烟发布了新的文献求助10
2秒前
2秒前
韩琳发布了新的文献求助10
2秒前
从容之卉关注了科研通微信公众号
2秒前
尹伊萍完成签到,获得积分20
3秒前
3秒前
3秒前
3秒前
zxw应助曹苍久采纳,获得10
3秒前
3秒前
3秒前
赘婿应助Jenny采纳,获得10
4秒前
韩琳发布了新的文献求助10
4秒前
4秒前
5秒前
韩琳发布了新的文献求助10
5秒前
司空悒发布了新的文献求助10
5秒前
5秒前
5秒前
沙漏发布了新的文献求助10
5秒前
tlz完成签到,获得积分10
5秒前
韩琳发布了新的文献求助10
5秒前
12133121发布了新的文献求助10
5秒前
韩琳发布了新的文献求助10
5秒前
woshi123应助欣喜沛芹采纳,获得10
5秒前
文若完成签到,获得积分10
6秒前
6秒前
6秒前
韩琳发布了新的文献求助10
6秒前
高分求助中
APA handbook of comparative psychology: Basic concepts, methods, neural substrate, and behavior 1000
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
Römisch-Germanische Forschungen 500
Electric machines: theory, operating applications, and controls 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
When Is Two-Stage Sample Robust Optimization Asymptotically Optimal? 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7600877
求助须知:如何正确求助?哪些是违规求助? 9177269
关于积分的说明 19650951
捐赠科研通 7176765
什么是DOI,文献DOI怎么找? 3268768
关于科研通互助平台的介绍 2433092
邀请新用户注册赠送积分活动 2262376