Estimating rates and patterns of diversification with incomplete sampling: a case study in the rosids
Abstract
Premise Recent advances in generating large‐scale phylogenies enable broad‐scale estimation of species diversification. These now common approaches typically are characterized by (1) incomplete species coverage without explicit sampling methodologies and/or (2) sparse backbone representation, and usually rely on presumed phylogenetic placements to account for species without molecular data. We used empirical examples to examine the effects of incomplete sampling on diversification estimation and provide constructive suggestions to ecologists and evolutionary biologists based on those results. Methods We used a supermatrix for rosids and one well‐sampled subclade (Cucurbitaceae) as empirical case studies. We compared results using these large phylogenies with those based on a previously inferred, smaller supermatrix and on a synthetic tree resource with complete taxonomic coverage. Finally, we simulated random and representative taxon sampling and explored the impact of sampling on three commonly used methods, both parametric (RPANDA and BAMM) and semiparametric (DR). Results We found that the impact of sampling on diversification estimates was idiosyncratic and often strong. Compared to full empirical sampling, representative and random sampling schemes either depressed or inflated speciation rates, depending on methods and sampling schemes. No method was entirely robust to poor sampling, but BAMM was least sensitive to moderate levels of missingmore »
- Authors:
-
- Florida Museum of Natural History University of Florida Gainesville Florida 32611 USA, State Key Laboratory of Systematic and Evolutionary Botany Institute of Botany Chinese Academy of Sciences Beijing 100093 China, Department of Bioscience Aarhus University Aarhus 8000 Denmark
- Department of Biological Sciences Mississippi State University Mississippi State Mississippi 39762 USA
- Department of Biology University of Florida Gainesville Florida 32611 USA, Biodiversity Institute University of Florida Gainesville Florida 32611 USA
- Florida Museum of Natural History University of Florida Gainesville Florida 32611 USA, Biodiversity Institute University of Florida Gainesville Florida 32611 USA, Genetics Institute University of Florida Gainesville Florida 32608 USA
- State Key Laboratory of Systematic and Evolutionary Botany Institute of Botany Chinese Academy of Sciences Beijing 100093 China
- Florida Museum of Natural History University of Florida Gainesville Florida 32611 USA, Department of Biology University of Florida Gainesville Florida 32611 USA, Biodiversity Institute University of Florida Gainesville Florida 32611 USA, Genetics Institute University of Florida Gainesville Florida 32608 USA
- Florida Museum of Natural History University of Florida Gainesville Florida 32611 USA, Biodiversity Institute University of Florida Gainesville Florida 32611 USA
- Publication Date:
- Research Org.:
- Univ. of Florida, Gainesville, FL (United States)
- Sponsoring Org.:
- USDOE Office of Science (SC); National Science Foundation (NSF); Chinese Academy of Sciences; National Natural Science Foundation of China (NSFC)
- OSTI Identifier:
- 1632777
- Alternate Identifier(s):
- OSTI ID: 1632778; OSTI ID: 1803330
- Grant/Contract Number:
- DE‐SC0018247; SC0018247; DEB-1208809; DEB-1442280; DBI-1523667; DEB-1916632; XDA19050103; XDB31000000; 31590822
- Resource Type:
- Published Article
- Journal Name:
- American Journal of Botany
- Additional Journal Information:
- Journal Name: American Journal of Botany Journal Volume: 107 Journal Issue: 6; Journal ID: ISSN 0002-9122
- Publisher:
- Wiley Blackwell (John Wiley & Sons)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 59 BASIC BIOLOGICAL SCIENCES; plant sciences; diversification; mega-phylogeny; modeling; rosids; sampling bias
Citation Formats
Sun, Miao, Folk, Ryan A., Gitzendanner, Matthew A., Soltis, Pamela S., Chen, Zhiduan, Soltis, Douglas E., and Guralnick, Robert P. Estimating rates and patterns of diversification with incomplete sampling: a case study in the rosids. United States: N. p., 2020.
Web. doi:10.1002/ajb2.1479.
Sun, Miao, Folk, Ryan A., Gitzendanner, Matthew A., Soltis, Pamela S., Chen, Zhiduan, Soltis, Douglas E., & Guralnick, Robert P. Estimating rates and patterns of diversification with incomplete sampling: a case study in the rosids. United States. https://doi.org/10.1002/ajb2.1479
Sun, Miao, Folk, Ryan A., Gitzendanner, Matthew A., Soltis, Pamela S., Chen, Zhiduan, Soltis, Douglas E., and Guralnick, Robert P. Tue .
"Estimating rates and patterns of diversification with incomplete sampling: a case study in the rosids". United States. https://doi.org/10.1002/ajb2.1479.
@article{osti_1632777,
title = {Estimating rates and patterns of diversification with incomplete sampling: a case study in the rosids},
author = {Sun, Miao and Folk, Ryan A. and Gitzendanner, Matthew A. and Soltis, Pamela S. and Chen, Zhiduan and Soltis, Douglas E. and Guralnick, Robert P.},
abstractNote = {Premise Recent advances in generating large‐scale phylogenies enable broad‐scale estimation of species diversification. These now common approaches typically are characterized by (1) incomplete species coverage without explicit sampling methodologies and/or (2) sparse backbone representation, and usually rely on presumed phylogenetic placements to account for species without molecular data. We used empirical examples to examine the effects of incomplete sampling on diversification estimation and provide constructive suggestions to ecologists and evolutionary biologists based on those results. Methods We used a supermatrix for rosids and one well‐sampled subclade (Cucurbitaceae) as empirical case studies. We compared results using these large phylogenies with those based on a previously inferred, smaller supermatrix and on a synthetic tree resource with complete taxonomic coverage. Finally, we simulated random and representative taxon sampling and explored the impact of sampling on three commonly used methods, both parametric (RPANDA and BAMM) and semiparametric (DR). Results We found that the impact of sampling on diversification estimates was idiosyncratic and often strong. Compared to full empirical sampling, representative and random sampling schemes either depressed or inflated speciation rates, depending on methods and sampling schemes. No method was entirely robust to poor sampling, but BAMM was least sensitive to moderate levels of missing taxa. Conclusions We suggest caution against uncritical modeling of missing taxa using taxonomic data for poorly sampled trees and in the use of summary backbone trees and other data sets with high representative bias, and we stress the importance of explicit sampling methodologies in macroevolutionary studies.},
doi = {10.1002/ajb2.1479},
journal = {American Journal of Botany},
number = 6,
volume = 107,
place = {United States},
year = {Tue Jun 09 00:00:00 EDT 2020},
month = {Tue Jun 09 00:00:00 EDT 2020}
}
https://doi.org/10.1002/ajb2.1479
Web of Science
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