J
John J. Schenk
Researcher at Ohio University
Publications - 35
Citations - 1380
John J. Schenk is an academic researcher from Ohio University. The author has contributed to research in topics: Mentzelia & Bartonia. The author has an hindex of 11, co-authored 29 publications receiving 1139 citations. Previous affiliations of John J. Schenk include Georgia Southern University & Washington State University.
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Journal ArticleDOI
Ecological opportunity and the origin of adaptive radiations
Jeremy B. Yoder,Erin Clancey,S. Des Roches,Jon Eastman,L. Gentry,William Godsoe,Travis J. Hagey,Denim M. Jochimsen,Benjamin P. Oswald,Jeanne M. Robertson,Brice A. J. Sarver,John J. Schenk,Stephen F. Spear,Luke J. Harmon +13 more
TL;DR: It is proposed that ecological opportunity could promote adaptive radiation by generating specific changes to the selective regimes acting on natural populations, both by relaxing effective stabilizing selection and by creating conditions that ultimately generate diversifying selection.
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Muroid rodent phylogenetics: 900-species tree reveals increasing diversification rates
TL;DR: The results provide a phylogenetic framework for comparative studies that is not highly dependent upon the signal from any one gene and compared the results of multigene supermatrix studies like this one with the principal published supertrees and concluded that the latter are unreliable for any comparative study in muroids.
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Ecological Opportunity and Incumbency in the Diversification of Repeated Continental Colonizations by Muroid Rodents
TL;DR: An extension of the conventional ecological opportunity model to include a geographic incumbency effect is presented, the largest muroid phylogeny to date is developed, and a pattern of incumbency that is consistent with ecological opportunity is seen, but they did not inhibit initial diversification rates of secondary colonizers.
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Consequences of Secondary Calibrations on Divergence Time Estimates.
TL;DR: Primary calibrations lead to a false impression of precision and the distribution of age estimates shift away from those that would be inferred by the primary analysis, suggesting that secondary calibrations should not be applied as the only source of calibration in divergence time analyses that test time-dependent hypotheses until the additional error associated with secondary calibration is more properly modeled.
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Effects of Substitution Models on Divergence Time Estimates: Simulations and an Empirical Study of Model Uncertainty using Cornales
TL;DR: Simulations demonstrated that use of underparameterized models affected age estimates more than use of overparameterization models, and increasing the number of calibration points can limit but not completely remove discrepancies introduced by underparametersized models.