2000
DOI: 10.1080/10635159950127411
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Phylogenetic Relationships Among the Phrynosomatid Sand Lizards Inferred from Mitochondrial DNA Sequences Generated by Heterogeneous Evolutionary Processes

Abstract: Abstract.•Nucleotide sequences of the mitochondrial protein coding cytochrome b (cyt b; 650 bp) and small-subunit 12S ribosomal RNA (~350 bp) genes were used in analyses of phylogenetic relationships among extant phrynosomatid sand lizards, including an examination of competing hypotheses regarding the evolution of "earlessness." Sequences were obtained from all currently recognized species of sand lizards as well as representatives of the first and second outgroups and analyzed using both parsimony and likeli… Show more

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Cited by 79 publications
(56 citation statements)
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“…However, a partitioning strategy not suited for portraying the evolutionary characteristics that results in a worse fit scenario of the data only increases the risk of a major source of phylogenetic error (Brown and Lemmon, 2007 Table 3 for justification for the partition strategy. and Queiroz, 2000). These types of phylogenetic errors may be defined as errors in estimating a parameter due to an inappropriate partitioning strategy or violations of assumptions in the method of estimation (Brandley et al, 2005), which is particularly troublesome in that it may result in well-supported but erroneous relationships.…”
Section: Differences In Bayesian Phylogenetic Estimates Between Analymentioning
confidence: 99%
“…However, a partitioning strategy not suited for portraying the evolutionary characteristics that results in a worse fit scenario of the data only increases the risk of a major source of phylogenetic error (Brown and Lemmon, 2007 Table 3 for justification for the partition strategy. and Queiroz, 2000). These types of phylogenetic errors may be defined as errors in estimating a parameter due to an inappropriate partitioning strategy or violations of assumptions in the method of estimation (Brandley et al, 2005), which is particularly troublesome in that it may result in well-supported but erroneous relationships.…”
Section: Differences In Bayesian Phylogenetic Estimates Between Analymentioning
confidence: 99%
“…Sequence for this region of mitochondrial DNA was not available for Uma scoparia; instead its sister species Uma notata was used (Wilgenbusch & De Queiroz 2000). Likelihood settings from best-fit model GTRCGCI were selected using Model test v. 3.06, with optimal model parameters of: empirical base frequencies (AZ0.426; CZ0.314; GZ0.063; TZ0.197); substitution rates (A : CZ0.493; A : GZ3.809; A : TZ0.660; C : GZ 0.357; C : TZ4.829; G : TZ1.000); gamma shape (0.655); and proportion of variable sites (0.139).…”
Section: Methodsmentioning
confidence: 99%
“…We performed ML analyses under the optimal model (Appendix 2) with the heuristic search algorithm using TBR branch swapping with 10 random sequence additions, simultaneously estimating parameter values (with 10 Γ rate categories) and tree topology (i.e., no initial parameter estimates or starting tree). We then successively re-estimated parameter values and searched for trees until we obtained a stable topology and ML score (Wilgenbusch and de Queiroz, 2000). We assessed nodal Parham et al 12 support with 10 bootstrap pseudoreplicates using TBR branch swapping and 10 random sequence additions.…”
Section: Phylogenetic Analysesmentioning
confidence: 99%