Colombia hosts the second highest amphibian species diversity on Earth, yet its fauna remains poorly studied, especially using molecular genetic techniques. We present the results of the first wide-scale DNA barcoding survey of anurans of Colombia, focusing on a transect across the Eastern Cordillera. We surveyed 10 sites between the Magdalena Valley to the west and the eastern foothills of the Eastern Cordillera, sequencing portions of the mitochondrial 16S ribosomal RNA and cytochrome oxidase subunit 1 (CO1) genes for 235 individuals from 52 nominal species. We applied two barcode algorithms, Automatic Barcode Gap Discovery and Refined Single Linkage Analysis, to estimate the number of clusters or “unconfirmed candidate species” supported by DNA barcode data. Our survey included ~7% of the anuran species known from Colombia. While barcoding algorithms differed slightly in the number of clusters identified, between three and ten nominal species may be obscuring candidate species (in some cases, more than one cryptic species per nominal species). Our data suggest that the high elevations of the Eastern Cordillera and the low elevations of the Chicamocha canyon acted as geographic barriers in at least seven nominal species, promoting strong genetic divergences between populations associated with the Eastern Cordillera.

Most global hotspots of biodiversity and endemism are in montane regions. One explanation is that montane regions have intrinsically higher speciation rates than lowland regions because complex mountain topography and climate variation facilitate genetic isolation among populations. Here, we ask from an intraspecific perspective whether frog species whose haplotypes are connected by topographically/climatically complex regions display strong genetic isolation (greater scaled genetic distances), compared with species whose haplotypes are connected by less complex regions. We analysed published DNA sequences of several frog species from tropical Central and South America for the mitochondrial cob, cox1 and 16S rRNA genes. Pairwise genetic distances among haplotypes within each species were scaled to the geographic distances between each pair of haplotypes. Topographic complexity was positively correlated with scaled genetic distances, and isolation-by-resistance was supported only in species from more topographically complex regions. This suggests that heterogeneous topographies increase landscape resistance, which in turn favours the appearance of isolation-by-resistance. Moreover, we found that the potential barriers that restrict gene flow within species are more closely related to factors associated with temperature and topography than to precipitation.

The tempo of evolutionary change through time is among the most heavily studied dimensions of macroevolution using phylogenies. Here, we present a simple, likelihood‐based method for comparing the rate of phenotypic evolution for continuous characters between trees. Our method is derived from a previous approach published by Brian O'Meara and colleagues in 2006. We examine the statistical performance of the method and find that it suffers from the typical downward bias expected for maximum likelihood estimates of the variance, but only for very small trees. We find that evolutionary rates are estimated with minimal bias for trees of even relatively modest size. We also find that type I error rates based on a likelihood‐ratio test are minimally elevated above the nominal level, even for small phylogenies. The type I error rate can be reduced to a level at or below its nominal value by substituting a test‐statistic distribution obtained via simulation under the null hypothesis of no difference in evolutionary rate among trees. We discuss the consequences of failing to account for uncertainty in the estimation of species means or in the phylogeny, and describe strategies for taking this uncertainty into consideration during estimation. We also identify how our approach is related to previous methods for comparing the rate of evolution among different clades of a single tree or between different phenotypic traits. Finally, we describe how the method can be applied to different evolutionary models and to discrete characters—options that are already implemented in software. Evolutionary biologists continue to be intrigued by changes in the tempo of phenotypic evolution across the tree of life. The method described herein should be useful for contexts in which changes in the evolutionary rate or process between two or more clades of distant or unknown relationship are of interest.