An adaptive radiation of frogs in a southeast Asian island archipelago

Abstract

Living amphibians exhibit a diversity of ecologies, life histories, and species-rich lineages that offers opportunities for studies of adaptive radiation. We characterize a diverse clade of frogs (Kaloula, Microhylidae) in the Philippine island archipelago as an example of an adaptive radiation into three primary habitat specialists or ecotypes. We use a novel phylogenetic estimate for this clade to evaluate the tempo of lineage accumulation and morphological diversification. Because species-level phylogenetic estimates for Philippine Kaloula are lacking, we employ dense population sampling to determine the appropriate evolutionary lineages for diversification analyses. We explicitly take phylogenetic uncertainty into account when calculating diversification and disparification statistics and fitting models of diversification. Following dispersal to the Philippines from Southeast Asia, Kaloula radiated rapidly into several well-supported clades. Morphological variation within Kaloula is partly explained by ecotype and accumulated at high levels during this radiation, including within ecotypes. We pinpoint an axis of morphospace related directly to climbing and digging behaviors and find patterns of phenotypic evolution suggestive of ecological opportunity with partitioning into distinct habitat specialists. We conclude by discussing the components of phenotypic diversity that are likely important in amphibian adaptive radiations.

Keywords: Comparative methods; Kaloula; disparity; diversification; ecomorphology; microhylidae.

Figure 1

Maximum-likelihood phylogram estimated from mitochondrial DNA sequences (12S and 16S ribosomal RNA genes) depicting the phylogenetic relationships of Kaloula (Anura: Microhylidae; see also Fig. S1). The gray box indicates the endemic Philippine radiation. Images of each species in the Philippine radiation are provided, except for the new species from Panay.

Figure 2

Relationship between morphological variation and ecotype categories in Kaloula. Species scores for the first two principal components (PC1 and PC2) are plotted; see Table4 for loadings and percent variance explained.

Figure 3

Disparification through relative time in Kaloula. Top-left panel shows MCCT chronogram (with shapes corresponding to ecotypes of Fig. 2) and top-right panel shows lineage-through-time plot. Middle and bottom panels show disparity-through-time (DTT) plots for PC1_phylo, PC2_phylo, PC3_phylo, and all three axes together (PC1–3_phylo). Solid black lines on DTT plots is observed disparity based on MCCT, gray lines and polygons represent median and 95% confidence intervals from BM simulations, respectively.

Figure 4

Uncertainty in disparification through time in Kaloula for PC1_phylo. Solid black line on DTT plot is observed disparity based on MCCT; gray polygons represent 95% confidence interval for observed disparity based on post–burn-in trees from BEAST analysis.