River network rearrangements promote speciation in lowland Amazonian birds

Abstract

Large Amazonian rivers impede dispersal for many species, but lowland river networks frequently rearrange, thereby altering the location and effectiveness of river barriers through time. These rearrangements may promote biotic diversification by facilitating episodic allopatry and secondary contact among populations. We sequenced genome-wide markers to evaluate the histories of divergence and introgression in six Amazonian avian species complexes. We first tested the assumption that rivers are barriers for these taxa and found that even relatively small rivers facilitate divergence. We then tested whether species diverged with gene flow and recovered reticulate histories for all species, including one potential case of hybrid speciation. Our results support the hypothesis that river rearrangements promote speciation and reveal that many rainforest taxa are micro-endemic, unrecognized, and thus threatened with imminent extinction. We propose that Amazonian hyper-diversity originates partly from fine-scale barrier displacement processes-including river dynamics-which allow small populations to differentiate and disperse into secondary contact.

Fig. 1.. Population genomic structure in six codistributed Amazonian bird species groups.

For each species, results of the best k value for STRUCTURE analysis of split datasets (left) and example replicates of the t-distributed stochastic neighbor embedding (t-SNE) analysis (right) are shown. Colored bars underneath the STRUCTURE plots and circles on the t-SNE plots are colored on the basis of major interfluvial regions in map 1 (top left). Map 2 (top right) shows the topography of the study region within the dark red box, where yellow contours represent the 250- to 300-m elevational zone demarcating dynamic lowland (<250 m; shaded in blue) from relatively stable upland (>300 m; shaded in red) basins. Map 3 (top right inset) shows precipitation during the driest annual quarter (76), with high precipitation in gray, low precipitation in red, and a strong cline across the middle to lower reaches of the rivers draining the Brazilian Shield (plotted using QGIS).

Fig. 2.. Summary of phylogenomic results for six Amazonian bird species groups examined in this study.

Results of species tree analysis in ASTRAL (41) showing the historical relationships among a priori defined populations in each species inferred from thousands of gene trees. All nodes are recovered with 100% bootstrap support except where noted.

Fig. 3.. Effective migration (gene flow) results estimated in EEMS.

Results are shown for (left to right and top to bottom) G. cyanicollis, M. rufa, Hypocnemis spp., T. aethiops, P. nigromaculata, and Willisornis spp. Effective migration rate (m)—a measure of gene flow—is shown on a log₁₀ scale relative to the expected value under an IBD model across the sampled range. Darker blues correspond to higher effective migration rate, whereas darker oranges correspond to lower rates.

Fig. 4.. Effective diversity (dissimilarity) results estimated in EEMS.

Results are shown for (left to right and top to bottom) G. cyanicollis, M. rufa, Hypocnemis spp., T. aethiops, P. nigromaculata, and Willisornis spp. Effective diversity (q) is shown on a log₁₀ scale relative to the expected value under an IBD model across the sampled range. Darker blues correspond to higher genetic diversity (dissimilarity), whereas darker oranges correspond to lower diversity.

Fig. 5.. Rivers are the most important predictors of genomic divergence.

The plots show the results of the variance partitioning (commonality analysis) of the multivariate logistic regression model, D ~ DIST + ENV + RIV, where D is the pairwise genomic divergences across t-SNE space, DIST is the dispersal distance, ENV is the environmental disparity, and RIV is the separation by rivers. The commonality coefficients of seven predictors (three unique and four common) for each species represent the proportion of variance of pairwise genomic divergence among samples that are explained by each predictor or set of predictors. The percent total represents the proportion of variance explained by the overall multivariate model that is explained by each predictor or set of predictors. Confidence intervals of 95% around each value were computed using 1000 bootstrap replicates with subsampling of 90% of samples. The order of species is (from left to right beginning at the top) Galbula, Malacoptila, Hypocnemis, Thamnophilus, Phlegopsis, and Willisornis. Exact values for these parameters can be obtained in Table 2.

Fig. 6.. Summary of phylogenomic network results for six Amazonian bird species groups examined in this study.

(A) Results of Bayesian network analysis in PhyloNet (44) showing the most credible topology for each species group. Reticulate branches are shown in red and labeled with inheritance probabilities. Tips are labeled with taxonomic designations for all polytypic species groups. (B) Results from TreeMix showing the inferred topology among populations (black branches) and inferred admixture edges (red arrows). The thickness of each migration edge is proportional to its inferred magnitude. (C) Results of the model-fitting exercise in TreeMix. The y axes show the average log(likelihood) among all TreeMix replicates that varied in missing data thresholds for each value of m (the number of admixture edges). Circles at the tips of all networks are colored on the basis of a priori defined populations (Fig. 1, map 1). Because PhyloNet and TreeMix populations were assigned using the results from STRUCTURE (45), multiple a priori defined populations may be sampled in a given tip.