Habitat specialization predicts demographic response and vulnerability of floodplain birds in Amazonia.

The annual flooding cycle of Amazonian rivers sustains the largest floodplains on Earth, which harbour a unique bird community. Recent studies suggest that habitat specialization drove different patterns of population structure and gene flow in floodplain birds. However, the lack of a direct estimate of habitat affinity prevents a proper test of its effects on population histories. In this work, we used occurrence data, satellite images and genomic data (ultra-conserved elements) from 24 bird species specialized on a variety of seasonally flooded environments to classify habitat affinities and test its influence on evolutionary histories of Amazonian floodplain birds. We demonstrate that birds with higher specialization in river islands and dynamic environments have gone through more recent demographic expansion and currently have less genetic diversity than floodplain generalist birds. Our results indicate that there is an intrinsic relationship between habitat affinity and environmental dynamics, influencing patterns of population structure, demographic history and genetic diversity. Within the floodplains, historical landscape changes have had more severe impacts on island specialists, making them more vulnerable to current and future anthropogenic changes, as those imposed by hydroelectric dams in the Amazon Basin.

Evidence of introgression, ecological divergence and adaptation in Asterias sea stars.

Hybrid zones are important windows into the evolutionary dynamics of populations, revealing how processes like introgression and adaptation structure population genomic variation. Importantly, they are useful for understanding speciation and how species respond to their environments. Here, we investigate two closely related sea star species, Asterias rubens and A. forbesi, distributed along rocky European and North American coastlines of the North Atlantic, and use genome-wide molecular markers to infer the distribution of genomic variation within and between species in this group. Using genomic data and environmental niche modelling, we document hybridization occurring between northern New England and the southern Canadian Maritimes. We investigate the factors that maintain this hybrid zone, as well as the environmental variables that putatively drive selection within and between species. We find that the two species differ in their environmental niche breadth; Asterias forbesi displays a relatively narrow environmental niche while conversely, A. rubens has a wider niche breadth. Species distribution models accurately predict hybrids to occur within environmental niche overlap, thereby suggesting environmental selection plays an important role in the maintenance of the hybrid zone. Our results imply that the distribution of genomic variation in North Atlantic sea stars is influenced by the environment, which will be crucial to consider as the climate changes.

Riverscape genomics of cichlid fishes in the lower Congo: Uncovering mechanisms of diversification in an extreme hydrological regime.

Freshwater fishes are notably diverse, given that freshwater habitat represents a tiny fraction of the earth's surface, but the mechanisms generating this diversity remain poorly understood. Rivers provide excellent models to understand how freshwater diversity is generated and maintained across heterogeneous habitats. In particular, the lower Congo River (LCR) consists of a dynamic hydroscape exhibiting extraordinary aquatic biodiversity, endemicity, morphological and ecological specialization. Previous studies have suggested that the numerous high-energy rapids throughout the LCR form physical barriers to gene flow, thus facilitating diversification and speciation, generating ichthyofaunal diversity. However, this hypothesis has not been fully explored using genome-wide SNPs for fish species distributed across the LCR. Here, we examined four lamprologine cichlids endemic to the LCR that are distributed along the river without range overlap. Using genome-wide SNP data, we tested the hypotheses that high-energy rapids serve as physical barriers to gene flow that generate genetic divergence at interspecific and intraspecific levels, and that gene flow occurs primarily in a downstream direction. Our results are consistent with the prediction that powerful rapids sometimes act as a barrier to gene flow but also suggest that, at certain temporal and spatial scales, they may provide multidirectional dispersal opportunities for riverine rheophilic cichlid fishes. These results highlight the complexity of diversification processes in rivers and the importance of assessing such processes across different riverscapes.

Genomic scale data shows that Parastacus nicoleti encompasses more than one species of burrowing continental crayfishes and that lineage divergence occurred with and without gene flow.

Delimiting species is a challenge, especially in scenarios of diversification with gene flow and when species are now allopatric where reproductive isolation cannot be directly tested. Continental burrowing crayfishes of the genus Parastacus present a disjoint distribution in southern South America. One of the species is P. nicoleti, which lives in underground waters in swampy and wooded areas of southern Chile. A previous assessment based on mitochondrial DNA sequences suggest that the taxon may represent a species complex. Here, using thousands of nuclear genomic single-nucleotide polymorphisms obtained via RADSeq from 81 specimens collected at 27 localities throughout the distributional range of the species, we apply an integrative species delimitation approach to test species boundaries and to investigate some aspects of the speciation process. Our analyses corroborate previous results; a scenario that we favor suggests that the P. nicoleti encompasses seven distinct species. Additionally, demographic analyses show that the distinct species have followed distinct trajectories in size change during the last 17.5 million years and that speciation in this group occurred both in strict isolation as well as in the presence of gene flow.

Asymmetrical gene flow in five co-distributed syngnathids explained by ocean currents and rafting propensity.

Ocean circulation driving macro-algal rafting is believed to serve as an important mode of dispersal for many marine organisms, leading to predictions on population-level genetic connectivity and the directionality of effective dispersal. Here, we use genome-wide single nucleotide polymorphism data to investigate whether gene flow directionality in two seahorses (Hippocampus) and three pipefishes (Syngnathus) follows the predominant ocean circulation patterns in the Gulf of Mexico and northwestern Atlantic. In addition, we explore whether gene flow magnitudes are predicted by traits related to active dispersal ability and habitat preference. We inferred demographic histories of these co-distributed syngnathid species, and coalescent model-based estimates indicate that gene flow directionality is in agreement with ocean circulation data that predicts eastward and northward macro-algal transport. However, the magnitude to which ocean currents influence this pattern appears strongly dependent on the species-specific traits related to rafting propensity and habitat preferences. Higher levels of gene flow and stronger directionality are observed in Hippocampus erectus, Syngnathus floridae and Syngnathus louisianae, which closely associated with the pelagic macro-algae Sargassum spp., compared to Hippocampus zosterae and the Syngnathus scovelli/Syngnathus fuscus sister-species pair, which prefer near shore habitats and are weakly associated with pelagic Sargassum. This study highlights how the combination of population genomic inference together with ocean circulation data can help explain patterns of population structure and diversity in marine ecosystems.

The drivers of tropical speciation.

Since the recognition that allopatric speciation can be induced by large-scale reconfigurations of the landscape that isolate formerly continuous populations, such as the separation of continents by plate tectonics, the uplift of mountains or the formation of large rivers, landscape change has been viewed as a primary driver of biological diversification. This process is referred to in biogeography as vicariance. In the most species-rich region of the world, the Neotropics, the sundering of populations associated with the Andean uplift is ascribed this principal role in speciation. An alternative model posits that rather than being directly linked to landscape change, allopatric speciation is initiated to a greater extent by dispersal events, with the principal drivers of speciation being organism-specific abilities to persist and disperse in the landscape. Landscape change is not a necessity for speciation in this model. Here we show that spatial and temporal patterns of genetic differentiation in Neotropical birds are highly discordant across lineages and are not reconcilable with a model linking speciation solely to landscape change. Instead, the strongest predictors of speciation are the amount of time a lineage has persisted in the landscape and the ability of birds to move through the landscape matrix. These results, augmented by the observation that most species-level diversity originated after episodes of major Andean uplift in the Neogene period, suggest that dispersal and differentiation on a matrix previously shaped by large-scale landscape events was a major driver of avian speciation in lowland Neotropical rainforests.

Phenotypic and Genetic Structure Support Gene Flow Generating Gene Tree Discordances in an Amazonian Floodplain Endemic Species.

Before populations become independent evolutionary lineages, the effects of micro evolutionary processes tend to generate complex scenarios of diversification that may affect phylogenetic reconstruction. Not accounting for gene flow in species tree estimates can directly impact topology, effective population sizes and branch lengths, and the resulting estimation errors are still poorly understood in wild populations. In this study, we used an integrative approach, including sequence capture of ultra-conserved elements (UCEs), mtDNA Sanger sequencing and morphological data to investigate species limits and phylogenetic relationships in face of gene flow in an Amazonian endemic species (Myrmoborus lugubris: Aves). We used commonly implemented species tree and model-based approaches to understand the potential effects of gene flow in phylogenetic reconstructions. The genetic structure observed was congruent with the four recognized subspecies of M. lugubris. Morphological and UCEs data supported the presence of a wide hybrid zone between M. l. femininus from the Madeira river and M. l. lugubris from the Middle and lower Amazon river, which were recovered as sister taxa by species tree methods. When fitting gene flow into simulated demographic models with different topologies, the best-fit model indicated these two taxa as non-sister lineages, a finding that is in agreement with the results of mitochondrial and morphological analyses. Our results demonstrated that failing to account for gene flow when estimating phylogenies at shallow divergence levels can generate topological uncertainty, which can nevertheless be statistically well supported, and that model testing approaches using simulated data can be useful tools to test alternative phylogenetic hypotheses.

Inferring responses to climate dynamics from historical demography in neotropical forest lizards.

We apply a comparative framework to test for concerted demographic changes in response to climate shifts in the neotropical lowland forests, learning from the past to inform projections of the future. Using reduced genomic (SNP) data from three lizard species codistributed in Amazonia and the Atlantic Forest (Anolis punctatus, Anolis ortonii, and Polychrus marmoratus), we first reconstruct former population history and test for assemblage-level responses to cycles of moisture transport recently implicated in changes of forest distribution during the Late Quaternary. We find support for population shifts within the time frame of inferred precipitation fluctuations (the last 250,000 y) but detect idiosyncratic responses across species and uniformity of within-species responses across forest regions. These results are incongruent with expectations of concerted population expansion in response to increased rainfall and fail to detect out-of-phase demographic syndromes (expansions vs. contractions) across forest regions. Using reduced genomic data to infer species-specific demographical parameters, we then model the plausible spatial distribution of genetic diversity in the Atlantic Forest into future climates (2080) under a medium carbon emission trajectory. The models forecast very distinct trajectories for the lizard species, reflecting unique estimated population densities and dispersal abilities. Ecological and demographic constraints seemingly lead to distinct and asynchronous responses to climatic regimes in the tropics, even among similarly distributed taxa. Incorporating such constraints is key to improve modeling of the distribution of biodiversity in the past and future.

Strategies for improving approximate Bayesian computation tests for synchronous diversification.

BACKGROUND: Estimating the variability in isolation times across co-distributed taxon pairs that may have experienced the same allopatric isolating mechanism is a core goal of comparative phylogeography. The use of hierarchical Approximate Bayesian Computation (ABC) and coalescent models to infer temporal dynamics of lineage co-diversification has been a contentious topic in recent years. Key issues that remain unresolved include the choice of an appropriate prior on the number of co-divergence events (Ψ), as well as the optimal strategies for data summarization. METHODS: Through simulation-based cross validation we explore the impact of the strategy for sorting summary statistics and the choice of prior on Ψ on the estimation of co-divergence variability. We also introduce a new setting (ß) that can potentially improve estimation of Ψ by enforcing a minimal temporal difference between pulses of co-divergence. We apply this new method to three empirical datasets: one dataset each of co-distributed taxon pairs of Panamanian frogs and freshwater fishes, and a large set of Neotropical butterfly sister-taxon pairs. RESULTS: We demonstrate that the choice of prior on Ψ has little impact on inference, but that sorting summary statistics yields substantially more reliable estimates of co-divergence variability despite violations of assumptions about exchangeability. We find the implementation of ß improves estimation of Ψ, with improvement being most dramatic given larger numbers of taxon pairs. We find equivocal support for synchronous co-divergence for both of the Panamanian groups, but we find considerable support for asynchronous divergence among the Neotropical butterflies. CONCLUSIONS: Our simulation experiments demonstrate that using sorted summary statistics results in improved estimates of the variability in divergence times, whereas the choice of hyperprior on Ψ has negligible effect. Additionally, we demonstrate that estimating the number of pulses of co-divergence across co-distributed taxon-pairs is improved by applying a flexible buffering regime over divergence times. This improves the correlation between Ψ and the true variability in isolation times and allows for more meaningful interpretation of this hyperparameter. This will allow for more accurate identification of the number of temporally distinct pulses of co-divergence that generated the diversification pattern of a given regional assemblage of sister-taxon-pairs.

Comment on Rieux and Balloux: calibration from tip-dating can compromise topological accuracy and evolutionary inference.

We contribute to the recent review of Rieux & Balloux, 2016, Mol. Ecol., 25, 1911 on inferences from tip-dated phylogenies by developing their discussion on the influence of population size (Ne ) under panmixia for the estimation of substitution rate (µ). We highlight how phylogenetic trees inferred with tip-dated sequences under large panmictic Ne tend to erroneously enforce an age-based coalescent pattern on the posterior distribution of trees, which in turn results in systematically inflated estimates of µ. We discuss the consequences of this and suggest how to accommodate the issue in the short term and long term.

Behavioural response to song and genetic divergence in two subspecies of white-crowned sparrows (Zonotrichia leucophrys).

Divergence in sexual signals may drive reproductive isolation between lineages, but behavioural barriers can weaken in contact zones. Here, we investigate the role of song as a behavioural and genetic barrier in a contact zone between two subspecies of white-crowned sparrows (Zonotrichia leucophrys). We employed a reduced genomic data set to assess population structure and infer the history underlying divergence, gene flow and hybridization. We also measured divergence in song and tested behavioural responses to song using playback experiments within and outside the contact zone. We found that the subspecies form distinct genetic clusters, and demographic inference supported a model of secondary contact. Song phenotype, particularly length of the first note (a whistle), was a significant predictor of genetic subspecies identity and genetic distance along the hybrid zone, suggesting a close link between song and genetic divergence in this system. Individuals from both parental and admixed localities responded significantly more strongly to their own song than to the other subspecies song, supporting song as a behavioural barrier. Putative parental and admixed individuals were not significantly different in their strength of discrimination between own and other songs; however, individuals from admixed localities tended to discriminate less strongly, and this difference in discrimination strength was explained by song dissimilarity as well as genetic distance. Therefore, we find that song acts as a reproductive isolating mechanism that is potentially weakening in a contact zone between the subspecies. Our findings also support the hypothesis that intraspecific song variation can reduce gene flow between populations.

Asynchronous demographic responses to Pleistocene climate change in Eastern Nearctic vertebrates.

Pleistocene climatic cycles altered species distributions in the Eastern Nearctic of North America, yet the degree of congruent demographic response to the Pleistocene among codistributed taxa remains unknown. We use a hierarchical approximate Bayesian computational approach to test if population sizes across lineages of snakes, lizards, turtles, mammals, birds, salamanders and frogs in this region expanded synchronously to Late Pleistocene climate changes. Expansion occurred in 75% of 74 lineages, and of these, population size trajectories across the community were partially synchronous, with coexpansion found in at least 50% of lineages in each taxonomic group. For those taxa expanding outside of these synchronous pulses, factors related to when they entered the community, ecological thresholds or biotic interactions likely condition their timing of response to Pleistocene climate change. Unified timing of population size change across communities in response to Pleistocene climate cycles is likely rare in North America.

Predicting the genetic consequences of future climate change: The power of coupling spatial demography, the coalescent, and historical landscape changes.

PREMISE OF THE STUDY: Climate change is a widely accepted threat to biodiversity. Species distribution models (SDMs) are used to forecast whether and how species distributions may track these changes. Yet, SDMs generally fail to account for genetic and demographic processes, limiting population-level inferences. We still do not understand how predicted environmental shifts will impact the spatial distribution of genetic diversity within taxa. METHODS: We propose a novel method that predicts spatially explicit genetic and demographic landscapes of populations under future climatic conditions. We use carefully parameterized SDMs as estimates of the spatial distribution of suitable habitats and landscape dispersal permeability under present-day, past, and future conditions. We use empirical genetic data and approximate Bayesian computation to estimate unknown demographic parameters. Finally, we employ these parameters to simulate realistic and complex models of responses to future environmental shifts. We contrast parameterized models under current and future landscapes to quantify the expected magnitude of change. KEY RESULTS: We implement this framework on neutral genetic data available from Penstemon deustus. Our results predict that future climate change will result in geographically widespread declines in genetic diversity in this species. The extent of reduction will heavily depend on the continuity of population networks and deme sizes. CONCLUSIONS: To our knowledge, this is the first study to provide spatially explicit predictions of within-species genetic diversity using climatic, demographic, and genetic data. Our approach accounts for climatic, geographic, and biological complexity. This framework is promising for understanding evolutionary consequences of climate change, and guiding conservation planning.

Urbanization shapes the demographic history of a native rodent (the white-footed mouse, Peromyscus leucopus) in New York City.

How urbanization shapes population genomic diversity and evolution of urban wildlife is largely unexplored. We investigated the impact of urbanization on white-footed mice,Peromyscus leucopus,in the New York City (NYC) metropolitan area using coalescent-based simulations to infer demographic history from the site-frequency spectrum. We assigned individuals to evolutionary clusters and then inferred recent divergence times, population size changes and migration using genome-wide single nucleotide polymorphisms genotyped in 23 populations sampled along an urban-to-rural gradient. Both prehistoric climatic events and recent urbanization impacted these populations. Our modelling indicates that post-glacial sea-level rise led to isolation of mainland and Long Island populations. These models also indicate that several urban parks represent recently isolated P. leucopus populations, and the estimated divergence times for these populations are consistent with the history of urbanization in NYC.

Detecting concerted demographic response across community assemblages using hierarchical approximate Bayesian computation.

Methods that integrate population-level sampling from multiple taxa into a single community-level analysis are an essential addition to the comparative phylogeographic toolkit. Detecting how species within communities have demographically tracked each other in space and time is important for understanding the effects of future climate and landscape changes and the resulting acceleration of extinctions, biological invasions, and potential surges in adaptive evolution. Here, we present a statistical framework for such an analysis based on hierarchical approximate Bayesian computation (hABC) with the goal of detecting concerted demographic histories across an ecological assemblage. Our method combines population genetic data sets from multiple taxa into a single analysis to estimate: 1) the proportion of a community sample that demographically expanded in a temporally clustered pulse and 2) when the pulse occurred. To validate the accuracy and utility of this new approach, we use simulation cross-validation experiments and subsequently analyze an empirical data set of 32 avian populations from Australia that are hypothesized to have expanded from smaller refugia populations in the late Pleistocene. The method can accommodate data set heterogeneity such as variability in effective population size, mutation rates, and sample sizes across species and exploits the statistical strength from the simultaneous analysis of multiple species. This hABC framework used in a multitaxa demographic context can increase our understanding of the impact of historical climate change by determining what proportion of the community responded in concert or independently and can be used with a wide variety of comparative phylogeographic data sets as biota-wide DNA barcoding data sets accumulate.

The aggregate site frequency spectrum for comparative population genomic inference.

Understanding how assemblages of species responded to past climate change is a central goal of comparative phylogeography and comparative population genomics, an endeavour that has increasing potential to integrate with community ecology. New sequencing technology now provides the potential to perform complex demographic inference at unprecedented resolution across assemblages of nonmodel species. To this end, we introduce the aggregate site frequency spectrum (aSFS), an expansion of the site frequency spectrum to use single nucleotide polymorphism (SNP) data sets collected from multiple, co-distributed species for assemblage-level demographic inference. We describe how the aSFS is constructed over an arbitrary number of independent population samples and then demonstrate how the aSFS can differentiate various multispecies demographic histories under a wide range of sampling configurations while allowing effective population sizes and expansion magnitudes to vary independently. We subsequently couple the aSFS with a hierarchical approximate Bayesian computation (hABC) framework to estimate degree of temporal synchronicity in expansion times across taxa, including an empirical demonstration with a data set consisting of five populations of the threespine stickleback (Gasterosteus aculeatus). Corroborating what is generally understood about the recent postglacial origins of these populations, the joint aSFS/hABC analysis strongly suggests that the stickleback data are most consistent with synchronous expansion after the Last Glacial Maximum (posterior probability = 0.99). The aSFS will have general application for multilevel statistical frameworks to test models involving assemblages and/or communities, and as large-scale SNP data from nonmodel species become routine, the aSFS expands the potential for powerful next-generation comparative population genomic inference.

Lack of support for the time-dependent molecular evolution hypothesis.

There is increasing momentum surrounding the hypothesis that rates of molecular evolution between individuals within contemporary populations are high, and that these rates decrease as a function of time, perhaps over several millions of years, before reaching stationarity. The implications of this are powerful, potentially reshaping our view of how climate history impacts upon both species distribution patterns and the geographic structuring of genetic variation within species. However, our assessment of the hypothesis reveals a lack of theoretical support and empirical evidence for hypothesized magnitudes of time-dependent rates of molecular evolution, with much of the apparent rate changes coming from artefacts and biases inherent in the methods of rate estimation. Our assessment also reveals a problem with how serial sampling is implemented for mutation rate estimation using ancient DNA samples, rendering published estimates unreliable.

Model misspecification confounds the estimation of rates and exaggerates their time dependency.

While welcoming the comment of Ho et al. (2015), we find little that undermines the strength of our criticism, and it would appear they have misunderstood our central argument. Here we respond with the purpose of reiterating that we are (i) generally critical of much of the evidence presented in support of the time-dependent molecular rate (TDMR) hypothesis and (ii) specifically critical of estimates of µ derived from tip-dated sequences that exaggerate the importance of purifying selection as an explanation for TDMR over extended timescales. In response to assertions put forward by Ho et al. (2015), we use panmictic coalescent simulations of temporal data to explore a fundamental assumption for tip-dated tree shape and associated mutation rate estimates, and the appropriateness and utility of the date randomization test. The results reveal problems for the joint estimation of tree topology, effective population size and µ with tip-dated sequences using BEAST. Given the simulations, BEAST consistently obtains incorrect topological tree structures that are consistent with the substantial overestimation of µ and underestimation of effective population size. Data generated from lower effective population sizes were less likely to fail the date randomization test yet still resulted in substantially upwardly biased estimates of rates, bringing previous estimates of µ from temporally sampled DNA sequences into question. We find that our general criticisms of both the hypothesis of time-dependent molecular evolution and Bayesian methods to estimate µ from temporally sampled DNA sequences are further reinforced.

Sampling strategies for frequency spectrum-based population genomic inference.

BACKGROUND: The allele frequency spectrum (AFS) consists of counts of the number of single nucleotide polymorphism (SNP) loci with derived variants present at each given frequency in a sample. Multiple approaches have recently been developed for parameter estimation and calculation of model likelihoods based on the joint AFS from two or more populations. We conducted a simulation study of one of these approaches, implemented in the Python module δaδi, to compare parameter estimation and model selection accuracy given different sample sizes under one- and two-population models. RESULTS: Our simulations included a variety of demographic models and two parameterizations that differed in the timing of events (divergence or size change). Using a number of SNPs reasonably obtained through next-generation sequencing approaches (10,000 - 50,000), accurate parameter estimates and model selection were possible for models with more ancient demographic events, even given relatively small numbers of sampled individuals. However, for recent events, larger numbers of individuals were required to achieve accuracy and precision in parameter estimates similar to that seen for models with older divergence or population size changes. We quantify i) the uncertainty in model selection, using tools from information theory, and ii) the accuracy and precision of parameter estimates, using the root mean squared error, as a function of the timing of demographic events, sample sizes used in the analysis, and complexity of the simulated models. CONCLUSIONS: Here, we illustrate the utility of the genome-wide AFS for estimating demographic history and provide recommendations to guide sampling in population genomics studies that seek to draw inference from the AFS. Our results indicate that larger samples of individuals (and thus larger AFS) provide greater power for model selection and parameter estimation for more recent demographic events.