Resolving evolutionary relationships and establishing population structure depends on molecular diagnosability that is often limited for closely related taxa. Here, we use 3,200 ddRAD‐seq loci across 290 mallards, American black ducks, and putative hybrids to establish population structure and estimate hybridization rates. We test between traditional assignment probability and accumulated recombination events based analyses to assign hybrids to generational classes. For hybrid identification, we report the distribution of recombination events complements ADMIXTURE simulation by extending resolution past F4 hybrid status; however, caution against hybrid assignment based on accumulated recombination events due to an inability to resolve F1 hybrids. Nevertheless, both analyses suggest that there are relatively few backcrossed stages before a lineage's hybrid ancestry is lost and the offspring are effectively parental again. We conclude that despite high rates of observed interspecific hybridization between mallards and black ducks in the middle part of the 20th century, our results do not support the predicted hybrid swarm. Conversely, we report that mallard samples genetically assigned to western and non‐western clusters. We indicate that these non‐western mallards likely originated from game‐farm stock, suggesting landscape level gene flow between domestic and wild conspecifics.
When a lineage originates from hybridization genomic blocks of contiguous ancestry from different ancestors are fragmented through genetic recombination. The resulting blocks are delineated by so called junctions, which accumulate with every generation that passes. Modeling the accumulation of ancestry block junctions can elucidate processes and timeframes of genomic admixture. Previous models have not addressed ancestry block dynamics for chromosomes that consist of a finite number of recombination sites. However, genomic data typically consist of informative markers that are interspersed with fragments for which no ancestry information is available. Hence, repeated recombination events may occur between markers, effectively removing existing junctions. Here, we present an analytical treatment of the dynamics of the mean number of junctions over time, taking into account the number of recombination sites per chromosome, population size, genetic map length, and the frequency of the ancestral species in the founding hybrid swarm. We describe the expected number of junctions using equidistant molecular markers and estimate the number of junctions using random markers. This extended theory of junctions thus reflects properties of empirical data and can serve to study the genomic patterns following admixture.
1. Molecular phylogenies form a potential source of information on rates of diversification, and the mechanisms that underlie diversification patterns. Diversification models have become increasingly complex over the past decade, and we have reached a point where the computation of the analytical likelihood of the model given a phylogeny is either unavailable or intractable. For such models, a likelihood-free approach such as Approximate Bayesian Computation (ABC) offers a solution. ABC is a Bayesian framework that uses one or more summary statistics instead of the likelihood function. Crucial to the performance of an ABC algorithm is the choice of summary statistics. 2. Here, we analyse the applicability of three traditional and often-used summary statistics (Gamma statistic, Phylogenetic Diversity and tree size) within an ABC framework and propose a new summary statistic: the normalized Lineages-Through-Time (nLTT) statistic. 3. We find that the traditional summary statistics perform poorly and should not be used as a substitute of the likelihood. By contrast, we find that the nLTT statistic performs on par with the likelihood. 4. We suggest to include the nLTT statistic in future ABC applications within phylogenetics. We argue that the use of ABC in diversification rate analysis is a promising new approach, but that care should be taken which summary statistics are chosen.
The relative importance of niche‐based (e.g., competitive or stress‐based) and stochastic (e.g., random dispersal) processes in structuring ecological communities is frequently analyzed by studying trait distributions of co‐occurring species. While filtering processes, such as the exclusion of stress‐intolerant species from particular habitats, increase the trait similarity between co‐occurring species, other processes, such as resource competition, can limit the similarity of co‐occurring species. Comparing the observed trait distribution patterns in communities to null expectations from randomized communities (e.g., a draw of the same observed richness from the regional pool) therefore gives a first indication of the dominant process driving community assembly. However, such comparisons do not inform us about the relative contribution of these different processes in shaping community compositions in case of their joint operation (a likely scenario). Using an Approximate Bayesian Computation approach, we develop a new method that allows inference of the relative importance of dispersal, filtering, and limiting similarity processes for the assembly of observed communities with known species and trait composition. We applied this approach to a tree community data set, collected across 20 plots along strong rainfall and fire gradients in a South African savanna. Based on comparisons with simulations, we find that our new approach is powerful in identifying which community assembly scenario has the highest probability to generate the observed trait distribution patterns, while traditional null model comparisons perform poorly in detecting signs of limiting similarity. For the studied savanna tree communities, our analysis yields that dispersal processes are most important in shaping the functional trait distribution patterns. Furthermore, our models indicate that filtering processes were relatively most important in areas with high fire frequencies, while limiting similarity processes were relatively most important in areas with low fire frequency and high rainfall. We conclude that our new method is a promising improvement on current approaches to estimate the relative importance of community assembly processes across different species groups, ecosystems, and biomes. Future model modifications (e.g., the inclusion of individual‐based processes) could provide further steps in uncovering the underlying assembly processes behind observed community patterns.
One of the most striking patterns observed among animals is that smaller-bodied taxa are generally much more diverse than larger-bodied taxa. This observation seems to be explained by the mere fact that smaller-bodied taxa tend to have an older evolutionary origin and have therefore had more time to diversify. A few studies, based on the prevailing null model of diversification (i.e. the stochastic constant-rate birth–death model), have suggested that this is indeed the correct explanation, and body-size dependence of speciation and extinction rates does not play a role. However, there are several potential shortcomings to these studies: a suboptimal statistical procedure and a relatively narrow range of body sizes in the analysed data. Here, we present a more coherent statistical approach, maximizing the likelihood of the constant-rate birth–death model with allometric scaling of speciation and extinction rates, given data on extant diversity, clade age and average body size in each clade. We applied our method to a dataset compiled from the literature that includes a wide range of Metazoan taxa (range from midges to elephants). We find that the higher diversity among small animals is indeed, partly, caused by higher clade age. However, it is also partly caused by the body-size dependence of speciation and extinction rates. We find that both the speciation rate and extinction rate decrease with body size such that the net diversification rate is close to 0. Even more interestingly, the allometric scaling exponent of speciation and extinction rates is approximately −0.25, which implies that the per generation speciation and extinction rates are independent of body size. This suggests that the observed relationship between diversity and body size pattern can be explained by clade age alone, but only if clade age is measured in generations rather than years. Thus, we argue that the most parsimonious explanation for the observation that smaller-bodied taxa are more diverse is that their evolutionary clock ticks faster.
Hybridization between species can either promote or impede adaptation. But we know very little about the genetic basis of hybrid fitness, especially in nondomesticated organisms, and when populations are facing environmental stress. We made genetically variable F2 hybrid populations from two divergent Saccharomyces yeast species. We exposed populations to ten toxins and sequenced the most resilient hybrids on low coverage using ddRADseq to investigate four aspects of their genomes: 1) hybridity, 2) interspecific heterozygosity, 3) epistasis (positive or negative associations between nonhomologous chromosomes), and 4) ploidy. We used linear mixed-effect models and simulations to measure to which extent hybrid genome composition was contingent on the environment. Genomes grown in different environments varied in every aspect of hybridness measured, revealing strong genotype–environment interactions. We also found selection against heterozygosity or directional selection for one of the parental alleles, with larger fitness of genomes carrying more homozygous allelic combinations in an otherwise hybrid genomic background. In addition, individual chromosomes and chromosomal interactions showed significant species biases and pervasive aneuploidies. Against our expectations, we observed multiple beneficial, opposite-species chromosome associations, confirmed by epistasis- and selection-free computer simulations, which is surprising given the large divergence of parental genomes (∼15%). Together, these results suggest that successful, stress-resilient hybrid genomes can be assembled from the best features of both parents without paying high costs of negative epistasis. This illustrates the importance of measuring genetic trait architecture in an environmental context when determining the evolutionary potential of genetically diverse hybrid populations.
Geographic isolation that drives speciation is often assumed to slowly increase over time, for instance through the formation of rivers, the formation of mountains or the movement of tectonic plates. Cyclic changes in connectivity between areas may occur with the advancement and retraction of glaciers, with water level fluctuations in seas between islands or in lakes that have an uneven bathymetry. These habitat dynamics may act as a driver of allopatric speciation and propel local diversity. Here we present a parsimonious model of the interaction between cyclical (but not necessarily periodic) changes in the environment and speciation, and provide an ABC-SMC method to infer the rates of allopatric and sympatric speciation from a phylogenetic tree. We apply our approach to the posterior sample of an updated phylogeny of the Lamprologini, a tribe of cichlid fish from Lake Tanganyika where such cyclic changes in water level have occurred. We find that water level changes play a crucial role in driving diversity in Lake Tanganyika. We note that if we apply our analysis to the Most Credible Consensus (MCC) tree, we do not find evidence for water level changes influencing diversity in the Lamprologini, suggesting that the MCC tree is a misleading representation of the true species tree. Furthermore, we note that the signature of habitat dynamics is found in the posterior sample despite the fact that this sample was constructed using a species tree prior that ignores habitat dynamics. However, in other cases this species tree prior might erase this signature. Hence we argue that in order to improve inference of the effect of habitat dynamics on biodiversity, phylogenetic reconstruction methods should include tree priors that explicitly take into account such dynamics.
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