MTML-msBayes uses hierarchical approximate Bayesian computation (HABC) under a coalescent model to infer temporal patterns of divergence and gene flow across codistributed taxon-pairs. Under a model ...of multiple codistributed taxa that diverge into taxon-pairs with subsequent gene flow or isolation, one can estimate hyper-parameters that quantify the mean and variability in divergence times or test models of migration and isolation. The software uses multi-locus DNA sequence data collected from multiple taxon-pairs and allows variation across taxa in demographic parameters as well as heterogeneity in DNA mutation rates across loci. The method also allows a flexible sampling scheme: different numbers of loci of varying length can be sampled from different taxon-pairs.
Simulation tests reveal increasing power with increasing numbers of loci when attempting to distinguish temporal congruence from incongruence in divergence times across taxon-pairs. These results are robust to DNA mutation rate heterogeneity. Estimating mean divergence times and testing simultaneous divergence was less accurate with migration, but improved if one specified the correct migration model. Simulation validation tests demonstrated that one can detect the correct migration or isolation model with high probability, and that this HABC model testing procedure was greatly improved by incorporating a summary statistic originally developed for this task (Wakeley's ΨW). The method is applied to an empirical data set of three Australian avian taxon-pairs and a result of simultaneous divergence with some subsequent gene flow is inferred.
To retain flexibility and compatibility with existing bioinformatics tools, MTML-msBayes is a pipeline software package consisting of Perl, C and R programs that are executed via the command line. Source code and binaries are available for download at http://msbayes.sourceforge.net/ under an open source license (GNU Public License).
The drivers of tropical speciation Smith, Brian Tilston; McCormack, John E; Cuervo, Andrés M ...
Nature,
2014-Nov-20, 2014-11-20, 20141120, Letnik:
515, Številka:
7527
Journal Article
Recenzirano
Odprti dostop
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.
Tens of millions of dried seahorses (genus Hippocampus) are traded annually, and the pressure from this trade along with their life history traits (involved parental care and small migration ...distances and home ranges) has led to near global population declines. This and other forms of overexploitation have led to all seahorse species being listed in Appendix II under the Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES). The signatory nations of CITES recommended a 10-cm size limit of seahorses to ensure harvested individuals have reached reproductive maturity, and have thus had the chance to produce offspring, to maintain a more sustainable global seahorse fishery. We assessed adherence to CITES recommendations using DNA barcoding and size measurements to compare two prominent U.S. dried seahorse markets: (1) traditional Chinese medicine (TCM), and (2) non-medicinal ecommerce and coastal curio (ECC). We also estimated U.S. import abundance from CITES records. Of the nine species identified among all samples (n = 532), eight were found in the TCM trade (n = 168); composed mostly (75%) of the Indo-Pacific species Hippocampus trimaculatus, and Hippocampus spinosissimus, and the Latin American Hippocampus ingens. In contrast, ECC samples (n = 344) included 5 species, primarily juvenile Indo-Pacific Hippocampus kuda (51.5%) and the western Atlantic Hippocampus zosterae (40.7). The majority of TCM samples (85.7%) met the CITES size recommendation, in contrast to 4.8% of ECC samples. These results suggest non-size discriminatory bycatch is the most likely source of imported ECC specimens. In addition, CITES records indicate that approximately 602,275 dried specimens were imported into the U.S. from 2004-2020, but the exact species composition remains unknown as many U.S. imports records list one species or Hippocampus spp. from confiscated shipments due to difficulties in morphological identification and large numbers of individuals per shipment. Molecular identification was used to identify the species composition of confiscated shipment imports containing undesignated species, and similar to TCM, found H. trimaculatus and H. spinosissimus the most abundant. By combining DNA barcoding, size comparisons, and CITES database records, these results provide an important glimpse into the two primary dried U.S. seahorse end-markets, and may further inform the conservation status of several Hippocampus species.
Understanding population structure and areas of demographic persistence and transients is critical for effective species management. However, direct observational evidence to address the geographic ...scale and delineation of ephemeral or persistent populations for many marine fishes is limited. The Lined seahorse (Hippocampus erectus) can be commonly found in three western Atlantic zoogeographic provinces, though inhabitants of the temperate northern Virginia Province are often considered tropical vagrants that only arrive during warm seasons from the southern provinces and perish as temperatures decline. Although genetics can locate regions of historical population persistence and isolation, previous evidence of Virginia Province persistence is only provisional due to limited genetic sampling (i.e., mitochondrial DNA and five nuclear loci). To test alternative hypotheses of historical persistence versus the ephemerality of a northern Virginia Province population we used a RADseq generated dataset consisting of 11,708 single nucleotide polymorphisms (SNP) sampled from individuals collected from the eastern Gulf of Mexico to Long Island, NY. Concordant results from genomic analyses all infer three genetically divergent subpopulations, and strongly support Virginia Province inhabitants as a genetically diverged and a historically persistent ancestral gene pool. These results suggest that individuals that emerge in coastal areas during the warm season can be considered "local" and supports offshore migration during the colder months. This research demonstrates how a large number of genes sampled across a geographical range can capture the diversity of coalescent histories (across loci) while inferring population history. Moreover, these results clearly demonstrate the utility of population genomic data to infer peripheral subpopulation persistence in difficult-to-observe species.
Aim
Quantifying abundance distributions is critical for understanding both how communities assemble, and how community structure varies through time and space, yet estimating abundances requires ...considerable investment in fieldwork. Community‐level population genetic data potentially offer a powerful way to indirectly infer richness, abundance and the history of accumulation of biodiversity within a community. Here we introduce a joint model linking neutral community assembly and comparative phylogeography to generate both community‐level richness, abundance and genetic variation under a neutral model, capturing both equilibrium and non‐equilibrium dynamics.
Location
Global.
Methods
Our model combines a forward‐time individual‐based community assembly process with a rescaled backward‐time neutral coalescent model of multi‐taxa population genetics. We explore general dynamics of genetic and abundance‐based summary statistics and use approximate Bayesian computation (ABC) to estimate parameters underlying the model of island community assembly. Finally, we demonstrate two applications of the model using community‐scale mtDNA sequence data and densely sampled abundances of an arachnid community on La Réunion. First, we use genetic data alone to estimate a summary of the abundance distribution, ground‐truthing this against the observed abundances. Then, we jointly use the observed genetic data and abundances to estimate the proximity of the community to equilibrium.
Results
Simulation experiments of our ABC procedure demonstrate that coupling abundance with genetic data leads to improved accuracy and precision of model parameter estimates compared with using abundance‐only data. We further demonstrate reasonable precision and accuracy in estimating a metric underlying the shape of the abundance distribution, temporal progress towards local equilibrium and several key parameters of the community assembly process. For the insular arachnid assemblage, we find the joint distribution of genetic diversity and abundance approaches equilibrium expectations, and that the Shannon entropy of the observed abundances can be estimated using genetic data alone.
Main conclusions
The framework that we present unifies neutral community assembly and comparative phylogeography to characterize the community‐level distribution of both abundance and genetic variation through time, providing a resource that should greatly enhance understanding of both the processes structuring ecological communities and the associated aggregate demographic histories.
Biodiversity hotspots, representing regions with high species endemism and conservation threat, have been mapped globally. Yet, biodiversity distribution data from within hotspots are too sparse for ...effective conservation in the face of rapid environmental change. Using frogs as indicators, ecological niche models under paleoclimates, and simultaneous Bayesian analyses of multispecies molecular data, we compare alternative hypotheses of assemblage-scale response to late Quaternary climate change. This reveals a hotspot within the Brazilian Atlantic forest hotspot. We show that the southern Atlantic forest was climatically unstable relative to the central region, which served as a large climatic refugium for neotropical species in the late Pleistocene. This sets new priorities for conservation in Brazil and establishes a validated approach to biodiversity prediction in other understudied, species-rich regions.
With increasing force, genetic divergence of mitochondrial DNA (mtDNA) is being argued as the primary tool for discovery of animal species. Two thresholds of single-gene divergence have been ...proposed: reciprocal monophyly, and 10 times greater genetic divergence between than within species (the “10× rule”). To explore quantitatively the utility of each approach, we couple neutral coalescent theory and the classical Bateson-Dobzhansky-Muller (BDM) model of speciation. The joint stochastic dynamics of these two processes demonstrate that both thresholds fail to “discover” many reproductively isolated lineages under a single incompatibility BDM model, especially when BDM loci have been subject to divergent selection. Only when populations have been isolated for > 4 million generations did these thresholds achieve error rates of <10% under our model that incorporates variable population sizes. The high error rate evident in simulations is corroborated with six empirical data sets. These properties suggest that single-gene, high-throughput approaches to discovering new animal species will bias large-scale biodiversity surveys, particularly toward missing reproductively isolated lineages that have emerged by divergent selection or other mechanisms that accelerate reproductive isolation. Because single-gene thresholds for species discovery can result in substantial error at recent divergence times, they will misrepresent the correspondence between recently isolated populations and reproductively isolated lineages (= species).
Although testing for simultaneous divergence (vicariance) across different population-pairs that span the same barrier to gene flow is of central importance to evolutionary biology, researchers often ...equate the gene tree and population/species tree thereby ignoring stochastic coalescent variance in their conclusions of temporal incongruence. In contrast to other available phylogeographic software packages, msBayes is the only one that analyses data from multiple species/population pairs under a hierarchical model.
msBayes employs approximate Bayesian computation (ABC) under a hierarchical coalescent model to test for simultaneous divergence (TSD) in multiple co-distributed population-pairs. Simultaneous isolation is tested by estimating three hyper-parameters that characterize the degree of variability in divergence times across co-distributed population pairs while allowing for variation in various within population-pair demographic parameters (sub-parameters) that can affect the coalescent. msBayes is a software package consisting of several C and R programs that are run with a Perl "front-end".
The method reasonably distinguishes simultaneous isolation from temporal incongruence in the divergence of co-distributed population pairs, even with sparse sampling of individuals. Because the estimate step is decoupled from the simulation step, one can rapidly evaluate different ABC acceptance/rejection conditions and the choice of summary statistics. Given the complex and idiosyncratic nature of testing multi-species biogeographic hypotheses, we envision msBayes as a powerful and flexible tool for tackling a wide array of difficult research questions that use population genetic data from multiple co-distributed species. The msBayes pipeline is available for download at http://msbayes.sourceforge.net/ under an open source license (GNU Public License). The msBayes pipeline is comprised of several C and R programs that are run with a Perl "front-end" and runs on Linux, Mac OS-X, and most POSIX systems. Although the current implementation is for a single locus per species-pair, future implementations will allow analysis of multi-loci data per species pair.
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•Multi-locus coalescent analyses reveal cryptic sympatric lineages within co-distributed Hylomyscus and Sylvisorex.•Concordance of spatial but not temporal patterns of ...diversification.•Pleistocene persistence of small mammals in Kenyan Highlands refugia inferred from time-calibrated species tree.•Lineage diversification associated with Plio-Pleistocene climatic changes.•Results have taxonomic and conservation implications for understudied biodiversity hotspot.
The Eastern Afromontane region of Africa is characterized by striking levels of endemism and species richness accompanied by significant conservation threat, a pattern typical across biodiversity hotspots. Using multi-locus molecular data under a coalescent species tree framework we identify major cryptic biogeographic patterns within and between two endemic montane small mammal species complexes, Hylomyscus mice and Sylvisorex shrews, co-distributed across the Albertine Rift and Kenya Highlands of the Eastern Afromontane Biodiversity Hotspot (EABH). Hypotheses put forward to account for the high diversity of the region include retention of older palaeo-endemic lineages across major regions in climatically stable refugia, as well as the accumulation of lineages associated with more recent differentiation between allopatric populations separated by unsuitable habitat during periods of Pleistocene aridification. Sympatric pairs of sister lineages were found to have significantly older divergence times than allopatric pairs. Genetic analyses and historical distribution modeling suggest that regional meta-populations have persisted since the Pliocene to mid-Pleistocene across a climatic gradient from the Albertine Rift in the west to the Kenya Highlands in the east for both focal taxa. Differing patterns of regional sub-division and demographic expansion were detected and are consistent with differing life histories as well as shared responses to regional variation in stability of suitable habitat. There is also strong support in both mice and shrew species for Late Miocene divergence with subsequent range expansion into sympatry in previously unidentified cryptic species pairs. These results highlight the broad temporal scale at which climatic and geological changes may have facilitated rare dispersal events between montane habitats as well as the long-term persistence of populations in both the Albertine Rift and the Kenyan Highlands that together contributed to the high species diversity and endemism in the EABH.
Biodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Within ecological communities drift, dispersal, speciation, and selection operate ...simultaneously to shape patterns of biodiversity. Reconciling the relative importance of these is hindered by current models and inference methods, which tend to focus on a subset of processes and their resulting predictions. Here we introduce massive ecoevolutionary synthesis simulations (MESS), a unified mechanistic model of community assembly, rooted in classic island biogeography theory, which makes temporally explicit joint predictions across three biodiversity data axes: (i) species richness and abundances, (ii) population genetic diversities, and (iii) trait variation in a phylogenetic context. Using simulations we demonstrate that each data axis captures information at different timescales, and that integrating these axes enables discriminating among previously unidentifiable community assembly models. MESS is unique in generating predictions of community‐scale genetic diversity, and in characterizing joint patterns of genetic diversity, abundance, and trait values. MESS unlocks the full potential for investigation of biodiversity processes using multidimensional community data including a genetic component, such as might be produced by contemporary eDNA or metabarcoding studies. We combine MESS with supervised machine learning to fit the parameters of the model to real data and infer processes underlying how biodiversity accumulates, using communities of tropical trees, arthropods, and gastropods as case studies that span a range of data availability scenarios, and spatial and taxonomic scales.