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Journal ArticleDOI

Considering Pleistocene North American wolves and coyotes in the eastern Canis origin story.

05 Jun 2021-Ecology and Evolution (John Wiley & Sons, Ltd)-Vol. 11, Iss: 13, pp 9137-9147
TL;DR: In this article, the authors re-analyze contemporary and ancient mitochondrial DNA genomes with Bayesian phylogenetic analyses to more accurately estimate divergence dates among lineages and combine that with a review of the literature on Late Pleistocene Canis distributions to identify potential Pleistogene progenitors to southern North American gray wolves and eastern wolves; and illuminate opportunities for ancient hybridization events.
Abstract: The evolutionary origins and hybridization patterns of Canis species in North America have been hotly debated for the past 30 years. Disentangling ancestry and timing of hybridization in Great Lakes wolves, eastern Canadian wolves, red wolves, and eastern coyotes are most often partitioned into a 2-species model that assigns all ancestry to gray wolves and/or coyotes, and a 3-species model that includes a third, North American evolved eastern wolf genome. The proposed models address recent or sometimes late Holocene hybridization events but have largely ignored potential Pleistocene era progenitors and opportunities for hybridization that may have impacted the current mixed genomes in eastern Canada and the United States. Here, we re-analyze contemporary and ancient mitochondrial DNA genomes with Bayesian phylogenetic analyses to more accurately estimate divergence dates among lineages. We combine that with a review of the literature on Late Pleistocene Canis distributions to: (a) identify potential Pleistocene progenitors to southern North American gray wolves and eastern wolves; and (b) illuminate opportunities for ancient hybridization events. Specifically, we propose that Beringian gray wolves (C. lupus) and extinct large wolf-like coyotes (C. latrans orcutti) are likely progenitors to Mexican and Plains gray wolves and eastern wolves, respectively, and may represent a potentially unrecognized source of introgressed genomic variation within contemporary Canis genomes. These events speak to the potential origins of contemporary genomes and provide a new perspective on Canis ancestry, but do not negate current conservation priorities of dwindling wolf populations with unique genomic signatures and key ecologically critical roles.
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TL;DR: In this article , the authors conducted an aerial survey in a 15,000 km2 study area around Algonquin Provincial Park in Ontario, Canada and found 145 colonies on 73 plots that averaged 4.5 km2 (+/−3.27 SD).
Abstract: Understanding spatial and temporal variation in beaver abundance is a central goal for a wide range of management issues, ranging from species reintroductions to mitigation of environmental and economic impacts. Yet due to high costs associated with surveys, many studies are limited to a single regional estimate, or a complete census of a smaller study area extrapolated to the surrounding landscape. We present a survey design that allows for predicting beaver abundance across the broader landscape through interpolation. In October 2019, we conducted an aerial survey in a 15,000 km2 study area around Algonquin Provincial Park in Ontario, Canada. We counted 145 colonies on 73 plots that averaged 4.5 km2 (+/−3.27 SD). Our regional estimate for beaver abundance of 0.55 (95% CI = +/−0.18) colonies/km2 is comparable to historical surveys conducted in the region in the 1970s. We then predicted beaver abundance in unsampled plots using a Poisson generalized additive model (adjusted R2 = 0.81, deviance explained = 55.9%) that included non-linear responses to elevation (P < 0.001), shoreline complexity (P = 0.003), and availability of shade-tolerant hardwoods (P = 0.001). Our species distribution model predicted strong east-west patterns in beaver abundance across the study region associated with spatial patterns in elevation and forest composition.

1 citations

Journal ArticleDOI
TL;DR: In this article , the authors presented data describing eastern wolves as a distinct taxonomic entity that evolved separately from grey wolves for the past ∼67,000 years with an admixture event with coyotes ∼37, 000 years ago.
Abstract: Abstract Southeastern Canada is inhabited by an amalgam of hybridizing wolf-like canids, raising fundamental questions regarding their taxonomy, origins, and timing of hybridization events. Eastern wolves (Canis lycaon), specifically, have been the subject of significant controversy, being viewed as either a distinct taxonomic entity of conservation concern or a recent hybrid of coyotes (C. latrans) and grey wolves (C. lupus). Mitochondrial DNA analyses show some evidence of eastern wolves being North American evolved canids. In contrast, nuclear genome studies indicate eastern wolves are best described as a hybrid entity, but with unclear timing of hybridization events. To test hypotheses related to these competing findings we sequenced whole genomes of 25 individuals, representative of extant Canadian wolf-like canid types of known origin and levels of contemporary hybridization. Here we present data describing eastern wolves as a distinct taxonomic entity that evolved separately from grey wolves for the past ∼67,000 years with an admixture event with coyotes ∼37,000 years ago. We show that Great Lakes wolves originated as a product of admixture between grey wolves and eastern wolves after the last glaciation (∼8,000 years ago) while eastern coyotes originated as a product of admixture between “western” coyotes and eastern wolves during the last century. Eastern wolf nuclear genomes appear shaped by historical and contemporary gene flow with grey wolves and coyotes, yet evolutionary uniqueness remains among eastern wolves currently inhabiting a restricted range in southeastern Canada.

1 citations

References
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Journal ArticleDOI
David Posada1
TL;DR: jModelTest is a new program for the statistical selection of models of nucleotide substitution based on "Phyml" that implements 5 different selection strategies, including "hierarchical and dynamical likelihood ratio tests," the "Akaike information criterion", the "Bayesian information criterion," and a "decision-theoretic performance-based" approach.
Abstract: jModelTest is a new program for the statistical selection of models of nucleotide substitution based on "Phyml" (Guindon and Gascuel 2003. A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol. 52:696-704.). It implements 5 different selection strategies, including "hierarchical and dynamical likelihood ratio tests," the "Akaike information criterion," the "Bayesian information criterion," and a "decision-theoretic performance-based" approach. This program also calculates the relative importance and model-averaged estimates of substitution parameters, including a model-averaged estimate of the phylogeny. jModelTest is written in Java and runs under Mac OSX, Windows, and Unix systems with a Java Runtime Environment installed. The program, including documentation, can be freely downloaded from the software section at http://darwin.uvigo.es.

9,748 citations

Journal ArticleDOI
TL;DR: The software package Tracer is presented, for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference, which provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more.
Abstract: Bayesian inference of phylogeny using Markov chain Monte Carlo (MCMC) plays a central role in understanding evolutionary history from molecular sequence data. Visualizing and analyzing the MCMC-generated samples from the posterior distribution is a key step in any non-trivial Bayesian inference. We present the software package Tracer (version 1.7) for visualizing and analyzing the MCMC trace files generated through Bayesian phylogenetic inference. Tracer provides kernel density estimation, multivariate visualization, demographic trajectory reconstruction, conditional posterior distribution summary, and more. Tracer is open-source and available at http://beast.community/tracer.

5,492 citations

Journal ArticleDOI
TL;DR: The Phylogeny.fr platform transparently chains programs to automatically perform phylogenetic analyses and can also meet the needs of specialists; the first ones will find up-to-date tools chained in a phylogeny pipeline to analyze their data in a simple and robust way, while the specialists will be able to easily build and run sophisticated analyses.
Abstract: Phylogenetic analyses are central to many research areas in biology and typically involve the identification of homologous sequences, their multiple alignment, the phylogenetic reconstruction and the graphical representation of the inferred tree. The Phylogeny.fr platform transparently chains programs to automatically perform these tasks. It is primarily designed for biologists with no experience in phylogeny, but can also meet the needs of specialists; the first ones will find up-to-date tools chained in a phylogeny pipeline to analyze their data in a simple and robust way, while the specialists will be able to easily build and run sophisticated analyses. Phylogeny.fr offers three main modes. The ‘One Click’ mode targets non-specialists and provides a ready-to-use pipeline chaining programs with recognized accuracy and speed: MUSCLE for multiple alignment, PhyML for tree building, and TreeDyn for tree rendering. All parameters are set up to suit most studies, and users only have to provide their input sequences to obtain a ready-to-print tree. The ‘Advanced’ mode uses the same pipeline but allows the parameters of each program to be customized by users. The ‘A la Carte’ mode offers more flexibility and sophistication, as users can build their own pipeline by selecting and setting up the required steps from a large choice of tools to suit their specific needs. Prior to phylogenetic analysis, users can also collect neighbors of a query sequence by running BLAST on general or specialized databases. A guide tree then helps to select neighbor sequences to be used as input for the phylogeny pipeline. Phylogeny.fr is available at: http://www.phylogeny.fr/

4,364 citations

Journal ArticleDOI
TL;DR: The BEAST software package unifies molecular phylogenetic reconstruction with complex discrete and continuous trait evolution, divergence-time dating, and coalescent demographic models in an efficient statistical inference engine using Markov chain Monte Carlo integration.
Abstract: The Bayesian Evolutionary Analysis by Sampling Trees (BEAST) software package has become a primary tool for Bayesian phylogenetic and phylodynamic inference from genetic sequence data. BEAST unifies molecular phylogenetic reconstruction with complex discrete and continuous trait evolution, divergence-time dating, and coalescent demographic models in an efficient statistical inference engine using Markov chain Monte Carlo integration. A convenient, cross-platform, graphical user interface allows the flexible construction of complex evolutionary analyses.

2,184 citations

Journal ArticleDOI
TL;DR: A series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release are described.
Abstract: Elaboration of Bayesian phylogenetic inference methods has continued at pace in recent years with major new advances in nearly all aspects of the joint modelling of evolutionary data. It is increasingly appreciated that some evolutionary questions can only be adequately answered by combining evidence from multiple independent sources of data, including genome sequences, sampling dates, phenotypic data, radiocarbon dates, fossil occurrences, and biogeographic range information among others. Including all relevant data into a single joint model is very challenging both conceptually and computationally. Advanced computational software packages that allow robust development of compatible (sub-)models which can be composed into a full model hierarchy have played a key role in these developments. Developing such software frameworks is increasingly a major scientific activity in its own right, and comes with specific challenges, from practical software design, development and engineering challenges to statistical and conceptual modelling challenges. BEAST 2 is one such computational software platform, and was first announced over 4 years ago. Here we describe a series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release.

2,045 citations

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