Abstracts For Presentations By Nicholas J Matzke
Table of Contents

The XIX International Botanical Congress (IBC 2017), Shenzhen, China: Measuring how the probability of long-distance dispersal depends on geographic distance, environmental distance, and co-evolving seed dispersal traits: BioGeoBEARS on a mega-phylogeny of angiosperms.

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Matzke, Nicholas J. (2017). Measuring how the probability of long-distance dispersal depends on geographic distance, environmental distance, and co-evolving seed dispersal traits: BioGeoBEARS on a mega-phylogeny of angiosperms. Accepted abstract for the special symposium "Key questions on angiosperm macroevolution: where do we stand, and where are we heading now? (two sessions)." The XIX International Botanical Congress (IBC 2017), Shenzhen Convention and Exhibition Center in Shenzhen, China, July 23-29, 2017.

Abstract:

Organism traits must be important in historical biogeography. In particular, rates of dispersal (both range-expansion dispersal, and jump dispersal leading to founder-event cladogenesis) must depend to some degree on traits such as seed traits and the vectors that transport seeds (e.g. animals, wind, water). However, to date no full-likelihood historical biogeographical models have been available that allow geographic range and traits to co-evolve on the phylogeny, with traits influencing dispersal ability. I present an addition to the R package BioGeoBEARS that enables an evolving discrete trait to influence both anagenetic and cladogenetic dispersal. This model can be freely combined with models adding parameters for jump dispersal (e.g., DEC+J), distance as a predictor of dispersal (+x models, with dispersal rate multiplied by distance^x), and other variants (e.g. +n, where the multiplier is environmental distance^n). I use Maximum Likelihood to apply the model to a phylogeny of over 14,000 angiosperms with areas coded for over 50 biome/continent combinations, and show that each predictor causes massive improvements in model fit, as measured by change in log-likelihood (delta lnL). Parameter x adds 15231 lnL, n adds another 618, and 3 parameters for seed traits add 2344. The model infers that plants with seeds classified as wind-dispersed have the lowest average rate of dispersal at this global scale (muliplier 0.001), animal-dispersed intermediate (multiplier 1) and water-dispersed the highest (8.18). Seed traits are classified very crudely in this analysis, so there must be care in interpretation (winged maple seeds and dandelion seeds are both "wind dispersed", and sampling of species and traits is incomplete), but overall the approach shows great promise. The study of long-distance dispersal need not rely on "dumb luck" and near-miraculous events to explain dispersal events, but rather, in the main, the causes of long-distance dispersal can be inferred statistically and understood mechanistically. BioGeoBEARS updates are at http://phylo.wikidot.com/biogeobears.

Keywords: biogeography long-distance dispersal seed traits seed dispersal syndrome BioGeoBEARS

Evolution 2017: Phylogenetic biogeography of fossil Canidae: combining models of imperfect detection, fossil databases as taphonomic controls, and Biogeographical Stochastic Mapping

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Matzke, Nicholas J; Säilä, Laura (2017). Phylogenetic biogeography of fossil Canidae: combining models of imperfect detection, fossil databases as taphonomic controls, and Biogeographical Stochastic Mapping. Evolution 2017, Portland, Oregon. June 23-27, 2017. http://www.evolutionmeetings.org/evolution-2017---portland-oregon.html

Nicholas Matzke, The Australian National University (Primary Presenter)
Laura Säilä, University of Helsinki

Title: Phylogenetic biogeography of fossil Canidae: combining models of imperfect detection, fossil databases as taphonomic controls, and Biogeographical Stochastic Mapping

Abstract: Probabilistic analyses of geographic range evolution have become increasingly popular as analysis tools in phylogenetic biogeography. However, the options for including fossils in these analyses have been limited. In addition, no phylogenetic biogeography methods have taken into account the fact that detection of presence and absence in regions will often be imperfect for fossil taxa. Here, both of these problems are addressed in the software BioGeoBEARS, and an example application to the global history of Canidae is presented. We manually curate a database of fossil Canidae occurrences, and use a database of other medium-sized mammal fossils (assembled from the literature as well as NOW and FAUNMAP) as a taphonomic control in order to measure detection effort in each region and time bin. We use Biogeographical Stochastic Mapping on a posterior sample of tip-dated phylogenies to estimate the frequency and timing of dispersal, vicariance, and other events, as well as their directionality and uncertainty.

Centre for Biodiversity Analysis, TEA Talk at ANU, 2017: Model-based inference of environmental niches and niche evolution: fundamental and practical issues for discussion

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Matzke, Nicholas J. (2017). Model-based inference of environmental niches and niche evolution: fundamental and practical issues for discussion. TEA Talk for the Centre for Biodiversity Analysis (CBA), Division of Evolution and Ecology, Research School of Biology, The Australian National University, Canberra, Australia. 12-2 pm, May 5, 2017. E&E Seminar Room, Gould Building 116, Daley Rd, ANU. http://cba.anu.edu.au/news-events/model-based-inference-environmental-niches-and-niche-evolution-fundamental-and-practical

Model-based inference of environmental niches and niche evolution: fundamental and practical issues for discussion

Abstract: Species Distribution Models (SDMs) typically rely on machine-learning approaches to estimate the niche of a species, where the "niche model" is effectively a correlational model built on physical environmental variables such as temperature and precipitation.

This approach is widely used, but has been criticised on a number of grounds, including (1) the problematic assumption that physical environmental variables are the most relevant ones to build models on; (2) the complex models that are fit by sophisticated algorithms, with the potential for overfitting and poor extrapolation ability; (3) the problem of confounding variables (dispersal limitation, evolutionary history, competition, etc.).

Some of these issues (not all!) may be ameliorated by including evolutionary information in the inference, and jointly modeling the niches of living species, and an evolutionary model describing how the niche models evolve on the evolutionary tree. This idea raises a host of theoretical issues (What is evolving? How do we model it?) and practical issues (The number of parameters rapidly increases with more species; Models that are evolutionarily conservative may have better extrapolation ability, but poorer fit to training data than machine-learning approaches.).

The topic has interesting connections to areas such as morphometrics in phylogenetics (see previous TEA talk by Sherratt and Brennan) and model-based inference in both ecology and evolution. I will present my current thinking and progress, but I am most interested in a free-flowing discussion of all aspects of niche evolution, both from a theoretical perspective and practical perspective (i.e., what do biologists need that they don't currently get from standard SDM approaches).

University of Canberra, 2017: Models matter: Better models for better inference in phylogenomic dating and biogeography

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Matzke, Nicholas J. (2017). Models matter: Better models for better inference in phylogenomic dating and biogeography. Weekly seminar series, Institute for Applied Ecology, University of Canberra, 3B12 (Building 3, Level B, room 12). April 19, 2017, 12:30 p.m. Hosted by Jonas.Bylemans & Emory Ingles.

Title: "Models matter: Better models for better inference in phylogenomic dating and biogeography"

Abstract: Biology and biogeography are in the midst of a data revolution. Often, the scientific questions we wish to answer are limited more by the shortcomings in the models used for statistical inference, than by shortcomings in data. However, these problems can be overcome by creative thinking and programming to develop new, more realistic models, followed by rigorous statistical model comparison. I illustrate with three studies using my R packages BEASTmasteR and BioGeoBEARS. First, I develop a "divide-and-conquer" pipeline to conduct a phylogenomic dating analysis on a dataset (Gehyra lizards from northern Australia, 44 species, 106 loci) otherwise too large for gene-tree/species-tree analyses in StarBeast2, overcoming the problems with a concatenation approach. Second, I "ground truth" various Bayesian Total Evidence dating approaches on a relatively high-quality dataset (fossil and living Canidae). Finally, I devote the majority of my talk to testing new models in biogeography with BioGeoBEARS. I show that traditional models are systematically outperformed (across many clades) by models that allow jump dispersal, and dispersal functions that depend on distance, environmental distance, and/or evolving traits. I conclude by outlining how model-based inference can be further expanded, for example to integrate historical and ecological biogeography (for example, in Species Distribution Modeling).

University of Auckland, 2017: Biogeography with jumps, distance, and trait-based dispersal

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Matzke, Nicholas J. (2017). "Biogeography with jumps, distance, and trait-based dispersal: Adding realism fits the data better than traditional models in historical biogeography." University of Auckland, School of Biological Sciences (SBS). 2017 Seminar Series. Federation of Graduate Women's Room, Old Government House (102), 1-2pm. April 11, 2017. Poster link
http://www.sbs.auckland.ac.nz/en/about/news-and-events/events/events-2017/04/biogeography-with-jumps-distance-and-trait-based-dispersal.html

Biogeography with jumps, distance, and trait-based dispersal: Adding realism fits the data better than traditional models in historical biogeography

Dr Nick Matzke, Moritz Lab, Centre for Biodiversity Analysis, Division of Evolution, Ecology, and Genetics, Australian National University

Abstract: Historical biogeography is the study of how species' geographic ranges have evolved across the globe on evolutionary (phylogenetic) timescales. While probabilistic models are used to make inferences from data in phylogenetics and many other fields, historical biogeography has been slow to join this revolution.

Much of the difficulty lies in the computational complexity of biogeography models – a DNA transition rate matrix is only 4x4, but a biogeography rate matrix can easily be 1000x1000 or higher, leading to severe computational constraints. As a result, our answers to fundamental biogeographic questions – for example, the importance of long-distance (‘jump’) dispersal, the relationship between distance and dispersal probability, the relationship between dispersal and key traits – have often been decided ahead of time by simplifying assumptions made in biogeography software, rather than being inferred from the data.

Dr Nick Matzke wrote the R package ‘BioGeoBEARS’ to overcome some of these difficulties, and to allow more biologically realistic models to be used with geographic range data. Using 20 island and continental clades, Dr Matzke will show that the data usually favours models that allow a non-zero probability of jump dispersal. He will also show that a relationship between dispersal and geographic distance is often supported by the data, and is likely to be a key feature of global historical biogeography analyses. Finally, he will give examples where trait-dependent dispersal ability is inferred from the data.

Despite progress, biogeography is only beginning to be explored with the tools of probabilistic inference. Dr Matzke will outline future research directions, for example, the integration of historical and ecological biogeography with phylogeny-informed species distribution modelling.

Poster: http://phylo.wdfiles.com/local--files/abstracts-for-presentations-by-nicholas-j-matzke/2017-04-11_UAuckland_biogeog_jumps_distance.jpg

Western Washington University (2017): Models matter: Better models for better inference in phylogenomic dating and biogeography

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Matzke, Nicholas J. (2017). Models matter: Better models for better inference in phylogenomic dating and biogeography. Biology Department, Western Washington University. Room BI234, 4 p.m., February 8, 2017.

Models matter: Better models for better inference in phylogenomic dating and biogeography

Nicholas J. Matzke
Discovery Early Career Researcher Award (DECRA) Fellow
Moritz Lab
The Australian National University, Canberra, Australia
http://www.nickmatzke.net

Abstract: Biology and biogeography are in the midst of multiple data revolutions caused by high-throughput sequencing and massive online databases. As a result, our ability to answer scientific questions is often limited less by data, and more by shortcomings in the models available for statistical inference. However, these problems can be overcome by creative thinking and programming to develop better methods with more realistic models, followed by statistical model comparison. I illustrate with three studies using my R packages BEASTmasteR and BioGeoBEARS:

First, I develop a "divide-and-conquer" pipeline to conduct a phylogenomic dating analysis on a dataset (Gehyra lizards from northern Australia, 44 species, 106 loci) otherwise too large for gene-tree/species-tree analyses. This overcomes the dating biases that occur when genes with different coalescent histories are concatenated into a single alignment, and also changes downstream inference about diversification and biogeography models.

Second, I use fossil dogs (family Canidae) to "ground truth" various phylogenetic dating methods that use a "total evidence" approach. "Total evidence" methods combine fossils, fossil dates, and living taxa (DNA and/or morphology) in a joint Bayesian inference of phylogeny and dates. Fossil dogs are an ideal test dataset, as they have an excellent fossil record, with fossil diversity greatly exceeding living diversity. I show that methods that model fossil sampling through time outperform methods that ignore this process.

Third, using BioGeoBEARS, I show that traditional models for how geographic range evolves on a phylogeny are outperformed, in many clades, by more complex models that allow a role for jump dispersal, geographic distance, or evolving dispersal-related traits, and that choice of model can strongly impact estimation of biogeographic history.

I conclude by outlining future directions in model-based inference in biogeography, such as global analyses of huge clades, and the integration of historical and ecological biogeography in phylogeny-informed Species Distribution Modeling.

Universidad de Concepción (2017): Measuring the influence of an evolving trait on evolutionary dispersal probability with Pacific rails, global legumes, and Indo-Pacific Cryptoblepharus lizards

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Matzke, Nicholas J. (2017). Measuring the influence of an evolving trait on evolutionary dispersal probability with Pacific rails, global legumes, and Indo-Pacific <i>Cryptoblepharus</i> lizards. Programa de Doctorado en Sistemática y Biodiversidad, Universidad de Concepción. Concepción, Chile. Thursday, January 19, 2017. Sponsored by Cristián E. Hernández, Laboratorio de Ecología Evolutiva y Filoinformática, Departamento de Zoología, Facultad de Ciencias Naturales y Oceanográficas. Universidad de Concepción, Casilla 160-C, Concepción, Chile.

Abstract: Organism traits must be important in historical biogeography. In particular, rates of dispersal (both range-expansion dispersal, and jump dispersal leading to founder-event speciation) must depend to some degree on traits such as flight and its loss, and seed dispersal mechanisms and the dispersal abilities of animals that transport seeds. However, to date, no probabilistic historical biogeographical models have been available that allow geographic range and traits to co-evolve on the phylogeny, with traits influencing dispersal ability. In purely continuous-time Markov models, adding a trait is just a matter of doubling the size of the rate matrix; however, biogeographical models also include a much more complex discrete-time model describing how geographic range can change during cladogenesis. Traits might also influence this process. I present an addition to the R package BioGeoBEARS that enables an evolving discrete trait to influence dispersal ability for both anagenetic and cladogenetic range change. This model can be freely combined with models adding jump dispersal (e.g., DEC+J), distance as a predictor of dispersal (+x models, with dispersal rate multiplied by distance^x), and other variants. I test the model on datasets where large evolutionary changes in dispersal ability are highly likely (e.g., Pacific rails that have lost flight; legumes where some species are nitrogen fixers, and littoral vs. non-littoral Cryptoblepharus lizards of the Indo-Pacific).

International Biogeography Society (2017): Joint Bayesian estimation of niche models and niche evolution: Comparing algorithms

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Matzke, Nicholas J.; Warren, Dan L. (2017). Joint Bayesian estimation of niche models and niche evolution: Comparing algorithms. International Biogeography Society, 2017 Biennial Meeting. Tucson, Arizona. January 10, 2017, talk MT2-5. Conference Programs and Abstracts, 8th Biennial Conference of The International Biogeography Society, Tucson, AZ, USA, January 9th-13th, 2017, p. 82.

Abstract: Current methods for studying phylogenetic niche conservatism and rates of niche evolution typically work by (1) estimating Ecological Niche Models (ENMs) for each species in a clade independently; (2) simplifying the ENM down to a summary statistic (e.g., mean temperature); (3) treating this summary statistic as if it were a measurement such as body size, and applying a simple evolutionary model such as Brownian motion. While this approach has value, it can be criticized on several grounds. We propose that an improvement would be to jointly estimate ENMs for a group of related species, as well as parameters for the evolution of each niche model axis, using Bayesian MCMC. However, because joint estimation combines the complexities of ENMs and evolutionary models, implementation and computation speed are nontrivial concerns. We perform a feasibility study by comparing implementations of phylogenetic ENM using R and RevBayes in terms of inference accuracy against simulations, and speed. We also assess the prospects for modeling additional processes that are often confounded in ENM, such as dispersal limitation and historical biogeography.

University of Bochum, Germany (2016): Trait-dependent dispersal models for phylogenetic biogeography in the R package BioGeoBEARS

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Matzke, Nicholas J. (2016). Trait-dependent dispersal models for phylogenetic biogeography in the R package BioGeoBEARS. Ringvorlesung Biodiversität (RUB), University of Bochum. Bochum, Germany. Speaker for Wintersemester 2016/2017 seminar series, December 6, 2016. 4:15 pm, room ND03/99. Hosted by Kristina Klaus.

Biology in the Pub (2016): Canberra

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November 19, 2016 - Speaker for Science in the Pub: Biology in the Pub. "Evolutionary biologist Nick Matzke (Biology@ANU) has analysed anti-evolution policies in the US. Guess what, they’ve evolved!" Saturday November 19, 2016. 7-9 pm, Smiths Alternative bookshop, Civic, Canberra, Australia. https://www.facebook.com/events/1749766278618789

Geological Society of America 2016: Inferring ancestor-descendant relationships in the fossil record (with statistics).

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Bapst, David W.; Hopkins, Melanie; Wright, April; Matzke, Nicholas J.; Lloyd, Graeme T. (2016). Inferring ancestor-descendant relationships in the fossil record (with statistics). Geological Society of America Abstracts with Programs, 48(7). https://gsa.confex.com/gsa/2016AM/webprogram/Paper277591.html http://dx.doi.org/10.1130/abs/2016AM-277591

Geological Science of America Annual Meeting in Denver, Colorado. Session No. 289: T151. New Approaches to Phylogenetic Paleobiology. Wednesday, 28 September 2016: 8:00 AM-12:00 PM, Mile High Ballroom 4AB (Colorado Convention Center). Paper No. 289-6, Presentation Time: 9:15 a.m.

BAPST, David W., Geology and Geological Engineering, South Dakota School of Mines and Technology, 501 E. St. Joseph, Rapid City, SD 57701; Earth and Planetary Sciences, University of California, Davis, One Shields Ave, Davis, CA 95616, HOPKINS, Melanie, Paleontology, American Museum of Natural History, Central Park West at 79th St, New York, NY 10024, WRIGHT, April, Ecology, Evolution, & Organismal Biology, Iowa State University, Ames, IA 50011, MATZKE, Nicholas J., Division of Evolution, Ecology, and Genetics, Research School of Biology, Australian National University, Canberra, ACT 2601, Australia and LLOYD, Graeme T., Department of Biological Sciences, Faculty of Science, Macquarie University, North Ryde, NSW 2109, Australia, moc.liamg|tspabwd#moc.liamg|tspabwd

Abstract: The idea that some of the taxa we recognize in the fossil record may actually be ancestral to other fossil or living lineages is wide-spread in popular thought. Historically, many paleontologists qualitatively implied ancestor-descendant relationships among sampled taxa. However, typical approaches for inferring phylogenies don’t allow taxon units to be ancestors, leading to the development of ‘parsimonious’ rules for diagnosing ancestry (e.g. lack of autapomorphies). One method, stratocladistics, inferred ancestors but that feature was overshadowed by larger debates, and did not lend itself to quantifying statistical support for particular ancestor-descendant relationships. Recent development of phylogenetic dating methods, such as cal3 and Bayesian tip-dating, allow for taxa to be inferred as sampled-ancestors a in a model-based framework. We present two empirical case examples of inferring ancestor-descendant relationships. First, with Paleozoic pterocephaliid trilobites, we contrast previously qualitative assessments of ancestor-descendant species-pairs with those inferred by cal3, and find high agreement except for anagenetic pairs, which were overwhelmingly inferred by cal3 as budding cladogenesis instead. Overall, this analysis suggests that budding is the dominant mode of morphological speciation. Second, we utilize a dataset of Mesozoic theropods to compare ancestral inference from tip-dating (via BEAST2 and MrBayes) and cal3. These analyses, despite similar model assumptions, infer very different frequencies of sampled ancestry, with some incongruence about which species are considered to be sampled-ancestors. Interestingly, although Archaeopteryx is popularly thought of as an ‘ancestral bird’, it is rarely placed as a ancestral taxon with this dataset, and then only to its close relative Wellnhoferia, not to the lineage leading to crown birds. Overall, while there is some dependency on the approaches used, there is a bright future for quantitative inference of ancestors, particularly as we expand methods to account for persistent chronospecies, and to account for different patterns in how lineages morphologically differentiate from each other.

Botany Society of America 2016: Bayesian estimation of the global biogeographic history of the Solanaceae

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Dupin, Julia; Matzke, Nicholas J.; Saarkinen, Tiina; Knapp, Sandra; Olmstead, Richard G.; Bohs, Lynn; Smith, Stacey D. (2016). "Bayesian estimation of the global biogeographic history of the Solanaceae." Botany Society of America 2016. July 3-August 3, Savannah, Georgia. http://2016.botanyconference.org/engine/search/533.html

Abstract: Aim. The tomato family Solanaceae is distributed on all major continents except Antarctica and has its center of diversity in South America. Its worldwide distribution suggests multiple long distance dispersals within and between the New and Old Worlds. Here we apply maximum likelihood (ML) methods and newly developed biogeographic stochastic mapping (BSM) to infer the ancestral range of the family and to estimate the frequency of dispersal and vicariance events resulting in its present-day distribution. Methods. Building on a recently inferred megaphylogeny of Solanaceae, we conducted ML model-fitting of a range of biogeographic models with the program BioGeoBEARS. We used the parameters from the best fitting model to estimate ancestral range probabilities and conduct stochastic mapping, from which we estimated the number and type of biogeographic events. Results. Our best model supported South America as the ancestral area for the Solanaceae and its major clades. The BSM analyses showed that dispersal events, particularly range expansions, are the principal mode by which members of the family have spread beyond South America. Conclusions. For Solanaceae, South America is not only the family's current center of diversity but also its ancestral range, and dispersal was the principal driver of range evolution. The most common dispersal patterns involved range expansions from South America into North and Central America, while dispersal in the reverse direction was less common. This directionality may be due to the early build-up of species richness in South America, resulting in large pool of potential migrants. These results demonstrate the utility of BSM not only for estimating ancestral ranges but also in inferring the frequency, direction, and timing of biogeographic events in a statistically rigorous framework.

Keywords: BioGeoBEARS, directionality, long-distance dispersal, historical biogeography, Biogeographic Stochastic Mapping (BSM), Solanaceae

SMBE 2016 poster #577: Trait-dependent dispersal models for phylogenetic biogeography, in the R package BioGeoBEARS

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Matzke, Nicholas J. (2016). "Trait-dependent dispersal models for phylogenetic biogeography, in the R package BioGeoBEARS." Poster #577, Society for Molecular Biology and Evolution Conference 2016. Poster session B, Hall 1, 6:00pm-8:00pm, July 5, 2016. http://smbe-2016.p.asnevents.com.au/days/2016-07-05/abstract/35582 http://phylo.wikidot.com/abstracts-for-presentations-by-nicholas-j-matzke#SMBE16_poster_traits

Poster PDF: http://phylo.wikidot.com/local--files/abstracts-for-presentations-by-nicholas-j-matzke/2016-07-04_SMBE_trait-based_dispersal_v4.pdf

Twitter: https://twitter.com/NickJMatzke/status/749749154713219072

Trait-dependent dispersal models for phylogenetic biogeography, in the R package BioGeoBEARS (#577)

Nicholas Matzke1

1. The Australian National University, Turner, ACT, Australia

Society for Molecular Biology and Evolution Conference 2016

Poster session B, Hall 1, 6:00pm-8:00pm

Abstract: Organism traits must be important in historical biogeography. In particular, rates of dispersal (both range-expansion dispersal, and jump dispersal leading to founder-event speciation) must depend to some degree on traits such as flight and its loss, and seed dispersal mechanisms and the dispersal abilities of animals that transport seeds. However, to date no probabilistic historical biogeographical models have been available that allow geographic range and traits to co-evolve on the phylogeny, with traits influencing dispersal ability. In purely continuous-time Markov models, adding a trait is just a matter of doubling the size of the rate matrix; however, biogeographical models also include a much more complex discrete-time model describing how geographic range can change during cladogenesis. Traits might also influence this process. I present an addition to the R package BioGeoBEARS that enables an evolving discrete trait to influence dispersal ability for both anagenetic and cladogenetic range change. This model can be freely combined with models adding jump dispersal (e.g., DEC+J), distance as a predictor of dispersal (+x models, with dispersal rate multiplied by distance^x), and other variants. I test the model against simulations and datasets where large evolutionary changes in dispersal ability are highly likely (e.g., Pacific rails, which have repeatedly lost flight).

Note: I should acknowledge that the first-published trait-based biogeography model published was in the archipelago program of Sukumaran et al. They use a simulation/classifier approach to make it more extensible for larger problems. A full likelihood model, like in BioGeoBEARS, allows traditional statistical model comparison (AIC etc.), but will be limited by computing speed to transition matrices of approximated 2(numareas + numtraitstates)<2500. The archipelago paper is: Sukumaran J, Economo EP, Lacey Knowles L. (2016). "Machine Learning Biogeographic Processes from Biotic Patterns: A New Trait-Dependent Dispersal and Diversification Model with Model Choice By Simulation-Trained Discriminant Analysis." Systematic Biology, 65(3):525-45. doi: 10.1093/sysbio/syv121.

See also this Tweet: https://twitter.com/nickjmatzke/status/745362390267498496

iEvoBio Lightning Talk: Trait-dependent dispersal models for phylogenetic biogeography, in the R package BioGeoBEARS

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At 2:12 pm, in room MR9C.

Slides at: http://phylo.wikidot.com/local--files/abstracts-for-presentations-by-nicholas-j-matzke/2016-06-21_Matzke_trait-dependent_dispersal_v4.pdf

SSB Special Symposium at Evolution 2016: Putting evolution into ecological niche modeling: Building the connection between phylogenies, paleobiology, and species distribution models

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Symposium: SSB1
Title: Putting evolution into ecological niche modeling: Building the connection between phylogenies, paleobiology, and species distribution models
Co-organizers: Nicholas J. Matzke and Dan Warren
Date: Sunday, June 19 (morning)
Time: 8:15 am-9:45 am, 10:15-11:45 am (12 slots at 15 minutes each)
Room: Ballroom C, Theater
Summary website: http://www.evolutionmeetings.org/special-talks.html
Organizational website: http://phylo.wikidot.com/putting-evolution-into-ecological-niche-modeling

Meeting: Evolution 2016
Location: Austin, TX
Venue: Austin Convention Center
Dates: June 17-21, 2016
Website: http://www.evolutionmeetings.org/evolution-2016---austin-texas.html

Summary: Species Distribution Models (SDMs) are increasingly popular tools in ecology, conservation biology, and climate change research. They have been used in hundreds of publications (Figure 1). The most common SDM methods correlate occurrence data with environmental variables, estimating an ecological or environmental niche model (ENM). This niche model is then projected onto a map to predict species distribution (or suitable habitat). Despite their immense popularity, SDM results are often limited by several common problems. Large data sets allow complex correlational models to be fit, but these models are often over-fit, extrapolating poorly to changed environments in the past 1,2 (when predicting paleo-distributions) or present 3 (when predicting species invasions). This lowers confidence in SDMs predicted under future climate change scenarios. Also, SDMs typically assume that geographic range is wholly determined by environment, ignoring dispersal limitation and other historical biogeography processes 4,5, as well as species interactions. This means that ENMs may include some environmental variables as predictors when they are only "accidental" correlates of some other spatial process, further contributing to the overfitting problem.

The fundamental issue underlying the above difficulties is that the SDMs are typically estimated one-species-at-a-time, at one time point (the Recent). This ignores any information that might be gained from the phylogenetic relationships of species, even though phylogenetic niche conservatism appears to be common 4. It also ignores any information that might be gained from time-series data on distributions and climate. As evolutionary biologists, we should be seeking ways to make evolutionary methods and models useful to the wider scientific community, and it seems likely that by combining information on present-day niches distributions, and how niches and distributions evolved on the phylogeny, will provide both evolutionary insight and improved niche models that more robust and do better at capturing the true predictors of species ranges 4. Therefore Symposium will be devoted to "building the connection" between SDMs and phylogenies. How can we integrate phylogenetic models of niche evolution and trait evolution into the SDM estimation process? How can we better integrate paleoclimate and paleo-range data, and historical biogeography? The Symposium will solicit contributions from researchers at the forefront of relevant areas, whether or not they consider themselves "species distribution modelers" per se. For example, workers in phylogenetic comparative methods and evolutionary morphometrics will have much to contribute to the question of how niche evolution should be modeled and estimated, as do conservation biologists who take into phylogenetic relatedness and diversity 6,7, and paleobiologists who have examined the congruence of SDM predictions and fossil occurrences 1,2,8-11. All symposium speakers will be asked to connect their research to the overall question, "How can we connect phylogeny, paleobiology, and species distribution modeling?"

The Skeptic Zone Podcast: The evolution of antievolutionism

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Matzke, Nicholas J. (2016). The Evolution of Antievolutionism. Podcast, "Maynard's Spooky Action" segment of The Skeptic Zone, April 10, 2016. Starts at 0:05:15. http://skepticzone.libsyn.com/the-skeptic-zone-390-10april2016

Maynard Interviews Dr Nick Matzke, a postdoctoral scientist at ANU, holding a Discovery Early Career Researcher Award (DECRA) from the Australian Research Council.

Australian Skeptics: The Evolution of Anti-evolutionism. Dinner Presentation

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Matzke, Nicholas J. (2016). The Evolution of Anti-evolutionism. Dinner Presentation for Australian Skeptics, April 9, 2016. http://www.skeptics.com.au/2016/03/06/sydney-dinner-april-9-the-evolution-of-antievolutionism/ PDF of presentation: http://phylo.wikidot.com/local--files/abstracts-for-presentations-by-nicholas-j-matzke/2016-04-09_Australian_Skeptics_v8.pdf

AUSTRALIAN SKEPTICS DINNER

SATURDAY April 9, 2016
Heritage Function Centre (upstairs),
Ryde-Eastwood Leagues Club, 117 Ryedale Road, West Ryde
6.30pm for 7.15pm $50 per person (includes buffet dinner)

You might have thought creationism was dead, done and dusted. But far from it. We're kicking off our new year of Skeptics dinners in Sydney with a bit of an eye-opener - the evolution of the anti-evolution movement.

Professor Graham Oppy, head of the School of Philosophical, Historical & International Studies at Monash University says that, since 2000, the teaching of creationism in science classes has become "more prevalent".

"Groups like CSF (Christian Science Foundation), Answers in Genesis, Creation Ministries, and Creation Research … work hard to get their materials into schools", he says, and this includes giving creationist 'showbags' to students in NSW.

Who better, then, to speak on this topic than someone involved in the infamous US Kitzmiller v Dover trial in 2005 over a policy that required the teaching of 'intelligent design' in biology classes.

Dr Nick Matzke is a postdoctoral scientist at ANU, holding a Discovery Early Career Researcher Award (DECRA) from the Australian Research Council. He is located in the Moritz Lab in ANU's Division of Evolution, Ecology, and Genetics, and is working in evolutionary biogeography & phylogenetics. From 2004-2007, Nick worked for the US National Centre for Science Education, which combats attempts to insert creationism and other anti-science topics into public schools. In December 2015, he published an article in Science magazine, "The Evolution of Anti-evolution Policies after //Kitzmiller v. Dover//," that presented a phylogenetic tree of anti-evolution legislation in the US.

So what's the latest on creationism, intelligent design, evolution and anti-evolution? How is the anti-evolution movement 'evolving' to spread its message? All of this … and food … at the Skeptics dinner on April 9 at the Ryde-Eastwood Leagues Club.

Molecular Paleobiology of Australia’s Terrestrial Vertebrates: Ground-truthing tip-dating methods and models using fossil Canidae reveals major differences in performance

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Matzke, Nicholas J. Ground-truthing tip-dating methods and models using fossil Canidae reveals major differences in performance. Molecular Paleobiology of Australia’s Terrestrial Vertebrates Conference. Melbourne, Victoria, Australia. Melbourne Museum, 11-11:15 a.m., Tuesday, April 5, 2016. http://www.australianmolecularpaleobiology.org/p/program.html

Abstract: Tip-dating methods - methods where the ages of fossil OTUs (operational taxonomic units/terminal taxa) are directly used as the primary source of dating information - are becoming popular alternatives to traditional "node-dating." However, they have not been extensively tested. Here, I "ground-truth" the most popular methods against a dated tree (~1-2 my resolution) of fossil Canidae. This "ground truth" tree was constructed in monographs by Canidae experts Wang and Tedford, who combined parsimony analysis with detailed knowledge of species stratigraphy and morphological gradations. The term "ground truth" is taken from accuracy assessment in remote sensing, and although the big picture of canid phylogeny and dating seems to be secure, I have no objection to interpretation of the study as a test of Bayesian methods to reproduce expert opinion, rather than literal "truth." Using a revised canid morphology dataset from Slater (PNAS, 2015), I compare MrBayes 3.2.5 (released April 2015) to Beast 2.3 combined with BEASTmasteR (phylo.wikidot.com/beastmaster), an R package that automates the conversion of dates, priors, and NEXUS character matrices into the complex Beast2 XML format. I find that unconstrained MrBayes analysis under the uniform tree prior fails to retrieve reasonable results, exhibiting extremely high uncertainty in dates. On the other hand, Beast2 inference matches the ground-truth well, under both birth-death serially sampled (BDSS, disallowing direct ancestors) and sampled ancestor (SABD) tree models, as does MrBayes using BDSS. MrBayes using SABD seems to have difficulty converging in some runs. These results, on a very high quality fossil dataset, indicate that while tip-dating is very promising, methodological issues in tip-dating can have drastic effects, and require close attention, especially on more typical datasets where the distinction between "method problems" and "data problems" will be more difficult to detect.

Trait-dependent dispersal models for phylogenetic biogeography, in the R package BioGeoBEARS

(link to this section)

Matzke, N.J. (2016). Trait-dependent dispersal models for phylogenetic biogeography, in the R package BioGeoBEARS. ANU Research School of Biology. Poster at Early-and Mid-Career Conference (Follow on Twitter at #RSBEMCR16). R. N. Robertson Lecture Theatre, Bldg. 46. Feb. 11th, 2016, 4:45 pm.

Link: http://phylo.wikidot.com/local--files/abstracts-for-presentations-by-nicholas-j-matzke/2016-02-11_ANU_trait-based_dispersal_v2.pdf

When Darwin Visited Valparaiso (Chile). Darwin Day Lecture at Valparaiso University

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Matzke, Nicholas J. (2016). When Darwin Visited Valparaiso (Chile). Darwin Day Lecture at Valparaiso University, Friday, Jan. 15, 3:30-4:30 pm, Christopher Center Library. Sponsor: Robert Swanson.

The Evolution of Antievolutionism before and after Kitzmiller v. Dover (2005)

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The Evolution of Antievolutionism before and after Kitzmiller v. Dover (2005)

by Nicholas J. Matzke, DECRA Fellow, Research School of Biology, ANU.
ua.ude.una|ekztam.kcin#ua.ude.una|ekztam.kcin
http://phylo.wikidot.com/nicholas-j-matzke

Date: 2016 (TBA)
Time: ???
Room: ???
Sponsor: Lindell Bromham, Tempo and Mode Seminar

Abstract: Antievolutionist creationism has had a number of major waves, focused in the U.S. but spreading internationally. The last major wave was "intelligent design" creationism, which received its greatest defeat in the Federal court case Kitzmiller v. Dover, decided December 20, 2005. This case challenged the constitutionality of an "intelligent design" policy required in high school biology classrooms in Dover, Pennsylvania. I worked on this case while at the National Center for Science Education (NCSE), a nonprofit watchdog group devoted to defending classroom coverage of evolution, global warming, and other allegedly "controversial" topics. I will discuss the case and its background, and also present a new study conducting a phylogenetic analysis of "crypto-creationist" proposals in the decade since Kitzmiller.

Trait-dependent dispersal models for phylogenetic biogeography, in the R package BioGeoBEARS

(link to this section)

Abstract published as: Matzke, N.J. (2016). Trait-dependent dispersal models for phylogenetic biogeography, in the R package BioGeoBEARS. Integrative and Comparative Biology 56(suppl 1), E330-E330. Meeting: http://www.sicb.org/meetings/2016/schedule/abstractdetails.php?id=1674 ; DOI: https://doi.org/10.1093/icb/icw001

Matzke, Nicholas J. (2016). Trait-dependent dispersal models for phylogenetic biogeography, in the R package BioGeoBEARS. Speciation and Biogeography session, Society of Integrative and Comparative Biology Annual Meeting, Jan. 3-8, 2016. Wednesday, January 6, 3:30-4:30 pm. 3:30 pm, Wed. Jan. 6, Poster P3-12.

Link: http://phylo.wikidot.com/local--files/abstracts-for-presentations-by-nicholas-j-matzke/2016-02-11_ANU_trait-based_dispersal_v2.pdf

Abstract: Organism traits must be important in historical biogeography. In particular, rates of dispersal (both range-expansion dispersal, and jump dispersal leading to founder-event speciation) must depend to some degree on traits such as flight and its loss, and seed dispersal mechanisms and the dispersal abilities of animals that transport seeds. However, to date no probabilistic historical biogeographical models have been available that allow geographic range and traits to co-evolve on the phylogeny, with traits influencing dispersal ability. In purely continuous-time Markov models, adding a trait is just a matter of doubling the size of the rate matrix; however, biogeographical models also include a much more complex discrete-time model describing how geographic range can change during cladogenesis. Traits might also influence this process. I present an addition to the R package BioGeoBEARS that enables an evolving discrete trait to influence dispersal ability for both anagenetic and cladogenetic range change. This model can be freely combined with models adding jump dispersal (e.g., DEC+J), distance as a predictor of dispersal (+x models, with dispersal rate multiplied by distance^x), and other variants. I test the model against simulations and datasets where large evolutionary changes in dispersal ability are highly likely (e.g., Pacific rails, which have repeatedly lost flight).

Trait-dependent dispersal models for phylogenetic biogeography, in the R package BioGeoBEARS

(link to this section)

Matzke, N. (2015). Trait-dependent dispersal models for phylogenetic biogeography, in the R package BioGeoBEARS. Annual Meeting of the Society of Australian Systematic Biologists, 2015. Tuesday, December 8, 2015. Sirius Room: From R to ecology, 3:50-4:10.

Abstract: Organism traits must be important in historical biogeography. In particular, rates of dispersal (both range-expansion dispersal, and jump dispersal leading to founder-event speciation) must depend to some degree on traits such as flight and its loss, and seed dispersal mechanisms and the dispersal abilities of animals that transport seeds. However, to date no probabilistic historical biogeographical models have been available that allow geographic range and traits to co-evolve on the phylogeny, with traits influencing dispersal ability. In purely continuous-time Markov models, adding a trait is just a matter of doubling the size of the rate matrix; however, biogeographical models also include a much more complex discrete-time model describing how geographic range can change during cladogenesis. Traits might also influence this process. I present an addition to the R package BioGeoBEARS that enables an evolving discrete trait to influence dispersal ability for both anagenetic and cladogenetic range change. This model can be freely combined with models adding jump dispersal (e.g., DEC+J), distance as a predictor of dispersal (+x models, with dispersal rate multiplied by distance^x), and other variants. I test the model against simulations/datasets where large evolutionary changes in dispersal ability are highly likely (e.g., Pacific rails).

Univ. Tasmania, Stochastic Modelling Meets Phylogenetics 2015 (#SMMP2015)

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Matzke, Nicholas J. (2015). Putting Evolution Into Ecological Niche Modelling (And: Statistical model choice in phylogenentic biogeography more generally). At: Stochastic Modelling meets Phylogenetics (SMMP), collaborative workshop November 16-18, University of Tasmania, Hobart. November 16, 2015, 12:30 pm. Mathematics & Physics Building, University of Tasmania. (#SMMP2015) http://www.maths.utas.edu.au/People/oreilly/SMMP/smmp2015.html
http://phylo.wikidot.com/local--files/abstracts-for-presentations-by-nicholas-j-matzke/2015-11-16_Matzke_UTas_v1_putting_evo_into_ENM.pdf

ANU - intro talk for Craig Moritz Lab Group

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Title: Biogeographical Stochastic Mapping: Bayesian estimation of the history and timing of biogeographical events on phylogenies

Nicholas Matzke (2015). "Biogeographical Stochastic Mapping: Bayesian estimation of the history and timing of biogeographical events on phylogenies." Craig Moritz Lab Group, Gould Meeting Room, 2 pm, August 5, 2015

Date: August 5, 2015
Time: 2-3 pm

Link: NA

Summary: Traditional likelihood methods in historical biogeography estimate the probability of each geographic range at each node. Usually the most-probable range at each node is plotted, and this is taken to be the approximate history. This is not technically accurate and might be badly misleading in some cases. A solution is stochastic mapping of possible histories on the phylogeny. This has been widely applied in phylogenetics for sequence data and discrete characters, but these character models are inappropriate in historical biogeography, where the state space is much more complex, and geographic range changes through both anagenetic and cladogenetic events. I present a novel algorithm that enables stochastic mapping on any biogeographic model available in BioGeoBEARS, as well as graphical display and statistical summary of the timing and frequency of dispersal and vicariance events. An animation of realizations of possible histories under the DEC and DEC+J models is demonstrated for Hawaiian Psychotria shrubs. R functions and an example script performing stochastic mapping are available at http://phylo.wikidot.com/biogeobears . The functions build upon on the R package BioGeoBEARS, available for all platforms at CRAN.

Contact: ua.ude.una|ekztamkcin#ua.ude.una|ekztamkcin

Supplementary Information: R source code is also archived in this article’s online Supplementary Data. (And here: http://phylo.wikidot.com/biogeobears#stochastic_mapping )

Society of Vertebrate Paleontology 2015

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SVP 75th Annual Meeting
October 14-17, 2015
Hyatt Regency Dallas
Dallas, Texas, USA

Submission Number: 891
Abstract Title: Bayesian tip-dating with continuous characters using BEASTmasteR
First Author: Nicholas Matzke
Session: Technical Session V
Session Title: Histology and Methods
Session Date: Wednesday, October 14, 2015
Session Time: 1:45 PM - 4:15 PM

Bayesian "tip-dating" is a method for simultaneously inferring the topology and dating of a phylogeny by including fossils as dated tips and conducting a total-evidence analysis, for example in the program BEAST2. Tip-dating is being actively explored, but all work to date has only used discrete (qualitative) characters for fossil tips. However, continuous (quantitative) characters are often available for fossil specimens, and ideally tip-dating analyses would include these as well. To enable such analyses, continuous-data capabilities were added to the R package BEASTmasteR. BEASTmasteR takes a data table of continuous traits and converts them into BEAST2 XML format, adding these characters to any DNA, amino acid, and/or discrete morphological data that is available. The likelihood of continuous traits on the tree is calculated using the Brownian motion model available in BEAST2 through modification of BEAST2's 2-dimensional continuous phylogeography model into a 1-dimensional model for any trait. Each trait is given a separate rate parameter which is also estimated. To test the validity of the model, continuous characters were simulated on an assumed tree (derived from a dated canid tree) with 22 tips (both fossil and living) under a Brownian motion model. Sets of 10, 25, or 100 continuous characters were generated and BEAST2 XML files were constructed using BEASTmasteR. Each BEAST2 inference was run for 50,000,000 generations. Inference on 10- or 25-character datasets converged quickly on the true tree, with the 25-character dataset showing higher posterior probabilities for many clades (only 4 branches with <50% posterior probability, PP) than the 10-character dataset (10 branches with <50% PP). Dating uncertainty also decreased by about 30%. However, the 100-character dataset failed to converge, perhaps because of the difficulty of jointly searching tree space and 100 rate parameters. The implications for practical analysis will be discussed, including the importance of the assumptions of independence between characters and independent rates. BEASTmasteR performance indicates that it should be helpful to researchers exploring continuous data: BEAST2 XML setup with continuous data takes <1 minute in BEASTmasteR, but at least 4 hours for an experienced user constructing the XML input by hand.

Evolution 2015

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Matzke, Nicholas J. (2015). Historical biogeography models with dispersal probability as a function of distance

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Matzke, Nicholas J. (2015). "Historical biogeography models with dispersal probability as a function of distance(s)." SSE symposium: Frontiers in Parametric Biogeography, Presentations for the SSB Biogeography Symposium in Guarujá, Brasil, Evolution 2015. 10:45-11:15 a.m.

PDF of presentation: http://phylo.wikidot.com/local--files/abstracts-for-presentations-by-nicholas-j-matzke/2015-06-30_Matzke_DEC%2BJ%2Bx_Evo2015_v3.pdf

Massana et al. (2015). Non-null effects of a null range: Exploring parameter estimation in the dispersal-extinction-cladogenesis model.

(link to this section)

Massana, Kathryn; Beaulieu, Jeremy; Matzke, Nicholas J.; O'Meara, Brian (2015). "Non-null effects of a null range: Exploring parameter estimation in the dispersal-extinction-cladogenesis model." SSE symposium: Frontiers in Parametric Biogeography, Presentations for the SSB Biogeography Symposium in Guarujá, Brasil, Evolution 2015. 8:45-9:15 a.m.

Dupin et al. (2015). Solanaceae biogeography: dispersal patterns over space and time.

(link to this section)

Dupin, Julia; Matzke, Nicholas; Knapp, Sandra; Bohs, Lynn; Olmstead, Richard; Särkinen, Tiina; Smith, Stacey D. (2015). "Solanaceae biogeography: dispersal patterns over space and time." Poster session, 7 p.m., Sala de exposições room, at Evolution 2015 in Guarujá, Brasil.

Society for Systematic Biologists Standalone Meeting 2015, Ann Arbor, Michigan

Zhang et al. (2015), Biogeography of Caribbean weevils highlights the importance of founder-event speciation

(link to this section)

Zhang, Guanyang; Barashat, Usmaan; Matzke, Nicholas J.; Franz, Nico (2015). Biogeography of Caribbean weevils highlights the importance of founder-event speciation. Society for Systematic Biologists Standalone Meeting 2015 (SSB2015), Ann Arbor, Michigan, May 21, 2015. http://ssb2015standalone.weebly.com/program.html http://www.slideshare.net/GYZhang1/b-100-zhang

Matzke (2015), BEASTmasteR: Tip-dating with fossils in Beast2, using R to convert NEXUS data files to XML input

(link to this section)
Matzke, Nicholas J. (2015). "BEASTmasteR: Tip-dating with fossils in Beast2, using R to convert NEXUS data files to XML input." Lightning Talk, Society of Systematic Biology Standalone Meeting 2015 (SSB2015), Ann Arbor, Michigan. 1:30 pm, session C, Michigan Union, Pendleton room. http://ssb2015standalone.weebly.com/program.html http://phylo.wdfiles.com/local--files/beastmaster/2015-05-21_Matzke_SSB2015_BEASTmasteR_v1.pdf

Dating dinos by putting fossils in trees: simultaneous estimation of evolutionary relationships and phylogenetic divergence times of dinosaurs (and other groups) with Bayesian MCMC techniques, February 27, 2015

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Title: Dating dinos by putting fossils in trees: simultaneous estimation of evolutionary relationships and phylogenetic divergence times of dinosaurs (and other groups) with Bayesian MCMC techniques

Date: Friday, February 27, 2015
Time: 4 pm
Location: Room 213 Academic Support Building B. Department of Math, Howard University: http://www.coas.howard.edu/mathematics/colloquia&seminars.html

Room: Room 213 Academic Support Building B
Host: Alex Burstein

SUMMARY:

Fossil data are crucial to correct estimation of phylogeny and divergence times. However, most traditional methods artificially separate the analysis of fossil relationships and divergence time analysis. For example, it is common for paleontologists to estimate the topological position of fossils using cladistic or Bayesian methods, either in a morphology-only or “total evidence” analysis. This tree, which is undated, may then be used by molecular biologists to supply calibration distributions for dating a molecules-only tree of living taxa, using a Bayesian MCMC program such as BEAST ("Bayesian Evolutionary Analysis by Sampling Trees"). Such trees form the starting point for various comparative methods which require dated phylogenies, e.g., model-based ancestral state analyses, diversification analyses, or historical biogeography.

Such procedures “throw away” most of the fossil data, treating paleontology as merely a source of calibration points for molecular analyses, and separate the questions of estimating relationships and dating, when in fact they may be linked. However, increasing collaboration between paleontologists, biologists, statisticians and computer scientists has been fruitful in yielding new technologies and techniques that attempt to combine fossil and living morphology, fossil dates, and molecular data in joint analyses, also known as "tip-dating" as the dated fossils are included as tips in the phylogenetic tree.

I discuss BEASTmasteR, an R package that can combine fossil, DNA, and dating information into the complex XML input required by BEAST. BEASTmasteR also produces XML Bayesian hierarchical models encoding absolute or relative dating information, including: (1) fossil tips with uncertain dates (e.g., date-ranges based on stratigraphic bins, or distributions derived from radiometric dates); (2) relative dating information for tips (e.g., in some cases two fossils from the same deposit have approximately the same date, despite their absolute date being uncertain; or one fossil may be known to be older than another); and (3) relative dating information for nodes with linked dates. These approaches are demonstrated on several invertebrate and vertebrate datasets. In assassin spiders, inclusion of amber-preserved fossils as tips supports divergences consistent with ancient Gondwanan vicariance. In salmonids, inclusion of Eosalmo as a tip suggests that genome duplication preceded the evolution of anadromy by 45-60 My. In hominids, linking nodes of a gene tree/species tree analysis to a fossil tip-dated phylogeny inferred a human-chimp divergence at 4.38-5.54 Ma, while a morphology-only analysis yielded 4.5-8.95 Ma. With theropod dinosaurs, Bayesian joint estimation supports traditional views about the relationships of Archaeopteryx to other dinosaurs.

http://phylo.wikidot.com/beastmaster

Bavaria State Botanical Garden and Herbarium, January 2015

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Title: Model Selection in Historical Biogeography: when is Founder-event Speciation important?

Date: Friday, January 26, 2015
Time: 11 am
Location: Botanische Staatssammlung München
(Bavarian State Collection for Botany, Munich, Bavaria, Germany)
http://www.snsb.mwn.de/index.php/en/institutionen-2?id=60

The Bavarian Natural History Collections (Staatliche Naturwissenschaftliche Sammlungen Bayerns, SNSB)
http://www.snsb.mwn.de/index.php/en/

Room: TBA
Host: Susanne Renner, Ludwig-Maximilians-Universität, Munich (LMU Munich), Germany; Director of the Botanical Gardens of Munich, Director of the Herbaria in Munich
http://www.sysbot.biologie.uni-muenchen.de/en/people/renner/

SUMMARY:

New Biogeography Model: Founder-event speciation, where a rare jump dispersal event founds a new genetically isolated lineage, has long been considered crucial by many historical biogeographers, but its importance is disputed within the vicariance school. Probabilistic modeling of geographic range evolution creates the potential to test different biogeographical models against data using standard statistical model choice procedures, as long as multiple models are available. I re-implement the Dispersal-Extinction-Cladogenesis (DEC) model of LAGRANGE in the R package BioGeoBEARS, and modify it to create a new model, DEC+J, which adds founder-event speciation, the importance of which is governed by a new free parameter, j. Both models are shown to be special cases of the "claSSE" model.

Simulation tests: The identifiability of DEC and DEC+J is tested on datasets simulated under a wide range of macroevolutionary models where geography evolves jointly with lineage birth/death events. The results confirm that DEC and DEC+J are identifiable even though these models ignore the fact that molecular phylogenies are missing many cladogenesis and extinction events. The simulations also indicate that DEC will have substantially increased errors in ancestral range estimation and parameter inference when the true model includes +J.

Empirical tests: DEC and DEC+J are compared on 13 empirical datasets drawn from studies of island clades. Likelihood ratio tests indicate that all clades reject DEC, and AICc model weights show large to overwhelming support for DEC+J, for the first time verifying the importance of founder-event speciation in island clades via statistical model choice. Under DEC+J, ancestral nodes are usually estimated to have ranges occupying only one island, rather than the widespread ancestors often favored by DEC. These results indicate that the assumptions of historical biogeography models can have large impacts on inference and require testing and comparison with statistical methods.

Further applications: Probabilistic modeling in biogeography opens up many possible research applications, including biogeographical stochastic mapping, biogeographical dating, and inclusion of phylogenetic information in species distribution modeling (SDM).

BioGeoBEARS: Help, tutorials and updates on the BioGeoBEARS R package are available at:

http://phylo.wikidot.com/biogeobears

University of Helsinki, January 2015

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Title: Model Selection in Historical Biogeography: when is Founder-event Speciation important?

Date: Friday, January 16, 2015: Lecture 2 pm
Time: 2 pm - 2:45 pm
Location: Geosciences Department, University of Helsinki, Finland
Room: TBA
Host: Laura K Säilä, Dept. of Geosciences, University of Helsinki, Finland

SUMMARY:

New Biogeography Model: Founder-event speciation, where a rare jump dispersal event founds a new genetically isolated lineage, has long been considered crucial by many historical biogeographers, but its importance is disputed within the vicariance school. Probabilistic modeling of geographic range evolution creates the potential to test different biogeographical models against data using standard statistical model choice procedures, as long as multiple models are available. I re-implement the Dispersal-Extinction-Cladogenesis (DEC) model of LAGRANGE in the R package BioGeoBEARS, and modify it to create a new model, DEC+J, which adds founder-event speciation, the importance of which is governed by a new free parameter, j. Both models are shown to be special cases of the "claSSE" model.

Simulation tests: The identifiability of DEC and DEC+J is tested on datasets simulated under a wide range of macroevolutionary models where geography evolves jointly with lineage birth/death events. The results confirm that DEC and DEC+J are identifiable even though these models ignore the fact that molecular phylogenies are missing many cladogenesis and extinction events. The simulations also indicate that DEC will have substantially increased errors in ancestral range estimation and parameter inference when the true model includes +J.

Empirical tests: DEC and DEC+J are compared on 13 empirical datasets drawn from studies of island clades. Likelihood ratio tests indicate that all clades reject DEC, and AICc model weights show large to overwhelming support for DEC+J, for the first time verifying the importance of founder-event speciation in island clades via statistical model choice. Under DEC+J, ancestral nodes are usually estimated to have ranges occupying only one island, rather than the widespread ancestors often favored by DEC. These results indicate that the assumptions of historical biogeography models can have large impacts on inference and require testing and comparison with statistical methods.

Further applications: Probabilistic modeling in biogeography opens up many possible research applications, including biogeographical stochastic mapping, biogeographical dating, and inclusion of phylogenetic information in species distribution modeling (SDM).

BioGeoBEARS: Help, tutorials and updates on the BioGeoBEARS R package are available at:

http://phylo.wikidot.com/biogeobears

IBS 2015, Bayreuth, Germany

(link to this section)

Title: Biogeographical Stochastic Mapping: Bayesian estimation of the history and timing of biogeographical events on phylogenies

Nicholas Matzke (2015). "Biogeographical Stochastic Mapping: Bayesian estimation of the history and timing of biogeographical events on phylogenies." Talk at the 2015 Biannual Meeting of the International Biogeography Society. Session: Historical and Paleo-Biogeography. January 10, 2015, 13:30-13:45, H 22, RW II.

Date: Saturday, January 10, 2015
Time: 1:30-1:45 pm

Link: http://www.bayceer.uni-bayreuth.de/ibs2015/en/prog/bayconf/beitrag_detail.php?id_obj=12643

Summary: Traditional likelihood methods in historical biogeography estimate the probability of each geographic range at each node. Usually the most-probable range at each node is plotted, and this is taken to be the approximate history. This is not technically accurate and might be badly misleading in some cases. A solution is stochastic mapping of possible histories on the phylogeny. This has been widely applied in phylogenetics for sequence data and discrete characters, but these character models are inappropriate in historical biogeography, where the state space is much more complex, and geographic range changes through both anagenetic and cladogenetic events. I present a novel algorithm that enables stochastic mapping on any biogeographic model available in BioGeoBEARS, as well as graphical display and statistical summary of the timing and frequency of dispersal and vicariance events. An animation of realizations of possible histories under the DEC and DEC+J models is demonstrated for Hawaiian Psychotria shrubs. R functions and an example script performing stochastic mapping are available at http://phylo.wikidot.com/biogeobears . The functions build upon on the R package BioGeoBEARS, available for all platforms at CRAN.

Contact: gro.soibmin|ekztam#gro.soibmin|ekztam

Supplementary Information: R source code is also archived in this article’s online Supplementary Data. (And here: http://phylo.wikidot.com/biogeobears#stochastic_mapping )

SVP 2014, Berlin: Putting fossils in trees: new methods for combining morphology, time, and molecules to estimate phylogenetic position and divergence times of living and fossil taxa

(link to this section)

Note 1: See the Abstracts for "Putting Fossils in Trees Symposium"
Note 2: See the BEASTmasteR code and example scripts!

Putting fossils in trees: new methods for combining morphology, time, and molecules to estimate phylogenetic position and divergence times of living and fossil taxa

Co-Convenors: Nicholas J. Matzke, April Wright, Graeme Lloyd, David W. Bapst

Fossil data are crucial to correct estimation of phylogeny and divergence times. However, most traditional methods artificially separate the analysis of fossil relationships and divergence time analysis. For example, it is common for paleontologists to estimate the topological position of fossils using cladistic or Bayesian methods, either in a morphology-only or “total evidence” analysis. This tree, which is undated, may then be used by molecular biologists to supply calibration distributions for dating a molecules-only tree of living taxa. Such trees form the starting point for various comparative methods which require dated phylogenies, e.g., model-based ancestral state analyses, diversification analyses, or historical biogeography.

Such procedures “throw away” most of the fossil data, treating paleontology as merely a source of calibration points for molecular analyses, and separate the questions of estimating relationships and dating, when in fact they may be linked. However, increasing collaboration between paleontologists, biologists, statisticians and computer scientists has been fruitful in yielding new technologies and techniques that attempt to combine fossil and living morphology, fossil dates, and molecular data in joint analyses. This symposium will be devoted to reviewing, discussing, and critiquing new methods and models for estimating phylogenetic trees and for incorporating fossils in the derivation of divergence times.

The three foci of the symposium are: 1. "Model-based methods: advantages and limitations." This will focus on the assumptions behind the current probabilistic models for morphological and fossil data, the resulting advantages and limitations, and suggestions for improvements. 2. "Fossils as terminal taxa in dating analyses: prospects and challenges." Methods using fossils as terminal taxa in dating analyses are new and mostly unevaluated, so participants will present case studies that give insight into the practical benefits and problems encountered in the use of such methods. 3. "Fossils as dual information sources: morphology and stratigraphy." The stratigraphic range and sampling frequency of clades also gives important information about the timing of clade origins. Stratocladistics was an early attempt to take this information into account, but was not widely adopted. Probabilistic methods, as well as advances in fossil databases, may allow improved approaches. Participants will review and critique recent developments in this area.

EvMorph series, University of Chicago, October 2014

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Evolutionary Morphology Seminar: Nicholas Matzke, University of Tennessee

When: Thursday, October 9, 2014 7:30–8:30 p.m.

Where: Henry Hinds Laboratory, Room 176

5734 South Ellis Avenue, Chicago, IL

Description: Model Selection in Historical Biogeography: When is Founder-Event Speciation Important?

Contact: Geophysical Sciences
773-834-0695

Tag: Seminars

Notes: Persons with disabilities who need an accommodation in order to participate in this event should contact the event sponsor for assistance. For events on the Student Events Calendar, please contact ORCSA at (773) 702-8787.

http://events.uchicago.edu/cal/event/eventView.do?b=de&amp%3BcalPath=%2Fpublic%2Fcals%2FMainCal&amp%3Bguid=CAL-ff808081-48cb3bcf-0148-cc0715b7-00001ab4eventscalendar%40uchicago.edu&amp%3BrecurrenceId=#.VDYcSFTIq6g.gmail

SMBE 2014, Puerto Rico

Primary endosymbiosis events date to the later Proterozoic with cross-calibrated phylogenetic dating of duplicated ATPase proteins

Monday 9th June: Life Technologies Lunchtime Symposium / Posters 1001 - 1278 - 9th June 13.00 - 15.30

P-86

Nicholas Matzke 1 ,2, Patrick Shih3 ,4

1 National Institute of Mathematical and Biological Synthesis, University of Tennessee, Knoxville, TN, USA,

2 Department of Integrative Biology, University of California, Berkeley, CA, USA,

3 Joint Bioenergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, USA, 4Department of Plant and Microbial Biology, University of California, Berkeley, CA, USA

Chloroplasts and mitochondria descended from bacterial ancestors, but the dating of these primary endosymbiosis events remains very uncertain, despite their importance for our understanding of the evolution of both bacteria and eukaryotes. All phylogenetic dating in the Proterozoic and before is difficult: Significant debates surround potential fossil calibration points based on the interpretation of the Precambrian microbial fossil record, and strict molecular clock methods cannot be expected to yield accurate dates over such vast timescales because of strong heterogeneity in rates. Even with more sophisticated relaxed-clock analyses, nodes that are distant from fossil calibrations will have a very high uncertainty in dating. However, endosymbiosis events and gene duplications provide some additional information that has never been exploited in dating; namely, that certain nodes on a gene tree must represent the same events, and thus must have the same or very similar dates, even if the exact date is uncertain. We devised techniques to exploit this information: cross-calibration, in which node date calibrations are reused across a phylogeny, and cross-bracing, in which node date calibrations are formally linked in a hierarchical Bayesian model. We apply these methods to proteins with ancient duplications that have remained associated and originated from plastid and mitochondrial endosymbionts: the α and β subunits of ATP synthase and its relatives, and the EF-Tu. The methods yield reductions in dating uncertainty of 14–26% while only using date calibrations derived from phylogenetically unambiguous Phanerozoic fossils of multicellular plants and animals. Our results suggest that primary plastid endosymbiosis occurred ~900 Mya and mitochondrial endosymbiosis occurred ~1,200 Mya.

See poster:

PDF of poster for SMBE 2014

This work is based on:

Shih, Patrick M.; Matzke, Nicholas J. (2013). "Primary endosymbiosis events date to the later Proterozoic with cross-calibrated phylogenetic dating of duplicated ATPase proteins." Proceedings of the National Academy of Sciences, 110(30), 12355-12360. (Scholar | DOI | Journal)

Also, see writeup of this article by:

Zhaxybayeva, Olga (2013). "Anciently duplicated genes reduce uncertainty in molecular clock estimates." Proceedings of the National Academy of Sciences, 110(30), 12168–12169. (Scholar | DOI | Journal)

Evolution 2014, Raleigh, NC

Simulation tests of probabilistic models for historical biogeography: DEC and DEC+J

PDF of draft talk

2C_306B Methodology
Date: Sunday, June 22, 2014
Time: 1:30 PM - 2:45 PM
Location: 306 B
Chair: Mario dos Reis

2:00 PM - 2:15 PM

18

Nicholas Matzke, NIMBioS, gro.soibmin|ekztam#gro.soibmin|ekztam (Presenter)

Contributed Presentation

Simulation tests of probabilistic models for historical biogeography: DEC and DEC+J

Several phylogenetic models for historical biogeography are in widespread use, e.g. character mapping, Dispersal-Vicariance Analysis (DIVA), and Dispersal-Extinction-Cladogenesis (DEC). In addition, new models have become available: BayArea, and the variety of models implemented in the R package BioGeoBEARS. These include DEC+J (which adds founder-event speciation to DEC) and DIVALIKE (a likelihood interpretation of DIVA; a DIVALIKE+J model is also available). There has been very little testing of biogeographical models against simulated data in the situation when the true model is substantially different than the assumed inference model. Also, all of the above models assume that the observed tree is the true tree, ignoring possible missing speciation/extinction events, and dependence of speciation/extinction rates on geographic range. These possibilities are taken into account by the GeoSSE and ClaSSE models, but at the cost of many more free parameters, which may strain typically small biogeographic datasets. To test the accuracy of DEC and DEC+J inference on datasets simulated under different biogeographical and SSE models, I jointly simulated phylogenies and geographic range under 6 macroevolutionary models. The first three assumed speciation/extinction were independent of geographic range: (1) Yule process (pure-birth, no extinction); (2) Birth-Death (BD) process with extinction rate 1/3 of the speciation rate; (3) BD process with extinction equal to speciation. The next three assumed an SSE model where the base speciation rate was multiplied by the number of areas occupied, and base extinction rate was divided by the number of areas occupied. This produced (4) SSE with speciation but zero extinction rate; (5) SSE with with the base extinction rate 1/3 of the speciation rate; and (6) SSE with base rates of speciation and extinction equal. For each of the 6 macroevolutionary models, all combinations of low/middle/high values were used for these biogeographic parameters: d (rate of range-expansion), e (rate of range-contraction), and j (relative weight of founder-events versus traditional DEC cladogenesis events at speciation). The datasets (138 parameter combinations, 100 simulations each with 50 living species) were subjected to inference under DEC and DEC+J. DEC and DEC+J were distinguishable under all 6 models, except when j was very small and d very high. DEC artificially raises d and e when DEC+J is the true model, and shows significantly reduced accuracy in inferring ancestral range. These results indicate that the fact that DEC+J is favored over DEC by many empirical datasets is not likely to be an artefact of missing SSE processes.

Non-null effects of a null range: Exploring parameter estimation in the dispersal-extinction-cladogenesis model

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Non-null effects of a null range: Exploring parameter estimation in the dispersal-extinction-cladogenesis model

3A_301A Phylogenetic Methods
Date: Monday, June 23, 2014
Time: 8:30 AM - 9:45 AM

Location: 301 A
Chair: Elizabeth Wade
9:15 AM - 9:30 AM

Kathryn Massana, University of Tennessee, Knoxville, ude.ktu|anassamk#ude.ktu|anassamk (Presenter)
Jeremy Beaulieu, NIMBios, gro.soibmin|ueiluaebj#gro.soibmin|ueiluaebj
Brian O'Meara, ude.ktu|araemob#ude.ktu|araemob
Nicholas Matzke, NIMBioS, gro.soibmin|ekztam#gro.soibmin|ekztam

Parametric models in historical biogeography that integrate geographic ranges and phylogenies have shown to be extremely informative in understanding the geographic range evolution of taxa. One such approach is the dispersal-extinction-cladogenesis (DEC) model, which has been widely used in empirical analyses of the evolution of geographic range using discrete area states. However, local extinction rates are difficult to estimate well in this model. We explore the cause of this as well as a potential solution.

rexpokit and cladoRcpp: R packages integrating FORTRAN and C++ for faster matrix exponentiation and likelihood calculations in historical biogeography

PDF of draft talk

ievobioE_402 iEvoBio software bazaar

Open-source software demos and reception for iEvoBio

Date: Tuesday, June 24, 2014

Time: 3:15 PM - 5:00 PM

Location: 402

rexpokit and cladoRcpp: R packages integrating FORTRAN and C++ for faster matrix exponentiation and likelihood calculations in historical biogeography (1219)
Nicholas Matzke, NIMBioS (United States)
Drew Schmidt, University of Tennessee

1219

Drew Schmidt, University of Tennessee, ude.ktu.htam|tdimhcs#ude.ktu.htam|tdimhcs
Nicholas Matzke, NIMBioS, gro.soibmin|ekztam#gro.soibmin|ekztam (Presenter)

iEvoBio Software Demo

rexpokit and cladoRcpp: R packages integrating FORTRAN and C++ for faster matrix exponentiation and likelihood calculations in historical biogeography

Probabilistic models for phylogeny-based inference of historical biogeography face several computational challenges, especially when programmed in R. The first is large state spaces: for example, an analysis using 10 discrete geography areas has 2^10=1024 possible combinations of presence/absence in each region, and a transition matrix that is 1024x1024. Exponentiating this matrix is extremely slow in standard R matrix exponentiation routines. The R package "rexpokit" integrates the FORTRAN EXPOKIT library, making exponentiation of such large matrices feasible, although not rapid. Further speed improvements are made by parallel processing. A second challenge is enumerating and assigning probabilities to different biogeographical events at cladogenesis. Here, a naive implementation would have to examine every possible combination of ancestor state, left descendant state, and right descendant state, which would be 1023^3, or over 1 billion combinations. Here I made great improvements in speed with algorithms that eliminate impossible combinations a priori, and use of Rcpp for all for-loops. This is implemented in the R package cladoRcpp. I will present quick demonstrations of these calculations, the resulting speedups, and suggest that these packages can serve as relatively simple examples for researchers wishing to integrate FORTRAN or C++ into their R programming.

Rexpokit: http://cran.r-project.org/web/packages/rexpokit/index.html CladoRcpp: http://cran.r-project.org/web/packages/cladoRcpp/index.html Used for historical biogeography by: BioGeoBEARS: BioGeography with Bayesian (and Likelihood) Evolutionary Analysis in R Scripts http://cran.r-project.org/web/packages/BioGeoBEARS/index.html Examples, updates, and help listserv are at PhyloWiki: http://phylo.wikidot.com/biogeobears

GNU General Public License version 3.0 (GPL-3.0) http://opensource.org/licenses/GPL-3.0

SVP 2014, Berlin: Tip-Dating: Estimating Dated Phylogenies Using Fossils as Terminal Taxa

(link to this section)

Note: See the BEASTmasteR code and example scripts!

Tip-Dating: Estimating Dated Phylogenies Using Fossils as Terminal Taxa - FULL

This workshop will introduce participants to new computational methods that allow joint inference of phylogenetic relationships and divergence times. In older dating methods, fossil relationships were estimated with an undated cladistic or Bayesian analysis, and then these fossils were converted, usually subjectively, into prior probability distributions on the dates of certain nodes. These calibrations were then used in molecular clock analyses to date molecular trees. This procedure essentially “threw away” hard-won fossil data (and any living morphology data as well) once the dating calibration was produced.

However, in the last two years, several methods have become available that allow the addition of fossil and living morphology, as well as fossil dates, to dating analyses. In these methods, the phylogenetic relationships of the fossils and living taxa are estimated simultaneously with the dating of the tree. These methods have the potential to revolutionary for paleontologists. First, because character and dating data from fossil specimens are a requirement for the method, paleontologists and morphologists will have an increased role to play in future divergence time analyses, previously the domain of molecular biologists. Second, the joint estimation of fossil relationships and the divergence times of fossil taxa is of intrinsic interest, and many phylogenetic comparative methods can be applied to fossil data once statistically-estimated, time-scaled trees of fossil taxa are available.

The two main methods in use currently are BEAST (Pyron 2011; Wood, Matzke et al. 2013; Alexandrous et al. 2013) and MrBayes 3.3 (Ronquist et al. 2012). Both take more skill and background than traditional phylogeny-estimation and dating methods. Therefore we will guide participants through tutorials and then help them to set up analyses of their own data.

Date: Tuesday, November 4

Time: 10:00am - 4:00pm

Location: The Leibniz Headquarters (Chausseestr. 111, 150 meters away from the Museum für Naturkunde and next to the UBahn station Naturkundemuseum)

Cost: Free (FULL!)
Minimum Number of Participants: 10
Maximum Number of Participants: 40

Leaders:

Nicholas J. Matzke
National Institute for Mathematical and Biological Synthesis
University of Tennessee
gro.soibmin|ekztam#gro.soibmin|ekztam

April Wright
Univeristy of Texas, Austin
moc.liamg|mlirpa.thgirw#moc.liamg|mlirpa.thgirw

Society for Molecular Biology and Evolution (SMBE) 2014 Poster

Title: "Primary endosymbiosis events date to the later Proterozoic with cross-calibrated phylogenetic dating of duplicated ATPase proteins."

Society for Molecular Biology and Evolution (SMBE) 2013 Poster

Title: "Tighter estimation of hominoid divergence times by hierarchical Bayesian analysis of dated fossil morphology and incompletely sorted genes."

International Biogeography Society 2013 Poster

Link to the poster PDF and poster abstract. Title: "Founder-event speciation in BioGeoBEARS package dramatically improves likelihoods and alters parameter inference in Dispersal-Extinction-Cladogenesis (DEC) analyses."

References also included

Animation Of The Geographical History Of The Hawaiian Islands

Animation Of The Geographical History Of The Hawaiian Islands, based on Clague (1996), R code by Nick Matzke.

R-based Labs for IB200B - Phylogenetics - Ecology & Evolution, spring 2011, U.C. Berkeley Dept. of Integrative Biology

R-based Labs for IB200B - Phylogenetics - Ecology & Evolution, spring 2011, U.C. Berkeley Dept. of Integrative Biology

WORKSHOP: Methodological Workshop on Biodiversity Dynamics

Methodological Workshop on Biodiversity Dynamics — for: "Evolution of Life on Pacific Islands and Reefs: Past, present, and future", May 26, 2011

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