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Publisher's Award for Excellence in Systematic Research


This Award is sponsored by Systematic Biology's publisher. The award is presented to the two best papers based on student research published in Systematic Biology during the previous year. The lead author must have been a student at the time the research was conducted. The Publisher's Award is $US 500 and is presented at the annual meeting to the student authors. If an article is co-authored by 2 or more students then special arrangements can be made to ensure appropriate recognition of each. The award was initiated with Volume 48 (1998) and the first award was presented at the 1999 meeting. The winner is selected by the Editor-In-Chief. No application is required.
2024 Publisher's Award for Excellence in Systematic Research

Xiao-Xu Pang, Beijing Normal University.

Xiao-Xu Pang, Da-Yong Zhang, Detection of Ghost Introgression Requires Exploiting Topological and Branch Length Information, Systematic Biology, Volume 73, Issue 1, January 2024, Pages 207–222, https://doi.org/10.1093/sysbio/syad077

Ghost introgression –  introgression from an extinct or unsampled lineage into an extant species – poses a significant problem for introgression inference methods. Xiao-Xu and collaborators evaluate the efficacy of full likelihood and heuristic approaches to detect outgroup ghost introgression and distinguishing it from other type of introgression scenarios. Using theory and simulations, they find that gene tree topologies or site pattern counts alone do not provide enough information to distinguish among these models, and that full-likelihood models that make use of branch length information are required to avoid running into unidentifiability issues.


Rong Zhang, Auckland University. Current affiliation: Fudan University

Rong Zhang, Alexei J Drummond, Fábio K Mendes, Fast Bayesian Inference of Phylogenies from Multiple Continuous Characters, Systematic Biology, Volume 73, Issue 1, January 2024, Pages 102–124, https://doi.org/10.1093/sysbio/syad067

Rong and collaborators present a novel total-evidence dating (TED) approach in which the phylogenetic tree and divergence times for both extant and fossil taxa are jointly estimated, integrating the evolution of continuous and discrete morphological characters (for fossil placement in the phylogeny) as well as molecular characters (for estimating branch lengths). They validate the accuracy and precision of their method using both simulations and an empirical dataset for the order Carnivora. A particularly exciting contribution to the field of macroevolution is the inclusion of continuous morphological characters with intra-species variation. This introduces challenges such as modeling covariance among characters and addressing non-identifiability, while also enabling the possibility of estimating a morphological clock alongside the molecular clock.

Past Winners

2023

Julia Van Etten, Rutgers University

J. Van Etten, T.G. Stephens, D. Bhattacharya. A k-mer-based approach for phylogenetic classification of taxa in environmental genomic data. Systematic Biology, September 2023. 72(5):1101-1118. https://doi.org/10.1093/sysbio/syad037


Editorial summary: Julia and collaborators assess the validity of alignment-free based methods such as k-mer based distances for phylogenetic classification and compare them with traditional multi-gene alignments. They demonstrate the accuracy of k-mer based distances when applied to highly incomplete genomes, showcasing their potential utility in characterizing cryptic species from environmental genome data. This type of data is common in unicellular algal and bacterial systematics. This method raised great interest among scientists working in the field of environmental genomics and meta genomics.

Lénard Lajos Szánthó, Eötvös University

L.L. Szánthó, N. Lartillot, G.J. Szöllősi, D. Schrempf. Compositionally constrained sites drive long-branch attraction. Systematic Biology, July 2023. 72(4):767-780. https://doi.org/10.1093/sysbio/syad013


Editorial summary: Lenard and collaborators investigate the link between long-branch attraction and across-site compositional heterogeneity in deep phylogenetics via simulations and empirical datasets. They also propose a new pipeline based on the CAT model (CAT-PMSF) to assess the risk of compositional heterogeneity bias when the CAT model does not converge. Given the computational effort required to run a CAT analysis on a large genomic dataset, this work is particularly relevant. The authors do not only offer a tool to help researchers be aware of the effects of this model deviation on phylogenetic accuracy, but also a way to solve it.

2022

Jérémy Andréoletti, ETH Zürich  and
Antoine Zwaans,
ETH Zürich

J. Andréoletti, A. Zwaans, R.C.M. Warnock, G. Aguirre-Fernández, J. Barido-Sottani, A. Gupta, T. Stadler, M. Manceau. The Occurrence Birth-Death Process for combined-evidence analysis in macroevolution and epidemiology. Systematic Biology, November 2022. 71(6):1440-1452. https://doi.org/10.1093/sysbio/syac037

Editorial summary: Jérémy, Antoine, and collaborators introduce a new model to compute the joint probability density of a phylogenetic tree and a record of occurrences: e.g., taxa with no associated data such as fossils representing extinct lineages with known stratigraphic age, or epidemiological patients for which there is no associated sequence. It extends a previous approach by the senior author, adding a piece-wise process that allows discrete shifts in the rate of parameters such as speciation, extinction and sampling. One interesting aspect of the model is that it can be used with mixed datasets, where some tips are associated with data (fossils with coded morphological characters) and others are not (fossil records from the Paleobiology Database). They implement their Occurrence Birth-Death Process (OBDP) as a new distribution in the Bayesian software RevBayes, allowing it to be used as a tree prior for morphological state reconstruction or biogeography.


Yueyu Jiang, University of California, San Diego

Y. Jiang, M. Balaban, Q. Zhu, S. Mirarab. DEPP: Deep Learning Enables Extending Species Trees using Single Genes. Systematic Biology, January 2023. 72(1):17-34. https://doi.org/10.1093/sysbio/syac031


Editorial summary: Yueyu and collaborators tackle a common problem in current phylogenomics, placing a sequence/s obtained from a single gene into a phylogenomic backbone. The common approach is to assume the that new sequences and the genomic reference phylogeny evolved under the same molecular evolutionary process. Here, they present a deep learning algorithm that learns to extend a genomic species tree without any prior knowledge of the model, and with levels of accuracy similar to model-based approaches. The method is very timely, especially for the fields of epidemiology and environmental DNA, and in line with recent advances in the field of online phylogenetics.

2021

Alexander A Fisher, University of California, Los Angeles

Alexander A Fisher, Xiang Ji, Zhenyu Zhang, Philippe Lemey, and Marc A Suchard. Relaxed Random Walks at Scale. Systematic Biology, March 2021. 70(2):258–267. https://doi.org/10.1093/sysbio/syaa056

Wilson X Guillory, Southern Illinois University

Wilson X Guillory and Jason L Brown. A New Method for Integrating Ecological Niche Modeling with Phylogenetics to Estimate Ancestral Distributions. Systematic Biology, September 2021. 70(5):1033–1045. https://doi.org/10.1093/sysbio/syab016

2020

Mariana P Braga, Stockholm University

Mariana P Braga, Michael J Landis, Sören Nylin, Niklas Janz, and Fredrik Ronquist. Bayesian Inference of Ancestral Host–Parasite Interactions under a Phylogenetic Model of Host Repertoire Evolution. Systematic Biology, November 2020. 69(6):1149–1162. https://doi.org/10.1093/sysbio/syaa019

Nicolás Mongiardino Koch, Yale University

Nicolás Mongiardino Koch and Luke A Parry. Death is on Our Side: Paleontological Data Drastically Modify Phylogenetic Hypotheses. Systematic Biology, November 2020. 69(6):1052-1067. https://doi.org/10.1093/sysbio/syaa023

2019

Miroslav Valan, Swedish Museum of Natural History and Stockholm University

Miroslav Valan, Karoly Makonyi, Atsuto Maki, Dominik Vondráček, and Fredrik Ronquist. Automated Taxonomic Identification of Insects with Expert-Level Accuracy Using Effective Feature Transfer from Convolutional Networks. Systematic Biology, November 2019. 68(6):876–895. https://doi.org/10.1093/sysbio/syz014

Kirilee Chaplin, Museums Victoria and The University of Melbourne

Kirilee Chaplin, Joanna Sumner, Christy A Hipsley, and Jane Melville. An Integrative Approach Using Phylogenomics and High-Resolution X-Ray Computed Tomography for Species Delimitation in Cryptic Taxa. Systematic Biology, March 2020. 69(2):294-307. https://doi.org/10.1093/sysbio/syz048


2018

Carolina Costa and Paula Lemos-Costa, University of Campinas (both authors share first-authorship and equal contribution)

Carolina Costa, Paula Lemos-Costa, Flavia Marquitti, Lucas Fernandes, Marlon Ramos, David Schneider, Ayana Martins, and Marcus De Aguiar. Signature of Microevolutionary Processes in Phylogenetic Patterns. Systematic  Biology, January  2019.  68(1):131–144. https://doi.org/10.1093/sysbio/syy049


Julien Troudet, French National Museum of Natural History

Julien Troudet, Régine Vignes-Lebbe, Philippe Grandcolas, and Frédéric Legendre. The Increasing Disconnection of Primary Biodiversity Data from Specimens. Systematic Biology, November 2018. 67(6):1110–1119. https://doi.org/10.1093/sysbio/syy044


2017

Jacob S. Berv, Cornell University

Jacob S. Berv and Daniel J. Field. Genomic Signature of an Avian Lilliput Effect across the K-Pg Extinction. Systematic Biology, January 2018. 67(1):1–13. https://doi.org/10.1093/sysbio/syx064

Konstantinos Angelis, University College London

Konstantinos Angelis, Sandra Álvarez-Carretero, Mario Dos Reis, and Ziheng Yang. An Evaluation of Different Partitioning Strategies for Bayesian Estimation of Species Divergence Times. Systematic Biology, January 2018. 67(1):61–77. https://doi.org/10.1093/sysbio/syx061


2016

Anna Kostikova, University of Lausanne, Swiss Institute of Bioinformatics
Anna Kostikova, Daniele Silvestro, Peter B. Pearman, Nicolas Salamin; Bridging Inter- and Intraspecific Trait Evolution with a Hierarchical Bayesian Approach, Systematic Biology, Volume 65, Issue 3, 1 May 2016, Pages 417–431, https://doi.org/10.1093/sysbio/syw010

Kathryn Everson, University of Alaska Museum
Kathryn M. Everson, Voahangy Soarimalala, Steven M. Goodman, Link E. Olson; Multiple Loci and Complete Taxonomic Sampling Resolve the Phylogeny and Biogeographic History of Tenrecs (Mammalia: Tenrecidae) and Reveal Higher Speciation Rates in Madagascar's Humid Forests, Systematic Biology, Volume 65, Issue 5, 1 September 2016, Pages 890–909, https://doi.org/10.1093/sysbio/syw034

2015

Eric W. Goolsby, University of Georgia
Eric W. Goolsby; Phylogenetic Comparative Methods for Evaluating the Evolutionary History of Function-Valued Traits. Syst Biol 2015; 64 (4): 568-578. doi: 10.1093/sysbio/syv012
 
Andrea S. Meseguer, Real Jardín Botánico CSIC
Andrea S. Meseguer, Jorge M. Lobo, Richard Ree, David J. Beerling, Isabel Sanmartín; Integrating Fossils, Phylogenies, and Niche Models into Biogeography to Reveal Ancient Evolutionary History: The Case of Hypericum (Hypericaceae). Syst Biol 2015; 64 (2): 215-232. doi: 10.1093/sysbio/syu088
​

2014

Lam si Tung Ho, University of Wisconsin – Madison
Lam si Tung Ho, Cécile Ané; A Linear-Time Algorithm for Gaussian and Non-Gaussian Trait Evolution Models. Syst Biol 2014; 63 (3): 397-408. doi: 10.1093/sysbio/syu005
 
Noah M. Reid, Louisiana State University
Noah M. Reid, Sarah M. Hird, Jeremy M. Brown, Tara A. Pelletier, John D. McVay, Jordan D. Satler, Bryan C. Carstens; Poor Fit to the Multispecies Coalescent is Widely Detectable in Empirical Data. Syst Biol 2014; 63 (3): 322-333. doi: 10.1093/sysbio/syt057
​

2013

Arley Camargo, Brigham Young University
Camargo, A., L. J. Avila, M. Morando, and J. W. Sites Jr. 2012. Accuracy and Precision of Species Trees: Effects of Locus, Individual, and Base Pair Sampling on Inference of Species Trees in Lizards of the Liolaemus darwinii Group (Squamata, Liolaemidae). Syst. Biol. 61(2):272-288 doi:10.1093/sysbio/syr105

Felipe Zapata, University of Missouri - St. Louis
Zapata, F. and I. Jiménez. 2012. Species Delimitation: Inferring Gaps in Morphology across Geography. Syst. Biol. 61(2):179-194 doi:10.1093/sysbio/syr084

2007

Rachel Mueller, University of California, Berkeley.
Mueller, R. 2006. Evolutionary Rates, Divergence Dates, and the Performance of Mitochondrial Genes in Bayesian Phylogenetic Analysis. Syst. Biol. 55(2): 289-300.

Eric Schuettpelz, Duke University.
Schuettpelz, E. and K.M. Pryer. 2006. Reconciling Extreme Branch Length Differences: Decoupling Time and Rate through the Evolutionary History of Filmy Ferns. Syst. Biol. 55(3): 485-502.

2006

Céline Poux, Radboud University, The Netherlands.
Poux,C., O. Madsen, E. Marquard, D.R. Vieites, W.W. de Jong, and M.Vences. 2005. Asynchronous Colonization of Madagascar by the Four Endemic Clades of Primates, Tenrecs, Carnivores, and Rodents as Inferred from Nuclear Genes. Syst. Biol. 54(5):719-730.

Richard C. Winkworth, Yale University.
Winkworth, R.C., D. Bryant, P.J. Lockhart, D. Havell, and V. Moulton. 2005.Biogeographic Interpretation of Splits Graphs: Least Squares Optimization of Branch Lengths. Syst. Biol. 54(1):56-65

2005

Alan Richard Lemmon and Emily Claire Moriarty (both students), The University of Texas, Austin.
Lemmon A.R., and E.C. Moriarty. 2004. The Importance of Proper Model Assumption in Bayesian Phylogenetics. Syst. Biol. 53(2):265-277.

Johan Nylander, Uppsala University, Sweden.
Nylander,J.A., A.F. Ronquist, J.P. Huelsenbeck, and J.L. Nieves-Aldrey. 2004. Bayesian Phylogenetic Analysis of Combined Data. Syst. Biol. 53(1):47-67

2004

Stéphane Aris-Brosou, North Carolina State University, Raleigh.
Aris-Brosou, S. 2003. Least and Most Powerful Phylogenetic Tests to Elucidate the Origin of the Seed Plants in Presence of Conflicting Signals under Misspecified Models. Syst. Biol. 52(6):781-793.

Rachel Collin, Smithsonian Tropical Research Institute, Panama.
Collin, R. 2003. Phylogenetic Relationships among Calyptraeid Gastropods and their Implications for the Biogeography of Speciation. Syst.Biol. 52(5):618-640

2003

Sérgio L. Pereira, Centre for Biodiversity and Conservation Biology, Royal Ontario Museum and Depto Biologia, Universidade de São Paulo, Brazil.
Pereira, S. L., A.J. Baker, and A. Wajnta. 2002. Combined Nuclear and Mitochondrial DNA Sequences Resolve Generic Relationships within the Cracidae (Galliformes, Aves). Syst. Biol. 51(6):946-958.

Marc A. Suchard, UCLA School of Medicine.
Suchard,M.A., R.E. Weiss, K.S. Dorman, and J.S. Sinsheimer.
2002. Oh Brother, Where Art Thou? A Bayes Factor Test for Recombination with Uncertain Heritage. Syst. Biol. 51(5):715-728.

2002

David Posada, Brigham Young University.
Posada, D. and K.A. Crandall. 2001. Selecting the Best-Fit Model of Nucleotide Substitution. Syst. Biol. 50(3): 580-601.

George Weiblen, Harvard University Herbaria.
Weiblen, G. 2001. Phylogenetic Relationships of Fig Wasps Pollinating Functionally Dioecious Ficus Based on Mitochondrial DNA Sequences and Morphology. Syst. Biol. 50(2): 243-267.

2000

Mark Simmons and Helga Ochoterena, Cornell University
J. Robert Macey and James Schulte, Washington University

1999

Richard Ree, Harvard University
Kevin McCracken, John Harshman
David McClellan, Louisiana State University

1998

Sharon Messenger, University of Texas at Austin
Sean Graham, University of Toronto
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