Add missing DOI to review paper

JOSS/paper.bib

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  @article{Barido-Sottani_Saupe_Smiley_Soul_Wright_Warnock_2020, title={Seven rules for simulations in paleobiology}, volume={46}, ISSN={0094-8373, 1938-5331}, DOI={10.1017/pab.2020.30}, abstractNote={Simulations are playing an increasingly important role in paleobiology. When designing a simulation study, many decisions have to be made and common challenges will be encountered along the way. Here, we outline seven rules for executing a good simulation study. We cover topics including the choice of study question, the empirical data used as a basis for the study, statistical and methodological concerns, how to validate the study, and how to ensure it can be reproduced and extended by others. We hope that these rules and the accompanying examples will guide paleobiologists when using simulation tools to address fundamental questions about the evolution of life.}, number={4}, journal={Paleobiology}, publisher={Cambridge University Press}, author={Barido-Sottani, Joëlle and Saupe, Erin E. and Smiley, Tara M. and Soul, Laura C. and Wright, April M. and Warnock, Rachel C. M.}, year={2020}, month=nov, pages={435–444}, language={en} }
- @article{Dolson_Ofria_2021, title={Digital Evolution for Ecology Research: A Review}, volume={9}, ISSN={2296-701X}, url={https://www.frontiersin.org/articles/10.3389/fevo.2021.750779}, abstractNote={In digital evolution, populations of computational organisms evolve via the same principles that govern natural selection in nature. These platforms have been used to great effect as a controlled system in which to conduct evolutionary experiments and develop novel evolutionary theory. In addition to their complex evolutionary dynamics, many digital evolution systems also produce rich ecological communities. As a result, digital evolution is also a powerful tool for research on eco-evolutionary dynamics. Here, we review the research to date in which digital evolution platforms have been used to address eco-evolutionary (and in some cases purely ecological) questions. This work has spanned a wide range of topics, including competition, facilitation, parasitism, predation, and macroecological scaling laws. We argue for the value of further ecological research in digital evolution systems and present some particularly promising directions for further research.}, journal={Frontiers in Ecology and Evolution}, author={Dolson, Emily and Ofria, Charles}, year={2021} }
+ @article{Dolson_Ofria_2021, title={Digital Evolution for Ecology Research: A Review}, volume={9}, ISSN={2296-701X}, DOI={10.3389/fevo.2021.750779}, url={https://www.frontiersin.org/articles/10.3389/fevo.2021.750779}, abstractNote={In digital evolution, populations of computational organisms evolve via the same principles that govern natural selection in nature. These platforms have been used to great effect as a controlled system in which to conduct evolutionary experiments and develop novel evolutionary theory. In addition to their complex evolutionary dynamics, many digital evolution systems also produce rich ecological communities. As a result, digital evolution is also a powerful tool for research on eco-evolutionary dynamics. Here, we review the research to date in which digital evolution platforms have been used to address eco-evolutionary (and in some cases purely ecological) questions. This work has spanned a wide range of topics, including competition, facilitation, parasitism, predation, and macroecological scaling laws. We argue for the value of further ecological research in digital evolution systems and present some particularly promising directions for further research.}, journal={Frontiers in Ecology and Evolution}, author={Dolson, Emily and Ofria, Charles}, year={2021} }
  @article{Guillerme_Puttick_Marcy_Weisbecker_2020, title={Shifting spaces: Which disparity or dissimilarity measurement best summarize occupancy in multidimensional spaces?}, volume={10}, rights={© 2020 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.}, ISSN={2045-7758}, DOI={10.1002/ece3.6452}, abstractNote={Multidimensional analysis of traits are now common in ecology and evolution and are based on trait spaces in which each dimension summarizes the observed trait combination (a morphospace or an ecospace). Observations of interest will typically occupy a subset of this space, and researchers will calculate one or more measures to quantify how organisms inhabit that space. In macroevolution and ecology, these measures called disparity or dissimilarity metrics are generalized as space occupancy measures. Researchers use these measures to investigate how space occupancy changes through time, in relation to other groups of organisms, or in response to global environmental changes. However, the mathematical and biological meaning of most space occupancy measures is vague with the majority of widely used measures lacking formal description. Here, we propose a broad classification of space occupancy measures into three categories that capture changes in size, density, or position. We study the behavior of 25 measures to changes in trait space size, density, and position on simulated and empirical datasets. We find that no measure describes all of trait space aspects but that some are better at capturing certain aspects. Our results confirm the three broad categories (size, density, and position) and allow us to relate changes in any of these categories to biological phenomena. Because the choice of space occupancy measures is specific to the data and question, we introduced https://tguillerme.shinyapps.io/moms/moms, a tool to both visualize and capture changes in space occupancy for any measurement. https://tguillerme.shinyapps.io/moms/moms is designed to help workers choose the right space occupancy measures, given the properties of their trait space and their biological question. By providing guidelines and common vocabulary for space occupancy analysis, we hope to help bridging the gap in multidimensional research between ecology and evolution.}, number={14}, journal={Ecology and Evolution}, author={Guillerme, Thomas and Puttick, Mark N. and Marcy, Ariel E. and Weisbecker, Vera}, year={2020}, pages={7261–7275}, language={en} }
  @article{Keating_Sansom_Sutton_Knight_Garwood_2020, title={Morphological Phylogenetics Evaluated Using Novel Evolutionary Simulations}, volume={69}, rights={All rights reserved}, ISSN={1063-5157}, DOI={10.1093/sysbio/syaa012}, abstractNote={Abstract.  Evolutionary inferences require reliable phylogenies. Morphological data have traditionally been analyzed using maximum parsimony, but recent simulat}, number={5}, journal={Systematic Biology}, publisher={Oxford Academic}, author={Keating, Joseph N. and Sansom, Robert S. and Sutton, Mark D. and Knight, Christopher G. and Garwood, Russell J.}, year={2020}, month=sep, pages={897–912}, language={en} }
  @article{Mongiardino_Koch_Garwood_Parry_2021, title={Fossils improve phylogenetic analyses of morphological characters}, volume={288}, rights={All rights reserved}, DOI={10.1098/rspb.2021.0044}, abstractNote={Fossils provide our only direct window into evolutionary events in the distant past. Incorporating them into phylogenetic hypotheses of living clades can help time-calibrate divergences, as well as elucidate macroevolutionary dynamics. However, the effect fossils have on phylogenetic reconstruction from morphology remains controversial. The consequences of explicitly incorporating the stratigraphic ages of fossils using tip-dated inference are also unclear. Here, we use simulations to evaluate the performance of inference methods across different levels of fossil sampling and missing data. Our results show that fossil taxa improve phylogenetic analysis of morphological datasets, even when highly fragmentary. Irrespective of inference method, fossils improve the accuracy of phylogenies and increase the number of resolved nodes. They also induce the collapse of ancient and highly uncertain relationships that tend to be incorrectly resolved when sampling only extant taxa. Furthermore, tip-dated analyses under the fossilized birth–death process outperform undated methods of inference, demonstrating that the stratigraphic ages of fossils contain vital phylogenetic information. Fossils help to extract true phylogenetic signals from morphology, an effect that is mediated by both their distinctive morphology and their temporal information, and their incorporation in total-evidence phylogenetics is necessary to faithfully reconstruct evolutionary history.}, number={1950}, journal={Proceedings of the Royal Society B: Biological Sciences}, publisher={Royal Society}, author={Mongiardino Koch, Nicolás and Garwood, Russell J. and Parry, Luke A.}, year={2021}, month=may, pages={20210044} }
  @article{Mongiardino_Koch_Garwood_Parry_2023, title={Inaccurate fossil placement does not compromise tip-dated divergence times}, volume={66}, rights={© 2023 The Authors. Palaeontology published by John Wiley & Sons Ltd on behalf of The Palaeontological Association.}, ISSN={1475-4983}, DOI={10.1111/pala.12680}, abstractNote={Time-scaled phylogenies underpin the interrogation of evolutionary processes across deep timescales, as well as attempts to link these to Earth’s history. By inferring the placement of fossils and using their ages as temporal constraints, tip dating under the fossilized birth–death (FBD) process provides a coherent prior on divergence times. At the same time, it also links topological and temporal accuracy, as incorrectly placed fossil terminals should misinform divergence times. This could pose serious issues for obtaining accurate node ages, yet the interaction between topological and temporal error has not been thoroughly explored. We simulate phylogenies and associated morphological datasets using methodologies that incorporate evolution under selection, and are benchmarked against empirical datasets. We find that datasets of 300 characters and realistic levels of missing data generally succeed in inferring the correct placement of fossils on a constrained extant backbone topology, and that true node ages are usually contained within Bayesian posterior distributions. While increased fossil sampling improves the accuracy of inferred ages, topological and temporal errors do not seem to be linked: analyses in which fossils resolve less accurately do not exhibit elevated errors in node age estimates. At the same time, inferred divergence times are biased, probably due to a mismatch between the FBD prior and the shape of our simulated trees. While these results are encouraging, suggesting that even fossils with uncertain affinities can provide useful temporal information, they also emphasize that palaeontological information cannot overturn discrepancies between model priors and the true diversification history.}, number={6}, journal={Palaeontology}, author={Mongiardino Koch, Nicolás and Garwood, Russell J. and Parry, Luke A.}, year={2023}, pages={e12680}, language={en} }
  @article{Puttick_O_Reilly_Pisani_Donoghue_2019, title={Probabilistic methods outperform parsimony in the phylogenetic analysis of data simulated without a probabilistic model}, volume={62}, ISSN={00310239}, DOI={10.1111/pala.12388}, abstractNote={Abstract: To understand patterns and processes of the diversification of life, we require an accurate understanding of taxon interrelationships. Recent studies have suggested that analyses of morphological character data using the Bayesian and maximum likelihood Mk model provide phylogenies of higher accuracy compared to parsimony methods. This has proved controversial, particularly studies simulating morphology-data under Markov models that assume shared branch lengths for characters, as it is claimed this leads to bias favouring the Bayesian or maximum likelihood Mk model over parsimony models which do not explicitly make this assumption. We avoid these potential issues by employing a simulation protocol in which character states are randomly assigned to tips, but datasets are constrained to an empirically realistic distribution of homoplasy as measured by the consistency index. Datasets were analysed with equal weights and implied weights parsimony, and the maximum likelihood and Bayesian Mk model. We find that consistent (low homoplasy) datasets render method choice largely irrelevant, as all methods perform well with high consistency (low homoplasy) datasets, but the largest discrepancies in accuracy occur with low consistency datasets (high homoplasy). In such cases, the Bayesian Mk model is significantly more accurate than alternative models and implied weights parsimony never significantly outperforms the Bayesian Mk model. When poorly supported branches are collapsed, the Bayesian Mk model recovers trees with higher resolution compared to other methods. As it is not possible to assess homoplasy independently of a tree estimate, the Bayesian Mk model emerges as the most reliable approach for categorical morphological analyses.}, number={1}, journal={Palaeontology}, author={Puttick, Mark N. and O’Reilly, Joseph E. and Pisani, Davide and Donoghue, Philip C. J.}, editor={Rahman, Imran}, year={2019}, pages={1–17}, language={en} }
- @article{Wright_Hillis_2014, title={Bayesian Analysis Using a Simple Likelihood Model Outperforms Parsimony for Estimation of Phylogeny from Discrete Morphological Data}, volume={9}, ISSN={1932-6203}, DOI={10.1371/journal.pone.0109210}, number={10}, journal={PLoS ONE}, author={Wright, April M. and Hillis, David M.}, editor={Poon, Art F. Y.}, year={2014}, month=oct, pages={e109210}, language={en} }
+ @article{Wright_Hillis_2014, title={Bayesian Analysis Using a Simple Likelihood Model Outperforms Parsimony for Estimation of Phylogeny from Discrete Morphological Data}, volume={9}, ISSN={1932-6203}, DOI={10.1371/journal.pone.0109210}, number={10}, journal={PLoS ONE}, author={Wright, April M. and Hillis, David M.}, editor={Poon, Art F. Y.}, year={2014}, month=oct, pages={e109210}, language={en} }