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Review
. 2023 Mar;38(3):250-260.
doi: 10.1016/j.tree.2022.10.013. Epub 2022 Nov 28.

Cross-disciplinary information for understanding macroevolution

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Free article
Review

Cross-disciplinary information for understanding macroevolution

Lee Hsiang Liow et al. Trends Ecol Evol. 2023 Mar.
Free article

Abstract

Many different macroevolutionary models can produce the same observations. Despite efforts in building more complex and realistic models, it may still be difficult to distinguish the processes that have generated the biodiversity we observe. In this opinion we argue that we can make new progress by reaching out across disciplines, relying on independent data and theory to constrain macroevolutionary inference. Using mainly paleontological insights and data, we illustrate how we can eliminate less plausible or implausible models, and/or parts of parameter space, while applying comparative phylogenetic approaches. We emphasize that such cross-disciplinary insights and data can be drawn between many other disciplines relevant to macroevolution. We urge cross-disciplinary training, and collaboration using common-use databases as a platform for increasing our understanding.

Keywords: fossils; independent evidence; macroevolution; model space; parameter space.

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Conflict of interest statement

Declaration of interests No interests are declared.

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