The paradox of predictability provides a bridge between micro- and macroevolution | ENEngelskEnglishThe paradox of predictability provides a bridge between micro- and macroevolution
2024
Tsuboi, Masahiro | De Lisle, Stephen | Grabowski, Mark | Hopkins, Melanie J. | Porto, Arthur Guimaraes Carvalho | Sztepanacz, Jacqueline | Voje, Kjetil L. | Balk, Meghan | Hildesheim, L. | Horta-Lacueva, L. | Hohmann, N. | Holstand, Agnes | Lürig, M. | Milocco, L. | Nileen, S | Passaotto, A. | Rossoni, D | Svensson, E | Villegas, C | Winslott, E | Liow, Lee Hsiang | Hunt, Gene | Houle, David | Love, Alan
The relationship between the evolutionary dynamics observed in contemporary populations (microevolution) and evolution on timescales of millions of years (macroevolution) has been a topic of considerable debate. Historically, this debate centers on inconsistencies between microevolutionary processes and macroevolutionary patterns. Here, we characterize a striking exception: emerging evidence indicates that standing variation in contemporary populations and macroevolutionary rates of phenotypic divergence is often positively correlated. This apparent consistency between micro- and macroevolution is paradoxical because it contradicts our previous understanding of phenotypic evolution and is so far unexplained. Here, we explore the prospects for bridging evolutionary timescales through an examination of this “paradox of predictability.” We begin by explaining why the divergence–variance correlation is a paradox, followed by data analysis to show that the correlation is a general phenomenon across a broad range of temporal scales, from a few generations to tens of millions of years. Then we review complementary approaches from quantitative genetics, comparative morphology, evo-devo, and paleontology to argue that they can help to address the paradox from the shared vantage point of recent work on evolvability. In conclusion, we recommend a methodological orientation that combines different kinds of short-term and long-term data using multiple analytical frameworks in an interdisciplinary research program. Such a program will increase our general understanding of how evolution works within and across timescales.
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