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Long-term studies provide unique insights into evolution

Abstract

From experimental evolution in the laboratory to sustained measurements of natural selection in the wild, long-term studies have revolutionized our understanding of evolution. By directly investigating evolutionary dynamics in real time, these approaches have provided unparallelled insights into the complex interplay between evolutionary process and pattern. These approaches can reveal oscillations, stochastic fluctuations and systematic trends that unfold over extended periods, expose critical time lags between environmental shifts and population responses, and illuminate how subtle effects may accumulate into significant evolutionary patterns. Long-term studies can also reveal otherwise cryptic trends that unfold over extended periods, and offer the potential for serendipity: observing rare events that spur new evolutionary hypotheses and research directions. Despite the challenges of conducting long-term research, exacerbated by modern funding landscapes favouring short-term projects, the contributions of long-term studies to evolutionary biology are indispensable. This is particularly true in our rapidly changing, human-dominated world, where such studies offer a crucial window into how environmental changes and altered species interactions shape evolutionary trajectories. In this Review article, we showcase the groundbreaking discoveries of long-term evolutionary studies, underscoring their crucial role in advancing our understanding of the complex nature of evolution across multiple systems and timescales.

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Fig. 1: Rapid hybrid speciation of Darwin’s finches on Daphne Major island in the Galápagos6,9.
Fig. 2: Temporal trends in fitness and mutations in the LTEE with E. coli70.
Fig. 3: Phenotypic plasticity and adaptive evolution contribute to advancing flowering phenology in response to climate change100,101.
Fig. 4: Predicting evolution in response to natural selection137.
Fig. 5: Investigating the evolution-to-ecology feedback cycle in island lizard communities25.

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References

  1. Grant, P. R. & Grant, B. R. Unpredictable evolution in a 30-year study of Darwin’s finches. Science 296, 707–711 (2002).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  2. Bozdag, G. O. et al. De novo evolution of macroscopic multicellularity. Nature 617, 747–754 (2023).

  3. Good, B. H., McDonald, M. J., Barrick, J. E., Lenski, R. E. & Desai, M. M. The dynamics of molecular evolution over 60,000 generations. Nature 551, 45–50 (2017).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  4. Kassen, R. Experimental Evolution and the Nature of Biodiversity (Oxford Univ. Press, 2024).

  5. Endler, J. A. Natural Selection in the Wild (Princeton Univ. Press, 1986).

  6. Grant, P. R. & Grant, B. R. 40 Years of Evolution: Darwin’s Finches on Daphne Major Island (Princeton Univ. Press, 2014). A seminal book summarizing compelling evidence for rapid evolution by natural selection, based on the meticulous long-term field studies by the authors, spanning four decades of morphological changes in Galápagos finches in response to environmental pressures.

  7. Losos, J. B. Improbable Destinies: Fate, Chance, and the Future of Evolution (Penguin, 2018).

  8. Exciting times for evolutionary biology. Nat. Ecol. Evol. 8, 593–594 (2024).

  9. Lamichhaney, S. et al. Rapid hybrid speciation in Darwin’s finches. Science 359, 224–228 (2018). This long-term field study documents the rapid formation of a new species in the wild through hybridization between two distinct species of Darwin’s finches in the Galápagos, demonstrating that hybridization can be a powerful mechanism driving rapid evolutionary diversification.

    Article  ADS  CAS  PubMed  Google Scholar 

  10. Lenski, R. E. Revisiting the design of the long-term evolution experiment with Escherichia coli. J. Mol. Evol. 91, 241–253 (2023). This paper offers valuable insights into the design and implementation of the LTEE, highlighting the key features that have made this study so successful for studying evolutionary dynamics, potential improvements to experimental design and future directions for this ongoing experiment.

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  11. Barrick, J. E. et al. Genome evolution and adaptation in a long-term experiment with Escherichia coli. Nature 461, 1243–1247 (2009).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  12. Blount, Z. D., Borland, C. Z. & Lenski, R. E. Historical contingency and the evolution of a key innovation in an experimental population of Escherichia coli. Proc. Natl Acad. Sci. USA 105, 7899–7906 (2008). This article demonstrates the crucial role of historical contingency in the evolution of novel traits, using the LTEE with E. coli to show that the emergence of a key innovation was dependent on the specific sequence of previous mutations, highlighting the importance of chance events and the order of mutations in shaping evolutionary outcomes.

    Article  ADS  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  13. Silvertown, J. et al. The Park Grass Experiment 1856–2006: its contribution to ecology. J. Ecol. 94, 801–814 (2006).

    Article  CAS  MATH  Google Scholar 

  14. Snaydon, R. & Davies, M. Rapid population differentiation in a mosaic environment. Heredity 37, 9–25 (1976).

    Article  MATH  Google Scholar 

  15. Siepielski, A. M. et al. No evidence that warmer temperatures are associated with selection for smaller body sizes. Proc. R. Soc. B 286, 20191332 (2019).

    Article  PubMed  PubMed Central  Google Scholar 

  16. Travisano, M. in Experimental Evolution: Concepts, Methods, and Applications of Selection Experiments (eds Garland, T. & Rose, M. R.) 111–133 (2009).

  17. Clutton-Brock, T. & Sheldon, B. C. Individuals and populations: the role of long-term, individual-based studies of animals in ecology and evolutionary biology. Trends Ecol. Evol. 25, 562–573 (2010). This paper emphasizes the critical importance of long-term, individual-based studies in understanding the complex interactions between ecological and evolutionary processes, as well as the role of individual variation in shaping population dynamics and evolutionary trajectories.

    Article  PubMed  MATH  Google Scholar 

  18. Sheldon, B. C., Kruuk, L. E. & Alberts, S. C. The expanding value of long-term studies of individuals in the wild. Nat. Ecol. Evol. 6, 1799–1801 (2022).

    Article  PubMed  MATH  Google Scholar 

  19. Coulson, T. et al. Age, sex, density, winter weather, and population crashes in Soay sheep. Science 292, 1528–1531 (2001).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  20. Ozgul, A. et al. The dynamics of phenotypic change and the shrinking sheep of St. Kilda. Science 325, 464–467 (2009).

    Article  ADS  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  21. Moose, S. P., Dudley, J. W. & Rocheford, T. R. Maize selection passes the century mark: a unique resource for 21st century genomics. Trends Plant Sci. 9, 358–364 (2004).

    Article  CAS  PubMed  Google Scholar 

  22. Reznick, D. N. & Travis, J. Experimental studies of evolution and eco-evo dynamics in guppies (Poecilia reticulata). Annu. Rev. Ecol. Evol. Syst. 50, 335–354 (2019). This article summarizes decades of field experiments of Trinidadian guppies investigating the complex interplay between ecological and evolutionary processes, focusing on how predation, resource availability and other environmental factors can drive adaptive changes in life history traits, morphology and behaviour.

    Article  MATH  Google Scholar 

  23. Reznick, D. N., Ghalambor, C. K. & Crooks, K. Experimental studies of evolution in guppies: a model for understanding the evolutionary consequences of predator removal in natural communities. Mol. Ecol. 17, 97–107 (2008).

    Article  PubMed  MATH  Google Scholar 

  24. Heckley, A. M., Pearce, A. E., Gotanda, K. M., Hendry, A. P. & Oke, K. B. Compiling forty years of guppy research to investigate the factors contributing to (non) parallel evolution. J. Evol. Biol. 35, 1414–1431 (2022).

    Article  PubMed  Google Scholar 

  25. Schoener, T. W., Kolbe, J. J., Leal, M., Losos, J. B. & Spiller, D. A. A multigenerational field experiment on eco-evolutionary dynamics of the influential lizard Anolis sagrei: a mid-term report. Copeia 105, 543–549 (2017). This study provides valuable insights into the interplay between ecological and evolutionary processes by demonstrating rapid adaptive changes in Anolis lizard populations in response to experimentally manipulated environmental conditions, highlighting the importance of long-term field studies in understanding the dynamics of eco-evolutionary feedbacks in real time.

    Article  Google Scholar 

  26. Travis, J. et al. in Advances in Ecological Research Vol. 50 (eds MoyaLarano, J. et al.) 1–40 (Elsevier, 2014).

  27. Philiptschenko, J. Variabilität Und Variation (Gebrüder Borntraeger, 1927).

  28. Rolland, J. et al. Conceptual and empirical bridges between micro-and macroevolution. Nat. Ecol. Evol. 7, 1181–1193 (2023).

    Article  PubMed  MATH  Google Scholar 

  29. Herron, M. D., Conlin, P. L. & Ratcliff, W. C. The Evolution of Multicellularity (CRC Press, 2022).

  30. Jacobeen, S. et al. Cellular packing, mechanical stress and the evolution of multicellularity. Nat. Phys. 14, 286–290 (2018).

    Article  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  31. Ratcliff, W. C., Fankhauser, J. D., Rogers, D. W., Greig, D. & Travisano, M. Origins of multicellular evolvability in snowflake yeast. Nat. Commun. 6, 6102 (2015).

    Article  ADS  CAS  PubMed  Google Scholar 

  32. Montrose, K. et al. Proteostatic tuning underpins the evolution of novel multicellular traits. Sci. Adv. 10, eadn2706 (2024).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Zamani-Dahaj, S. A. et al. Spontaneous emergence of multicellular heritability. Genes 14, 1635 (2023).

    Article  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  34. Coyne, J. A. & Orr, H. A. Speciation (Sinauer Associates, 2004).

  35. Grant, P. R. & Grant, B. R. How and Why Species Multiply: The Radiation of Darwin’s Finches (Princeton Univ. Press, 2007).

  36. Cracraft, J. in Evolution Innovation (ed. Nitecki, M. H.) 21–44 (1990).

  37. Miller, A. H. & Stroud, J. T. Novel tests of the key innovation hypothesis: adhesive toepads in arboreal lizards. Syst. Biol. 71, 139–152 (2022).

    Article  MATH  Google Scholar 

  38. Stroud, J. T. & Losos, J. B. Ecological opportunity and adaptive radiation. Annu. Rev. Ecol. Evol. Syst. 47, 507–532 (2016).

    Article  MATH  Google Scholar 

  39. Simpson, G. G. in The Major Features of Evolution (Columbia Univ. Press, 1953).

  40. Erwin, D. H. A conceptual framework of evolutionary novelty and innovation. Biol. Rev. 96, 1–15 (2021).

    Article  PubMed  MATH  Google Scholar 

  41. Miller, A. H., Stroud, J. T. & Losos, J. B. The ecology and evolution of key innovations. Trends Ecol. Evol. 38, 122–131 (2023).

    Article  PubMed  MATH  Google Scholar 

  42. Rabosky, D. L. Phylogenetic tests for evolutionary innovation: the problematic link between key innovations and exceptional diversification. Phil. Trans. R. Soc. B 372, 20160417 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  43. Blount, Z. D., Barrick, J. E., Davidson, C. J. & Lenski, R. E. Genomic analysis of a key innovation in an experimental Escherichia coli population. Nature 489, 513–518 (2012).

    Article  ADS  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  44. Hall, B. G. Chromosomal mutation for citrate utilization by Escherichia coli K-12. J. Bacteriol. 151, 269–273 (1982).

    Article  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  45. Turner, C. B., Blount, Z. D., Mitchell, D. H. & Lenski, R. E. Evolution of a cross-feeding interaction following a key innovation in a long-term evolution experiment with Escherichia coli. Microbiology 169, 001390 (2023).

    Article  PubMed  PubMed Central  Google Scholar 

  46. Eldredge, N. et al. The dynamics of evolutionary stasis. Paleobiology 31, 133–145 (2005).

    Article  MATH  Google Scholar 

  47. Siepielski, A. M., DiBattista, J. D. & Carlson, S. M. It’s about time: the temporal dynamics of phenotypic selection in the wild. Ecol. Lett. 12, 1261–1276 (2009).

    Article  PubMed  Google Scholar 

  48. Siepielski, A. M. et al. Precipitation drives global variation in natural selection. Science 355, 959–962 (2017).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  49. Wake, D. B., Roth, G. & Wake, M. H. On the problem of stasis in organismal evolution. J. Theor. Biol. 101, 211–224 (1983).

    Article  ADS  MATH  Google Scholar 

  50. Estes, S. & Arnold, S. J. Resolving the paradox of stasis: models with stabilizing selection explain evolutionary divergence on all timescales. Am. Nat. 169, 227–244 (2007).

    Article  PubMed  MATH  Google Scholar 

  51. Charlesworth, B., Lande, R. & Slatkin, M. A neo-Darwinian commentary on macroevolution. Evolution 36, 474–498 (1982).

    PubMed  MATH  Google Scholar 

  52. Stroud, J. T., Moore, M., Langerhans, R. B. & Losos, J. B. Fluctuating selection maintains distinct species phenotypes in an ecological community in the wild. Proc. Natl Acad. Sci. USA 120, e2222071120 (2023).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Gibbs, H. L. & Grant, P. R. Oscillating selection on Darwin’s finches. Nature 327, 511–513 (1987).

    Article  ADS  MATH  Google Scholar 

  54. Eldredge, N. Macroevolution Dynamics (McGraw-Hill, 1989).

  55. Svensson, E. & Calsbeek, R. The Adaptive Landscape in Evolutionary Biology (Oxford Univ. Press, 2012).

  56. Wadgymar, S. M., Daws, S. C. & Anderson, J. T. Integrating viability and fecundity selection to illuminate the adaptive nature of genetic clines. Evol. Lett. 1, 26–39 (2017).

    Article  PubMed  PubMed Central  Google Scholar 

  57. Grant, P. R. & Grant, B. R. From microcosm to macrocosm: adaptive radiation of Darwin’s finches. Evol. J. Linn. Soc. 3, kzae006 (2024).

  58. Burga, A., Ben-David, E., Lemus Vergara, T., Boocock, J. & Kruglyak, L. Fast genetic mapping of complex traits in C. elegans using millions of individuals in bulk. Nat. Commun. 10, 2680 (2019).

    Article  ADS  PubMed  PubMed Central  Google Scholar 

  59. Huxley, J. Evolution: The Modern Synthesis (Allen and Unwin, 1942).

  60. Gould, S. J. The Structure of Evolutionary Theory (Harvard Univ. Press, 2002).

  61. Dobzhansky, T. Genetics and the Origin of Species (Columbia Univ. Press, 1982).

  62. Fisher, R. A. The Genetical Theory of Natural Selection (Clarendon Press, 1930).

  63. Wright, S. Evolution in Mendelian populations. Genetics 16, 97–159 (1931).

    Article  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  64. Haldane, J. B. The Causes of Evolution Vol. 5 (Princeton Univ. Press, 1990).

  65. Wadgymar, S. M., DeMarche, M. L., Josephs, E. B., Sheth, S. N. & Anderson, J. T. Local adaptation: causal agents of selection and adaptive trait divergence. Annu. Rev. Ecol. Evol. Syst. 53, 87–111 (2022).

    Article  PubMed  PubMed Central  Google Scholar 

  66. Crawley, M. et al. Determinants of species richness in the Park Grass Experiment. Am. Nat. 165, 179–192 (2005).

    Article  CAS  PubMed  MATH  Google Scholar 

  67. Snaydon, R. Rapid population differentiation in a mosaic environment. I. The response of Anthoxanthum odoratum populations to soils. Evolution 24, 257–269 (1970).

  68. Clausen, J., Keck, D. D. & Hiesey, W. M. Regional differentiation in plant species. Am. Nat. 75, 231–250 (1941).

    Article  MATH  Google Scholar 

  69. Clausen, J. & Hiesey, W. M. Experimental Studies on the Nature of Species. IV. Genetic Structure of Ecological Races (Carnegie Institute, 1958).

  70. Couce, A. et al. Changing fitness effects of mutations through long-term bacterial evolution. Science 383, eadd1417 (2024). This article provides a groundbreaking demonstration of how the fitness effects of mutations can change over the course of long-term evolution, using the LTEE with E. coli to show that mutations that were initially beneficial can become neutral or even deleterious as the genetic background evolves through time.

    Article  CAS  PubMed  Google Scholar 

  71. Wiser, M. J., Ribeck, N. & Lenski, R. E. Long-term dynamics of adaptation in asexual populations. Science 342, 1364–1367 (2013).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  72. Kryazhimskiy, S., Rice, D. P., Jerison, E. R. & Desai, M. M. Global epistasis makes adaptation predictable despite sequence-level stochasticity. Science 344, 1519–1522 (2014).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  73. Lenski, R. E. Experimental evolution and the dynamics of adaptation and genome evolution in microbial populations. ISME J. 11, 2181–2194 (2017).

    Article  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  74. Couce, A. & Tenaillon, O. A. The rule of declining adaptability in microbial evolution experiments. Front. Genet. 6, 128797 (2015).

    Article  MATH  Google Scholar 

  75. Chou, H.-H., Chiu, H.-C., Delaney, N. F., Segrè, D. & Marx, C. J. Diminishing returns epistasis among beneficial mutations decelerates adaptation. Science 332, 1190–1192 (2011).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  76. Burke, M. K. et al. Genome-wide analysis of a long-term evolution experiment with Drosophila. Nature 467, 587–590 (2010).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  77. Bonnet, T. et al. Genetic variance in fitness indicates rapid contemporary adaptive evolution in wild animals. Science 376, 1012–1016 (2022). This paper compiles long-term datasets from evolutionary field studies to assess rapid adaptive evolution in a wide range of wild animal populations, highlighting the importance of considering contemporary evolutionary changes in conservation and management strategies.

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  78. Kruuk, L. E. et al. Antler size in red deer: heritability and selection but no evolution. Evolution 56, 1683–1695 (2002).

    CAS  PubMed  MATH  Google Scholar 

  79. Kruuk, L. E., Merilä, J. & Sheldon, B. C. Phenotypic selection on a heritable size trait revisited. Am. Nat. 158, 557–571 (2001).

    Article  CAS  PubMed  MATH  Google Scholar 

  80. Milner, J. M., Albon, S. D., Illius, A. W., Pemberton, J. M. & Clutton-Brock, T. H. Repeated selection of morphometric traits in the Soay sheep on St Kilda. J. Anim. Ecol. 68, 472–488 (1999).

    Article  Google Scholar 

  81. Larsson, K., Van der Jeugd, H. P., Van der Veen, I. T. & Forslund, P. Body size declines despite positive directional selection on heritable size traits in a barnacle goose population. Evolution 52, 1169–1184 (1998).

    Article  PubMed  MATH  Google Scholar 

  82. Merilä, J., Kruuk, L. & Sheldon, B. Cryptic evolution in a wild bird population. Nature 412, 76–79 (2001).

    Article  ADS  PubMed  MATH  Google Scholar 

  83. Stroud, J. T. et al. Observing character displacement from process to pattern in a novel vertebrate community. Nat. Commun. 15, 9862 (2024).

    Article  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  84. Gauzere, J. et al. Maternal effects do not resolve the paradox of stasis in birth weight in a wild red deer populaton. Evolution 76, 2605–2617 (2022).

    Article  PubMed  PubMed Central  MATH  Google Scholar 

  85. Kruuk, L. E., Clutton-Brock, T. & Pemberton, J. M. in Quantitative Genetics in the Wild Vol. 10 (eds Charmantier, A. et al.) 160–176 (Oxford Univ. Press, 2014).

  86. Pemberton, J. M. Evolution of quantitative traits in the wild: mind the ecology. Phil. Trans. R. Soc. B 365, 2431–2438 (2010).

    Article  PubMed  PubMed Central  MATH  Google Scholar 

  87. Conner, J. K. Quantitative genetic approaches to evolutionary constraint: how useful? Evolution 66, 3313–3320 (2012).

    Article  PubMed  MATH  Google Scholar 

  88. Price, T., Kirkpatrick, M. & Arnold, S. J. Directional selection and the evolution of breeding date in birds. Science 240, 798–799 (1988).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  89. Etterson, J. R. & Shaw, R. G. Constraint to adaptive evolution in response to global warming. Science 294, 151–154 (2001).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  90. Sheldon, B. C., Kruuk, L. E. B. & Merila, J. Natural selection and inheritance of breeding time and clutch size in the collared flycatcher. Evolution 57, 406–420 (2003).

    CAS  PubMed  MATH  Google Scholar 

  91. Brookfield, J. F. Why are estimates of the strength and direction of natural selection from wild populations not congruent with observed rates of phenotypic change? BioEssays 38, 927–934 (2016).

    Article  PubMed  MATH  Google Scholar 

  92. Glądalski, M. et al. Extreme temperature drop alters hatching delay, reproductive success, and physiological condition in great tits. Int. J. Biometeorol. 64, 623–629 (2020).

    Article  PubMed  Google Scholar 

  93. Benton, T. G., Grant, A. & Clutton-Brock, T. H. Does environmental stochasticity matter? Analysis of red deer life-histories on Rum. Evol. Ecol. 9, 559–574 (1995).

    Article  MATH  Google Scholar 

  94. Pemberton, J. M., Kruuk, L. E. & Clutton-Brock, T. The unusual value of long-term studies of individuals: the example of the Isle of Rum red deer project. Annu. Rev. Ecol. Evol. Syst. 53, 327–351 (2022).

    Article  MATH  Google Scholar 

  95. Brown, W. L. & Wilson, E. O. Character displacement. Syst. Zool. 5, 49–64 (1956).

    Article  MATH  Google Scholar 

  96. Grant, P. R. & Grant, B. R. The founding of a new population of Darwin’s finches. Evolution 49, 229–240 (1995).

    Article  PubMed  MATH  Google Scholar 

  97. Grant, P. R. & Grant, B. R. Evolution of character displacement in Darwin’s finches. Science 313, 224–226 (2006).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  98. Boag, P. T. The heritability of external morphology in Darwin’s ground finches (Geospiza) on Isla Daphne Major, Galapagos. Evolution 37, 877–894 (1983).

  99. Lamichhaney, S. et al. A beak size locus in Darwin’s finches facilitated character displacement during a drought. Science 352, 470–474 (2016).

    Article  ADS  CAS  PubMed  Google Scholar 

  100. Anderson, J. T., Inouye, D. W., McKinney, A. M., Colautti, R. I. & Mitchell-Olds, T. Phenotypic plasticity and adaptive evolution contribute to advancing flowering phenology in response to climate change. Proc. R. Soc. B Biol. Sci. 279, 3843–3852 (2012). This article highlights the importance of both phenotypic plasticity and adaptive evolution in enabling plant populations to respond to contemporary climate change by demonstrating that earlier flowering times in a long-term study of mountain wildflowers is driven by a combination of plastic responses and genetic changes.

    Article  Google Scholar 

  101. Wadgymar, S. M., Ogilvie, J. E., Inouye, D. W., Weis, A. E. & Anderson, J. T. Phenological responses to multiple environmental drivers under climate change: insights from a long-term observational study and a manipulative field experiment. New Phytol. 218, 517–529 (2018).

    Article  PubMed  Google Scholar 

  102. Anderson, J. T. & Gezon, Z. J. Plasticity in functional traits in the context of climate change: a case study of the subalpine forb Boechera stricta (Brassicaceae). Glob. Chang. Biol. 21, 1689–1703 (2015).

    Article  ADS  PubMed  MATH  Google Scholar 

  103. Charmantier, A. et al. Adaptive phenotypic plasticity in response to climate change in a wild bird population. Science 320, 800–803 (2008).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  104. Primack, R. B., Higuchi, H. & Miller-Rushing, A. J. The impact of climate change on cherry trees and other species in Japan. Biol. Conserv. 142, 1943–1949 (2009).

    Article  MATH  Google Scholar 

  105. Bates, J. M. et al. Climate change affects bird nesting phenology: comparing contemporary field and historical museum nesting records. J. Anim. Ecol. 92, 263–272 (2023).

    Article  PubMed  Google Scholar 

  106. De Lisle, S. P., Mäenpää, M. I. & Svensson, E. I. Phenotypic plasticity is aligned with phenological adaptation on both micro- and macroevolutionary timescales. Ecol. Lett. 25, 790–801 (2022).

    Article  PubMed  MATH  Google Scholar 

  107. Bonnet, T. et al. The role of selection and evolution in changing parturition date in a red deer population. PLoS Biol. 17, e3000493 (2019).

    Article  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  108. Martin, R. A., da Silva, C. R., Moore, M. P. & Diamond, S. E. When will a changing climate outpace adaptive evolution? Wiley Interdiscip. Rev. Clim. Change 14, e852 (2023).

    Article  MATH  Google Scholar 

  109. Simmonds, E. G., Cole, E. F., Sheldon, B. C. & Coulson, T. Phenological asynchrony: a ticking time-bomb for seemingly stable populations? Ecol. Lett. 23, 1766–1775 (2020).

    Article  PubMed  Google Scholar 

  110. Merilä, J. & Hendry, A. P. Climate change, adaptation, and phenotypic plasticity: the problem and the evidence. Evol. Appl. 7, 1–14 (2014).

    Article  PubMed  PubMed Central  MATH  Google Scholar 

  111. Valladares, F. et al. The effects of phenotypic plasticity and local adaptation on forecasts of species range shifts under climate change. Ecol. Lett. 17, 1351–1364 (2014).

    Article  PubMed  MATH  Google Scholar 

  112. Ford, E. B. Problems of heredity in the Lepidoptera. Biol. Rev. 12, 461–501 (1937).

    Article  MATH  Google Scholar 

  113. Kettlewell, H. B. D. Selection experiments on industrial melanism in the Lepidoptera. Heredity 9, 323–342 (1955).

    Article  Google Scholar 

  114. Cook, L. M., Grant, B. S., Saccheri, I. J. & Mallet, J. Selective bird predation on the peppered moth: the last experiment of Michael Majerus. Biol. Lett. 8, 609–612 (2012).

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  115. Kettlewell, H. B. D. The Evolution of Melanism (Oxford Univ. Press, 1973).

  116. Cook, L. M., Dennis, R. L. & Dockery, M. The melanic form of the peppered moth, Biston betularia (Linnaeus, 1758)(Lepidoptera: Geometridae), in Manchester: the end of an era. Entomol. Gaz. 62, 91–99 (2011).

    Google Scholar 

  117. Czorlich, Y., Aykanat, T., Erkinaro, J., Orell, P. & Primmer, C. Rapid evolution in salmon life history induced by direct and indirect effects of fishing. Science 376, 420–423 (2022).

    Article  ADS  CAS  PubMed  Google Scholar 

  118. Heino, M., Díaz, Pauli, B. & Dieckmann, U. Fisheries-induced evolution. Annu. Rev. Ecol. Evol. Syst. 46, 461–480 (2015).

    Article  MATH  Google Scholar 

  119. Donihue, C. M. & Lambert, M. R. Adaptive evolution in urban ecosystems. Ambio 44, 194–203 (2015).

    Article  ADS  PubMed  MATH  Google Scholar 

  120. Santangelo, J. S. et al. Global urban environmental change drives adaptation in white clover. Science 375, 1275–1281 (2022).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  121. Lambert, M. R. & Donihue, C. M. Urban biodiversity management using evolutionary tools. Nat. Ecol. Evol. 4, 903–910 (2020).

    Article  PubMed  MATH  Google Scholar 

  122. Blount, Z. D., Lenski, R. E. & Losos, J. B. Contingency and determinism in evolution: replaying life’s tape. Science 362, eaam5979 (2018).

    Article  PubMed  Google Scholar 

  123. Reznick, D. & Travis, J. Is evolution predictable? Science 359, 738–739 (2018).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  124. Conway Morris, S. Evolution: like any other science it is predictable. Phil. Trans. R. Soc. B 365, 133–145 (2010).

    Article  PubMed Central  Google Scholar 

  125. Beavan, A. J., Domingo-Sananes, M. R. & McInerney, J. O. Contingency, repeatability, and predictability in the evolution of a prokaryotic pangenome. Proc. Natl Acad. Sci. USA 121, e2304934120 (2024).

    Article  CAS  PubMed  Google Scholar 

  126. Morris, S. C. Life’s Solution: Inevitable Humans in a Lonely Universe (Cambridge Univ. Press, 2003).

  127. Nosil, P., Flaxman, S. M., Feder, J. L. & Gompert, Z. Increasing our ability to predict contemporary evolution. Nat. Commun. 11, 5592 (2020).

    Article  ADS  CAS  PubMed  PubMed Central  Google Scholar 

  128. Marques, D. A., Jones, F. C., Di Palma, F., Kingsley, D. M. & Reimchen, T. E. Experimental evidence for rapid genomic adaptation to a new niche in an adaptive radiation. Nat. Ecol. Evol. 2, 1128–1138 (2018).

    Article  PubMed  PubMed Central  MATH  Google Scholar 

  129. Gompert, Z., Flaxman, S. M., Feder, J. L., Chevin, L.-M. & Nosil, P. Laplace’s demon in biology: models of evolutionary prediction. Evolution 76, 2794–2810 (2022).

    PubMed  Google Scholar 

  130. Barrick, J. E. & Lenski, R. E. Genome dynamics during experimental evolution. Nat. Rev. Genet. 14, 827–839 (2013).

    Article  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  131. Jerison, E. R., Nguyen Ba, A. N., Desai, M. M. & Kryazhimskiy, S. Chance and necessity in the pleiotropic consequences of adaptation for budding yeast. Nat. Ecol. Evol. 4, 601–611 (2020).

    Article  PubMed  PubMed Central  Google Scholar 

  132. Tenaillon, O. et al. The molecular diversity of adaptive convergence. Science 335, 457–461 (2012).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  133. Lang, G. I. et al. Pervasive genetic hitchhiking and clonal interference in forty evolving yeast populations. Nature 500, 571–574 (2013).

    Article  ADS  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  134. Salverda, M. L., Koomen, J., Koopmanschap, B., Zwart, M. P. & de Visser, J. A. G. Adaptive benefits from small mutation supplies in an antibiotic resistance enzyme. Proc. Natl Acad. Sci. USA 114, 12773–12778 (2017).

    Article  ADS  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  135. Tenaillon, O. et al. Tempo and mode of genome evolution in a 50,000-generation experiment. Nature 536, 165–170 (2016).

    Article  ADS  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  136. Quandt, E. M., Deatherage, D. E., Ellington, A. D., Georgiou, G. & Barrick, J. E. Recursive genomewide recombination and sequencing reveals a key refinement step in the evolution of a metabolic innovation in Escherichia coli. Proc. Natl Acad. Sci. USA 111, 2217–2222 (2014).

    Article  ADS  CAS  PubMed  Google Scholar 

  137. Nosil, P. et al. Natural selection and the predictability of evolution in Timema stick insects. Science 359, 765–770 (2018). This article demonstrates that the direction and magnitude of natural selection can be used to predict evolutionary changes in wild populations using long-term field studies of natural selection in Californian Timema stick insects.

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  138. Nosil, P. et al. Evolution repeats itself in replicate long-term studies in the wild. Sci. Adv. 10, eadl3149 (2024).

    Article  PubMed  PubMed Central  Google Scholar 

  139. Thurman, T. J. et al. The difficulty of predicting evolutionary change in response to novel ecological interactions: a field experiment with Anolis lizards. Am. Nat. 201, 537–556 (2023).

    Article  PubMed  MATH  Google Scholar 

  140. Chevin, L.-M., Gompert, Z. & Nosil, P. Frequency dependence and the predictability of evolution in a changing environment. Evol. Lett. 6, 21–33 (2022).

    Article  PubMed  MATH  Google Scholar 

  141. Hendry, A. P. Prediction in ecology and evolution. BioScience 73, 785–799 (2023).

    Article  MATH  Google Scholar 

  142. Schluter, D. Variable success in linking micro and macroevolution. Evol. J. Linn. Soc. 3, kzae016 (2024).

  143. Hendry, A. P. Eco-Evolutionary Dynamics (Princeton Univ. Press, 2017).

  144. Schoener, T. W. The newest synthesis: understanding the interplay of evolutionary and ecological dynamics. Science 331, 426–429 (2011).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  145. Post, D. M. & Palkovacs, E. P. Eco-evolutionary feedbacks in community and ecosystem ecology: interactions between the ecological theatre and the evolutionary play. Phil. Trans. R. Soc. B 364, 1629–1640 (2009).

    Article  PubMed  PubMed Central  MATH  Google Scholar 

  146. Bassar, R. D., Coulson, T., Travis, J. & Reznick, D. N. Towards a more precise—and accurate—view of eco-evolution. Ecol. Lett. 24, 623–625 (2021).

    Article  PubMed  MATH  Google Scholar 

  147. Hendry, A. P. A critique for eco-evolutionary dynamics. Funct. Ecol. 33, 84–94 (2019).

    Article  MATH  Google Scholar 

  148. Kokko, H. & López-Sepulcre, A. The ecogenetic link between demography and evolution: can we bridge the gap between theory and data? Ecol. Lett. 10, 773–782 (2007).

    Article  PubMed  MATH  Google Scholar 

  149. Yoshida, T., Jones, L. E., Ellner, S. P., Fussmann, G. F. & Hairston, N. G. Jr. Rapid evolution drives ecological dynamics in a predator–prey system. Nature 424, 303–306 (2003).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  150. Mougi, A. Eco-evolutionary dynamics in microbial interactions. Sci. Rep. 13, 9042 (2023).

    Article  ADS  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  151. Hart, S. P., Turcotte, M. M. & Levine, J. M. Effects of rapid evolution on species coexistence. Proc. Natl Acad. Sci. USA 116, 2112–2117 (2019).

    Article  ADS  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  152. Rodríguez-Verdugo, A. & Ackermann, M. Rapid evolution destabilizes species interactions in a fluctuating environment. ISME J. 15, 450–460 (2021).

    Article  PubMed  MATH  Google Scholar 

  153. Kasada, M., Yamamichi, M. & Yoshida, T. Form of an evolutionary tradeoff affects eco-evolutionary dynamics in a predator–prey system. Proc. Natl Acad. Sci. USA 111, 16035–16040 (2014).

    Article  ADS  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  154. De Meester, L. et al. Analysing eco-evolutionary dynamics—the challenging complexity of the real world. Funct. Ecol. 33, 43–59 (2019).

    Article  MATH  Google Scholar 

  155. Spiller, D. A., Schoener, T. W. & Piovia-Scott, J. in Ecology and Evolution of Plant–Herbivore Interactions on Islands (eds Moreira, X. & Abdala-Roberts, L.) 177–197 (Springer, 2024).

  156. Reznick, D. N. et al. Eco-evolutionary feedbacks predict the time course of rapid life-history evolution. Am. Nat. 194, 671–692 (2019).

    Article  PubMed  MATH  Google Scholar 

  157. Gordon, S. P. et al. Adaptive changes in life history and survival following a new guppy introduction. Am. Nat. 174, 34–45 (2009).

    Article  PubMed  MATH  Google Scholar 

  158. Westrick, S. E., Broder, E. D., Reznick, D. N., Ghalambor, C. K. & Angeloni, L. Rapid evolution and behavioral plasticity following introduction to an environment with reduced predation risk. Ethology 125, 232–240 (2019).

    Article  MATH  Google Scholar 

  159. Lapiedra, O., Schoener, T. W., Leal, M., Losos, J. B. & Kolbe, J. J. Predator-driven natural selection on risk-taking behavior in anole lizards. Science 360, 1017–1020 (2018).

    Article  ADS  CAS  PubMed  Google Scholar 

  160. Losos, J. B., Schoener, T. W. & Spiller, D. A. Predator-induced behaviour shifts and natural selection in field-experimental lizard populations. Nature 432, 505–508 (2004).

    Article  ADS  CAS  PubMed  Google Scholar 

  161. Simon, T. N. et al. Local adaptation in Trinidadian guppies alters stream ecosystem structure at landscape scales despite high environmental variability. Copeia 105, 504–513 (2017).

    Article  Google Scholar 

  162. Lapiedra, O. et al. Predator-driven behavioural shifts in a common lizard shape resource-flow from marine to terrestrial ecosystems. Ecol. Lett. 27, e14335 (2024).

    Article  PubMed  MATH  Google Scholar 

  163. Schoener, T. W., Spiller, D. A. & Losos, J. B. Predation on a common Anolis lizard: can the food-web effects of a devastating predator be reversed? Ecol. Monogr. 72, 383–407 (2002).

    Article  Google Scholar 

  164. Hendry, A. P. Eco-evolutionary dynamics: an experimental demonstration in nature. Curr. Biol. 33, R814–R817 (2023).

    Article  CAS  PubMed  MATH  Google Scholar 

  165. Waide, R. B. & Kingsland, S. E. The Challenges of Long Term Ecological Research: A Historical Analysis (Springer, 2021).

  166. Bono, J. M., Olesnicky, E. C. & Matzkin, L. M. Connecting genotypes, phenotypes and fitness: harnessing the power of CRISPR/Cas9 genome editing. Mol. Ecol. 24, 3810–3822 (2015).

    Article  CAS  PubMed  MATH  Google Scholar 

  167. Wang, Z. et al. Automated detection of an insect-induced keystone vegetation phenotype using airborne LiDAR. Methods Ecol. Evol. 15, 978–993 (2024).

    Article  MATH  Google Scholar 

  168. Kays, R., Crofoot, M. C., Jetz, W. & Wikelski, M. Terrestrial animal tracking as an eye on life and planet. Science 348, aaa2478 (2015).

    Article  PubMed  Google Scholar 

  169. Nathan, R. et al. Big-data approaches lead to an increased understanding of the ecology of animal movement. Science 375, eabg1780 (2022).

    Article  CAS  PubMed  MATH  Google Scholar 

  170. Lande, R. & Arnold, S. J. The measurement of selection on correlated characters. Evolution 37, 1220–1226 (1983).

    Article  MATH  Google Scholar 

  171. Svensson, E. I. Phenotypic selection in natural populations: what have we learned in 40 years? Evolution 77, 1493–1504 (2023).

    Article  PubMed  MATH  Google Scholar 

  172. Huang, X., Rymbekova, A., Dolgova, O., Lao, O. & Kuhlwilm, M. Harnessing deep learning for population genetic inference. Nat. Rev. Genet. 25, 61–78 (2024).

    Article  CAS  PubMed  Google Scholar 

  173. Borowiec, M. L. et al. Deep learning as a tool for ecology and evolution. Methods Ecol. Evol. 13, 1640–1660 (2022).

    Article  MATH  Google Scholar 

  174. Stoddard, M. C., Kilner, R. M. & Town, C. Pattern recognition algorithm reveals how birds evolve individual egg pattern signatures. Nat. Commun. 5, 4117 (2014).

    Article  ADS  CAS  PubMed  Google Scholar 

  175. Grenfell, B. T. et al. Unifying the epidemiological and evolutionary dynamics of pathogens. Science 303, 327–332 (2004).

    Article  ADS  CAS  PubMed  MATH  Google Scholar 

  176. Faria, N. R. et al. The early spread and epidemic ignition of HIV-1 in human populations. Science 346, 56–61 (2014).

    Article  ADS  CAS  PubMed  PubMed Central  MATH  Google Scholar 

  177. Dadonaite, B. et al. Spike deep mutational scanning helps predict success of SARS-CoV-2 clades. Nature 631, 617–626 (2024).

  178. Bitter, M. C. et al. Continuously fluctuating selection reveals fine granularity of adaptation. Nature 634, 389–396 (2024).

    Article  CAS  PubMed  MATH  Google Scholar 

  179. Rudman, S. M. et al. Direct observation of adaptive tracking on ecological time scales in Drosophila. Science 375, eabj7484 (2022).

    Article  CAS  PubMed  PubMed Central  MATH  Google Scholar 

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Acknowledgements

We thank J. Anderson, Z. Blount, S. Brown, T. Grainger, J. Losos, M. Moore and K. Thompson for valuable feedback on earlier versions of this manuscript; B. Sheldon, D. Schluter and an anonymous reviewer for critical feedback that greatly improved our manuscript; and M. Belan (ArtSci Studios) for the illustrations. This work was supported by grants from the US National Institutes of Health (grant no. 5R35GM138030) and the NSF Division of Environmental Biology (grant no. DEB-1845363) to W.C.R.

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Stroud, J.T., Ratcliff, W.C. Long-term studies provide unique insights into evolution. Nature 639, 589–601 (2025). https://doi.org/10.1038/s41586-025-08597-9

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