Neutral syndrome

Abstract

Neutral models of evolution assume the absence of natural selection. Formerly confined to ecology and evolutionary biology, neutral models are spreading. In recent years they’ve been applied to explaining the diversity of baby names, scientific citations, cryptocurrencies, pot decorations, literary lexica, tumour variants and much more besides. Here, we survey important neutral models and highlight their similarities. We investigate the most widely used tests of neutrality, show that they are weak and suggest more powerful methods. We conclude by discussing the role of neutral models in the explanation of diversity. We suggest that the ability of neutral models to fit low-information distributions should not be taken as evidence for the absence of selection. Nevertheless, many studies, in increasingly diverse fields, make just such claims. We call this tendency ‘neutral syndrome’.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: How mutation, drift and selection maintain variation.
Fig. 2: Variant abundance distribution-based tests of neutrality are weak.
Fig. 3: Testing neutrality with time series data.

References

  1. 1.

    Darwin, C.R. On the Origin of Species by Means of Natural Selection, or the Preservation of Favoured Races in the Struggle for Life. (John Murray, 1859).

  2. 2.

    Macarthur, R. H. On the relative abundance of bird species. Proc. Natl Acad. Sci. USA 43, 293–295 (1957).

    CAS  PubMed  Google Scholar 

  3. 3.

    Hutchinson, G. E. Homage to Santa Rosalia, or, why are there so many kinds of animals? Am. Nat. 153, 145–159 (1959).

    Google Scholar 

  4. 4.

    Community Structure and the Niche (ed. Giller, P.) (Chapman and Hall, 1984).

  5. 5.

    Chase, J.M. & Leibold, M. Ecological Niches: Linking Classical and Contemporary Approaches (University of Chicago Press, 2003).

  6. 6.

    Price, T. D. et al. Niche filling slows the diversification of Himalayan songbirds. Nature 509, 222–225 (2014).

    CAS  PubMed  Google Scholar 

  7. 7.

    Dobzhansky, T. Genetics and the Origin of Species (Columbia University Press; 1951., 1951).

  8. 8.

    Levene, H. Genetic equilibrium when more than one ecological niche is available. Am. Nat. 87, 331–333 (1953).

    Google Scholar 

  9. 9.

    Clarke, B. C. The evolution of genetic diversity. Proc. R. Soc. Lond. B Biol. Sci. 205, 453–474 (1979).

    CAS  PubMed  Google Scholar 

  10. 10.

    Delph, L. F. & Kelly, J. K. On the importance of balancing selection in plants. New Phytol. 201, 45–56 (2014).

    PubMed  Google Scholar 

  11. 11.

    Merlo, L. M., Pepper, J. W., Reid, B. J. & Maley, C. C. Cancer as an evolutionary and ecological process. Nat. Rev. Cancer 6, 924–935 (2006).

    CAS  PubMed  Google Scholar 

  12. 12.

    Plaks, V., Kong, N. & Werb, Z. The cancer stem cell niche: how essential is the niche in regulating stemness of tumor cells? Cell Stem Cell 16, 225–238 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Chamberlin, E. H. The product as an economic variable. Q. J. Econ. 67, 1–29 (1953).

    Google Scholar 

  14. 14.

    Hotelling, H. Stability in competition. Econ. J. (Lond.) 153, 41–57 (1929).

    Google Scholar 

  15. 15.

    Lancaster, K. The economics of product variety: a survey. Mark. Sci. 9, 189–206 (1990).

    Google Scholar 

  16. 16.

    Saviotti, P.P. Technological Evolution, Variety and the Economy (Edward Elgar, 1996).

  17. 17.

    Hannan, M. T. & Freeman, J. The population ecology of organizations. Am. J. Sociol. 82, 929–964 (1977).

    Google Scholar 

  18. 18.

    Carroll, G. R. Concentration and specialization: dynamics of niche width in populations of organizations. Am. J. Sociol. 90, 1262–1283 (1985).

    Google Scholar 

  19. 19.

    Singh, J. V. & Lumsden, C. J. Theory and research in organizational ecology. Annu. Rev. Sociol. 16, 161–195 (1990).

    Google Scholar 

  20. 20.

    Gentzkow, M., Shapiro, J. M. & Sinkinson, M. Competition and ideological diversity: historical evidence from US newspapers. Am. Econ. Rev. 104, 3073–3114 (2014).

    Google Scholar 

  21. 21.

    Fosfuri, A., Giarratana, M.S. & Sebrek, S.S. Resource partitioning and strategies in markets for technology. Strateg. Organ. https://doi.org/10.1177/1476127018791329 (2018).

  22. 22.

    Kimura, M. & Crow, J. F. The number of alleles that can be maintained in a finite population. Genetics 49, 725–738 (1964).

    CAS  PubMed  PubMed Central  Google Scholar 

  23. 23.

    Crow, J. & Kimura, M. An Introduction to Population Genetics Theory. (Harper and Row, 1970).

  24. 24.

    Hubbell, S.P. The Unified Neutral Theory of Biodiversity and Biogeography (Princeton University Press, 2001).

  25. 25.

    Bell, G. Neutral macroecology. Science 293, 2413–2418 (2001).

    CAS  PubMed  Google Scholar 

  26. 26.

    Neiman, F. Stylistic variation in evolutionary perspective–inferences from decorative diversity and interassemblage distance in Illinois woodland ceramic assemblages. American Antiquity 60, 7–36 (1995).

    Google Scholar 

  27. 27.

    Shennan, S. & Wilkinson, J. Ceramic style change and neutral evolution: a case study from Neolithic Europe. Am. Antiq. 66, 577–593 (2001).

    Google Scholar 

  28. 28.

    Hahn, M. W. & Bentley, R. A. Drift as a mechanism for cultural change: an example from baby names. Proc. Biol. Sci. 270(Suppl 1), S120–S123 (2003).

    PubMed  PubMed Central  Google Scholar 

  29. 29.

    Bentley, R. A., Hahn, M. W. & Shennan, S. J. Random drift and culture change. Proc. Biol. Sci. 271, 1443–1450 (2004).

    PubMed  PubMed Central  Google Scholar 

  30. 30.

    Bentley, R. A., Lipo, C. P., Herzog, H. A. & Hahn, M. W. Regular rates of popular culture change reflect random copying. Evol. Hum. Behav. 28, 151–158 (2007).

    Google Scholar 

  31. 31.

    Lycett, S. J. Acheulean variation and selection: does handaxe symmetry fit neutral expectations? J. Archaeol. Sci. 35, 2640–2648 (2008).

    Google Scholar 

  32. 32.

    Schauer, P. Cultural Evolution in the Age of Athens: Drift and Selection in Greek Figure-Painted Pottery. PhD thesis (University College London, 2008).

  33. 33.

    Bentley, R. A., Ormerod, P. & Shennan, S. Population-level neutral model already explains linguistic patterns. Proc. Bio.Sci. 278, 1770–1772 (2011). discussion 1773–1776.

    Google Scholar 

  34. 34.

    Acerbi, A. & Bentley, R. A. Biases in cultural transmission shape the turnover of popular traits. Evol. Hum. Behav. 35, 228–236 (2014).

    Google Scholar 

  35. 35.

    ElBahrawy, A., Alessandretti, L., Kandler, A., Pastor-Satorras, R. & Baronchelli, A. Evolutionary dynamics of the cryptocurrency market. R. Soc. Open Sci. 4, 170623–170623 (2017).

    PubMed  PubMed Central  Google Scholar 

  36. 36.

    Newberry, M. G., Ahern, C. A., Clark, R. & Plotkin, J. B. Detecting evolutionary forces in language change. Nature 551, 223–226 (2017).

    CAS  PubMed  Google Scholar 

  37. 37.

    Simon, H. A. On a class of skew distribution functions. Biometrika 42, 425–440 (1955).

    Google Scholar 

  38. 38.

    Price, D. J. Networks of scientific papers. Science 149, 510–515 (1965).

    CAS  PubMed  Google Scholar 

  39. 39.

    Barabási, A.-L. & Albert, R. Emergence of scaling in random networks. Science 286, 509–512 (1999).

    PubMed  Google Scholar 

  40. 40.

    Mitzenmacher, M. A brief history of generative models for power law and lognormal distributions. Internet Math. 1, 226–251 (2003).

    Google Scholar 

  41. 41.

    Newman, M. E. J. Power laws, Pareto distributions and Zipf’s law. Contemporary Physics 46, 323–351 (2005).

    Google Scholar 

  42. 42.

    Redner, S. Citation statistics from 110 years of Physical Review. Phys. Today 58, 49–54 (2005).

    Google Scholar 

  43. 43.

    Ohta, T. & Gillespie, J. H. Development of neutral and nearly neutral theories. Theor. Popul. Biol. 49, 128–142 (1996).

    CAS  PubMed  Google Scholar 

  44. 44.

    Kreitman, M. The neutral theory is dead. Long live the neutral theory. BioEssays 18, 678–683 (1996). discussion 683.

    CAS  PubMed  Google Scholar 

  45. 45.

    Hey, J. The neutralist, the fly and the selectionist. Trends Ecol. Evol. 14, 35–38 (1999).

    CAS  PubMed  Google Scholar 

  46. 46.

    Proulx, S. R. & Adler, F. R. The standard of neutrality: still flapping in the breeze? J. Evol. Biol. 23, 1339–1350 (2010).

    CAS  PubMed  Google Scholar 

  47. 47.

    Kern, A. D. & Hahn, M. W. The Neutral Theory in light of natural selection. Mol. Biol. Evol. 35, 1366–1371 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Jensen, J. D. et al. The importance of the Neutral Theory in 1968 and 50 years on: a response to Kern and Hahn 2018. Evolution 73, 111–114 (2019).

    PubMed  Google Scholar 

  49. 49.

    Ricklefs, R. E. The unified neutral theory of biodiversity: do the numbers add up? Ecology 87, 1424–1431 (2006).

    PubMed  Google Scholar 

  50. 50.

    Leigh, E. G. Jr. Neutral theory: a historical perspective. J. Evol. Biol. 20, 2075–2091 (2007).

    PubMed  Google Scholar 

  51. 51.

    Clark, J. S. Beyond neutral science. Trends Ecol. Evol. 24, 8–15 (2009).

    PubMed  Google Scholar 

  52. 52.

    Wennekes, P. L., Rosindell, J. & Etienne, R. S. The neutral-niche debate: a philosophical perspective. Acta Biotheor. 60, 257–271 (2012).

    PubMed  PubMed Central  Google Scholar 

  53. 53.

    Rosindell, J., Hubbell, S. P., He, F., Harmon, L. J. & Etienne, R. S. The case for ecological neutral theory. Trends Ecol. Evol. 27, 203–208 (2012).

    PubMed  Google Scholar 

  54. 54.

    Clark, J. S. The coherence problem with the Unified Neutral Theory of Biodiversity. Trends Ecol. Evol. 27, 198–202 (2012).

    PubMed  Google Scholar 

  55. 55.

    Williams, M. J., Werner, B., Barnes, C. P., Graham, T. A. & Sottoriva, A. Identification of neutral tumor evolution across cancer types. Nat. Genet. 48, 238–244 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. 56.

    Tarabichi, M. et al. Neutral tumor evolution? Nat. Genet. 50, 1630–1633 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. 57.

    Heide, T. et al. Reply to ‘Neutral tumor evolution?’. Nat. Genet. 50, 1633–1637 (2018).

    CAS  PubMed  Google Scholar 

  58. 58.

    McDonald, T. O., Chakrabarti, S. & Michor, F. Currently available bulk sequencing data do not necessarily support a model of neutral tumor evolution. Nat. Genet. 50, 1620–1623 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  59. 59.

    Werner, B., Williams, M. J., Barnes, C. P., Graham, T. A. & Sottoriva, A. Reply to ‘Currently available bulk sequencing data do not necessarily support a model of neutral tumor evolution’. Nat. Genet. 50, 1624–1626 (2018).

    CAS  PubMed  Google Scholar 

  60. 60.

    Balaparya, A. & De, S. Revisiting signatures of neutral tumor evolution in the light of complexity of cancer genomic data. Nat. Genet. 50, 1626–1628 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. 61.

    Williams, M. J. et al. Reply to ‘Revisiting signatures of neutral tumor evolution in the light of complexity of cancer genomic data’. Nat. Genet. 50, 1628–1630 (2018).

    CAS  PubMed  Google Scholar 

  62. 62.

    Ayala, F. J. & Campbell, C. A. Frequency-dependent selection. Annu. Rev. Ecol. Syst. 5, 115–138 (1974).

    Google Scholar 

  63. 63.

    Nosil, P. Frequency-dependent selection: when being different makes you not stand out. Curr. Biol. 16, R806–R808 (2006).

    CAS  PubMed  Google Scholar 

  64. 64.

    Volkov, I., Banavar, J. R., He, F., Hubbell, S. P. & Maritan, A. Density dependence explains tree species abundance and diversity in tropical forests. Nature 438, 658–661 (2005).

    CAS  PubMed  Google Scholar 

  65. 65.

    Adler, P. B., Hillerislambers, J. & Levine, J. M. A niche for neutrality. Ecol. Lett. 10, 95–104 (2007).

    PubMed  Google Scholar 

  66. 66.

    Boyd, R. & Richerson, P.J. Culture and the Evolutionary Process (University of Chicago Press, 1985).

  67. 67.

    Richerson, P.J. & Boyd, R. Not by Genes Alone (University of Chicago Press, 2005).

  68. 68.

    Morgan, T. J. H. & Laland, K. N. The biological bases of conformity. Front. Neurosci. 6, 87 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  69. 69.

    Ohta, T. Population size and rate of evolution. J. Mol. Evol. 1, 305–314 (1972).

    PubMed  Google Scholar 

  70. 70.

    Akashi, H., Osada, N. & Ohta, T. Weak selection and protein evolution. Genetics 192, 15–31 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  71. 71.

    Willis, J.C. Age and Area: a Study in Geographical Distribution and Origin of Species (Cambridge University Press, 1922).

  72. 72.

    Willis, J.C. The Course of Evolution by Differentiation or Divergent Mutation Rather Than by Selection (Cambridge University Press, 1940).

  73. 73.

    Volkov, I., Banavar, J. R., Hubbell, S. P. & Maritan, A. Neutral theory and relative species abundance in ecology. Nature 424, 1035–1037 (2003).

    CAS  PubMed  Google Scholar 

  74. 74.

    Bentley, R. A. & Shennan, S. J. Cultural Transmission and Stochastic Network Growth. Am. Antiq. 68, 459–485 (2003).

    Google Scholar 

  75. 75.

    Herzog, H. A., Bentley, R. A. & Hahn, M. W. Random drift and large shifts in popularity of dog breeds. Proc. Biol. Sci. 271(Suppl 5), S353–S356 (2004).

    PubMed  PubMed Central  Google Scholar 

  76. 76.

    Bentley, R. A. Random drift versus selection in academic vocabulary: an evolutionary analysis of published keywords. PLoS One 3, e3057 (2008).

    PubMed  PubMed Central  Google Scholar 

  77. 77.

    Tomasových, A. & Kidwell, S. M. Predicting the effects of increasing temporal scale on species composition, diversity, and rank-abundance distributions. Paleobiology 36, 672–695 (2010).

    Google Scholar 

  78. 78.

    Premo, L. S. & Scholnick, J. B. The spatial scale of social learning affects cultural diversity. American Antiquity 76, 163–176 (2011).

    Google Scholar 

  79. 79.

    Premo, L. S. Cultural transmission and diversity in time-averaged assemblages. Curr. Anthropol. 55, 105–114 (2014).

    Google Scholar 

  80. 80.

    Porcic, M. Exploring the effects of assemblage accumulation on diversity and innovation rate estimates in neutral, conformist, and anti-conformist models of cultural transmission. J. Archaeol. Method Theory 22, 1071–1092 (2015).

    Google Scholar 

  81. 81.

    Albert, R., Jeong, H. & Barabási, A.-L. Diameter of the world-wide web. Nature 401, 130–131 (1999).

    CAS  Google Scholar 

  82. 82.

    Lima-Mendez, G. & van Helden, J. The powerful law of the power law and other myths in network biology. Mol. Biosyst. 5, 1482–1493 (2009).

    CAS  PubMed  Google Scholar 

  83. 83.

    Clauset, A., Shalizi, C. & Newman, M. E. J. Power-law distributions in empirical data. SIAM Rev. 51, 661–703 (2009).

    Google Scholar 

  84. 84.

    Al Hammal, O., Alonso, D., Etienne, R. S. & Cornell, S. J. When can species abundance data reveal non-neutrality? PLOS Comput. Biol. 11, e1004134 (2015).

    PubMed  PubMed Central  Google Scholar 

  85. 85.

    Takeuchi, Y. & Innan, H. Evaluating the performance of neutrality tests of a local community using a niche-structured simulation model. Oikos 124, 1203–1214 (2015).

    Google Scholar 

  86. 86.

    Brzezinski, M. Power laws in citation distributions: evidence from Scopus. Scientometrics 103, 213–228 (2015).

    PubMed  PubMed Central  Google Scholar 

  87. 87.

    McGill, B. J. A test of the unified neutral theory of biodiversity. Nature 422, 881–885 (2003).

    CAS  PubMed  Google Scholar 

  88. 88.

    Etienne, R. & Olff, H. A novel genealogical approach to neutral biodiversity theory. Ecol. Lett. 7, 170–175 (2004).

    Google Scholar 

  89. 89.

    McGill, B. J., Maurer, B. A. & Weiser, M. D. Empirical evaluation of neutral theory. Ecology 87, 1411–1423 (2006).

    PubMed  Google Scholar 

  90. 90.

    Connolly, S. R. et al. Commonness and rarity in the marine biosphere. Proc. Natl Acad. Sci. USA 111, 8524–8529 (2014).

    CAS  PubMed  Google Scholar 

  91. 91.

    Broido, A. D. & Clauset, A. Scale-free networks are rare. Nat. Commun. 10, 1017 (2019).

    PubMed  PubMed Central  Google Scholar 

  92. 92.

    Gillespie, J. The Causes of Molecular Evolution (Oxford University Press, 1991).

  93. 93.

    Bell, G. The distribution of abundance in neutral communities. Am. Nat. 155, 606–617 (2000).

    PubMed  Google Scholar 

  94. 94.

    Magurran, A. E. Species abundance distributions: pattern or process? Funct. Ecol. 19, 177–181 (2005).

    Google Scholar 

  95. 95.

    McGill, B. J. et al. Species abundance distributions: moving beyond single prediction theories to integration within an ecological framework. Ecol. Lett. 10, 995–1015 (2007).

    PubMed  Google Scholar 

  96. 96.

    Purves, D. & Pacala, S. in Biotic Interactions in the Tropics (eds Burslem, D.F.R.P., Pinard, M.A. & Hartley, S.E.) 107–138 (Cambridge University Press, 2006).

  97. 97.

    Matthews, T. J. & Whittaker, R. J. Neutral theory and the species abundance distribution: recent developments and prospects for unifying niche and neutral perspectives. Ecol. Evol. 4, 2263–2277 (2014).

    PubMed  PubMed Central  Google Scholar 

  98. 98.

    Tokeshi, M. Species abundance patterns and community structure. Adv. Ecol. Res. 24, 111–186 (1993).

    Google Scholar 

  99. 99.

    Rosindell, J., Cornell, S. J., Hubbell, S. P. & Etienne, R. S. Protracted speciation revitalizes the neutral theory of biodiversity. Ecol. Lett. 13, 716–727 (2010).

    PubMed  Google Scholar 

  100. 100.

    Williams, M. J. et al. Quantification of subclonal selection in cancer from bulk sequencing data. Nat. Genet. 50, 895–903 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  101. 101.

    Ewens, W. J. The sampling theory of selectively neutral alleles. Theor. Popul. Biol. 3, 87–112 (1972).

    CAS  PubMed  Google Scholar 

  102. 102.

    Ewens, W. Mathematical Population Genetics. 1. Theoretical Introduction (Springer, 2004).

  103. 103.

    Slatkin, M. An exact test for neutrality based on the Ewens sampling distribution. Genet. Res. 64, 71–74 (1994).

    CAS  PubMed  Google Scholar 

  104. 104.

    Slatkin, M. A correction to the exact test based on the Ewens sampling distribution. Genet. Res. 68, 259–260 (1996).

    CAS  PubMed  Google Scholar 

  105. 105.

    Watterson, G. A. Heterosis or neutrality? Genetics 85, 789–814 (1977).

    CAS  PubMed  PubMed Central  Google Scholar 

  106. 106.

    Watterson, G. A. The homozygosity test of neutrality. Genetics 88, 405–417 (1978).

    CAS  PubMed  PubMed Central  Google Scholar 

  107. 107.

    Garrigan, D. & Hedrick, P. W. Perspective: detecting adaptive molecular polymorphism: lessons from the MHC. Evolution 57, 1707–1722 (2003).

    CAS  PubMed  Google Scholar 

  108. 108.

    Lansing, J. S. et al. Male dominance rarely skews the frequency distribution of Y chromosome haplotypes in human populations. Proc. Natl Acad. Sci. USA 105, 11645–11650 (2008).

    CAS  PubMed  Google Scholar 

  109. 109.

    Etienne, R. S. A neutral sampling formula for multiple samples and an ‘exact’ test of neutrality. Ecol. Lett. 10, 608–618 (2007).

    PubMed  Google Scholar 

  110. 110.

    Jabot, F. & Chave, J. Analyzing tropical forest tree species abundance distributions using a nonneutral model and through approximate Bayesian inference. Am. Nat. 178, E37–E47 (2011).

    PubMed  Google Scholar 

  111. 111.

    Steele, J., Glatz, C. & Kandler, A. Ceramic diversity, random copying, and tests for selectivity in ceramic production. J. Archaeol. Sci. 37, 1348–1358 (2010).

    Google Scholar 

  112. 112.

    Fama, E. F. The behaviour of stock-market prices. J. Bus. 38, 34–105 (1965).

    Google Scholar 

  113. 113.

    Fama, E. F. Efficient capital markets: a review of theory and empirical work. Finance 25, 383–417 (1970).

    Google Scholar 

  114. 114.

    Poterba, J. M. & Summers, L. H. Mean reversion in stock prices: evidence and implications. J. Financ. Econ. 22, 27–59 (1988).

    Google Scholar 

  115. 115.

    Bollback, J. P., York, T. L. & Nielsen, R. Estimation of 2Nes from temporal allele frequency data. Genetics 179, 497–502 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  116. 116.

    Mathieson, I. & McVean, G. Estimating selection coefficients in spatially structured populations from time series data of allele frequencies. Genetics 193, 973–984 (2013).

    PubMed  PubMed Central  Google Scholar 

  117. 117.

    Feder, A. F., Kryazhimskiy, S. & Plotkin, J. B. Identifying signatures of selection in genetic time series. Genetics 196, 509–522 (2014).

    PubMed  Google Scholar 

  118. 118.

    Malaspinas, A.-S., Malaspinas, O., Evans, S. N. & Slatkin, M. Estimating allele age and selection coefficient from time-serial data. Genetics 192, 599–607 (2012).

    PubMed  PubMed Central  Google Scholar 

  119. 119.

    Schraiber, J. G., Evans, S. N. & Slatkin, M. Bayesian inference of natural selection from allele frequency time series. Genetics 203, 493–511 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  120. 120.

    Khatri, B. S. Quantifying evolutionary dynamics from variant-frequency time series. Sci. Rep. 6, 32497 (2016).

    PubMed  PubMed Central  Google Scholar 

  121. 121.

    Ferrer-Admetlla, A., Leuenberger, C., Jensen, J. D. & Wegmann, D. An approximate Markov model for the Wright-Fisher diffusion and its application to time series data. Genetics 203, 831–846 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  122. 122.

    Tataru, P., Simonsen, M., Bataillon, T. & Hobolth, A. Statistical inference in the Wright-Fisher model using allele frequency data. Syst. Biol. 66, e30–e46 (2017).

    PubMed  Google Scholar 

  123. 123.

    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).

    PubMed  PubMed Central  Google Scholar 

  124. 124.

    Crema, E., Edinborough, K., Kerig, T. & Shennan, S. An approximate Bayesian computation approach for inferring patterns of cultural evolutionary change. J. Archaeol. Sci. 50, 160–170 (2014).

    Google Scholar 

  125. 125.

    Crema, E. R., Kandler, A. & Shennan, S. Revealing patterns of cultural transmission from frequency data: equilibrium and non-equilibrium assumptions. Sci. Rep. 6, 39122 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  126. 126.

    Kandler, A. & Shennan, S. A generative inference framework for analysing patterns of cultural change in sparse population data with evidence for fashion trends in LBK culture. J. R. Soc. Interface 12, 20150905 (2015).

    PubMed  PubMed Central  Google Scholar 

  127. 127.

    Foll, M., Shim, H. & Jensen, J. D. WFABC: a Wright-Fisher ABC-based approach for inferring effective population sizes and selection coefficients from time-sampled data. Mol. Ecol. Resour. 15, 87–98 (2015).

    PubMed  Google Scholar 

  128. 128.

    Shim, H., Laurent, S., Matuszewski, S., Foll, M. & Jensen, J. D. Detecting and quantifying changing selection intensities from time-sampled polymorphism data. G3 (Bethesda) 6, 893–904 (2016).

    CAS  Google Scholar 

  129. 129.

    Chisholm, R. A. et al. Temporal variability of forest communities: empirical estimates of population change in 4000 tree species. Ecol. Lett. 17, 855–865 (2014).

    PubMed  Google Scholar 

  130. 130.

    Clark, J. S. & McLachlan, J. S. Stability of forest biodiversity. Nature 423, 635–638 (2003).

    CAS  PubMed  Google Scholar 

  131. 131.

    Gillespie, J. H. A randomized SAS-CFF model of natural selection in a random environment. Theor. Popul. Biol. 21, 219–237 (1982).

    Google Scholar 

  132. 132.

    Pham, T., Sheridan, P. & Shimodaira, H. Joint estimation of preferential attachment and node fitness in growing complex networks. Sci. Rep. 6, 32558 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  133. 133.

    Golosovsky, M. Mechanisms of complex network growth: Synthesis of the preferential attachment and fitness models. Phys. Rev. E 97, 062310 (2018).

    CAS  PubMed  Google Scholar 

  134. 134.

    Bailey, M. H. et al. Comprehensive characterization of cancer driver genes and mutations. Cell 173, 371–385.e18 (2018).

    CAS  PubMed  PubMed Central  Google Scholar 

  135. 135.

    Haegeman, B. & Loreau, M. A mathematical synthesis of niche and neutral theories in community ecology. J. Theor. Biol. 269, 150–165 (2011).

    PubMed  Google Scholar 

  136. 136.

    Chisholm, R. A. & Pacala, S. W. Niche and neutral models predict asymptotically equivalent species abundance distributions in high-diversity ecological communities. Proc. Natl Acad. Sci. USA 107, 15821–15825 (2010).

    CAS  PubMed  Google Scholar 

  137. 137.

    Shmueli, G. To explain or to predict? Stat. Sci. 25, 289–310 (2010).

    Google Scholar 

  138. 138.

    Chisholm, R. A. et al. Species-area relationships and biodiversity loss in fragmented landscapes. Ecol. Lett. 21, 804–813 (2018).

    PubMed  PubMed Central  Google Scholar 

  139. 139.

    Bell, G. Fluctuating selection: the perpetual renewal of adaptation in variable environments. Phil. Trans. R. Soc. Lond. B 365, 87–97 (2010).

    Google Scholar 

  140. 140.

    Condit, R., Chisholm, R. A. & Hubbell, S. P. Thirty years of forest census at Barro Colorado and the importance of immigration in maintaining diversity. PLoS One 7, e49826 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  141. 141.

    Leigh, E. G., Wright, S. J., Herre, E. A. & Putz, F. E. The decline of tree diversity on newly isolated tropical islands: A test of a null hypothesis and some implications. Evol. Ecol. 7, 76–102 (1993).

    Google Scholar 

  142. 142.

    Chave, J. Neutral theory and community ecology. Ecol. Lett. 7, 241–253 (2004).

    Google Scholar 

  143. 143.

    Hu, X.-S., He, F. & Hubbell, S. P. Neutral theory in macroecology and population genetics. Oikos 113, 548–556 (2006).

    Google Scholar 

  144. 144.

    Alonso, D., Etienne, R. S. & McKane, A. J. The merits of neutral theory. Trends Ecol. Evol. 21, 451–457 (2006).

    PubMed  Google Scholar 

  145. 145.

    Yule, G. A mathematical theory of evolution, based on the conclusions of Dr J. C. Willis, F.R.S. Phil. Trans. R. Soc. Lond. B 213, 21–87 (1924).

    Google Scholar 

  146. 146.

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

    CAS  PubMed  PubMed Central  Google Scholar 

  147. 147.

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

    Google Scholar 

  148. 148.

    Moran, P. A. Random processes in genetics. Math. Proc. Camb. Philos. Soc. 54, 60–71 (1958).

    Google Scholar 

  149. 149.

    Cavalli-Sforza, L. L. & Edwards, A. W. F. Phylogenetic analysis. Models and estimation procedures. Am. J. Hum. Genet. 19, 233–257 (1967).

    CAS  PubMed  PubMed Central  Google Scholar 

  150. 150.

    Harding, E. F. The probabilities of rooted tree- shapes generated by random bifurcation. Adv. Appl. Probab. 3, 44–77 (1971).

    Google Scholar 

  151. 151.

    Mooers, A. & Heard, S. B. Inferring evolutionary process from the phylogenetic tree shape. Q. Rev. Biol. 72, 31–54 (1997).

    Google Scholar 

  152. 152.

    Nee, S. Birth-death models in macroevolution. Annu. Rev. Ecol. Evol. Syst. 200, 1–17 (2006).

    Google Scholar 

  153. 153.

    Zipf, G.K. Human Behavior and the Principle of Least Effort: An Introduction to Human Ecology (Addison-Wesley, 1949).

  154. 154.

    Perc, M. The Matthew effect in empirical data. J. R. Soc. Interface 11, 20140378 (2014).

    PubMed  PubMed Central  Google Scholar 

  155. 155.

    Bianconi, G. & Barabási, A.-L. Competition and multiscaling in evolving networks. Europhys. Lett. 54, 436 (2001).

    CAS  Google Scholar 

  156. 156.

    Kong, J. S., Sarshar, N. & Roychowdhury, V. P. Experience versus talent shapes the structure of the Web. Proc. Natl Acad. Sci. USA 105, 13724–13729 (2008).

    CAS  PubMed  Google Scholar 

  157. 157.

    Vallade, M. & Houchmandzadeh, B. Analytical solution of a neutral model of biodiversity. Phys. Rev. E 68, 061902 (2003).

    CAS  Google Scholar 

  158. 158.

    Alonso, D. & McKane, A. Sampling Hubbell’s neutral theory of biodiversity. Ecol. Lett. 7, 901–910 (2004).

    Google Scholar 

Download references

Author information

Affiliations

Authors

Corresponding author

Correspondence to Armand M. Leroi.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Peer review information Primary Handling Editor: Aisha Bradshaw

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Leroi, A.M., Lambert, B., Rosindell, J. et al. Neutral syndrome. Nat Hum Behav (2020). https://doi.org/10.1038/s41562-020-0844-7

Download citation