The information provided by the absence of cues: insights from Bayesian models of within and transgenerational plasticity

Abstract

Empirical studies of phenotypic plasticity often use an experimental design in which the subjects in experimental treatments are exposed to cues, while the subjects in control treatments are maintained in the absence of those cues. However, researchers have virtually ignored the question of what, if any, information might be provided to subjects by the absence of the cues in control treatments. We apply basic principles of information-updating to several experimental protocols used to study phenotypic plasticity in response to cues from predators to show why the reliability of the information provided by the absence of those cues in a control treatment might vary as a function of the subjects’ experiences in the experimental treatment. We then analyze Bayesian models designed to mimic fully factorial experimental studies of trans and within-generational plasticity, in which parents, offspring, both or neither are exposed to cues from predators, and the information-states of the offspring in the different groups are compared at the end of the experiment. The models predict that the pattern of differences in offspring information-state across the four treatment groups will vary among experiments, depending on the reliability of the information provided by the control treatment, and the parent’s initial estimate of the value of the state (the parental Prior). We suggest that variation among experiments in the reliability of the information provided by the absence of particular cues in the control treatment may be a general phenomenon, and that Bayesian approaches can be useful in interpreting the results of such experiments.

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References

  1. Adamec RE, Blundell J, Burton P (2006) Relationship of the predatory attack experience to neural plasticity, pCREB expression and neuroendocrine response. Neurosci Biobehav Rev 30:356–375. https://doi.org/10.1016/j.neubiorev.2005.04.004

    CAS  Article  PubMed  Google Scholar 

  2. Agrawal AA, Laforsch C, Tollrian R (1999) Transgenerational induction of defences in animals and plants. Nature 401:60–63. https://doi.org/10.1038/43425

    CAS  Article  Google Scholar 

  3. Armstrong DP, Raeburn EH, Lewis RM, Ravine D (2006) Modeling vital rates of a reintroduced New Zealand robin population as a function of predator control. J Wildl Manage 70:1028–1036. https://doi.org/10.2193/0022-541x(2006)70[1028:Mvroar]2.0.Co;2

    Article  Google Scholar 

  4. Bailey NW, Gray B, Zuk M (2010) Acoustic experience shapes alternative mating tactics and reproductive investment in male field crickets. Curr Biol 20:845–849. https://doi.org/10.1016/j.cub.2010.02.063

    CAS  Article  PubMed  Google Scholar 

  5. Beaty LE et al (2016) Shaped by the past, acting in the present: transgenerational plasticity of anti-predatory traits. Oikos 125:1570–1576. https://doi.org/10.1111/oik.03114

    Article  Google Scholar 

  6. Bonduriansky R, Crean AJ, Day T (2012) The implications of nongenetic inheritance for evolution in changing environments. Evol Appl 5:192–201. https://doi.org/10.1111/j.1752-4571.2011.00213.x

    Article  PubMed  Google Scholar 

  7. Dall SRX, McNamara JM, Leimar O (2015) Genes as cues: phenotypic integration of genetic and epigenetic information from a Darwinian perspective. Trends Ecol Evol 30:327–333. https://doi.org/10.1016/j.tree.2015.04.002

    Article  PubMed  Google Scholar 

  8. Dion E, Monteiro A, Nieberding CM (2019) The role of learning on insect and spider sexual behaviors, sexual trait evolution, and speciation. Front Ecol Evol. https://doi.org/10.3389/fevo.2018.00225

    Article  Google Scholar 

  9. Donelan SC, Trussell GC (2018) Parental and embryonic experiences with predation risk affect prey offspring behaviour and performance. Proc R Soc Lond Ser B-Biol Sci. https://doi.org/10.1098/rspb.2018.0034

    Article  Google Scholar 

  10. Dukas R, Morse DH (2003) Crab spiders affect flower visitation by bees. Oikos 101:157–163. https://doi.org/10.1034/j.1600-0706.2003.12143.x

    Article  Google Scholar 

  11. English S, Fawcett TW, Higginson AD, Trimmer PC, Uller T (2016) Adaptive use of information during growth can explain long-term effects of early life experiences. Am Nat 187:620–632. https://doi.org/10.1086/685644

    Article  PubMed  Google Scholar 

  12. Engqvist L, Reinhold K (2016) Adaptive trans-generational phenotypic plasticity and the lack of an experimental control in reciprocal match/mismatch experiments. Methods Ecol Evol 7:1482–1488. https://doi.org/10.1111/2041-210x.12618

    Article  Google Scholar 

  13. Ezard THG, Prizak R, Hoyle RB (2014) The fitness costs of adaptation via phenotypic plasticity and maternal efects. Funct Ecol 28:693–701. https://doi.org/10.1111/1365-2435.12207

    Article  Google Scholar 

  14. Fawcett TW, Frankenhuis WE (2015) Adaptive explanations for sensitive windows in development. Front Zool. https://doi.org/10.1186/1742-9994-12-s1-s3

    Article  PubMed  PubMed Central  Google Scholar 

  15. Ferrari MCO, Wisenden BD, Chivers DP (2010) Chemical ecology of predator-prey interactions in aquatic ecosystems: a review and prospectus. Can J Zool 88:698–724. https://doi.org/10.1139/z10-029

    Article  Google Scholar 

  16. Festa-Bianchet M, Coulson T, Gaillard JM, Hogg JT, Pelletier F (2006) Stochastic predation events and population persistence in bighorn sheep. Proc R Soc Lond Ser B-Biol Sci 273:1537–1543. https://doi.org/10.1098/rspb.2006.3467

    Article  Google Scholar 

  17. Fischer B, van Doorn GS, Dieckmann U, Taborsky B (2014) The evolution of age-dependent plasticity. Am Nat 183:108–125. https://doi.org/10.1086/674008

    Article  PubMed  Google Scholar 

  18. Fowler-Finn KD, Rodriguez RL (2012) Experience-mediated plasticity in mate preferences: mating assurance in a variable environment. Evolution 66:459–468. https://doi.org/10.1111/j.1558-5646.2011.01446.x

    Article  PubMed  Google Scholar 

  19. Frankenhuis WE, Panchanathan K (2011) Balancing sampling and specialization: an adaptationist model of incremental development. Proc R Soc Lond Ser B-Biol Sci 278:3558–3565. https://doi.org/10.1098/rspb.2011.0055

    Article  Google Scholar 

  20. Gilbert JJ (2011) Induction of different defences by two enemies in the rotifer Keratella tropica: response priority and sensitivity to enemy density. Freshw Biol 56:926–938. https://doi.org/10.1111/j.1365-2427.2010.02538.x

    Article  Google Scholar 

  21. Hales NR, Schield DR, Andrew AL, Card DC, Walsh MR, Castoe TA (2017) Contrasting gene expression programs correspond with predator-induced phenotypic plasticity within and across generations in Daphnia. Mol Ecol 26:5003–5015. https://doi.org/10.1111/mec.14213

    CAS  Article  PubMed  Google Scholar 

  22. Hoyle RB, Ezard THG (2012) The benefits of maternal effects in novel and in stable environments. J R Soc Interface 9:2403–2413. https://doi.org/10.1098/rsif.2012.0183

    Article  PubMed  PubMed Central  Google Scholar 

  23. Kasumovic MM, Brooks RC (2011) It’s all who you know: the evolution of socially cued anticipatory plasticity as a mating strategy. Q Rev Biol 86:181–197. https://doi.org/10.1086/661119

    Article  PubMed  Google Scholar 

  24. Lange A, Dukas R (2009) Bayesian approximations and extensions: optimal decisions for small brains and possibly big ones too. J Theor Biol 259:503–516. https://doi.org/10.1016/j.jtbi.2009.03.020

    Article  PubMed  Google Scholar 

  25. Leimar O, McNamara JM (2015) The evolution of transgenerational integration of information in heterogeneous environments. Am Nat 185:E55–E69. https://doi.org/10.1086/679575

    Article  PubMed  Google Scholar 

  26. Leimar O, Hammerstein P, Van Dooren TJM (2006) A new perspective on developmental plasticity and the principles of adaptive morph determination. Am Nat 167:367–376. https://doi.org/10.1086/499566

    Article  PubMed  Google Scholar 

  27. Loose CJ, Dawidowicz P (1994) Trade-offs in diel vertical migration by zooplankton-the costs of predator avoidance. Ecology 75:2255–2263. https://doi.org/10.2307/1940881

    Article  Google Scholar 

  28. Luquet E, Tariel J (2016) Offspring reaction norms shaped by parental environment: interaction between within- and trans-generational plasticity of inducible defenses. BMC Evol Biol. https://doi.org/10.1186/s12862-016-0795-9

    Article  PubMed  PubMed Central  Google Scholar 

  29. Luttbeg B, Trussell GC (2013) How the informational environment shapes how prey estimate predation risk and the resulting indirect effects of predators. Am Nat 181:182–194. https://doi.org/10.1086/668823

    Article  PubMed  Google Scholar 

  30. Luttbeg B, Ferrari MCO, Blumstein DT, Chivers DP (2020) Safety cues can give prey more valuable information than danger cues. Am Nat 195:636–648. https://doi.org/10.1086/707544

    Article  PubMed  Google Scholar 

  31. Magurran AE (2005) Evolutionary ecology. The trinidadian guppy. Oxford University Press, Oxford, UK

    Google Scholar 

  32. Mangel M, Beder JH (1985) Search and stock depletion- theory and applications. Can J Fish Aquat Sci 42:150–163. https://doi.org/10.1139/f85-019

    Article  Google Scholar 

  33. McNamara JM, Green RF, Olsson O (2006) Bayes’ theorem and its applications in animal behaviour. Oikos 112:243–251. https://doi.org/10.1111/j.0030-1299.2006.14228.x

    Article  Google Scholar 

  34. McNamara JM, Dall SRX, Hammerstein P, Leimar O (2016) Detection vs. selection: integration of genetic, epigenetic and environmental cues in fluctuating environments. Ecol Lett 19:1267–1276. https://doi.org/10.1111/ele.12663

    Article  PubMed  Google Scholar 

  35. Miyakawa H, Sugimoto N, Kohyama TI, Iguchi T, Miura T (2015) Intra-specific variations in reaction norms of predator-induced polyphenism in the water flea Daphnia pulex. Ecol Res 30:705–713. https://doi.org/10.1007/s11284-015-1272-4

    Article  Google Scholar 

  36. Morse DH (1986) Predatory risk to insects foraging at flowers. Oikos 46:223–228. https://doi.org/10.2307/3565470

    Article  Google Scholar 

  37. Nettle D, Bateson M (2015) Adaptive developmental plasticity: what is it, how can we recognize it and when can it evolve? Proc R Soc Lond Ser B-Biol Sci 282:23–31. https://doi.org/10.1098/rspb.2015.1005

    Article  Google Scholar 

  38. Nettle D, Frankenhuis WE, Rickard IJ (2013) The evolution of predictive adaptive responses in human life history. Proc R Soc Lond Ser B-Biol Sci. https://doi.org/10.1098/rspb.2013.1343

    Article  Google Scholar 

  39. Panchanathan K, Frankenhuis WE (2016) The evolution of sensitive periods in a model of incremental development. Proc R Soc Lond Ser B-Biol Sci. https://doi.org/10.1098/rspb.2015.2439

    Article  Google Scholar 

  40. Quigley J, Bedford T, Walls L (2007) Estimating rate of occurrence of rare events with empirical bayes: a railway application. Reliab Eng Syst Safety 92:619–627. https://doi.org/10.1016/j.ress.2006.02.007

    Article  Google Scholar 

  41. Rebar D, Barbosa F, Greenfield MD (2016) Acoustic experience influences male and female pre- and postcopulatory behaviors in a bushcricket. Behav Ecol 27:434–443. https://doi.org/10.1093/beheco/arv171

    Article  Google Scholar 

  42. Rebar D, Barbosa F, Greenfield MD (2019) Female reproductive plasticity to the social environment and its impact on male reproductive success. Behav Ecol Sociobiol. https://doi.org/10.1007/s00265-019-2661-4

    Article  Google Scholar 

  43. Reddon AR, Chouinard-Thuly L, Leris I, Reader SM (2018) Wild and laboratory exposure to cues of predation risk increases relative brain mass in male guppies. Funct Ecol 32:1847–1856. https://doi.org/10.1111/1365-2435.13128

    Article  Google Scholar 

  44. Relyea RA (2001) Morphological and behavioral plasticity of larval anurans in response to different predators. Ecology 82:523–540. https://doi.org/10.1890/0012-9658(2001)082[0523:Mabpol]2.0.Co;2

    Article  Google Scholar 

  45. Roux O, Diabate A, Simard F (2014) Divergence in threat sensitivity among aquatic larvae of cryptic mosquito species. J Anim Ecol 83:702–711. https://doi.org/10.1111/1365-2656.12163

    Article  PubMed  Google Scholar 

  46. Seiter M, Schausberger P (2015) Maternal intraguild predation risk affects offspring antipredator behavior and learning in mites. Sci Rep 5:15046. https://doi.org/10.1038/srep15046

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  47. Shaffery HM, Relyea RA (2016) Dissecting the smell of fear from conspecific and heterospecific prey: investigating the processes that induce antipredator defenses. Oecologia 180:55–65. https://doi.org/10.1007/s00442-015-3444-x

    Article  PubMed  Google Scholar 

  48. Stamps JA, Frankenhuis WE (2016) Bayesian models of development. Trends Ecol Evol 31:260–268. https://doi.org/10.1016/j.tree.2016.01.012

    Article  PubMed  Google Scholar 

  49. Stamps JA, Krishnan VV (2014a) Combining information from ancestors and personal experiences to predict individual differences in developmental trajectories. Am Nat 184:647–657. https://doi.org/10.1086/678116

    Article  PubMed  Google Scholar 

  50. Stamps JA, Krishnan VV (2014b) Individual differences in the potential and realized developmental plasticity of personality traits. Front Ecol Evol. https://doi.org/10.3389/fevo.2014.00069

    Article  Google Scholar 

  51. Stamps JA, Krishnan VV (2017) Age-dependent changes in behavioural plasticity: insights from Bayesian models of development. Anim Behav 126:53–67. https://doi.org/10.1016/j.anbehav.2017.01.013

    Article  Google Scholar 

  52. Stamps J, Biro PA, Mitchell DJ, Saltz J (2018) Bayesian updating during development predicts genotypic differences in plasticity. Evolution. https://doi.org/10.1111/evo.13585

    Article  PubMed  Google Scholar 

  53. Stein LR, Bukhari SA, Bell AM (2018) Personal and transgenerational cues are nonadditive at the phenotypic and molecular level. Nat Ecol Evol 2:1306–1311. https://doi.org/10.1038/s41559-018-0605-4

    Article  PubMed  PubMed Central  Google Scholar 

  54. Stoffer B, Uetz GW (2015) The effects of social experience with varying male availability on female mate preferences in a wolf spider. Behav Ecol Sociobiol 69:927–937. https://doi.org/10.1007/s00265-015-1904-2

    Article  Google Scholar 

  55. Stoffer B, Uetz GW (2016) Social experience affects female mate preferences for a visual trait in a wolf spider. Behav Ecol 27:252–261. https://doi.org/10.1093/beheco/arv143

    Article  Google Scholar 

  56. Storm JJ, Lima SL (2010) Mothers forewarn offspring about predators: a transgenerational maternal effect on behavior. Am Nat 175:382–390. https://doi.org/10.1086/650443

    Article  PubMed  Google Scholar 

  57. Styron RH, Hetland EA (2014) Estimated likelihood of observing a large earthquake on a continental low-angle normal fault and implications for low-angle normal fault activity. Geophys Res Lett 41:2342–2350. https://doi.org/10.1002/2014gl059335

    Article  Google Scholar 

  58. Sultan SE (2017) Developmental plasticity: re-conceiving the genotype. Interface Focus. https://doi.org/10.1098/rsfs.2017.0009

    Article  PubMed  PubMed Central  Google Scholar 

  59. Uller T (2008) Developmental plasticity and the evolution of parental effects. Trends Ecol Evol 23:432–438. https://doi.org/10.1016/j.tree.2008.04.005

    Article  PubMed  Google Scholar 

  60. Van Buskirk J, Arioli M (2002) Dosage response of an induced defense: how sensitive are tadpoles to predation risk? Ecology 83:1580–1585. https://doi.org/10.2307/3071977

    Article  Google Scholar 

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Acknowledgements

We thank Yifeng Xu for help with programming, Juliette Tariel for sharing unpublished data, and Barney Luttbeg for insightful comments on a previous draft of the manuscript. This material is partially based on work supported by the National Science Foundation under Grant No. IOS 1121980 and the National Institutes of Health under award number 2R01GM082937-06A1.

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JAS and AMB jointly formulated the ideas, JAS designed and analyzed the models, JAS and AMB jointly wrote the article.

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Correspondence to Judy A. Stamps.

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This article does not contain any studies with human participants or animals performed by any of the authors.

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Communicated by Ola Olsson.

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Stamps, J.A., Bell, A.M. The information provided by the absence of cues: insights from Bayesian models of within and transgenerational plasticity. Oecologia 194, 585–596 (2020). https://doi.org/10.1007/s00442-020-04792-9

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Keywords

  • Developmental plasticity
  • Parental effects
  • Within-generational plasticity
  • WGP
  • Transgenerational plasticity
  • TGP
  • Socially cued plasticity
  • Updating
  • Social cues