Host use diversification during range shifts shapes global variation in Lepidopteran dietary breadth

Abstract

Niche breadths tend to be greater at higher latitudes. This pattern is frequently assumed to emerge from the cumulative effects of multiple, independent local adaptation events along latitudinal environmental gradients, although evidence that generalization is more beneficial at higher-latitude locations remains equivocal. Here I propose an alternative hypothesis: that latitudinal variation in niche breadths emerges as a non-adaptive consequence of range shift dynamics. Based on analysis of a global dataset comprising more than 6,934 globally distributed dietary records from 4,410 Lepidopteran species, this hypothesis receives robust support. Population-level dietary niche breadths are better explained by the relative position of the population within its geographic range and the species’ poleward range extent than by the latitude of diet observation. Broader diets are observed closer to poleward range limits and in species that have attained higher latitudes. Moreover, latitudinal variation in diet breadth is more prominent within and among species undergoing rapid, contemporary range shifts than for species with more stable ranges. Together these results suggest that latitudinal patterns in niche breadth represent a transient and emergent property of recent geographic range dynamics and need not require underlying gradients in selective agents or fitness trade-offs. The results have wide-ranging implications for global ecology and for anticipating changes in host use during ongoing distributional shifts of pests and disease vectors.

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: Distribution of Lepidopteran dietary niche breadths in the dataset.
Fig. 2: Effect of relative range position, range dynamics and latitude on dietary niche breadth in Lepidopterans.

Data availability

All data used in this study are freely publicly available from the cited sources17,19,20. Reuse of the HOSTS dataset is conditional upon permission from the curators.

References

  1. 1.

    Forister, M. L. et al. The global distribution of diet breadth in insect herbivores. Proc. Natl Acad. Sci. USA 112, 442–447 (2015).

    CAS  PubMed  Google Scholar 

  2. 2.

    MacArthur, R. H. Geographical Ecology: Patterns in the Distribution of Species (Harper and Row, 1972).

  3. 3.

    Addo-Bediako, A., Chown, S. L. & Gaston, K. J. Thermal tolerance, climatic variability and latitude. Proc. Biol. Sci. 267, 739–745 (2000).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

    Vázquez, D. P. & Stevens, R. D. The latitudinal gradient in niche breadth: concepts and evidence. Am. Nat. 164, E1–E19 (2004).

    PubMed  Google Scholar 

  5. 5.

    Novotny, V. et al. Why are there so many species of herbivorous insects in tropical rainforests? Science 313, 1115–1118 (2006).

    CAS  PubMed  Google Scholar 

  6. 6.

    Dyer, L. A. et al. Host specificity of Lepidoptera in tropical and temperate forests. Nature 448, 696–699 (2007).

    CAS  PubMed  Google Scholar 

  7. 7.

    Lancaster, L. T. Widespread range expansions shape latitudinal variation in insect thermal limits. Nat. Clim. Change 6, 618–621 (2016).

    Google Scholar 

  8. 8.

    Slove, J., Janz, N., Strimmer, K., Midford, P. & Leibowits, T. The relationship between diet breadth and geographic range size in the butterfly subfamily Nymphalinae – a study of global scale. PLoS ONE 6, e16057 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  9. 9.

    Nylin, S. et al. Embracing colonizations: a new paradigm for species association dynamics. Trends Ecol. Evol. 33, 4–14 (2018).

    PubMed  Google Scholar 

  10. 10.

    Janz, N. & Nylin, S. in Specialization, Speciation, and Radiation (ed. Tilmon, K.) 203–215 (Univ. California Press, 2008).

  11. 11.

    Lancaster, L. T., Dudaniec, R. Y., Hansson, B. & Svensson, E. I. Latitudinal shift in thermal niche breadth results from thermal release during a climate-mediated range expansion. J. Biogeogr. 42, 1953–1963 (2015).

    Google Scholar 

  12. 12.

    Losos, Jackman, Larson, Queiroz & Rodriguez-Schettino Contingency and determinism in replicated adaptive radiations of island lizards. Science 279, 2115–2118 (1998).

    CAS  PubMed  Google Scholar 

  13. 13.

    Agosta, S. J., Janz, N. & Brooks, D. R. How specialists can be generalists: resolving the ‘parasite paradox’; and implications for emerging infectious disease. Zoology 27, 151–162 (2010).

    Google Scholar 

  14. 14.

    Lancaster, L. T., Morrison, G. & Fitt, R. N. Life history trade-offs, the intensity of competition, and coexistence in novel and evolving communities under climate change. Phil. Trans. R. Soc. B 372, 20160046 (2017).

    PubMed  Google Scholar 

  15. 15.

    Hewitt, G. The genetic legacy of the Quaternary ice ages. Nature 405, 907–913 (2000).

    CAS  PubMed  Google Scholar 

  16. 16.

    Davis, M. B., Shaw, R. G. & Etterson, J. R. Evolutionary responses to changing climate. Ecology 86, 1704–1714 (2005).

    Google Scholar 

  17. 17.

    Robinson, G. S., Ackery, P. R., Kitching, I. J., Beccaloni, G. W. & Hernández, L. M. HOSTS – A Database of the World’s Lepidopteran Hostplants (Natural History Museum, accessed 15 June 2016); http://www.nhm.ac.uk/hosts

  18. 18.

    GBIF.org (The Global Biodiversity Information Facility, accessed 7 August 2016); www.gbif.org

  19. 19.

    Mason, S. C. et al. Geographical range margins of many taxonomic groups continue to shift polewards. Biol. J. Linn. Soc. 115, 586–597 (2015).

    Google Scholar 

  20. 20.

    Pöyry, J., Luoto, M., Heikkinen, R. K., Kuussaari, M. & Saarinen, K. Species traits explain recent range shifts of Finnish butterflies. Glob. Change Biol. 15, 732–743 (2009).

    Google Scholar 

  21. 21.

    Schmitt, T. Molecular biogeography of Europe: Pleistocene cycles and postglacial trends. Front. Zool. 4, 11 (2007).

    PubMed  PubMed Central  Google Scholar 

  22. 22.

    Parmesan, C. et al. Poleward shifts in geographical ranges of butterfly species associated with regional warming. Nature 399, 579–583 (1999).

    CAS  Google Scholar 

  23. 23.

    Kerdelhué, C. et al. Quaternary history and contemporary patterns in a currently expanding species. BMC Evol. Biol. 9, 220 (2009).

    PubMed  PubMed Central  Google Scholar 

  24. 24.

    de Jong, M. A., Wahlberg, N., van Eijk, M., Brakefield, P. M. & Zwaan, B. J. Mitochondrial DNA signature for range-wide populations of Bicyclus anynana suggests a rapid expansion from recent refugia. PLoS ONE 6, e21385 (2011).

    PubMed  PubMed Central  Google Scholar 

  25. 25.

    Eidesen, P. B. et al. Genetic roadmap of the Arctic: plant dispersal highways, traffic barriers and capitals of diversity. New Phytol. 200, 898–910 (2013).

    PubMed  Google Scholar 

  26. 26.

    Todisco, V. et al. Mitochondrial phylogeography of the Holarctic Parnassius phoebus complex supports a recent refugial model for alpine butterflies. J. Biogeogr. 39, 1058–1072 (2012).

    Google Scholar 

  27. 27.

    Chen, I.-C., Hill, J. K., Ohlemüller, R., Roy, D. B. & Thomas, C. D. Rapid range shifts of species associated with high levels of climate warming. Science 333, 1024–1026 (2011).

    CAS  PubMed  Google Scholar 

  28. 28.

    Pateman, R. M., Hill, J. K., Roy, D. B., Fox, R. & Thomas, C. D. Temperature-dependent alterations in host use drive rapid range expansion in a butterfly. Science 336, 1028–1030 (2012).

    CAS  PubMed  Google Scholar 

  29. 29.

    Braschler, B. & Hill, J. K. Role of larval host plants in the climate-driven range expansion of the butterfly Polygonia c-album. J. Anim. Ecol. 76, 415–423 (2007).

    PubMed  Google Scholar 

  30. 30.

    Suehiro, W. et al. Radiocarbon analysis reveals expanded diet breadth associates with the invasion of a predatory ant. Sci. Rep. 7, 15016 (2017).

    PubMed  PubMed Central  Google Scholar 

  31. 31.

    Shively, R., Barboza, P., Doak, P. & Jung, T. S. Increased diet breadth of little brown bats (Myotis lucifugus) at their northern range limit: a multimethod approach. Can. J. Zool. 96, 31–38 (2018).

    CAS  Google Scholar 

  32. 32.

    Eloy de Amorim, M. et al. Lizards on newly created islands independently and rapidly adapt in morphology and diet. Proc. Natl Acad. Sci. USA 114, 8812–8816 (2017).

    CAS  PubMed  Google Scholar 

  33. 33.

    Singer, M. C. & Parmesan, C. Colonizations cause host shifts, diversification of preferences and expansion of butterfly diet breadth. Preprint at bioRxiv https://doi.org/10.1101/2020.03.31.017830 (2020).

  34. 34.

    Slatyer, R. A., Hirst, M. & Sexton, J. P. Niche breadth predicts geographical range size: a general ecological pattern. Ecol. Lett. 16, 1104–1114 (2013).

    PubMed  Google Scholar 

  35. 35.

    Mattila, N., Kaitala, V., Komonen, A., Päivinen, J. & Kotiaho, J. S. Ecological correlates of distribution change and range shift in butterflies. Insect Conserv. Divers. 4, 239–246 (2011).

    Google Scholar 

  36. 36.

    Fordyce, J. A. & Nice, C. C. Contemporary patterns in a historical context: phylogenetic history of the pipevine swallowtail, Battus philenor (Papilionidae). Evolution 57, 1089–1099 (2003).

    Google Scholar 

  37. 37.

    Bridle, J. R., Buckley, J., Bodsworth, E. J. & Thomas, C. D. Evolution on the move: specialization on widespread resources associated with rapid range expansion in response to climate change. Proc. Biol. Sci. 281, 20131800 (2014).

    PubMed  PubMed Central  Google Scholar 

  38. 38.

    Dapporto, L. & Dennis, R. L. H. The generalist–specialist continuum: testing predictions for distribution and trends in British butterflies. Biol. Conserv. 157, 229–236 (2013).

    Google Scholar 

  39. 39.

    Janz, N., Nyblom, K. & Nylin, S. Evolutionary dynamics of host-plant specialization: a case study of the tribe Nymphalini. Evolution 55, 783–796 (2001).

    CAS  PubMed  Google Scholar 

  40. 40.

    de la Paz Celorio-Mancera, M. et al. Mechanisms of macroevolution: polyphagous plasticity in butterfly larvae revealed by RNA-Seq. Mol. Ecol. 22, 4884–4895 (2013).

    PubMed  Google Scholar 

  41. 41.

    Snell-Rood, E. C., Troth, A. & Moczek, A. P. DNA methylation as a mechanism of nutritional plasticity: limited support from horned beetles. J. Exp. Zool. B 320, 22–34 (2013).

    CAS  Google Scholar 

  42. 42.

    Janz, N. & Nylin, S. The role of female search behaviour in determining host plant range in plant feeding insects: a test of the information processing hypothesis. Proc. R. Soc. B 264, 701–707 (1997).

    Google Scholar 

  43. 43.

    Jahner, J. P., Bonilla, M. M., Badik, K. J., Shapiro, A. M. & Forister, M. L. Use of exotic hosts by Lepidoptera: widespread species colonize more novel hosts. Evolution 65, 2719–2724 (2011).

    PubMed  Google Scholar 

  44. 44.

    Singer, M. C., Stefanescu, C. & Pen, I. When random sampling does not work: standard design falsely indicates maladaptive host preferences in a butterfly. Ecol. Lett. 5, 1–6 (2002).

    Google Scholar 

  45. 45.

    Singer, M. C. & Lee, J. R. Discrimination within and between host species by a butterfly: implications for design of preference experiments. Ecol. Lett. 3, 101–105 (2000).

    Google Scholar 

  46. 46.

    Forister, M. L. & Jenkins, S. H. A neutral model for the evolution of diet breadth. Am. Nat. 190, E40–E54 (2017).

    PubMed  Google Scholar 

  47. 47.

    Singer, M. C., Wee, B., Hawkins, S. & Butcher, M. in Specialization, Speciation, and Radiation: The Evolutionary Biology of Herbivorous Insects (ed. Tilmon, K.) 311–324 (Univ. California Press, 2008).

  48. 48.

    South, A. rworldmap: a new R package for mapping global data. R J. 3, 35–43 (2011).

    Google Scholar 

  49. 49.

    Natural Earth v.1.4.0 (Natural Earth, 2011); https://go.nature.com/2VHqgTQ

  50. 50.

    Gillespie, C. S. Fitting heavy tailed distributions: the poweRlaw package. J. Stat. Softw. 64, 1–16 (2015).

    Google Scholar 

  51. 51.

    R Core Development Team R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2012).

  52. 52.

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

    Google Scholar 

  53. 53.

    Bates, D., Maechler, M., Bolker, B. & Walker, S. Fitting linear mixed-effects models using lme4. J. Stat. Softw. 67, 1–49 (2015).

    Google Scholar 

  54. 54.

    Kuznetsova, A., Brockhoff, P. B. & Christensen, R. H. B. lmerTest: Tests for Random and Fixed Effects for Linear Mixed Effects Models (lmer Objects of lme4package) (2014).

  55. 55.

    Mazerolle, M. J. AICcmodavg: Model Selection and Multimodel Inference based on (Q)AIC(c) (2015).

  56. 56.

    Frank, A. F. mer-utils.R (GitHub, 2014); https://go.nature.com/2W5PLx5

  57. 57.

    Wickham, H. Ggplot2: Elegant Graphics for Data Analysis (Springer, 2009).

  58. 58.

    Jin, Y. & Qian, H. V. PhyloMaker: an R package that can generate very large phylogenies for vascular plants. Ecography (Cop.) 42, 1353–1359 (2019).

    Google Scholar 

  59. 59.

    Zanne, A. E. et al. Three keys to the radiation of angiosperms into freezing environments. Nature 506, 89–92 (2014).

    CAS  PubMed  Google Scholar 

  60. 60.

    Smith, S. A. & Brown, J. W. Constructing a broadly inclusive seed plant phylogeny. Am. J. Bot. 105, 302–314 (2018).

    PubMed  Google Scholar 

  61. 61.

    Lüdecke, D. sjPlot: Data Visualization for Statistics in Social Science. R version 2.4.0 (2018); https://CRAN.R-project.org/package=sjPlot

Download references

Acknowledgements

I thank M. C. Singer for helpful discussions and comments. I thank I. Kitching for permissions to use the Lepidopteran host plant database curated by the Natural History Museum London. I also thank the authors of refs. 19,20 for making their range shift data publicly available, and to all contributors to and curators of the open access databases used in this study.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Lesley T. Lancaster.

Ethics declarations

Competing interests

The author declares no competing interests.

Additional information

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

Extended data

Extended Data Fig. 1 Alternative distributional forms fitted to dietary niche breadths in the dataset.

The number of host plants used per Lepidopteran population (n = 6934 observations) was best fit by a discrete, truncated lognormal distribution. P-values reflect the null hypothesis that data were sampled from a particular distribution.

Extended Data Fig. 2 Distribution of Lepidopteran dietary niche in the dataset.

Histogram of number of host species used (i.e., dietary breadth) per Lepidopteran populations in the dataset (n = 6934 observations). A) The full distribution, B) Inset of the distribution (limited to n = 100 records per category), to show the distribution of the tail.

Extended Data Fig. 3 Data range corresponding to main text Fig. 2: Relationships between geographic range position and diet breadth.

a) Boxplots comparing geographic range positions of generalist and specialist populations of Lepidopterans (specialist = only one host recorded for the population, n = 3100 populations; generalist = more than 1 host recorded for the population, n = 3834 populations). Midline = median value; upper and lower limits of box = 3rd and 1st quartile; whiskers are 1.5x interquartile range. B) For the n = 1239 species with host range observations in multiple locations (totalling n = 3769 observations), boxplots represent the median ± quartiles of residual proportional host use of populations at different distances from the poleward geographic range margins, whiskers are 1.5x the interquartile range, and the full data range is depicted in grey. Residual host range calculated from the model presented in Table 1D, see also Fig. 2 legend.

Extended Data Fig. 4 Geographic locations of dietary niche data used in this study.

Each location (n = 148) appearing in the final dataset is colour-coded by the log-transformed number of unique Lepidopteran species-host plant associations in that location (n = 20 categories). Locations lacking colour are not present in the dataset.

Supplementary information

Supplementary Information

Supplementary results and Tables 1–5.

Reporting Summary

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Lancaster, L.T. Host use diversification during range shifts shapes global variation in Lepidopteran dietary breadth. Nat Ecol Evol 4, 963–969 (2020). https://doi.org/10.1038/s41559-020-1199-1

Download citation

Further reading

Search

Sign up for the Nature Briefing newsletter for a daily update on COVID-19 science.
Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing