Landscape Ecology

, Volume 31, Issue 9, pp 2115–2131 | Cite as

Swallowtail butterflies show positive edge responses predicted by resource use

Research Article

Abstract

Context

The prevalence of edges is increasing due to anthropogenic landscape change. Edge responses can vary considerably between and within species. Understanding species’ responses to edges, and the causes of variation in such responses is central to managing biodiversity in contemporary landscapes.

Objective

A resource distribution model predicts that species that require complementary resources in different land cover types will be most abundant at edges, displaying a positive edge response. Eastern tiger (Papilio glaucus) and spicebush (P. troilus) swallowtail butterflies use forest plant species for oviposition sites but open-habitat plants for nectar. They are excellent models for testing the positive edge response and exploring sources of variability in edge responses, such as species-specific traits or temporal effects.

Methods

In southwestern Ontario, we examined both the abundance and flight orientation of these species in relation to forest/meadow edges and at different times of day. We used a transect method similar to the Pollard walk and a catch and release method, respectively.

Results

The distribution and flight behaviour of these butterfly species were overall consistent with a positive edge response. Both species were most abundant at the edge and oriented their flight towards the edge from the forest and meadow. However, P. glaucus demonstrated a much stronger positive edge response, while P. troilus showed temporal variation in its response.

Conclusions

Our results confirm the ability of the resource distribution model to predict species edge responses and movement behaviours, but also indicate that species-specific traits and time of sampling can influence such responses.

Keywords

Habitat Landscape Fragmentation Resource distribution Edge Butterfly Variation Temporal effects Flight orientation 

Notes

Acknowledgments

We thank Sarah Kruis, Ryan Smith, and volunteers who helped with field work and data entry. The Nature Conservancy of Canada, Long Point Regional Conservation Authority, Mary Gartshore and Peter Carson, Brian Craig and Paula Jongerden, Jim and Carol Knack, and Kathryn Boothby kindly allowed us to work on their properties. This research was supported by the Canada Foundation for Innovation, Natural Sciences and Engineering Research Council of Canada (including a graduate scholarship to J. C. Siu), Canada Research Chairs, and Ontario Ministry of Research and Innovation. Handling of swallowtail butterflies was authorized by the Ontario Ministry of Natural Resources (Wildlife Scientific Collector’s Authorization No. 1067555).

Supplementary material

10980_2016_385_MOESM1_ESM.docx (16 kb)
Supplementary material 1 (DOCX 15 kb)

References

  1. Argus W (1992) The phytogeography of rare vascular plants in Ontario and its bearing on plant conservation. Can J Bot 70:469–490CrossRefGoogle Scholar
  2. Bartoń K (2013) MuMIn: multi-model inference. R package version 1.9.18. http://cran.r-project.org/web/packages/MuMIn/. Accessed 19 Dec 2013
  3. Bates D, Maechler M, Bolker B, Walker S (2013) lme4: linear mixed-effects models using Eigen and S4. R package version 1.0-5. http://cran.r-project.org/web/packages/lme4/. Accessed 25 Oct 2013
  4. Benjamini Y, Hochberg Y (1995) Controlling the false discovery rate: a practical and powerful approach to multiple testing. J R Stat Soc 57:289–300Google Scholar
  5. Brommer JE, Fred MS (1999) Movement of the Apollo butterfly Parnassius apollo related to host plant and nectar plant patches. Ecol Entomol 24:125–131CrossRefGoogle Scholar
  6. Burnham KP, Anderson DR (2002) Model selection and multimodel inference: a practical information-theoretic approach, 2nd edn. Springer-Verlag New York Inc, New YorkGoogle Scholar
  7. Caballero-Mendieta N, Cordero C (2013) Male mating costs in a butterfly that produces small ejaculates. Physiol Entomol 38:318–325CrossRefGoogle Scholar
  8. Conradt L, Bodsworth EJ, Roper TJ, Thomas CD (2000) Non-random dispersal in the butterfly Maniola jurtina: implications for metapopulation models. Proc Biol Sci 267:1505–1510CrossRefPubMedPubMedCentralGoogle Scholar
  9. Conradt L, Roper TJ, Thomas CD (2001) Dispersal behaviour of individuals in metapopulations of two British Butterflies. Oikos 95:416–424CrossRefGoogle Scholar
  10. Crins WJ (1997) Rare and endangered plants and their habitats in Canada. Can Field Nat 111:506–519Google Scholar
  11. Fisher NI (1993) Statistical analysis of circular data. The Press Syndicate of the University of Cambridge, CambridgeCrossRefGoogle Scholar
  12. Fletcher RJ Jr, Ries L, Battin J, Chalfoun AD (2007) The role of habitat area and edge in fragmented landscapes: definitively distinct or inevitably intertwined? This review is one of a series dealing with some aspects of the impact of habitat fragmentation on animals and plants. This series is one of severa. Can J Zool 85:1017–1030CrossRefGoogle Scholar
  13. Fonderflick J, Besnard A, Martin J-L (2013) Species traits and the response of open-habitat species to forest edge in landscape mosaics. Oikos 122:42–51CrossRefGoogle Scholar
  14. Grossmueller DW, Lederhouse RC (1987) The role of nectar source distribution in habitat use and oviposition by the tiger swallowtail buterfly. J Lepid Soc 41:159–165Google Scholar
  15. Haddad NM (1999) Corridor use predicted from behaviors at habitat boundaries. Am Nat 153:215–227CrossRefGoogle Scholar
  16. Haddad NM, Baum KA (1999) An experimental test of corridor effects on butterfly densities. Ecol Appl 9:623–633CrossRefGoogle Scholar
  17. Hirota T, Obara Y (2000) Time allocation to the reproductive and feeding behaviors in the male cabbage butterfly. Zool Sci 17:323–327PubMedGoogle Scholar
  18. Hurst ZM, McCleery RA, Collier BA, Fletcher RJ Jr, Silvy NJ, Taylor PJ, Monadjem A (2013) Dynamic edge effects in small mammal communities across a conservation-agricultural interface in Swaziland. PLoS One 8:e74520CrossRefPubMedPubMedCentralGoogle Scholar
  19. Ide J (2004) Diurnal and seasonal changes in the mate-locating behavior of the satyrine butterfly Lethe diana. Ecol Res 19:189–196CrossRefGoogle Scholar
  20. Kareiva PM, Shigesada N (1983) Analyzing insect movement as a correlated random walk. Oecologia 56:234–238CrossRefGoogle Scholar
  21. Klein AL, Araújo AM (2010) Courtship behavior of Heliconius erato phyllis (Lepidoptera, Nymphalidae) towards virgin and mated females: conflict between attraction and repulsion signals? J Ethol 28:409–420CrossRefGoogle Scholar
  22. Kuefler D, Haddad NM (2006) Local versus landscape determinants of butterfly movement behaviors. Ecography 29:549–560CrossRefGoogle Scholar
  23. Laurance W (2008) Theory meets reality: how habitat fragmentation research has transcended island biogeographic theory. Biol Conserv 141:1731–1744CrossRefGoogle Scholar
  24. Lidicker WZ (1999) Responses of mammals to habitat edges: an overview. Landscape Ecol 14:333–343CrossRefGoogle Scholar
  25. Lindell CA, Riffell SK, Kaiser SA, Battin AL, Smith ML, Sisk TD (2007) Edge responses of tropical and temperate birds. Wilson J Onithol 119:205–220CrossRefGoogle Scholar
  26. Lund U, Agostinelli C (2013) Circular: circular statistics. R package version 30.4-3. http://cran.r-project.org/web/packages/circular/. Accessed 15 Feb 2013
  27. Macreadie PI, Connolly RM, Jenkins GP et al (2010a) Edge patterns in aquatic invertebrates explained by predictive models. Mar Freshw Res 61:214–218CrossRefGoogle Scholar
  28. Macreadie PI, Connolly RM, Jenkins GP, Hindell JS, Keough MJ (2010b) Resource distribution influences positive edge effects in a seagrass fish. Ecology 91:2013–2021CrossRefPubMedGoogle Scholar
  29. Murcia C (1995) Edge effects in fragmented forests: implications for conservation. Trends Ecol Evol 10:58–62CrossRefPubMedGoogle Scholar
  30. Nitao JK, Ayres MP, Lederhouse RC, Scriber JM (1991) Larval adaptation to lauraceous hosts: geographic divergence in the spicebush swallowtail butterfly. Ecology 72:1428–1435CrossRefGoogle Scholar
  31. Pexioto PEC, Benson WW (2009) Daily activity patterns of two co-occurring tropical satyrine butterflies. J Insect Sci 9:1–14Google Scholar
  32. Pollard E (1977) A method for assessing changes in the abundance of butterflies. Biol Conserv 12:115–134CrossRefGoogle Scholar
  33. R Development Core Team (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. http://www.r-project.org/. Accessed 25 Sept 2013
  34. Ries L, Debinski DM (2001) Butterfly responses to habitat edges in the highly fragmented prairies of Central Iowa. J Anim Ecol 70:840–852CrossRefGoogle Scholar
  35. Ries L, Fletcher RJ, Battin J, Sisk TD (2004) Ecological responses to habitat edges: mechanisms, models, and variability explained. Annu Rev Ecol Evol Syst 35:491–522CrossRefGoogle Scholar
  36. Ries L, Sisk TD (2004) A predictive model of edge effects. Ecology 85:2917–2926CrossRefGoogle Scholar
  37. Ries L, Sisk TD (2008) Butterfly edge effects are predicted by a simple model in a complex landscape. Oecologia 156:75–86CrossRefPubMedGoogle Scholar
  38. Roland J (1982) Melanism and diel activity of alpine Colias (Lepidoptera: Pieridae). Oecologia 53:214–221CrossRefGoogle Scholar
  39. Roland J (2006) Effect of melanism of alpine Colias nastes butterflies (Lepidoptera: Pieridae) on activity and predation. Can Entomol 138:52–58CrossRefGoogle Scholar
  40. Ross JA, Matter SF, Roland J (2005) Edge avoidance and movement of the butterfly Parnassius smintheus in matrix and non-matrix habitat. Landscape Ecol 20:127–135CrossRefGoogle Scholar
  41. Rutowski RL (1991) The evolution of male mate-locating behaviour in butterflies. Am Nat 138:1121–1139CrossRefGoogle Scholar
  42. Samejima Y, Tsubaki Y (2010) Body temperature and body size affect flight performance in a damselfly. Behav Ecol Sociobiol 64:685–692CrossRefGoogle Scholar
  43. Schtickzelle N, Joiris A, Van Dyck H, Baguette M (2007) Quantitative analysis of changes in movement behaviour within and outside habitat in a specialist butterfly. BMC Evol Biol. doi:10.1186/1471-2148-7-4 Google Scholar
  44. Schultz CB (1998) Dispersal behavior and its implications for reserve design in a rare oregon butterfly. Conserv Biol 12:284–292CrossRefGoogle Scholar
  45. Schultz CB, Franco AM, Crone EE (2012) Response of butterflies to structural and resource boundaries. J Anim Ecol 81:724–734CrossRefPubMedGoogle Scholar
  46. Scott JA (1986) The butterflies of North America: a natural history and field guide. Standford University Press, CaliforniaGoogle Scholar
  47. Scriber JM, Giebink BL, Snider D (1991) Reciprocal latitudinal clines in oviposition behavior of Papilio glaucus and P. canadensis across the Great Lakes hybrid zone: possible sex-linkage of oviposition preferences. Oecologia 87:360–368CrossRefGoogle Scholar
  48. Skórka P, Nowicki P, Lenda M, Witek M, Śliwińska EB, Settele J, Woyciechowski M (2013) Different flight behaviour of the endangered scarce large blue butterfly Phengaris teleius (Lepidoptera: Lycaenidae) within and outside its habitat patches. Landscape Ecol 28:533–546Google Scholar
  49. Tiple AD, Khurad AM, Dennis RLH (2009) Adult butterfly feeding–nectar flower associations: constraints of taxonomic affiliation, butterfly, and nectar flower morphology. J Nat Hist 43:855–884CrossRefGoogle Scholar
  50. Tscharntke T, Steffan-Dewenter I, Kruess A, Thies C (2002) Contribution of small habitat fragments to conservation of insect communities of grassland-cropland landscapes. Ecol Appl 12:354–363Google Scholar
  51. Turchin P (1991) Translating foraging movements in heterogeneous environments into the spatial distribution of foragerse. Ecology 72:1253–1266CrossRefGoogle Scholar
  52. Turchin P, Odendaal FJ, Rausher MD (1991) Quantifying inset movement in the field. Environ Entomol 20:955–963CrossRefGoogle Scholar
  53. Van Dyck H, Matthysen E (1998) Thermoregulatory differences between phenotypes in the speckled wood butterfly: hot perchers and cold patrollers? Oecologia 114:326–334CrossRefGoogle Scholar
  54. Watt WB (1968) Significance of pigment polymorphisms in Colias butterflies. I. Variation of melanin pigment in relation to thermoregulation. Evolution 22:437–458CrossRefGoogle Scholar
  55. Wiens JA, Crawford CS, Gosz JR (1985) Boundary dynamics: a conceptual framework for studying landscape ecosystems. Oikos 45:412–427CrossRefGoogle Scholar
  56. Zar JH (2010) Statistical analysis, 5th edn. Pearson Hall, Upper Saddle RiverGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  • Jenna C. Siu
    • 1
  • Daria Koscinski
    • 1
  • Nusha Keyghobadi
    • 1
  1. 1.Department of BiologyUniversity of Western OntarioLondonCanada

Personalised recommendations