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Theoretical Ecology

, Volume 10, Issue 2, pp 167–179 | Cite as

Interspecific interactions and range limits: contrasts among interaction types

  • William Godsoe
  • Nathaniel J. Holland
  • Chris Cosner
  • Bruce E. Kendall
  • Angela Brett
  • Jill Jankowski
  • Robert D. Holt
ORIGINAL PAPER

Abstract

There is a great deal of interest in the effects of biotic interactions on geographic distributions. Nature contains many different types of biotic interactions (notably mutualism, commensalism, predation, amensalism, and competition), and it is difficult to compare the effects of multiple interaction types on species’ distributions. To resolve this problem, we analyze a general, flexible model of pairwise biotic interactions that can describe all interaction types. In the absence of strong positive feedback, a species’ ability to be present depends on its ability to increase in numbers when it is rare and the species it is interacting with is at equilibrium. This insight leads to counterintuitive conclusions. Notably, we often predict the same range limit when the focal species experiences competition, predation, or amensalism. Similarly, we often predict the same range margin or when the species experiences mutualism, commensalism, or benefits from prey. In the presence of strong positive density-dependent feedback, different species interactions produce different range limits in our model. In all cases, the abiotic environment can indirectly influence the impact of biotic interactions on range limits. We illustrate the implications of this observation by analyzing a stress gradient where biotic interactions are harmful in benign environments but beneficial in stressful environments. Our results emphasize the need to consider the effects of all biotic interactions on species’ range limits and provide a systematic comparison of when biotic interactions affect distributions.

Keywords

Species’ distributions Biotic interactions Range limits Mutualism Competition Stress gradient hypothesis 

Notes

Acknowledgements

This work was supported by the Biotic Interactions Working Group at the National Institute for Mathematical and Biological Synthesis, sponsored by the National Science Foundation, the US Department of Homeland Security, and the US Department of Agriculture through NSF Award Nos. EF-0832858 and DBI-1300426, with additional support from The University of Tennessee, Knoxville. Helpful comments from Rowan Sprague and two anonymous reviewers.

Supplementary material

12080_2016_319_MOESM1_ESM.pdf (725 kb)
ESM 1 (PDF 724 kb)

References

  1. Adler PB, HilleRisLambers J, Levine JM (2007) A niche for neutrality. Ecol Lett 10:95–104CrossRefPubMedGoogle Scholar
  2. Afkhami ME, McIntyre PJ, Strauss SY (2014) Mutualist-mediated effects on species' range limits across large geographic scales. Ecol Lett 17:1265–1273CrossRefPubMedGoogle Scholar
  3. Araújo MB, Rozenfeld A (2014) The geographic scaling of biotic interactions. Ecography 37:406–415Google Scholar
  4. Arditi R, Ginzburg LR (1989) Coupling in predator-prey dynamics: ratio-dependence. J Theor Biol 139:311–326CrossRefGoogle Scholar
  5. Beddington JR (1975) Mutual interference between parasites or predators and its effect on searching efficiency. J Anim Ecol:331–340Google Scholar
  6. Bever JD et al (2010) Rooting theories of plant community ecology in microbial interactions. Trends Ecol Evol 25:468–478CrossRefPubMedPubMedCentralGoogle Scholar
  7. Bolker BM, Pacala SW (1999) Spatial moment equations for plant competition: understanding spatial strategies and the advantages of short dispersal. Am Nat 153:575–602CrossRefGoogle Scholar
  8. Buenau KE, Rassweiler A, Nisbet RM (2007) The effects of landscape structure on space competition and alternative stable states. Ecology 88:3022–3031CrossRefPubMedGoogle Scholar
  9. Bull CM, Possingham H (1995) A model to explain ecological parapatry. Am Nat:935–947Google Scholar
  10. Callaway RM et al (2002) Positive interactions among alpine plants increase with stress. Nature 417:844–848CrossRefPubMedGoogle Scholar
  11. Case TJ, Taper ML (2000) Interspecific competition, environmental gradients, gene flow, and the coevolution of species' borders. Am Nat 155:583–605CrossRefPubMedGoogle Scholar
  12. Case TJ, Holt RD, McPeek MA, Keitt TH (2005) The community context of species borders: ecological and evolutionary perspectives. Oikos 102:28–46CrossRefGoogle Scholar
  13. Chamberlain SA, Bronstein JL, Rudgers JA (2014) How context dependent are species interactions? Ecol Lett 17(7):881–890Google Scholar
  14. Chase JM, Leibold MA (2003) Ecological niches—linking classical and contemporary approaches. The University of Chicago Press, Chicago ILCrossRefGoogle Scholar
  15. Chesson P (2000a) General theory of competitive coexistence in spatially-varying environments. Theor Popul Biol 58:211–237CrossRefPubMedGoogle Scholar
  16. Chesson P (2000b) Mechanisms of maintenance of species diversity. Annu Rev Ecol Evol Syst 31:343–366CrossRefGoogle Scholar
  17. Chesson P, Donahue MJ, Melbourne BA, Sears ALW (2005) Scale transition theory for understanding mechanisms in metacommunities. In: Holyoak M, Leibold MA, Holt RD (eds) Metacommunities: spatial dynamics and ecological communities. University of Chicago Press, Chicago, p 279–306Google Scholar
  18. Colwell RK, Rangel TF (2009) Hutchinson's duality: the once and future niche. Proc Natl Acad Sci 106:19651–19658CrossRefPubMedPubMedCentralGoogle Scholar
  19. Cosner C (2005) A dynamic model for the ideal-free distribution as a partial differential equation. Theor Popul Biol 67:101–108CrossRefPubMedGoogle Scholar
  20. Cosner C, Winkler M (2014) Well-posedness and qualitative properties of a dynamical model for the ideal free distribution. J Math Biol 69:1343–1382CrossRefPubMedGoogle Scholar
  21. Courchamp F, Berec L, Gascoigne J (2008) Allee effects in ecology and conservation. Environ Conserv 36:80–85Google Scholar
  22. Davis AJ, Jenkinson LS, Lawton JH, Shorrocks B, Wood S (1998) Making mistakes when predicting shifts in species range in response to global warming. Nature 391:783–786CrossRefPubMedGoogle Scholar
  23. de Villemereuil PB, López-Sepulcre A (2011) Consumer functional responses under intra-and inter-specific interference competition. Ecol Model 222:419–426CrossRefGoogle Scholar
  24. DeAngelis DL, Goldstein RA, O'Neill RV (1975) A model for tropic interaction. Ecology:881–892Google Scholar
  25. DeAngelis D, Post WM, Travis CC (2012) Positive feedback in natural systems vol 15. Springer Science & Business MediaGoogle Scholar
  26. Dickie IA, Bolstridge N, Cooper JA, Peltzer DA (2010) Co-invasion by Pinus and its mycorrhizal fungi. New Phytol 187:475–484CrossRefPubMedGoogle Scholar
  27. Dieckmann U, Law R, Metz JAJ (2000) The geometry of ecological interactions: simplifying spatial complexity. Cambridge University Press, CambridgeGoogle Scholar
  28. Donahue MJ, Desharnais RA, Robles CD, Arriola P (2011) Mussel bed boundaries as dynamic equilibria: thresholds, phase shifts, and alternative states. Am Nat 178:612–625CrossRefPubMedGoogle Scholar
  29. Elith J, Leathwick JR (2009) Species distribution models: ecological explanation and prediction across space and time. Annu Rev Ecol, Evol Syst 40:677–697CrossRefGoogle Scholar
  30. Fishman MA, Hadany L (2010) Plant-pollinator population dynamics. Theor Popul Biol 78:270–277CrossRefPubMedGoogle Scholar
  31. Gabriel J-P, Saucy F, Bersier L-F (2005) Paradoxes in the logistic equation? Ecol Model 185:147–151CrossRefGoogle Scholar
  32. García-Ramos G, Sánchez-Garduño F, Maini PK (2000) Dispersal can sharpen parapatric boundaries on a spatially varying environment. Ecology 81:749–760CrossRefGoogle Scholar
  33. Gascoigne JC, Lipcius RN (2004) Allee effects driven by predation. J Appl Ecol 41:801–810CrossRefGoogle Scholar
  34. Godsoe W, Murray R, Plank MJ (2015) Information on biotic interactions improves transferability of distribution models. Am Nat 185:281–290CrossRefPubMedGoogle Scholar
  35. Goldberg EE, Lande R (2007) Species' borders and dispersal barriers. Am Nat 170:297–304PubMedGoogle Scholar
  36. Hargreaves AL, Samis KE, Eckert CG (2014) Are Species' range limits simply niche limits writ large? A review of transplant experiments beyond the range. Am Nat 183:157–173CrossRefPubMedGoogle Scholar
  37. Hirota M, Holmgren M, van Nes EH, Scheffer M (2011) Global resilience of tropical forest and savanna to critical transitions. Science 334:232–235CrossRefPubMedGoogle Scholar
  38. Hirzel AH, Le Lay G (2008) Habitat suitability modelling and niche theory. J Appl Ecol 45:1372–1381CrossRefGoogle Scholar
  39. Holland JN, DeAngelis DL (2009) Consumer-resource theory predicts dynamic transitions between outcomes of interspecific interactions. Ecol Lett 12:1357–1366CrossRefPubMedGoogle Scholar
  40. Holland JN, DeAngelis DL (2010) A consumer-resource approach to the density-dependent population dynamics of mutualism. Ecology 91:1286–1295CrossRefPubMedGoogle Scholar
  41. Holling CS (1959) The components of predation as revealed by a study of small-mammal predation of the European pine sawfly. Can Entomol 91:293–320CrossRefGoogle Scholar
  42. Holt RD (2009) Bringing the hutchinsonian niche into the twenty-first century: ecological and evolutionary perspectives. Proc Natl Acad Sci 106:19659–19665CrossRefPubMedPubMedCentralGoogle Scholar
  43. Holt RD, Keitt TH (2000) Alternative causes for range limits: a metapopulation perspective. Ecol Lett 3:41–47CrossRefGoogle Scholar
  44. Holt RD, Barfield M (2009) Trophic interactions and range limits: the diverse roles of predation. Proc R Soc B 276:1435–1442Google Scholar
  45. Huisman G, De Boer RJ (1997) A formal derivation of the “Beddington” functional response. J Theor Biol 185:389–400CrossRefGoogle Scholar
  46. Hutson V, Law R, Lewis D (1985) Dynamics of ecologically obligate mutualisms-effects of spatial diffusion on resilience of the interacting species. Am Nat:445–449Google Scholar
  47. Keitt TH, Lewis MA, Holt RD (2001) Allee effects, invasion pinning, and species’ borders. Am Nat 157:203–216PubMedGoogle Scholar
  48. Kimbrell T, Holt RD (2005) Individual behaviour, space and predator evolution promote persistence in a two-patch system with predator switching. Evol Ecol Res 7:53–71Google Scholar
  49. Kot M (2001) Elements of mathematical ecology. Cambridge University Press, CambridgeGoogle Scholar
  50. Lavergne S, Mouquet N, Thuiller W, Ronce O (2010) Biodiversity and climate change: integrating evolutionary and ecological responses of species and communities. Annu Rev Ecol Evol Syst 41:321–350CrossRefGoogle Scholar
  51. Louthan AM, Doak DF, Angert AL (2015) Where and when do species interactions set range limits? Trends Ecol Evol 30:780–792CrossRefPubMedGoogle Scholar
  52. MacArthur RH (1972) Geographical ecology: patterns in the distribution of species. Harper & Row, New YorkGoogle Scholar
  53. MacArthur RH, Levins R (1964) Competition, habitat selection, and character displacement in a patchy environment. Proc Natl Acad Sci 51:1207–1210CrossRefPubMedPubMedCentralGoogle Scholar
  54. MacLean WP, Holt RD (1979) Distributional patterns in St. Croix Sphaerodactylus lizards: the taxon cycle in action. Biotropica:189–195Google Scholar
  55. May RM (1973) Qualitative stability in model ecosystems. Ecology:638–641Google Scholar
  56. May RM, Leonard WJ (1975) Nonlinear aspects of competition between three species. SIAM J Appl Math 29:243–253CrossRefGoogle Scholar
  57. Ohgushi T, Schmitz O, Holt RD (2012) Trait-mediated indirect interactions: ecological and evolutionary perspectives. Cambridge University Press, CambridgeCrossRefGoogle Scholar
  58. Oro D, Martínez-Abraín A, Paracuellos M, Nevado JC, Genovart M (2006) Influence of density dependence on predator–prey seabird interactions at large spatio-temporal scales. Proc R Soc Lond B Biol Sci 273:379–383CrossRefGoogle Scholar
  59. Parker MA (2001) Mutualism as a constraint on invasion success for legumes and rhizobia. Divers Distrib 7:125–136CrossRefGoogle Scholar
  60. Pellmyr O (2003) Yuccas, yucca moths, and coevolution: a review. Ann Mo Bot Gard 90:35–55CrossRefGoogle Scholar
  61. Petraitis P (2013) Multiple stable states in natural ecosystems. Oxford University Press, OxfordGoogle Scholar
  62. Pielou EC (1974) Competition on an environmental gradient. SpringerGoogle Scholar
  63. Pigot AL, Tobias JA (2013) Species interactions constrain geographic range expansion over evolutionary time. Ecol Lett 16:330–338CrossRefPubMedGoogle Scholar
  64. Pulliam R (2000) On the relationship between niche and distribution. Ecol Lett 3:349–361CrossRefGoogle Scholar
  65. Rosenzweig ML, MacArthur RH (1963) Graphical representation and stability conditions of predator-prey interactions. Am Nat:209–223Google Scholar
  66. Samaniego H, Marquet PA (2013) Range structure analysis: unveiling the internal structure of species’ ranges. Theor Ecol 6:419–426CrossRefGoogle Scholar
  67. Scheffer M (2009) Critical transitions in nature and society. Princeton University Press, PrincetonGoogle Scholar
  68. Sexton JP, McIntyre PJ, Angert AL, Rice KJ (2009) Evolution and ecology of species range limits. Annu Rev Ecol Evol Syst 40:415–436. doi: 10.1146/annurev.ecolsys.110308.120317 CrossRefGoogle Scholar
  69. Shurin JB, Amarasekare P, Chase JM, Holt RD, Hoopes MF, Leibold MA (2004) Alternative stable states and regional community structure. J Theor Biol 227:359–368CrossRefPubMedGoogle Scholar
  70. Sinclair ARE, Krebs CJ (2002) Complex numerical responses to top–down and bottom–up processes in vertebrate populations. Phil Trans Royal Soc B: Biol Sci 357:1221–1231CrossRefGoogle Scholar
  71. Skalski GT, Gilliam JF (2001) Functional responses with predator interference: viable alternatives to the Holling type II model. Ecology 82:3083–3092CrossRefGoogle Scholar
  72. Smith HL, Thieme HR, Thieme HR (2011) Dynamical systems and population persistence vol 118. American Mathematical Society, Providence, RIGoogle Scholar
  73. Snyder RE, Chesson P (2004) How the spatial scales of dispersal, competition, and environmental heterogeneity interact to affect coexistence. Am Nat 164:633–650CrossRefPubMedGoogle Scholar
  74. Soberón J (2007) Grinnellian and Eltonian niches and geographic distributions of species. Ecol Lett 10:1115–11123CrossRefPubMedGoogle Scholar
  75. Soliveres S et al (2015) Intransitive competition is widespread in plant communities and maintains their species richness. Ecol Lett 18:790–798CrossRefPubMedPubMedCentralGoogle Scholar
  76. Staver AC, Levin SA (2012) Integrating theoretical climate and fire effects on savanna and forest systems. Am Nat 180:211–224CrossRefPubMedGoogle Scholar
  77. Staver AC, Archibald S, Levin SA (2011) The global extent and determinants of savanna and Forest as alternative biome states. Science 334:230–232. doi: 10.1126/science.1210465 CrossRefPubMedGoogle Scholar
  78. Thuiller W et al (2014) Does probability of occurrence relate to population dynamics? Ecography 37:1155–1166CrossRefPubMedPubMedCentralGoogle Scholar
  79. Van Gils JA, Piersma T (2004) Digestively constrained predators evade the cost of interference competition. J Anim Ecol 73:386–398CrossRefGoogle Scholar
  80. Wilson WG, Nisbet RM (1997) Cooperation and competition along smooth environmental gradients. Ecology 78:2004–2017CrossRefGoogle Scholar
  81. Wisz MS et al (2013) The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling. Biol Rev 88:15–30. doi: 10.1111/j.1469-185X.2012.00235.x CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2016

Authors and Affiliations

  1. 1.Bio-Protection ResearchCentre Lincoln UniversityLincolnNew Zealand
  2. 2.Department of Biology and BiochemistryUniversity of HoustonHoustonUSA
  3. 3.Department of MathematicsUniversity of MiamiCoral GablesUSA
  4. 4.Bren School of Environmental Science and ManagementUniversity of CaliforniaSanta BarbaraUSA
  5. 5.Hagley Community CollegeChristchurchNew Zealand
  6. 6.Biodiversity Research CentreUniversity of British ColumbiaVancouverCanada
  7. 7.Department of BiologyUniversity of FloridaGainesvilleUSA

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