, Volume 701, Issue 1, pp 159–172 | Cite as

Do productivity and disturbance interact to modulate macroinvertebrate diversity in streams?

  • Jonathan D. Tonkin
  • Russell G. Death
  • Kevin J. Collier
Primary Research Paper


Although disturbance and productivity are clearly strong influences on lotic diversity, rarely have their interactive effects been studied in running water systems. We hypothesised that the presence or absence of canopy cover in streams would alter productivity–disturbance–diversity relationships due to differential effects on the food base, and tested this hypothesis in 47 mountain streams in the central North Island of New Zealand. Canopy cover had no influence on algal biomass in these streams, but a link between disturbance and productivity was found in open canopy streams where taxonomic richness of invertebrates increased log-linearly with increasing algal biomass and peaked at intermediate levels of disturbance. Community evenness declined with disturbance, but only at closed canopy sites where both invertebrate taxonomic richness and Simpson’s diversity index were higher. Although there was a peak in richness at intermediate rates of disturbance, our results do not directly match predictions of the dynamic equilibrium model which predicts that the level of disturbance maximising diversity interacts with habitat productivity. Rather, we suggest the combined effects of productivity and disturbance are additive rather than multiplicative such that productivity simply sets the upper limit to richness in streams.


Dynamic equilibrium model Trade-off Intermediate disturbance hypothesis Richness Canopy cover 



We are grateful to Keith Wood at Ernslaw One Limited for access to Karioi Forest sites. We are also grateful to Roger Tonkin, Amber McEwan, Nicki Atkinson, Manas Chakraborty, Robert Charles, Logan Brown, and Alana Lawrence for assistance in the field. Michel Dedual, Glenn Mclean and Mike Joy provided logistical support during the site selection and fieldwork stages. Thanks to Jane Tonkin for reviewing a draft copy of this manuscript. Angus McIntosh, Ian Henderson and Christopher Robinson provided useful comments to improve this manuscript. Massey University Doctoral Scholarship supported JDT during the study.


  1. Abrams, P. A., 1995. Monotonic or unimodal diversity productivity gradients—What does competition theory predict. Ecology 76: 2019–2027.CrossRefGoogle Scholar
  2. Akaike, H., 1974. New look at statistical-model identification. IEEE Transactions on Automatic Control AC19: 716–723.Google Scholar
  3. Allan, J. D., 1995. Stream Ecology: Structure and Function of Running Waters. Chapman and Hall, London.Google Scholar
  4. Barquin, J., 2004. Spatial patterns of invertebrate communities in spring and runoff-fed streams. PhD thesis, Massey University, New Zealand.Google Scholar
  5. Barquin, J. & R. G. Death, 2006. Spatial patterns of macroinvertebrate diversity in New Zealand springbrooks and rhithral streams. Journal of the North American Benthological Society 25: 768–786.CrossRefGoogle Scholar
  6. Cadotte, M. W., 2007. Competition-colonization trade-offs and disturbance effects at multiple scales. Ecology 88: 823–829.PubMedCrossRefGoogle Scholar
  7. Cardinale, B. J., H. Hillebrand & D. F. Charles, 2006. Geographic patterns of diversity in streams are predicted by a multivariate model of disturbance and productivity. Journal of Ecology 94: 609–618.CrossRefGoogle Scholar
  8. Chase, J. M. & M. A. Leibold, 2002. Spatial scale dictates the productivity–biodiversity relationship. Nature 416: 427–430.PubMedCrossRefGoogle Scholar
  9. Chesson, P. & N. Huntly, 1997. The roles of harsh and fluctuating conditions in the dynamics of ecological communities. The American Naturalist 150: 519–553.PubMedCrossRefGoogle Scholar
  10. Clarke, K. R., 1993. Nonparametric multivariate analyses of changes in community structure. Australian Journal of Ecology 18: 117–143.CrossRefGoogle Scholar
  11. Clarke, K. R. & R. N. Gorley, 2006. PRIMER v6: User Manual/Tutorial. PRIMER-E, Plymouth.Google Scholar
  12. Connell, J. H., 1978. Diversity in tropical rain forests and coral reefs. Science 199: 1302–1310.PubMedCrossRefGoogle Scholar
  13. Currie, D. J., 1991. Energy and large-scale patterns of animal-species and plant-species richness. American Naturalist 137: 27–49.CrossRefGoogle Scholar
  14. Death, R. G., 2002. Predicting invertebrate diversity from disturbance regimes in forest streams. Oikos 97: 18–30.CrossRefGoogle Scholar
  15. Death, R. G., 2010. Disturbance and riverine benthic communities: what has it contributed to general ecological theory? River Research and Applications 26: 15–25.CrossRefGoogle Scholar
  16. Death, R. G. & M. J. Winterbourn, 1994. Environmental stability and community persistence: a multivariate perspective. Journal of the North American Benthological Society 13: 125–139.CrossRefGoogle Scholar
  17. Death, R. G. & M. J. Winterbourn, 1995. Diversity patterns in stream benthic invertebrate communities: the influence of habitat stability. Ecology 76: 1446–1460.CrossRefGoogle Scholar
  18. Death, R. G. & E. M. Zimmermann, 2005. Interaction between disturbance and primary productivity in determining stream invertebrate diversity. Oikos 111: 392–402.CrossRefGoogle Scholar
  19. Fuller, R. L., C. LaFave, M. Anastasi, J. Molina, H. Salcedo & S. Ward, 2008. The role of canopy cover on the recovery of periphyton and macroinvertebrate communities after a month-long flood. Hydrobiologia 598: 47–57.CrossRefGoogle Scholar
  20. Gafner, K. & C. T. Robinson, 2007. Nutrient enrichment influences the responses of stream macroinvertebrates to disturbance. Journal of the North American Benthological Society 26: 92–102.CrossRefGoogle Scholar
  21. Graham, A. A., D. J. McCaughan & F. S. McKee, 1988. Measurement of surface area of stones. Hydrobiologia 157: 85–87.CrossRefGoogle Scholar
  22. Grime, J. P., 1973. Control of species density in herbaceous vegetation. Journal of Environmental Management 1: 151–167.Google Scholar
  23. Haddad, N. M., M. Holyoak, T. M. Mata, K. F. Davies, B. A. Melbourne & K. Preston, 2008. Species' traits predict the effects of disturbance and productivity on diversity. Ecology Letters 11: 348–356.Google Scholar
  24. Hastings, A., 1980. Disturbance, coexistence, history, and competition for space. Theoretical Population Biology 18: 363–373.CrossRefGoogle Scholar
  25. Hubbell, S. P., 2001. The Unified Neutral Theory of Biodiversity and Biogeography. Princeton University Press, Princeton, NJ.Google Scholar
  26. Huston, M., 1979. A general hypothesis of species diversity. The American Naturalist 113: 81–100.CrossRefGoogle Scholar
  27. Huston, M., 1994. Biological Diversity: The Coexistence of Species on Changing Landscapes. Cambridge University Press, Cambridge.Google Scholar
  28. Koenker, R., 2011. quantreg: Quantile Regression. R package version 4.71.Google Scholar
  29. Kondoh, M., 2001. Unifying the relationships of species richness to productivity and disturbance. Proceedings of the Royal Society of London Series B-Biological Sciences 268: 269–271.CrossRefGoogle Scholar
  30. Lake, P. S., 2000. Disturbance, patchiness, and diversity in streams. Journal of the North American Benthological Society 19: 573–592.CrossRefGoogle Scholar
  31. Mackay, R. J., 1992. Colonization by lotic macroinvertebrates—a review of processes and patterns. Canadian Journal of Fisheries and Aquatic Sciences 49: 617–628.CrossRefGoogle Scholar
  32. Mackey, R. L. & D. J. Currie, 2001. The diversity–disturbance relationship: is it generally strong and peaked? Ecology 82: 3479–3492.Google Scholar
  33. Magurran, A. E., 2004. Measuring Biological Diversity. Blackwell Science Ltd., Oxford.Google Scholar
  34. Milner, A. M. & G. E. Petts, 1994. Glacial rivers—physical habitat and ecology. Freshwater Biology 32: 295–307.CrossRefGoogle Scholar
  35. Mitchell-Olds, T. & R. G. Shaw, 1987. Regression analysis of natural selection: statistical inference and biological interpretation. Evolution 41: 1149–1161.CrossRefGoogle Scholar
  36. Mittelbach, G. G., C. F. Steiner, S. M. Scheiner, K. L. Gross, H. L. Reynolds, R. B. Waide, M. R. Willig, S. I. Dodson & L. Gough, 2001. What is the observed relationship between species richness and productivity? Ecology 82: 2381–2396.CrossRefGoogle Scholar
  37. Morin, A., W. Lamourex & J. Busnarda, 1999. Empirical models predicting primary productivity from chlorophyll a and water temperature for stream periphyton and lake and ocean phytoplankton. Journal of the North American Benthological Society 18: 299–307.CrossRefGoogle Scholar
  38. Oksanen, J., F. G. Blanchet, R. Kindt, P. Legendre, P. R. Minchin, R. B. O’Hara, G. L. Simpson, P. Solymos, M. Henry, H. Stevens & H. Wagner, 2011. Vegan: Community Ecology Package. R package version 2.0-1.Google Scholar
  39. Pfankuch, D., 1975. Stream Reach Inventory and Channel Stability Evaluation. USDA Forest Service Region 1, Missoula, Montana.Google Scholar
  40. Quinn, G. P. & M. Keogh, 2002. Experimental Design and Data Analysis for Biologists. Cambridge University Press, Cambridge.CrossRefGoogle Scholar
  41. R Development Core Team, 2011. R: A Language and Environment for Statistical Computing. R Foundation of Statistical Computing, Vienna, Austria.Google Scholar
  42. Resh, V. H., A. V. Brown, A. P. Covich, M. E. Gurtz, H. W. Li, G. W. Minshall, S. R. Reice, A. L. Sheldon, J. B. Wallace & R. C. Wissmar, 1988. The role of disturbance in stream ecology. Journal of the North American Benthological Society 7: 433–455.CrossRefGoogle Scholar
  43. Robinson, C. T. & G. W. Minshall, 1986. Effects of disturbance frequency on stream benthic community structure in relation to canopy cover and season. Journal of the North American Benthological Society 5: 237–248.CrossRefGoogle Scholar
  44. Rosenzweig, M. L., 1995. Species Diversity in Space and Time. Cambridge University Press, Cambridge.CrossRefGoogle Scholar
  45. Rosenzweig, M. L. & Z. Abramsky, 1993. How are diversity and productivity related? In Ricklefs, R. E. & D. Schluter (eds), Species Diversity in Biological Communities. University of Chicago Press, Chicago, IL: 52–65.Google Scholar
  46. Roxburgh, S. H., K. Shea & J. B. Wilson, 2004. The intermediate disturbance hypothesis: patch dynamics and mechanisms of species coexistence. Ecology 85: 359–371.CrossRefGoogle Scholar
  47. Scholes, L., P. H. Warren & A. P. Beckerman, 2005. The combined effects of energy and disturbance on species richness in protist microcosms. Ecology Letters 8: 730–738.CrossRefGoogle Scholar
  48. Scrimgeour, G. J. & M. J. Winterbourn, 1989. Effects of floods on epilithon and benthic macroinvertebrate populations in an unstable New Zealand river. Hydrobiologia 171: 33–44.CrossRefGoogle Scholar
  49. Simpson, E. H., 1949. Measurement of diversity. Nature 163: 688.CrossRefGoogle Scholar
  50. Sousa, W. P., 1979. Disturbance in marine intertidal boulder fields: the nonequilibrium maintenance of species diversity. Ecology 60: 1225–1239.CrossRefGoogle Scholar
  51. Steinman, A. D. & G. A. Lamberti, 1996. Biomass and pigments of benthic algae. In Hauer, F. R. & G. A. Lamberti (eds), Methods in Stream Ecology. Academic Press, San Diego, CA: 295–314.Google Scholar
  52. Steinman, A. D., P. J. Mulholland, A. V. Palumbo, T. F. Flum, J. W. Elwood & D. L. Deangelis, 1990. Resistance of lotic ecosystems to a light elimination disturbance—a laboratory stream study. Oikos 58: 80–90.CrossRefGoogle Scholar
  53. Svensson, J. R., M. Lindegarth, M. Siccha, M. Lenz, M. Molis, M. Wahl & H. Pavia, 2007. Maximum species richness at intermediate frequencies of disturbance: Consistency among levels of productivity. Ecology 88: 830–838.Google Scholar
  54. Tilman, D., 1994. Competition and biodiversity in spatially structured habitats. Ecology 75: 2–16.CrossRefGoogle Scholar
  55. Tonkin, J. D., 2011. The effects of productivity and disturbance on diversity in stream communities. PhD thesis, Massey University, New Zealand.Google Scholar
  56. Towns, D. R. & W. L. Peters, 1996. Leptophlebiidae (Insecta: Ephemeroptera), Vol. 36. Manaaki Whenua Press, Lincoln, New Zealand.Google Scholar
  57. Townsend, C. R., M. R. Scarsbrook & S. Doledec, 1997. The intermediate disturbance hypothesis, refugia, and biodiversity in streams. Limnology and Oceanography 42: 938–949.CrossRefGoogle Scholar
  58. Winterbourn, M. J., 1990. Interactions among nutrients, algae and invertebrates in a New Zealand mountain stream. Freshwater Biology 23: 463–474.CrossRefGoogle Scholar
  59. Winterbourn, M. J., 1997. New Zealand mountain stream communities: stable yet disturbed? In Streit, B., T. Stadler & C. M. Lively (eds), Evolutionary Ecology of Freshwater Animals. Birkhauser Verlag, Basel: 31–54.CrossRefGoogle Scholar
  60. Winterbourn, M. J. & K. J. Collier, 1987. Distribution of benthic invertebrates in acid, brown water streams in the South Island of New Zealand. Hydrobiologia 153: 277–286.CrossRefGoogle Scholar
  61. Winterbourn, M. J., J. S. Rounick & B. Cowie, 1981. Are New Zealand stream ecosystems really different? New Zealand Journal of Marine and Freshwater Research 15: 321–328.CrossRefGoogle Scholar
  62. Winterbourn, M. J., K. L. D. Gregson & C. H. Dolphin, 2000. Guide to the aquatic insects of New Zealand. Entomological Society of New Zealand, Auckland.Google Scholar
  63. Wolman, M. J., 1954. A method of sampling coarse river bed material. Transactions of the American Geophysical Union 35: 951–956.Google Scholar
  64. Wootton, J. T., 1998. Effects of disturbance on species diversity: a multitrophic perspective. American Naturalist 152: 803–825.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media B.V. 2012

Authors and Affiliations

  • Jonathan D. Tonkin
    • 1
    • 4
  • Russell G. Death
    • 1
  • Kevin J. Collier
    • 2
    • 3
  1. 1.Institute of Natural Resources – Ecology (PN-624)Massey UniversityPalmerston NorthNew Zealand
  2. 2.Centre for Biodiversity and Ecology Research, Department of Biological Sciences, School of Science and EngineeringUniversity of WaikatoHamiltonNew Zealand
  3. 3.Waikato Regional CouncilHamiltonNew Zealand
  4. 4.Department of Marine and Environmental ManagementBay of Plenty PolytechnicTaurangaNew Zealand

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