Population Ecology

, Volume 50, Issue 3, pp 319–324

An experimental design and a statistical analysis separating interference from exploitation competition

Forum

Abstract

Previous experimental studies of competition among foragers rarely distinguished between exploitation and interference competition. In many systems this separation is experimentally impossible without interfering with the natural behavior of the animals. Consequently, these studies can only demonstrate the combined effect of interference and exploitation on the forager’s feeding rate, namely, it usually decreases in a decelerating rate as a function of density. We suggest here a simple experimental and statistical procedure that facilitates the separation of the effects of interference from those of exploitation. This procedure includes manipulation of both predator density and the foraging experiment duration. The statistical analysis is based on multiple linear regression. The working assumption is that exploitation can be neglected at the beginning of the foraging experiment because, initially, predators do not experience diminishing returns in prey capture rates. Using both the results of an individual-based simulation and a field experiment dataset of gerbils foraging for seeds in an artificial food patch located in the field, we demonstrate that our procedure can successfully detect and separate the effect of interference from the combined overall effect of competition (i.e., interference plus exploitation).

Keywords

Functional response Individual based model Searching behavior 

References

  1. Abramsky Z, Rosenzweig ML, Subach A (2001) The cost of interspecific competition in two gerbil species. J Anim Ecol 70:561–567CrossRefGoogle Scholar
  2. Anholt BR (1990) An experimental separation of interference and exploitative competition in a larval damselfly. Ecology 71:1483–1493CrossRefGoogle Scholar
  3. Connell JH (1983) On the prevalence and relative importance of interspecific competition: evidence from field experiments. Am Nat 122:661–696CrossRefGoogle Scholar
  4. DeAngelis DL, Goldstein RA, O’Neil RV (1975) A model for trophic interaction. Ecology 56:881–892CrossRefGoogle Scholar
  5. Gurevitch J, Morrow LL, Wallace A, Walsh JS (1992) A meta-analysis of competition in field experiments. Am Nat 140:539–572CrossRefGoogle Scholar
  6. Gurevitch J, Morrision JA, Hedges LV (2000) The interaction between competition and predation: a meta-analysis of field experiments. Am Nat 155:435–453PubMedCrossRefGoogle Scholar
  7. Hart DD (1987) Experimental studies of exploitative competition in a grazing stream insect. Oecologia 73:41–47CrossRefGoogle Scholar
  8. Huisman G, De Boer RJ (1997) A formal derivation of the “Beddington” functional response. J Theor Biol 185:389–400CrossRefGoogle Scholar
  9. Keddy PA (2001) Competition, 2nd edn. Kluwer, NorwellGoogle Scholar
  10. Lerman K, Galstyan A (2002) Mathematical model of foraging in a group of robots: effect of interference. Auton Robots 13:127–141CrossRefGoogle Scholar
  11. Moody AL, Ruxton GD (1996) The intensity of interference varies with food density: support for behaviour-based models of interference. Oecologia 108:446–449CrossRefGoogle Scholar
  12. Morin PJ (1999) Community ecology. Blackwell, MaldenGoogle Scholar
  13. Neter J, Kutner MH, Nachtsheim CJ, Wasserman W (1996) Applied and linear regression models, 3rd edn. Irwin, ChicagoGoogle Scholar
  14. Nicholls CF, Doxtator EA (1960) An aquarium for maintaining constant prey population densities in studies of predator–prey interactions. J Fish Res Board Can 17:687–688Google Scholar
  15. O’Day DK (2007) Data analysis and visualization with Excel tools and charts. http://processtrends.com/index.htm
  16. Ovadia O, zu Dohna H (2003) The effect of intra- and interspecific aggression on patch residence time in the Negev desert gerbils: a competing risk analysis. Behav Ecol 14:583–591CrossRefGoogle Scholar
  17. Ovadia O, Ziv Y, Abramsky Z, Pinshow B, Kotler BP (2001) Harvest rates and foraging strategies in Negev desert gerbils. Behav Ecol 12:219–226CrossRefGoogle Scholar
  18. Peckarsky BL (1991) Mechanisms of intra- and interspecific interference between larval stoneflies. Oecologia 85:521–529CrossRefGoogle Scholar
  19. Schoener TW (1983) Field experiments on interspecific competition. Am Nat 122:240–285CrossRefGoogle Scholar
  20. Smallegange IM, Van der Meer J, Kurvers RHJM (2006) Disentangling interference competition from exploitative competition in a crab-bivalve system using a novel experimental approach. Oikos 113:157–167CrossRefGoogle Scholar
  21. Stillman RA, Goss-Custard JD, Clarke RT, Durell SEALD (1996) Shape of interference function in a foraging vertebrate. J Anim Ecol 65:813–824CrossRefGoogle Scholar
  22. Stillman RA, Goss-Custard JD, Caldow RWG (1997) Modelling interference from basic foraging behaviour. J Anim Ecol 66:692–703CrossRefGoogle Scholar
  23. Sutherland WJ, Koene P (1982) Field estimates of the strength of interference between oystercatchers Haermatopus ostralegus. Oecologia 55:108–109CrossRefGoogle Scholar
  24. Tilman D (1987) The importance of the mechanisms of interspecific competition. Am Nat 129:769–774CrossRefGoogle Scholar
  25. Vahl WK, Van der Meer J, Weissing FJ, Van Dullemen D, Piersma T (2005) The mechanisms of interference competition: two experiments on foraging waders. Behav Ecol 16:845–855CrossRefGoogle Scholar
  26. Van der Meer J, Ens BJ (1997) Models of interference and their consequences for the spatial distribution of ideal and free predators. J Anim Ecol 66:846–858CrossRefGoogle Scholar
  27. Wootton JT (1994) Predicting direct and indirect effects: an integrated approach using experiments and path analysis. Ecology 75:151–165CrossRefGoogle Scholar

Copyright information

© The Society of Population Ecology and Springer 2008

Authors and Affiliations

  1. 1.Department of Life SciencesBen-Gurion University of the NegevBeer-ShevaIsrael

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