, Volume 138, Issue 1, pp 1–4 | Cite as

Design and analysis of multiple choice feeding preference data

  • Jeffrey S. Prince
  • W. G. LeBlanc
  • S. Maciá


Traditional analyses of feeding experiments that test consumer preference for an array of foods suffer from several defects. We have modified the experimental design to incorporate into a multivariate analysis the variance due to autogenic change in control replicates. Our design allows the multiple foods to be physically paired with their control counterparts. This physical proximity of the multiple food choices in control/experimental pairs ensures that the variance attributable to external environmental factors jointly affects all combinations within each replicate. Our variance term, therefore, is not a contrived estimate as is the case for the random pairing strategy proposed by previous studies. The statistical analysis then proceeds using standard multivariate statistical tests. We conducted a multiple choice feeding experiment using our experimental design and utilized a Monte Carlo analysis to compare our results with those obtained from an experimental design that employed the random pairing strategy. Our experimental design allowed detection of moderate differences among feeding means when the random design did not.


Feeding preference Hotelling’s T2 


  1. Carpenter RC (1986) Partitioning herbivory and its effects on coral reef algal communities. Ecol Monogr 56:345–363Google Scholar
  2. Coen LD, Tanner CE (1989) Morphological variation and differential susceptibility to herbivory in the tropical brown alga Lobophora variegata. Mar Ecol Prog Ser 54:287–298Google Scholar
  3. Hay ME (1981) Herbivory, algal distribution and the maintenance of between-habitat diversity on a tropical fringing reef. Am Nat 118:520–540CrossRefGoogle Scholar
  4. Lewis SM (1986) The role of herbivorous fishes in the organization of a Caribbean reef community. Ecol Monogr 56:183–200Google Scholar
  5. Littell RC, Freund RJ, Spector PC (1991) SAS system for linear models, 3rd edn. SAS Institute, Cary, N.C.Google Scholar
  6. Manly BFJ (1993) Comments on the design and analysis of multiple-choice feeding-preference experiments. Oecologia 93:149–152Google Scholar
  7. Peterson CH, Renaud PE (1989) Analysis of feeding preference experiments. Oecologia 80:82–86Google Scholar
  8. Prince JS, LeBlanc WG (1992) Comparative feeding preference of Strongylocentrotus droebachiensis (Echinoidea) for the invasive seaweed Codium fragile ssp. tomentosoides (Chlorophyta) and four other seaweeds. Mar Biol 113:159–163Google Scholar
  9. Roa R (1992) Design and analysis of multiple-choice feeding-preference experiments. Oecologia 89:509–515Google Scholar
  10. Ryther JH, Dunstan WM (1971) Nitrogen, phosphorus and eutrophication in the coastal marine environment. Science 171:1008–1013PubMedGoogle Scholar
  11. SAS (1989) SAS/STAT User’s Guide, Version 6, 4th edn, vol 2. SAS Institute, Cary, N.C.Google Scholar
  12. Schiel DR (1982) Selective feeding by the echinoid, Evechinus choroticus , and the removal by plants from subtidal algal stands in northern New Zealand. Oecologia 54:379–388Google Scholar
  13. Yao Y (1965) An approximate degrees of freedom solution to the multivariate Behrens-Fisher problem. Biometrika 52:139–147Google Scholar

Copyright information

© Springer-Verlag 2003

Authors and Affiliations

  1. 1.Department of BiologyThe University of MiamiCoral GablesUSA
  2. 2.Department of Institutional ResearchValencia Community CollegeOrlandoUSA
  3. 3. Marine LaboratoryHofstra UniversitySt. Ann’s BayJamaica, West Indies

Personalised recommendations