Verifying Small Sample Bootstrap Estimates of Species Interactions

  • Robert W. Jernigan
  • David C. Culver
Conference paper


Qualms about bootstrap confidence intervals have led to the development of new techniques with the added complexities of bias estimation and acceleration constants. These complications make the current theory appear almost Ptolemaic to the uninformed. Furthermore, bootstrap estimates based on small samples must be interpreted with caution. It seems prudent and advisable to look at other analyses to, at least partially, verify bootstrap results in small samples. Here, we analyze using the bootstrap and traditional nonparametric and parametric tests the results of a small scale perturbation experiment in ecological research to assess the importance of the interspecific interactions of competition, prédation, and mutualism.


Species Interaction Washout Rate Interspecific Interaction Bootstrap Estimate Bootstrap Confidence Interval 
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  1. Culver, D.C., Fong, D.W. and Jernigan, R.W.(1990) Assessing species interactions in cave communities, preliminary report.Google Scholar
  2. Efron, B. and Tibshirani, R.(1986) Bootstrap methods for standard errors, confidence intervals, and other measures of statistical accuracy, Statistical Science, 1, 54–77.MathSciNetCrossRefGoogle Scholar
  3. Felsenstein, J.(1986) Discussion [of Wu(1986)], Ann. Statist. 14, 1304–1305.CrossRefGoogle Scholar
  4. Hall, P.(1988). Theoretical comparison of bootstrap confidence intervals. Ann. Statist. 16, 927–953.MathSciNetMATHCrossRefGoogle Scholar
  5. Marasculio, L.A. and McSweeney, M. (1967) Nonparametric post hoc comparisons for trend, Psy. Bull. 67, 401–412.CrossRefGoogle Scholar
  6. Romano, J.P.(1989) Bootstrap and randomization tests of some nonparametric hypotheses, Ann. Statist. 17, 141–159.MathSciNetMATHCrossRefGoogle Scholar
  7. Schenker, N.(1985). Qualms about bootstrap confidence intervals. JASA, 80, 360–361.MathSciNetGoogle Scholar
  8. Wu, C.F.J.(1986). Jackknife, bootstrap and other resampling methods in regression analysis. Ann. Statist. 14, 1261–1295.MathSciNetMATHCrossRefGoogle Scholar

Copyright information

© Springer-Verlag New York, Inc. 1992

Authors and Affiliations

  • Robert W. Jernigan
    • 1
  • David C. Culver
    • 2
  1. 1.Department of Mathematics and StatisticsThe American UniversityUSA
  2. 2.Department of BiologyThe American UniversityUSA

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