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HYPOTHESIS TESTING WITH THE SIMILARITY INDEX
Citation:
Leonard, A. C., S E. Franson, V. S. Hertzberg, M K. Smith, AND G P. Toth. HYPOTHESIS TESTING WITH THE SIMILARITY INDEX. MOLECULAR ECOLOGY 8(12):2105-2114, (1999).
Impact/Purpose:
The objective of this task is to develop molecular indicators to evaluate the integrity and sustainability of aquatic fish, invertebrate, and plant communities (GPRA goal 4.5.2). Specifically, this subtask aims to evaluate methods for the measurement of:
fish and invertebrate community composition, especially for morphologically indistinct (cryptic) species
population genetic structure of aquatic indicator species and its relationship to landscape determinants of population structure (to aid in defining natural assessment units and to allow correlation of population substructure with regional stressor coverages)
genetic diversity within populations of aquatic indicator species, as an indicator of vulnerability to further exposure and as an indicator of cumulative exposure
patterns of temporal change in genetic diversity of aquatic indicator species, as a monitoring tool for establishing long-term population trends.
Description:
Mulltilocus DNA fingerprinting methods have been used extensively to address genetic issues in wildlife populations. Hypotheses concerning population subdivision and differing levels of diversity can be addressed through the use of the similarity index (S), a band-sharing coefficient, and many researchers construct hypothesis tests with S based on the work of Lynch. It is shown in the present study, through mathematical analysis and through simulations, that estimates of the variance of a mean S based on Lynch's work are downwardly biased. An unbiased alternative is presented and mathematically justified. It is shown further, however, that even when the bias in Lynch's estimator is corrected, the estimator is highly imprecise compared with estimates based on an alternative approach such as "parametric bootstrapping" of allele frequencies. Also discussed are permutation tests and their construction given the interdependence of Ss which share individuals. A simulation illustrates how some published misuses of these tests can lead to incorrect conclusions in hypothesis testing.