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Adequacy of sample size for estimating a value from field observational data
Citation:
Cormier, S., G. Suter, M. Fernandez, AND L. Zhang. Adequacy of sample size for estimating a value from field observational data. ECOTOXICOLOGY AND ENVIRONMENTAL SAFETY. Elsevier Science Ltd, New York, NY, 203:110992, (2020). https://doi.org/10.1016/j.ecoenv.2020.110992
Impact/Purpose:
This paper concerns the validation of empirical models. It demonstrates a technique for evaluating whether sample sizes of individual taxa are adequate for modeling a community response. Along with other methods, this demonstrates a simple but useful check of data suitability for model development. The statistical approach may be useful for resource managers who need to evaluate data suitability.
Description:
In 2011, the U.S. EPA Office of Research and Development released a field-based method for deriving aquatic life benchmarks for conductivity. Since its release, it has been verified, validated, and corroborated by the authors, reviewers, and independent researchers. However, the method and published results have been recently challenged as being artifacts of small sample sizes, prompting this re-evaluation. This paper supplements prior causal analyses by weighing evidence that specifically addresses the hypothesis that the benchmark is a statistical artifact. Four types of evidence are presented: (1) Permutation analyses show that the data sets are able to reliably estimate the extirpation of 5% of genera. (2) Analyses show that 25 occurrences of a genus are sufficient to estimate extirpation. (3) Coherent ecological explanations show that the claimed influence of sample size is actually a result of community ecology. (4) A review of relevant independent studies supports the benchmark. The permutation test is a useful test of the adequacy of field data sets. Furthermore, this weight-of-evidence approach and the individual types of evidence can be a model for analysis of other field-based benchmark values.
URLs/Downloads:
DOI: Adequacy of sample size for estimating a value from field observational data
https://pubmed.ncbi.nlm.nih.gov/32771767/