Reexamining Sample Size Requirements for Multivariate, Abundance-Based Community Research: When Resources are Limited, the Research Does Not Have to Be

Community ecologists commonly perform multivariate techniques (e.g., ordination, cluster analysis) to assess patterns and gradients of taxonomic variation. A critical requirement for a meaningful statistical analysis is accurate information on the taxa found within an ecological sample. However, ove...

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Bibliographic Details
Published in:PloS one 2015-06, Vol.10 (6), p.e0128379-e0128379
Main Authors: Forcino, Frank L, Leighton, Lindsey R, Twerdy, Pamela, Cahill, James F
Format: Article
Language:English
Subjects:
Abundance
Atmospheric sciences
Carabidae
Cluster analysis
Communities
Community ecology
Community-Based Participatory Research
Databases as Topic
Datasets
Earth science
Ecological effects
Ecological monitoring
Ecological research
Ecologists
Ecology
Expeditions
Fisheries
Health Resources
Mathematical analysis
Multivariate Analysis
Normal distribution
Ordination
Oversampling
Parasites
Research Design
Research projects
Researchers
Resource availability
Sample Size
Snow
Statistical analysis
Statistical methods
Statistics
Taxa
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Summary:Community ecologists commonly perform multivariate techniques (e.g., ordination, cluster analysis) to assess patterns and gradients of taxonomic variation. A critical requirement for a meaningful statistical analysis is accurate information on the taxa found within an ecological sample. However, oversampling (too many individuals counted per sample) also comes at a cost, particularly for ecological systems in which identification and quantification is substantially more resource consuming than the field expedition itself. In such systems, an increasingly larger sample size will eventually result in diminishing returns in improving any pattern or gradient revealed by the data, but will also lead to continually increasing costs. Here, we examine 396 datasets: 44 previously published and 352 created datasets. Using meta-analytic and simulation-based approaches, the research within the present paper seeks (1) to determine minimal sample sizes required to produce robust multivariate statistical results when conducting abundance-based, community ecology research. Furthermore, we seek (2) to determine the dataset parameters (i.e., evenness, number of taxa, number of samples) that require larger sample sizes, regardless of resource availability. We found that in the 44 previously published and the 220 created datasets with randomly chosen abundances, a conservative estimate of a sample size of 58 produced the same multivariate results as all larger sample sizes. However, this minimal number varies as a function of evenness, where increased evenness resulted in increased minimal sample sizes. Sample sizes as small as 58 individuals are sufficient for a broad range of multivariate abundance-based research. In cases when resource availability is the limiting factor for conducting a project (e.g., small university, time to conduct the research project), statistically viable results can still be obtained with less of an investment.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0128379