Rapid bioassessment protocols (RBP) have been used widely to assess and compare benthic macro invertebrate communities, often in the context of determining impacts from impairments to water quality. Given that a relatively small sample of 100 organisms often was used to calculate various biological metrics, the question of how frequently differences are inferred when in fact the subsamples are from the same population (i.e., Type 1 errors) is of interest. The analysis of 72 large (300-1760 organism) field samples uses the differentiation criteria recommended in the first edition of EPA' s RBP 1989 guidance manual as a case example. A minimum of 100 subsamples each of 100 organisms was used to evaluate the uncertainty of metric estimates. Variability in estimates of Community Loss, Similarity (R-Ratio), Jaccard, Sorensen, Bray-Curtis Similarity indicies, and Bray-Curtis Dissimilarity as well as Diversity and Evenness also are presented. Decision criteria for judging two samples are from different parent distributions are provided for each metric at alpha= 0.15 for Type 1 errors. The proposed decision criteria are based on pooling all of the estimates of a given metric using the entirety of the calculated values of that metric derived from all subsamples of the 72 field samples. The findings demonstrate the need to vet current and potential ecological numerical metrics, for variability when estimating their values from subsamples.
Published in | International Journal of Environmental Monitoring and Analysis (Volume 10, Issue 5) |
DOI | 10.11648/j.ijema.20221005.13 |
Page(s) | 127-139 |
Creative Commons |
This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited. |
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Copyright © The Author(s), 2022. Published by Science Publishing Group |
Macroinvertebrate Indicies, Ecological Indicies, Community Loss Index, Type 1 Errors in Indicies, Jaccard, Sorensen, Bray-Curtis Similarity Indicies, Proposed Criteria
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APA Style
Russell Anthony Isaac, James Heltshe. (2022). Variation of Subsample Estimates of Selected Benthic Macroinvertebrate Mathematical Indices: Retrospective Analysis and Proposed Criteria. International Journal of Environmental Monitoring and Analysis, 10(5), 127-139. https://doi.org/10.11648/j.ijema.20221005.13
ACS Style
Russell Anthony Isaac; James Heltshe. Variation of Subsample Estimates of Selected Benthic Macroinvertebrate Mathematical Indices: Retrospective Analysis and Proposed Criteria. Int. J. Environ. Monit. Anal. 2022, 10(5), 127-139. doi: 10.11648/j.ijema.20221005.13
@article{10.11648/j.ijema.20221005.13, author = {Russell Anthony Isaac and James Heltshe}, title = {Variation of Subsample Estimates of Selected Benthic Macroinvertebrate Mathematical Indices: Retrospective Analysis and Proposed Criteria}, journal = {International Journal of Environmental Monitoring and Analysis}, volume = {10}, number = {5}, pages = {127-139}, doi = {10.11648/j.ijema.20221005.13}, url = {https://doi.org/10.11648/j.ijema.20221005.13}, eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijema.20221005.13}, abstract = {Rapid bioassessment protocols (RBP) have been used widely to assess and compare benthic macro invertebrate communities, often in the context of determining impacts from impairments to water quality. Given that a relatively small sample of 100 organisms often was used to calculate various biological metrics, the question of how frequently differences are inferred when in fact the subsamples are from the same population (i.e., Type 1 errors) is of interest. The analysis of 72 large (300-1760 organism) field samples uses the differentiation criteria recommended in the first edition of EPA' s RBP 1989 guidance manual as a case example. A minimum of 100 subsamples each of 100 organisms was used to evaluate the uncertainty of metric estimates. Variability in estimates of Community Loss, Similarity (R-Ratio), Jaccard, Sorensen, Bray-Curtis Similarity indicies, and Bray-Curtis Dissimilarity as well as Diversity and Evenness also are presented. Decision criteria for judging two samples are from different parent distributions are provided for each metric at alpha= 0.15 for Type 1 errors. The proposed decision criteria are based on pooling all of the estimates of a given metric using the entirety of the calculated values of that metric derived from all subsamples of the 72 field samples. The findings demonstrate the need to vet current and potential ecological numerical metrics, for variability when estimating their values from subsamples.}, year = {2022} }
TY - JOUR T1 - Variation of Subsample Estimates of Selected Benthic Macroinvertebrate Mathematical Indices: Retrospective Analysis and Proposed Criteria AU - Russell Anthony Isaac AU - James Heltshe Y1 - 2022/10/17 PY - 2022 N1 - https://doi.org/10.11648/j.ijema.20221005.13 DO - 10.11648/j.ijema.20221005.13 T2 - International Journal of Environmental Monitoring and Analysis JF - International Journal of Environmental Monitoring and Analysis JO - International Journal of Environmental Monitoring and Analysis SP - 127 EP - 139 PB - Science Publishing Group SN - 2328-7667 UR - https://doi.org/10.11648/j.ijema.20221005.13 AB - Rapid bioassessment protocols (RBP) have been used widely to assess and compare benthic macro invertebrate communities, often in the context of determining impacts from impairments to water quality. Given that a relatively small sample of 100 organisms often was used to calculate various biological metrics, the question of how frequently differences are inferred when in fact the subsamples are from the same population (i.e., Type 1 errors) is of interest. The analysis of 72 large (300-1760 organism) field samples uses the differentiation criteria recommended in the first edition of EPA' s RBP 1989 guidance manual as a case example. A minimum of 100 subsamples each of 100 organisms was used to evaluate the uncertainty of metric estimates. Variability in estimates of Community Loss, Similarity (R-Ratio), Jaccard, Sorensen, Bray-Curtis Similarity indicies, and Bray-Curtis Dissimilarity as well as Diversity and Evenness also are presented. Decision criteria for judging two samples are from different parent distributions are provided for each metric at alpha= 0.15 for Type 1 errors. The proposed decision criteria are based on pooling all of the estimates of a given metric using the entirety of the calculated values of that metric derived from all subsamples of the 72 field samples. The findings demonstrate the need to vet current and potential ecological numerical metrics, for variability when estimating their values from subsamples. VL - 10 IS - 5 ER -