Performance of the Standard Cabin Method:Comparison of BEAST Models and Error Rates to Detect Simulated Degradation from Multiple Data Sets

The objective of this study was to evaluate the performance of 3 bioassessment models for reference data sets collected from the Australia Capital Territory (ACT), the Yukon River Basin (YT), and the Laurentian Great Lakes (GL) built following the standard Canadian Aquatic Biomonitoring Network (CAB...

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Published in:Freshwater Science
Main Authors: Strachan, Stephanie A, Reynoldson, Trefor
Format: Article in Journal/Newspaper
Language:English
Published: 2014
Subjects:
Online Access:https://researchprofiles.canberra.edu.au/en/publications/e5e121ef-5910-4ce8-93b6-3a61022a67e6
https://doi.org/10.1086/678948
http://www.scopus.com/inward/record.url?scp=84937577801&partnerID=8YFLogxK
http://www.mendeley.com/research/performance-standard-cabin-method-comparison-beast-models-error-rates-detect-simulated-degradation-m
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spelling ftcanberrauncris:oai:pure.atira.dk:publications/e5e121ef-5910-4ce8-93b6-3a61022a67e6 2023-05-15T18:45:59+02:00 Performance of the Standard Cabin Method:Comparison of BEAST Models and Error Rates to Detect Simulated Degradation from Multiple Data Sets Strachan, Stephanie A Reynoldson, Trefor 2014 https://researchprofiles.canberra.edu.au/en/publications/e5e121ef-5910-4ce8-93b6-3a61022a67e6 https://doi.org/10.1086/678948 http://www.scopus.com/inward/record.url?scp=84937577801&partnerID=8YFLogxK http://www.mendeley.com/research/performance-standard-cabin-method-comparison-beast-models-error-rates-detect-simulated-degradation-m eng eng info:eu-repo/semantics/closedAccess Strachan , S A & Reynoldson , T 2014 , ' Performance of the Standard Cabin Method : Comparison of BEAST Models and Error Rates to Detect Simulated Degradation from Multiple Data Sets ' , Freshwater Science , vol. 33 , no. 4 , pp. 1225-1237 . https://doi.org/10.1086/678948 article 2014 ftcanberrauncris https://doi.org/10.1086/678948 2022-10-31T06:44:55Z The objective of this study was to evaluate the performance of 3 bioassessment models for reference data sets collected from the Australia Capital Territory (ACT), the Yukon River Basin (YT), and the Laurentian Great Lakes (GL) built following the standard Canadian Aquatic Biomonitoring Network (CABIN) method. To evaluate the models, we used validation reference-site data, which were artificially impaired to simulate 3 levels of eutrophication by varying the proportions of sensitive, intermediate, and tolerant taxa. Models correctly classified 56 to 62% of reference sites. Type 1 errors (assessing reference sites as degraded) were high for all data sets and ranged from 30 to 75%, in part because the biological communities of the validation sites extended to or beyond the range of the reference-site data used to build the models. Capturing the full range of ecological variation with adequate sample size is critical for reference-condition approach (RCA)-type models. Type 2 errors (assessing degraded sites as in reference condition) varied greatly among data sets and for each reference group within each data set. Resource managers must carefully consider the risks associated with making errors. Thus, standard methods for quality assurance of assessment models should include simulated data so that error rates and adjusted assessment thresholds can be reported to ensure that degradation can be detected and that undisturbed sites are not mistakenly subjected to unnecessary management action. Article in Journal/Newspaper Yukon river Yukon University of Canberra Research Portal Yukon Freshwater Science 33 4 1225 1237
institution Open Polar
collection University of Canberra Research Portal
op_collection_id ftcanberrauncris
language English
description The objective of this study was to evaluate the performance of 3 bioassessment models for reference data sets collected from the Australia Capital Territory (ACT), the Yukon River Basin (YT), and the Laurentian Great Lakes (GL) built following the standard Canadian Aquatic Biomonitoring Network (CABIN) method. To evaluate the models, we used validation reference-site data, which were artificially impaired to simulate 3 levels of eutrophication by varying the proportions of sensitive, intermediate, and tolerant taxa. Models correctly classified 56 to 62% of reference sites. Type 1 errors (assessing reference sites as degraded) were high for all data sets and ranged from 30 to 75%, in part because the biological communities of the validation sites extended to or beyond the range of the reference-site data used to build the models. Capturing the full range of ecological variation with adequate sample size is critical for reference-condition approach (RCA)-type models. Type 2 errors (assessing degraded sites as in reference condition) varied greatly among data sets and for each reference group within each data set. Resource managers must carefully consider the risks associated with making errors. Thus, standard methods for quality assurance of assessment models should include simulated data so that error rates and adjusted assessment thresholds can be reported to ensure that degradation can be detected and that undisturbed sites are not mistakenly subjected to unnecessary management action.
format Article in Journal/Newspaper
author Strachan, Stephanie A
Reynoldson, Trefor
spellingShingle Strachan, Stephanie A
Reynoldson, Trefor
Performance of the Standard Cabin Method:Comparison of BEAST Models and Error Rates to Detect Simulated Degradation from Multiple Data Sets
author_facet Strachan, Stephanie A
Reynoldson, Trefor
author_sort Strachan, Stephanie A
title Performance of the Standard Cabin Method:Comparison of BEAST Models and Error Rates to Detect Simulated Degradation from Multiple Data Sets
title_short Performance of the Standard Cabin Method:Comparison of BEAST Models and Error Rates to Detect Simulated Degradation from Multiple Data Sets
title_full Performance of the Standard Cabin Method:Comparison of BEAST Models and Error Rates to Detect Simulated Degradation from Multiple Data Sets
title_fullStr Performance of the Standard Cabin Method:Comparison of BEAST Models and Error Rates to Detect Simulated Degradation from Multiple Data Sets
title_full_unstemmed Performance of the Standard Cabin Method:Comparison of BEAST Models and Error Rates to Detect Simulated Degradation from Multiple Data Sets
title_sort performance of the standard cabin method:comparison of beast models and error rates to detect simulated degradation from multiple data sets
publishDate 2014
url https://researchprofiles.canberra.edu.au/en/publications/e5e121ef-5910-4ce8-93b6-3a61022a67e6
https://doi.org/10.1086/678948
http://www.scopus.com/inward/record.url?scp=84937577801&partnerID=8YFLogxK
http://www.mendeley.com/research/performance-standard-cabin-method-comparison-beast-models-error-rates-detect-simulated-degradation-m
geographic Yukon
geographic_facet Yukon
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Yukon
genre_facet Yukon river
Yukon
op_source Strachan , S A & Reynoldson , T 2014 , ' Performance of the Standard Cabin Method : Comparison of BEAST Models and Error Rates to Detect Simulated Degradation from Multiple Data Sets ' , Freshwater Science , vol. 33 , no. 4 , pp. 1225-1237 . https://doi.org/10.1086/678948
op_rights info:eu-repo/semantics/closedAccess
op_doi https://doi.org/10.1086/678948
container_title Freshwater Science
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container_issue 4
container_start_page 1225
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