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Sampling re-design increases power to detect change in the Great Barrier Reef’s inshore water quality

Monitoring programs are fundamental to understanding the state and trend of aquatic ecosystems. Sampling designs are a crucial component of monitoring programs and ensure that measurements evaluate progress toward clearly stated management objectives, which provides a mechanism for adaptive manageme...

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Autores principales: Lloyd-Jones, Luke R., Kuhnert, Petra M., Lawrence, Emma, Lewis, Stephen E., Waterhouse, Jane, Gruber, Renee K., Kroon, Frederieke J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9333274/
https://www.ncbi.nlm.nih.gov/pubmed/35901047
http://dx.doi.org/10.1371/journal.pone.0271930
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author Lloyd-Jones, Luke R.
Kuhnert, Petra M.
Lawrence, Emma
Lewis, Stephen E.
Waterhouse, Jane
Gruber, Renee K.
Kroon, Frederieke J.
author_facet Lloyd-Jones, Luke R.
Kuhnert, Petra M.
Lawrence, Emma
Lewis, Stephen E.
Waterhouse, Jane
Gruber, Renee K.
Kroon, Frederieke J.
author_sort Lloyd-Jones, Luke R.
collection PubMed
description Monitoring programs are fundamental to understanding the state and trend of aquatic ecosystems. Sampling designs are a crucial component of monitoring programs and ensure that measurements evaluate progress toward clearly stated management objectives, which provides a mechanism for adaptive management. Here, we use a well-established marine monitoring program for inshore water quality in the Great Barrier Reef (GBR), Australia to investigate whether a sampling re-design has increased the program’s capacity to meet its primary objectives. Specifically, we use bootstrap resampling to assess the change in statistical power to detect temporal water quality trends in a 15-year inshore marine water quality data set that includes data from both before and after the sampling re-design. We perform a comprehensive power analysis for six water quality analytes at four separate study areas in the GBR Marine Park and find that the sampling re-design (i) increased power to detect trends in 23 of the 24 analyte-study area combinations, and (ii) resulted in an average increase in power of 34% to detect increasing or decreasing trends in water quality analytes. This increase in power is attributed more to the addition of sampling locations than increasing the sampling rate. Therefore, the sampling re-design has substantially increased the capacity of the program to detect temporal trends in inshore marine water quality. Further improvements in sampling design need to focus on the program’s capability to reliably detect trends within realistic timeframes where inshore improvements to water quality can be expected to occur.
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spelling pubmed-93332742022-07-29 Sampling re-design increases power to detect change in the Great Barrier Reef’s inshore water quality Lloyd-Jones, Luke R. Kuhnert, Petra M. Lawrence, Emma Lewis, Stephen E. Waterhouse, Jane Gruber, Renee K. Kroon, Frederieke J. PLoS One Research Article Monitoring programs are fundamental to understanding the state and trend of aquatic ecosystems. Sampling designs are a crucial component of monitoring programs and ensure that measurements evaluate progress toward clearly stated management objectives, which provides a mechanism for adaptive management. Here, we use a well-established marine monitoring program for inshore water quality in the Great Barrier Reef (GBR), Australia to investigate whether a sampling re-design has increased the program’s capacity to meet its primary objectives. Specifically, we use bootstrap resampling to assess the change in statistical power to detect temporal water quality trends in a 15-year inshore marine water quality data set that includes data from both before and after the sampling re-design. We perform a comprehensive power analysis for six water quality analytes at four separate study areas in the GBR Marine Park and find that the sampling re-design (i) increased power to detect trends in 23 of the 24 analyte-study area combinations, and (ii) resulted in an average increase in power of 34% to detect increasing or decreasing trends in water quality analytes. This increase in power is attributed more to the addition of sampling locations than increasing the sampling rate. Therefore, the sampling re-design has substantially increased the capacity of the program to detect temporal trends in inshore marine water quality. Further improvements in sampling design need to focus on the program’s capability to reliably detect trends within realistic timeframes where inshore improvements to water quality can be expected to occur. Public Library of Science 2022-07-28 /pmc/articles/PMC9333274/ /pubmed/35901047 http://dx.doi.org/10.1371/journal.pone.0271930 Text en © 2022 Lloyd-Jones et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lloyd-Jones, Luke R.
Kuhnert, Petra M.
Lawrence, Emma
Lewis, Stephen E.
Waterhouse, Jane
Gruber, Renee K.
Kroon, Frederieke J.
Sampling re-design increases power to detect change in the Great Barrier Reef’s inshore water quality
title Sampling re-design increases power to detect change in the Great Barrier Reef’s inshore water quality
title_full Sampling re-design increases power to detect change in the Great Barrier Reef’s inshore water quality
title_fullStr Sampling re-design increases power to detect change in the Great Barrier Reef’s inshore water quality
title_full_unstemmed Sampling re-design increases power to detect change in the Great Barrier Reef’s inshore water quality
title_short Sampling re-design increases power to detect change in the Great Barrier Reef’s inshore water quality
title_sort sampling re-design increases power to detect change in the great barrier reef’s inshore water quality
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9333274/
https://www.ncbi.nlm.nih.gov/pubmed/35901047
http://dx.doi.org/10.1371/journal.pone.0271930
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