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A biological condition gradient for Caribbean coral reefs: Part II. Numeric rules using sessile benthic organisms
The Biological Condition Gradient (BCG) is a conceptual model used to describe incremental changes in biological condition along a gradient of increasing anthropogenic stress. As coral reefs collapse globally, scientists and managers are focused on how to sustain the crucial structure and functions,...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9067392/ https://www.ncbi.nlm.nih.gov/pubmed/35516524 http://dx.doi.org/10.1016/j.ecolind.2022.108576 |
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author | Santavy, Deborah L Jackson, Susan K Jessup, Benjamin Horstmann, Christina Rogers, Caroline Weil, Ernesto Szmant, Alina Miranda, David Cuevas Walker, Brian K. Jeffrey, Christopher Ballantine, David Fisher, William S Clark, Randy Torres, Hector Ruiz Todd, Brandi Raimondo, Sandy |
author_facet | Santavy, Deborah L Jackson, Susan K Jessup, Benjamin Horstmann, Christina Rogers, Caroline Weil, Ernesto Szmant, Alina Miranda, David Cuevas Walker, Brian K. Jeffrey, Christopher Ballantine, David Fisher, William S Clark, Randy Torres, Hector Ruiz Todd, Brandi Raimondo, Sandy |
author_sort | Santavy, Deborah L |
collection | PubMed |
description | The Biological Condition Gradient (BCG) is a conceptual model used to describe incremental changes in biological condition along a gradient of increasing anthropogenic stress. As coral reefs collapse globally, scientists and managers are focused on how to sustain the crucial structure and functions, and the benefits that healthy coral reef ecosystems provide for many economies and societies. We developed a numeric (quantitative) BGC model for the coral reefs of Puerto Rico and the US Virgin Islands to transparently facilitate ecologically meaningful management decisions regarding these fragile resources. Here, reef conditions range from natural, undisturbed conditions to severely altered or degraded conditions. Numeric decision rules were developed by an expert panel for scleractinian corals and other benthic assemblages using multiple attributes to apply in shallow-water tropical fore reefs with depths <30 m. The numeric model employed decision rules based on metrics (e.g., % live coral cover, coral species richness, pollution-sensitive coral species, unproductive and sediment substrates, % cover by Orbicella spp.) used to assess coral reef condition. Model confirmation showed the numeric BCG model predicted the panel’s median site ratings for 84% of the sites used to calibrate the model and 89% of independent validation sites. The numeric BCG model is suitable for adaptive management applications and supports bioassessment and criteria development. It is a robust assessment tool that could be used to establish ecosystem condition that would aid resource managers in evaluating and communicating current or changing conditions, protect water and habitat quality in areas of high biological integrity, or develop restoration goals with stakeholders and other public beneficiaries. |
format | Online Article Text |
id | pubmed-9067392 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
record_format | MEDLINE/PubMed |
spelling | pubmed-90673922022-05-04 A biological condition gradient for Caribbean coral reefs: Part II. Numeric rules using sessile benthic organisms Santavy, Deborah L Jackson, Susan K Jessup, Benjamin Horstmann, Christina Rogers, Caroline Weil, Ernesto Szmant, Alina Miranda, David Cuevas Walker, Brian K. Jeffrey, Christopher Ballantine, David Fisher, William S Clark, Randy Torres, Hector Ruiz Todd, Brandi Raimondo, Sandy Ecol Indic Article The Biological Condition Gradient (BCG) is a conceptual model used to describe incremental changes in biological condition along a gradient of increasing anthropogenic stress. As coral reefs collapse globally, scientists and managers are focused on how to sustain the crucial structure and functions, and the benefits that healthy coral reef ecosystems provide for many economies and societies. We developed a numeric (quantitative) BGC model for the coral reefs of Puerto Rico and the US Virgin Islands to transparently facilitate ecologically meaningful management decisions regarding these fragile resources. Here, reef conditions range from natural, undisturbed conditions to severely altered or degraded conditions. Numeric decision rules were developed by an expert panel for scleractinian corals and other benthic assemblages using multiple attributes to apply in shallow-water tropical fore reefs with depths <30 m. The numeric model employed decision rules based on metrics (e.g., % live coral cover, coral species richness, pollution-sensitive coral species, unproductive and sediment substrates, % cover by Orbicella spp.) used to assess coral reef condition. Model confirmation showed the numeric BCG model predicted the panel’s median site ratings for 84% of the sites used to calibrate the model and 89% of independent validation sites. The numeric BCG model is suitable for adaptive management applications and supports bioassessment and criteria development. It is a robust assessment tool that could be used to establish ecosystem condition that would aid resource managers in evaluating and communicating current or changing conditions, protect water and habitat quality in areas of high biological integrity, or develop restoration goals with stakeholders and other public beneficiaries. 2022-02 /pmc/articles/PMC9067392/ /pubmed/35516524 http://dx.doi.org/10.1016/j.ecolind.2022.108576 Text en https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) ). |
spellingShingle | Article Santavy, Deborah L Jackson, Susan K Jessup, Benjamin Horstmann, Christina Rogers, Caroline Weil, Ernesto Szmant, Alina Miranda, David Cuevas Walker, Brian K. Jeffrey, Christopher Ballantine, David Fisher, William S Clark, Randy Torres, Hector Ruiz Todd, Brandi Raimondo, Sandy A biological condition gradient for Caribbean coral reefs: Part II. Numeric rules using sessile benthic organisms |
title | A biological condition gradient for Caribbean coral reefs: Part II. Numeric rules using sessile benthic organisms |
title_full | A biological condition gradient for Caribbean coral reefs: Part II. Numeric rules using sessile benthic organisms |
title_fullStr | A biological condition gradient for Caribbean coral reefs: Part II. Numeric rules using sessile benthic organisms |
title_full_unstemmed | A biological condition gradient for Caribbean coral reefs: Part II. Numeric rules using sessile benthic organisms |
title_short | A biological condition gradient for Caribbean coral reefs: Part II. Numeric rules using sessile benthic organisms |
title_sort | biological condition gradient for caribbean coral reefs: part ii. numeric rules using sessile benthic organisms |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9067392/ https://www.ncbi.nlm.nih.gov/pubmed/35516524 http://dx.doi.org/10.1016/j.ecolind.2022.108576 |
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