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An Evaluation of Plotless Sampling Using Vegetation Simulations and Field Data from a Mangrove Forest
In vegetation science and forest management, tree density is often used as a variable. To determine the value of this variable, reliable field methods are necessary. When vegetation is sparse or not easily accessible, the use of sample plots is not feasible in the field. Therefore, plotless methods,...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3695089/ https://www.ncbi.nlm.nih.gov/pubmed/23826233 http://dx.doi.org/10.1371/journal.pone.0067201 |
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author | Hijbeek, Renske Koedam, Nico Khan, Md Nabiul Islam Kairo, James Gitundu Schoukens, Johan Dahdouh-Guebas, Farid |
author_facet | Hijbeek, Renske Koedam, Nico Khan, Md Nabiul Islam Kairo, James Gitundu Schoukens, Johan Dahdouh-Guebas, Farid |
author_sort | Hijbeek, Renske |
collection | PubMed |
description | In vegetation science and forest management, tree density is often used as a variable. To determine the value of this variable, reliable field methods are necessary. When vegetation is sparse or not easily accessible, the use of sample plots is not feasible in the field. Therefore, plotless methods, like the Point Centred Quarter Method, are often used as an alternative. In this study we investigate the accuracy of different plotless sampling methods. To this end, tree densities of a mangrove forest were determined and compared with estimates provided by several plotless methods. None of these methods proved accurate across all field sites with mean underestimations up to 97% and mean overestimations up to 53% in the field. Applying the methods to different vegetation patterns shows that when random spatial distributions were used the true density was included within the 95% confidence limits of all the plotless methods tested. It was also found that, besides aggregation and regularity, density trends often found in mangroves contribute to the unreliability. This outcome raises questions about the use of plotless sampling in forest monitoring and management, as well as for estimates of density-based carbon sequestration. We give recommendations to minimize errors in vegetation surveys and recommendations for further in-depth research. |
format | Online Article Text |
id | pubmed-3695089 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-36950892013-07-03 An Evaluation of Plotless Sampling Using Vegetation Simulations and Field Data from a Mangrove Forest Hijbeek, Renske Koedam, Nico Khan, Md Nabiul Islam Kairo, James Gitundu Schoukens, Johan Dahdouh-Guebas, Farid PLoS One Research Article In vegetation science and forest management, tree density is often used as a variable. To determine the value of this variable, reliable field methods are necessary. When vegetation is sparse or not easily accessible, the use of sample plots is not feasible in the field. Therefore, plotless methods, like the Point Centred Quarter Method, are often used as an alternative. In this study we investigate the accuracy of different plotless sampling methods. To this end, tree densities of a mangrove forest were determined and compared with estimates provided by several plotless methods. None of these methods proved accurate across all field sites with mean underestimations up to 97% and mean overestimations up to 53% in the field. Applying the methods to different vegetation patterns shows that when random spatial distributions were used the true density was included within the 95% confidence limits of all the plotless methods tested. It was also found that, besides aggregation and regularity, density trends often found in mangroves contribute to the unreliability. This outcome raises questions about the use of plotless sampling in forest monitoring and management, as well as for estimates of density-based carbon sequestration. We give recommendations to minimize errors in vegetation surveys and recommendations for further in-depth research. Public Library of Science 2013-06-27 /pmc/articles/PMC3695089/ /pubmed/23826233 http://dx.doi.org/10.1371/journal.pone.0067201 Text en © 2013 Hijbeek et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Hijbeek, Renske Koedam, Nico Khan, Md Nabiul Islam Kairo, James Gitundu Schoukens, Johan Dahdouh-Guebas, Farid An Evaluation of Plotless Sampling Using Vegetation Simulations and Field Data from a Mangrove Forest |
title | An Evaluation of Plotless Sampling Using Vegetation Simulations and Field Data from a Mangrove Forest |
title_full | An Evaluation of Plotless Sampling Using Vegetation Simulations and Field Data from a Mangrove Forest |
title_fullStr | An Evaluation of Plotless Sampling Using Vegetation Simulations and Field Data from a Mangrove Forest |
title_full_unstemmed | An Evaluation of Plotless Sampling Using Vegetation Simulations and Field Data from a Mangrove Forest |
title_short | An Evaluation of Plotless Sampling Using Vegetation Simulations and Field Data from a Mangrove Forest |
title_sort | evaluation of plotless sampling using vegetation simulations and field data from a mangrove forest |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3695089/ https://www.ncbi.nlm.nih.gov/pubmed/23826233 http://dx.doi.org/10.1371/journal.pone.0067201 |
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