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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,...

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Autores principales: Hijbeek, Renske, Koedam, Nico, Khan, Md Nabiul Islam, Kairo, James Gitundu, Schoukens, Johan, Dahdouh-Guebas, Farid
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
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.
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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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