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Can Community Members Identify Tropical Tree Species for REDD+ Carbon and Biodiversity Measurements?

Biodiversity conservation is a required co-benefit of REDD+. Biodiversity monitoring is therefore needed, yet in most areas it will be constrained by limitations in the available human professional and financial resources. REDD+ programs that use forest plots for biomass monitoring may be able to ta...

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Detalles Bibliográficos
Autores principales: Zhao, Mingxu, Brofeldt, Søren, Li, Qiaohong, Xu, Jianchu, Danielsen, Finn, Læssøe, Simon Bjarke Lægaard, Poulsen, Michael Køie, Gottlieb, Anna, Maxwell, James Franklin, Theilade, Ida
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5096847/
https://www.ncbi.nlm.nih.gov/pubmed/27814370
http://dx.doi.org/10.1371/journal.pone.0152061
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author Zhao, Mingxu
Brofeldt, Søren
Li, Qiaohong
Xu, Jianchu
Danielsen, Finn
Læssøe, Simon Bjarke Lægaard
Poulsen, Michael Køie
Gottlieb, Anna
Maxwell, James Franklin
Theilade, Ida
author_facet Zhao, Mingxu
Brofeldt, Søren
Li, Qiaohong
Xu, Jianchu
Danielsen, Finn
Læssøe, Simon Bjarke Lægaard
Poulsen, Michael Køie
Gottlieb, Anna
Maxwell, James Franklin
Theilade, Ida
author_sort Zhao, Mingxu
collection PubMed
description Biodiversity conservation is a required co-benefit of REDD+. Biodiversity monitoring is therefore needed, yet in most areas it will be constrained by limitations in the available human professional and financial resources. REDD+ programs that use forest plots for biomass monitoring may be able to take advantage of the same data for detecting changes in the tree diversity, using the richness and abundance of canopy trees as a proxy for biodiversity. If local community members are already assessing the above-ground biomass in a representative network of forest vegetation plots, it may require minimal further effort to collect data on the diversity of trees. We compare community members and trained scientists’ data on tree diversity in permanent vegetation plots in montane forest in Yunnan, China. We show that local community members here can collect tree diversity data of comparable quality to trained botanists, at one third the cost. Without access to herbaria, identification guides or the Internet, community members could provide the ethno-taxonomical names for 95% of 1071 trees in 60 vegetation plots. Moreover, we show that the community-led survey spent 89% of the expenses at village level as opposed to 23% of funds in the monitoring by botanists. In participatory REDD+ programs in areas where community members demonstrate great knowledge of forest trees, community-based collection of tree diversity data can be a cost-effective approach for obtaining tree diversity information.
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spelling pubmed-50968472016-11-18 Can Community Members Identify Tropical Tree Species for REDD+ Carbon and Biodiversity Measurements? Zhao, Mingxu Brofeldt, Søren Li, Qiaohong Xu, Jianchu Danielsen, Finn Læssøe, Simon Bjarke Lægaard Poulsen, Michael Køie Gottlieb, Anna Maxwell, James Franklin Theilade, Ida PLoS One Collection Review Biodiversity conservation is a required co-benefit of REDD+. Biodiversity monitoring is therefore needed, yet in most areas it will be constrained by limitations in the available human professional and financial resources. REDD+ programs that use forest plots for biomass monitoring may be able to take advantage of the same data for detecting changes in the tree diversity, using the richness and abundance of canopy trees as a proxy for biodiversity. If local community members are already assessing the above-ground biomass in a representative network of forest vegetation plots, it may require minimal further effort to collect data on the diversity of trees. We compare community members and trained scientists’ data on tree diversity in permanent vegetation plots in montane forest in Yunnan, China. We show that local community members here can collect tree diversity data of comparable quality to trained botanists, at one third the cost. Without access to herbaria, identification guides or the Internet, community members could provide the ethno-taxonomical names for 95% of 1071 trees in 60 vegetation plots. Moreover, we show that the community-led survey spent 89% of the expenses at village level as opposed to 23% of funds in the monitoring by botanists. In participatory REDD+ programs in areas where community members demonstrate great knowledge of forest trees, community-based collection of tree diversity data can be a cost-effective approach for obtaining tree diversity information. Public Library of Science 2016-11-04 /pmc/articles/PMC5096847/ /pubmed/27814370 http://dx.doi.org/10.1371/journal.pone.0152061 Text en © 2016 Zhao 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 (http://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 Collection Review
Zhao, Mingxu
Brofeldt, Søren
Li, Qiaohong
Xu, Jianchu
Danielsen, Finn
Læssøe, Simon Bjarke Lægaard
Poulsen, Michael Køie
Gottlieb, Anna
Maxwell, James Franklin
Theilade, Ida
Can Community Members Identify Tropical Tree Species for REDD+ Carbon and Biodiversity Measurements?
title Can Community Members Identify Tropical Tree Species for REDD+ Carbon and Biodiversity Measurements?
title_full Can Community Members Identify Tropical Tree Species for REDD+ Carbon and Biodiversity Measurements?
title_fullStr Can Community Members Identify Tropical Tree Species for REDD+ Carbon and Biodiversity Measurements?
title_full_unstemmed Can Community Members Identify Tropical Tree Species for REDD+ Carbon and Biodiversity Measurements?
title_short Can Community Members Identify Tropical Tree Species for REDD+ Carbon and Biodiversity Measurements?
title_sort can community members identify tropical tree species for redd+ carbon and biodiversity measurements?
topic Collection Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5096847/
https://www.ncbi.nlm.nih.gov/pubmed/27814370
http://dx.doi.org/10.1371/journal.pone.0152061
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