Can community members identify tropical tree species for REDD+ carbon and biodiversity measurements?
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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.
In: PloS one, Vol. 11, No. 11, e0152061, 2016.Research output: Contribution to journal › Journal article › Research › peer-review
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TY - JOUR
T1 - Can community members identify tropical tree species for REDD+ carbon and biodiversity measurements?
AU - Zhao, Mingxu
AU - Brofeldt, Søren
AU - Li, Qiaohong
AU - Xu, Jianchu
AU - Danielsen, Finn
AU - Læssøe, Simon Bjarke Lægaard
AU - Poulsen, Michael Køie
AU - Gottlieb, Anna
AU - Maxwell, James Franklin
AU - Theilade, Ida
PY - 2016
Y1 - 2016
N2 - 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.
AB - 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.
U2 - 10.1371/journal.pone.0152061
DO - 10.1371/journal.pone.0152061
M3 - Journal article
C2 - 27814370
VL - 11
JO - PLoS ONE
JF - PLoS ONE
SN - 1932-6203
IS - 11
M1 - e0152061
ER -
ID: 168883551