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Epiphytic bryophyte biomass estimation on tree trunks and upscaling in tropical montane cloud forests

Epiphytic bryophytes (EB) are some of the most commonly found plant species in tropical montane cloud forests, and they play a disproportionate role in influencing the terrestrial hydrological and nutrient cycles. However, it is difficult to estimate the abundance of EB due to the nature of their “e...

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Autores principales: Lai, Guan-Yu, Liu, Hung-Chi, Kuo, Ariel J., Huang, Cho-ying
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295022/
https://www.ncbi.nlm.nih.gov/pubmed/32566412
http://dx.doi.org/10.7717/peerj.9351
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author Lai, Guan-Yu
Liu, Hung-Chi
Kuo, Ariel J.
Huang, Cho-ying
author_facet Lai, Guan-Yu
Liu, Hung-Chi
Kuo, Ariel J.
Huang, Cho-ying
author_sort Lai, Guan-Yu
collection PubMed
description Epiphytic bryophytes (EB) are some of the most commonly found plant species in tropical montane cloud forests, and they play a disproportionate role in influencing the terrestrial hydrological and nutrient cycles. However, it is difficult to estimate the abundance of EB due to the nature of their “epiphytic” habitat. This study proposes an allometric scaling approach implemented in twenty-one 30 × 30 m plots across an elevation range in 16,773 ha tropical montane cloud forests of northeastern Taiwan to measure EB biomass, a primary metric for indicating plant abundance and productivity. A general allometry was developed to estimate EB biomass of 100 cm(2) circular-shaped mats (n = 131) with their central depths. We developed a new point-intercept instrument to rapidly measure the depths of EB along tree trunks below 300 cm from the ground level (sampled stem surface area (SSA)) (n = 210). Biomass of EB of each point measure was derived using the general allometry and was aggregated across each SSA, and its performance was evaluated. Total EB biomass of a tree was estimated by referring to an in-situ conversion model and was interpolated for all trees in the plots (n = 1451). Finally, we assessed EB biomass density at the plot scale of the study region. The general EB biomass-depth allometry showed that the depth of an EB mat was a salient variable for biomass estimation (R(2) = 0.72, p < 0.001). The performance of upscaling from mats to SSA was satisfactory, which allowed us to further estimate mean (±standard deviation) EB biomass of the 21 plots (272 ± 104 kg ha(−1)). Since a significant relationship between tree size and EB abundance is commonly found, regional EB biomass may be mapped by integrating our method and three-dimensional remotely sensed airborne data.
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spelling pubmed-72950222020-06-20 Epiphytic bryophyte biomass estimation on tree trunks and upscaling in tropical montane cloud forests Lai, Guan-Yu Liu, Hung-Chi Kuo, Ariel J. Huang, Cho-ying PeerJ Ecology Epiphytic bryophytes (EB) are some of the most commonly found plant species in tropical montane cloud forests, and they play a disproportionate role in influencing the terrestrial hydrological and nutrient cycles. However, it is difficult to estimate the abundance of EB due to the nature of their “epiphytic” habitat. This study proposes an allometric scaling approach implemented in twenty-one 30 × 30 m plots across an elevation range in 16,773 ha tropical montane cloud forests of northeastern Taiwan to measure EB biomass, a primary metric for indicating plant abundance and productivity. A general allometry was developed to estimate EB biomass of 100 cm(2) circular-shaped mats (n = 131) with their central depths. We developed a new point-intercept instrument to rapidly measure the depths of EB along tree trunks below 300 cm from the ground level (sampled stem surface area (SSA)) (n = 210). Biomass of EB of each point measure was derived using the general allometry and was aggregated across each SSA, and its performance was evaluated. Total EB biomass of a tree was estimated by referring to an in-situ conversion model and was interpolated for all trees in the plots (n = 1451). Finally, we assessed EB biomass density at the plot scale of the study region. The general EB biomass-depth allometry showed that the depth of an EB mat was a salient variable for biomass estimation (R(2) = 0.72, p < 0.001). The performance of upscaling from mats to SSA was satisfactory, which allowed us to further estimate mean (±standard deviation) EB biomass of the 21 plots (272 ± 104 kg ha(−1)). Since a significant relationship between tree size and EB abundance is commonly found, regional EB biomass may be mapped by integrating our method and three-dimensional remotely sensed airborne data. PeerJ Inc. 2020-06-12 /pmc/articles/PMC7295022/ /pubmed/32566412 http://dx.doi.org/10.7717/peerj.9351 Text en © 2020 Lai et al. https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.
spellingShingle Ecology
Lai, Guan-Yu
Liu, Hung-Chi
Kuo, Ariel J.
Huang, Cho-ying
Epiphytic bryophyte biomass estimation on tree trunks and upscaling in tropical montane cloud forests
title Epiphytic bryophyte biomass estimation on tree trunks and upscaling in tropical montane cloud forests
title_full Epiphytic bryophyte biomass estimation on tree trunks and upscaling in tropical montane cloud forests
title_fullStr Epiphytic bryophyte biomass estimation on tree trunks and upscaling in tropical montane cloud forests
title_full_unstemmed Epiphytic bryophyte biomass estimation on tree trunks and upscaling in tropical montane cloud forests
title_short Epiphytic bryophyte biomass estimation on tree trunks and upscaling in tropical montane cloud forests
title_sort epiphytic bryophyte biomass estimation on tree trunks and upscaling in tropical montane cloud forests
topic Ecology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7295022/
https://www.ncbi.nlm.nih.gov/pubmed/32566412
http://dx.doi.org/10.7717/peerj.9351
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