TY - JOUR T1 - An allometric scaling approach to estimate epiphytic bryophyte biomass in tropical montane cloud forests JF - bioRxiv DO - 10.1101/2020.02.01.928515 SP - 2020.02.01.928515 AU - Guan-Yu Lai AU - Hung-Chi Liu AU - Ariel J. Kuo AU - Cho-ying Huang Y1 - 2020/01/01 UR - http://biorxiv.org/content/early/2020/02/02/2020.02.01.928515.abstract N2 - 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 to measure EB biomass, implemented in 16,773 ha tropical montane cloud forests of northeastern Taiwan. A general allometry was developed to estimate EB biomass of 100 cm2 circular-shaped mats (n = 131) and their central depths. A point-intercept instrument was invented to measure the depths of EB along tree trunks (n = 210) below 3-m from the ground level (sampled stem surface area [SSA]) in twenty-one 30 × 30 m plots. 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 and preliminarily estimated EB biomass 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 (R2 = 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) and to provide preliminary estimation of the total EB biomass of 4562 Mg for the study region. 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 airborne data. ER -