Allometric equations to assess biomass, carbon and nitrogen content of black pine and red pine trees in southern Korea

Abstract

A total of 74 Japanese black pine (Pinus thunbergii Parl.) and red pine (P. densiflora S. et Z.) trees were destructively sampled in southern Korea, which is severely affected by pine wilt disease (PWD). Species-specific allometric equations were developed to estimate the biomass, carbon (C) and nitrogen (N) content of the tree components (i.e., stem wood, stem bark, branches, needles and roots) based on the diameter at breast height (DBH) and stem diameter at 20 cm aboveground (D20). The C concentrations of the various tree components were not correlated with DBH (P > 0.05), except for the C concentration in the stem bark (r = -0.29, P < 0.05) of the black pine and the branches (r = 0.40, P < 0.05) of the red pine. However, the N concentrations in the stem wood (r = -0.53, P < 0.05), stem bark (r = -0.37, P < 0.05) and branches (r = -0.40, P < 0.05) of the black pine were negatively correlated with DBH. The mean C concentrations of the tree components were not significantly different between the black pine and red pine, except for the stem bark, whereas the mean N concentrations were significantly lower in the black pine than in the red pine, except for the stem bark. The allometric equations developed for the biomass, C and N content for all the tree components were significant (P < 0.05). The adjusted coefficient of determination (adj. R 2 ) of the DBH allometric equations ranged from 0.66 to 0.97, while the coefficients for the D20 equations were between 0.66 and 0.95. Black pines consistently exhibited more biomass, C and N content in the tree components compared with the red pines with similar DBH or D20. These results suggest that the accuracy of estimates for biomass, C and N stocks in black pine and red pine forests could be improved by specific allometric equations for PWD-disturbed forests.

Carbon and Nitrogen Accumulation and Decomposition from Coarse Woody Debris in a Naturally Regenerated Korean Red Pine (Pinus densiflora S. et Z.) Forest

“…In regard to the contribution of CWD to N input in this study site, annual N input from CWD caused by annual tree mortality comprised approximately 11.1% of total N stock in CWD, and comprised less than 3.5% of 65.65 kg N ha −1 year −1 from total fine litterfall, indicating less contribution of CWD to N cycles than fine litter. However, the forests have a potential for the rapid increase in the amount of CWD following tree mortality, because the red pine forests have been widely threatened by severe pine wilt disease across the Eastern Asian countries [20,21].…”

Carbon storage and carbon pool characteristics of Larix gmelinii forest in Daxing’anling, Inner Mongolia, China

“…The living standing trees of mature forest are in the peak period of growth, with large quantity and high quality, while the number of living standing trees of young forest is small and the quality is low. The lignification degree of standing trees in middle-aged and near-mature forests is higher, and the carbon content is also higher, while the lignification degree of standing trees in young and near-mature forests is lower, and the carbon content is also lower (Kim et al, 2017;Dong et al, 2018). These findings are important for understanding the dynamics and management of forest carbon pools.…”

Comparisons of carbon and nitrogen dynamics of litterfall components in adjacent Pinus densiflora and Quercus variabilis stands

“…The variations in the C and N concentrations of the litterfall components are mainly determined by the species and sampling months (Thomas, Martin 2012;Kim et al 2019;See et al 2019;Erkan et al 2020). Many studies have reported that the C concentration of the litterfall is negatively correlated with the N and positively correlated with the lignin concentration (Macinnis-Ng, Schwendenmann 2015; Kim et al 2017;See et al 2019). In this study, the higher C concentration of the leaf litter in the P. densiflora than in the Q. variabilis stands could be due to the difference in the lignin and N concentrations determined by the genetic factors between the tree species (Thomas, Martin, 2012;See et al 2019).…”