Biomass Equations for 24 Understory Species in Coniferous and Broadleaved Mixed Forests in Northeastern China

Abstract

Understory plants are important components of forest ecosystem productivity and diversity. Compared to biomass models of overstory canopy trees, few are available for understory saplings and shrubs and therefore their roles in estimation of forest carbon pools are often ignored. In this study, we harvested 24 understory species including 4 saplings, 9 tree-like shrubs and 11 typical shrubs in coniferous and broadleaved mixed forest in northeastern China and developed the best fit allometric equations of above-and below-ground and total biomass by species-specific or multispecies using morphological measurements of basal diameter, height and crown area as independent variables. The result showed that single basal diameter, height or crown area had good explanatory power for both species-specific and multispecies (p<0.001). The best-fit models included only basal diameter in sapling and tree-like shrubs, and combinations of crown area, height, and basal diameter in typical shrubs. The logarithmic model was most desired among the 4 model forms of linear, quadratic, multiple linear and logarithmic, for species-specific and multispecies. The models we developed should help the estimation of forest ecosystem carbon stocks, especially for belowground component, and provide tools for quantification of individual species biomass of understory plants.

Estimating the aboveground biomass and carbon stocks of tall shrubs in a prerestoration degraded salt marsh

“…Our results fill a gap in the available data on degraded wetlands and may be useful for other restoration projects. They should, however, only be used while carefully considering their site‐specific applicability (Ali et al 2015; He et al 2016). Brand and Smith (1985) suggested if accumulating sufficient raw data to generate a specific biomass equation is impractical, one can generate an equation for species of interest by combining published raw data, or when not available, by comparing published equations and using them to determine an appropriate range of estimates.…”

“…Plants were selected at random to represent a range of sizes, shapes, forms, and stem numbers (Brown 1976; Dickinson & Zenner 2010; Ali et al 2015; He et al 2016). Plant locations covered diverse hydrogeomorphic conditions (Fig.…”

“…Additionally, we felt the slight increase in explanatory power and reduction in standard error with the two-variable equations did not compensate for the risk of measurement error (He et al 2016). Because the diameter-height variable was not significant in any model, the three-variable models were not used.…”