Allometric biomass equations for 12 tree species in coniferous and broadleaved mixed forests, Northeastern China

PLoS One. 2018 Jan 19;13(1):e0186226. doi: 10.1371/journal.pone.0186226. eCollection 2018.

Abstract

Understanding forest carbon budget and dynamics for sustainable resource management and ecosystem functions requires quantification of above- and below-ground biomass at individual tree species and stand levels. In this study, a total of 122 trees (9-12 per species) were destructively sampled to determine above- and below-ground biomass of 12 tree species (Acer mandshuricum, Acer mono, Betula platyphylla, Carpinus cordata, Fraxinus mandshurica, Juglans mandshurica, Maackia amurensis, P. koraiensis, Populus ussuriensis, Quercus mongolica, Tilia amurensis and Ulmus japonica) in coniferous and broadleaved mixed forests of Northeastern China, an area of the largest natural forest in the country. Biomass allocation was examined and biomass models were developed using diameter as independent variable for individual tree species and all species combined. The results showed that the largest biomass allocation of all species combined was on stems (57.1%), followed by coarse root (21.3%), branch (18.7%), and foliage (2.9%). The log-transformed model was statistically significant for all biomass components, although predicting power was higher for species-specific models than for all species combined, general biomass models, and higher for stems, roots, above-ground biomass, and total tree biomass than for branch and foliage biomass. These findings supplement the previous studies on this forest type by additional sample trees, species and locations, and support biomass research on forest carbon budget and dynamics by management activities such as thinning and harvesting in the northeastern part of China.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Biomass*
  • China
  • Forests*
  • Models, Theoretical
  • Plant Structures
  • Species Specificity
  • Trees / classification*

Grants and funding

This research is supported by the Fundamental Research Funds for the State Key Program of National Natural Science Foundation of China (41330530) and the National Basic Research Program of China (973 Program: 2011CB403203).