Forests (Apr 2020)

Comparison of Allometric Equation and Destructive Measurement of Carbon Storage of Naturally Regenerated Understory in a <i>Pinus rigida</i> Plantation in South Korea

  • Si Ho Han,
  • Byung Bae Park

DOI
https://doi.org/10.3390/f11040425
Journal volume & issue
Vol. 11, no. 4
p. 425

Abstract

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The forest understory plays an important role in the carbon and nutrient cycling and forest stability, but cost-efficient quantification of its biomass remains challenging. Most of the existing biomass allometric equations have been developed and designed only for mature forest trees (i.e., Diameter at breast height (DBH) ≥ 10 cm), and those for trees with DBH less than 10 cm are not readily available. In this study, we compared the biomass by plant component (i.e., foliage, branch, and stem) measured by a destructive method with those estimated by the existing biomass allometric equations for understory trees with DBH less than 10 cm in a Pinus rigida plantation. We also developed an allometric biomass equation for the identified understory tree species, namely, Quercus variabilis, Quercus acutissima, Quercus mongolica, Quercus serrata, and Carpinus laxiflora. The estimated biomass using allometric equations for foliage, branch, and stem was lower than the values obtained using the destructive method by 64%, 41%, and 18%, respectively. The biomass allometric equations developed in this study showed high coefficients of determination (mean R2 = 0.970) but varied depending on species and tree part (range: 0.824–0.984 for foliage, 0.825–0.952 for branch, and 0.884–0.999 for the stem, respectively). The computed biomass of the understory vegetation was 22.9 Mg ha−1, representing 12.0% of the total biomass of the P. rigida plantation. The present study demonstrates that understory trees with DBH less than 10 cm account for a considerable portion of carbon stock in forest ecosystems, and therefore suggests that more biomass allometric equations should be optimized for small-DBH trees to improve forest carbon stock estimation.

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