Biomass and production of a naturally regenerated oak forest in southern Korea

Park, In Hyeop; Son, Yowhan; Kim, Dong Yeob; Jin, Hyun O; Yi, Myong Jong; Kim, Rae Hyun; Hwang, Jung Ok

doi:10.1007/s11284-004-0021-x

Cited by 3 publications

(3 citation statements)

References 8 publications

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“…form factor or mean height are not exactly defi ned and the given values in publications are not compatible. The outliers were two temperate mixed deciduous forests (Newman et al, 2006) showing small biomass for GH and Quercus stands in Korea (Son et al, 2004) with big biomass at GH compared to Park et al (2005).…”

Section: Model Constructionmentioning

confidence: 99%

“…Additional published data were from oak forest in Korea (Li et al, 2012) (includes Son et al, 2004Park et al, 2005) and stand level biomass data by age classes for oak forests in Poland (Orzeł et al, 2006). Rice et al (2004) provided suffi cient data in their Table 5 for an old-growth Amazon rainforest to calculate G and they also gave an estimate of the closed canopy height (40 m) and the emergent tree height (55 m).…”

Section: Biomass Data and Published Biomass Estimates For Model Assesmentioning

confidence: 99%

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Estimation of above-ground biomass in forest stands from regression on their basal area and height

et al. 2016

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A generic regression model for above-ground biomass of forest stands was constructed based on published data (R2 = 0.88, RSE = 32.8 t/ha). The model was used 1) to verify two allometric regression models of trees from Scandinavia applied to repeated measurements of 275 sample plots from database of Estonian Network of Forest Research (FGN) in Estonia, 2) to analyse impact of between-tree competition on biomass, and 3) compare biomass estimates made with different European biomass models applied on standardized forest structures. The model was verified with biomass measurements from hemiboreal and tropical forests. The analysis of two Scandinavian models showed that older allometric regression models may give biased estimates due to changed growth conditions. More biomass can be stored in forest stands where competition between trees is stronger. The tree biomass calculation methods used in different countries have also substantial influence on the estimates at stand-level. A common database of forest biomass measurements from Europe in similar to pan-tropical tree measurement data may be helpful to harmonise carbon accounting methods.

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Section: Model Constructionmentioning

confidence: 99%

Section: Biomass Data and Published Biomass Estimates For Model Assesmentioning

confidence: 99%

Estimation of above-ground biomass in forest stands from regression on their basal area and height

et al. 2016

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“…For example, BEF were obtained by compiling data from the literature to estimate country-level biomass (Fang et al 1998, Van Camp et al 2004. Reliable estimation and rep-Smalian's formula (Avery and Burkhart 1983, Park et al 2005b, Li et al 2011.…”

Section: Introductionmentioning

confidence: 99%

Notes on the biomass expansion factors of Quercus mongolica and Quercus variabilis forests in Korea

Son

Lee

et al. 2012

J. Ecol. Environ.

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Biomass expansion factors, which convert timber volume (or dry weight) to biomass, are used for estimating the forest biomass and accounting for the carbon budget at a regional or national scale. We estimated the biomass conversion and expansion factors (BCEF), biomass expansion factors (BEF), root to shoot ratio (R), and ecosystem biomass expansion factor (EBEF) for Quercus mongolica Fisch. and Quercus variabilis Bl. forests based on publications in Korea. The mean BCEF, BEF, and R for Q. mongolica was 1.

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Bayesian meta-analysis of regional biomass factors for Quercus mongolica forests in South Korea

Lam

Kim

et al. 2015

J. For. Res.

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Indirect approaches to estimation of biomass factors are often applied to measure carbon flux in the forestry sector. An assumption underlying a country-level carbon stock estimate is the representativeness of these factors. Although intensive studies have been conducted to quantify biomass factors, each study typically covers a limited geographic area. The goal of this study was to employ a meta-analysis approach to develop regional biomass factors for Quercus mongolica forests in South Korea. The biomass factors of interest were biomass conversion and expansion factor (BCEF), biomass expansion factor (BEF) and root-to-shoot ratio (RSR). Our objectives were to select probability density functions (PDFs) that best fitted the three biomass factors and to quantify their means and uncertainties. A total of 12 scientific publications were selected as data sources based on a set of criteria. From these publications we chose 52 study sites spread out across South Korea. The statistical model for the metaanalysis was a multilevel model with publication (data source) as the nesting factor specified under the Bayesian framework. Gamma, Log-normal and Weibull PDFs were evaluated. The Log-normal PDF yielded the best quantitative and qualitative fit for the three biomass factors. However, a poor fit of the PDF to the long right tail of observed BEF and RSR distributions was apparent. The median posterior estimates for means and 95 % credible intervals for BCEF, BEF and RSR across all 12 publications were 1.016 (0.800-1.299), 1.414 (1.304-1.560) and 0.260 (0.200-0.335), respectively. The Log-normal PDF proved useful for estimating carbon stock of Q. mongolica forests on a regional scale and for uncertainty analysis based on Monte Carlo simulation.

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Biomass and production of a naturally regenerated oak forest in southern Korea

Cited by 3 publications

References 8 publications

Estimation of above-ground biomass in forest stands from regression on their basal area and height

Estimation of above-ground biomass in forest stands from regression on their basal area and height

Notes on the biomass expansion factors of Quercus mongolica and Quercus variabilis forests in Korea

Bayesian meta-analysis of regional biomass factors for Quercus mongolica forests in South Korea

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