# Research Trends and Future Direction for Utilization of Woody Biomass in Japan
## 3 Supply Potential and Availability of Woody Biomass  
### Methods and Results of Supply Potential Estimation  
#### 3.1.1 Methods  
Because some of the reviewed papers estimated multiple regions simultaneously, 32 cases were organized as one case of estimation results for each region (Table 1). The supply potential of woody biomass was estimated using government forestry survey data. However, there are differences between the long- and short-term estimates, depending on the period of estimation. Long-term estimation is based on the concept of a \"normal forest\" (i.e., a forest that undergoes sustainable management through the cutting down and replanting of trees at an amount equivalent to the annual growth) and estimates the supply potential for an entire harvest period, assuming that the forest can be harvested sustainably over a long period. Long-term estimation considers the growth of trees but cannot accurately estimate specific annual supply potentials, such as cases 1 to 24 in Table 1. On the other hand, short-term estimation is used to estimate the supply potential for a specific year in areas that have been either harvested or are planned. Short-term estimation provides relatively accurate estimates of the annual supply potential based on actual harvesting records, such as cases 25 to 32 in Table 1. However, this may underestimate the potential, as in some areas forest operational records only record harvesting activities subsidized by the government [16,17]. \begin{table}
\begin{tabular}{c c c c c c c c} \hline \hline  & & & \multicolumn{6}{c}{**Factors for Estimating Supply Potential**} \\ \cline{4-9}
**Case** & & & \multicolumn{2}{c}{**Sare of**} & \multicolumn{2}{c}{**Biomass Rate [\%]**} & \\ \cline{4-9}
**No.** & & & **Target Forest Type** & & & **Pre-** & & **Pre-** \\  & & & **[\%]** & **Commercial Thinning** & & **Felling** & & **Rate [\%]** & **Yield Rate [\%]** \\ \hline
1 & Yusuhara, Kochi Pref., 2009 & Conifer plantations & 41.9 & N.A. & 100 & 15 & 115 & 100 \\
2 & Nasushiobara, Tochigi Pref., 2013 & Conifer plantations & 10.2 & 100 & 55 & 26 & 109 & 100 \\
3 & Kanuma area, Tochigi Pref., 2013 & Conifer plantations & 76.7 & 100 & 55 & 26 & 109 & 100 \\
4 & Tochigi Pref., 2017 & Conifer plantations & 32.5 & 90 & 50 & 25 & 100 & 100 \\
5 & Tochigi Pref., 2019 & Conifer plantations & 37.9 & 90 & 50 & 25 & 100 & 100 \\
6 & Fukushima Priet., 2020 & Conifer plantations & 37.5 & 15 & 15 & 15 & 100 & 90 \\
7 & Ibaraki Pref., 2020 & Conifer plantations & 60.6 & 15 & 15 & 15 & 100 & 90 \\
8 & Tochigi Pref., 2020 & Conifer plantations & 46.9 & 15 & 15 & 15 & 100 & 90 \\
9 & Gumna Pref., 2020 & Conifer plantations & 41.1 & 15 & 15 & 15 & 100 & 90 \\
10 & Japan, 2021 & Conifer plantations & 41.3 & 15 & 15 & 15 & 100 & 90 \\
11 & Hokkaido, 2021 & Conifer plantations & 24.6 & 15 & 15 & 15 & 100 & 90 \\  
roadleaf natural & & & & & & \\
30 & Northern Chiba Pref., 2010 & forest and Conifer plantations & N.A. & 100 & 100 & 100 & 123 & 100 \\
31 & Western Saitama Pref., & & & & & & & \\  & forest and Conifer plantations & N.A. & 100 & 100 & 100 & 123 & 100 \\
2010 & & Broadleaf natural & & & & & & \\
32 & N.A., 2011 & forest and Conifer plantations & N.A. & 100 & 100 & 100 & 109 & 100 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Results of woody biomass supply potential and availability. The estimation of woody biomass supply potential primarily relies on government forestry survey data (e.g., forest registers and forest management plans). The total supply potential is calculated by aggregating the supply potential of each sub-compartment within a study area. Utilizing Geographic Information Systems, the spatial distribution of supply potential for the sub-compartment can be visualized.