# 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
#### 3.1.2 Results  
(1) Target forest types  
Woody biomass was originally a forest-derived resource, and theoretically, any forest can produce woody biomass. However, the reviewed papers covered only part of the forests in the study area, rather than the entire forest. Among them, all studies focused on privately ownediferous-planted forests, with a few simultaneously examining privately owned natural hardwood forests or national coniferous-planted forests. We extracted the target forested area from each paper and calculated the share of the target forested area relative to the total forested area in the study area (Figure 1). It should be noted that some studies lacked specific data; therefore, the estimates were based solely on privately owned coniferous-planted forests. The results indicate that the target forested area in relation to the total forest area in the study area ranged from 10.2% to 76.7%, demonstrating significant variation depending on the characteristics of the forests within the study area. The maximum and minimum values in the box plots were identified as outliers owing to their representation of areas at the municipal level, showing prominent local forest characteristics. The maximum value of 76.7% corresponds to Case 3 in Table 1, where the forests in this area are predominantly privately owned. Conversely, the minimum value of 10.2% corresponds to Case 2 in Table 1, with the forests in this region being primarily national. The median and mean values in Figure 1 are 42.0% and 42.5%, respectively, which closely resemble the ratio of the total privately owned coniferous-planted forests to the total forest area in Japan (41.8%). (2) Results and factors influencing supply potential estimation  
The supply potential of woody biomass is directly related to forest area; a larger forest area corresponds to a greater supply potential. To compare the estimation results from the reviewed papers, the annual supply potential was divided by the target forested area. The results, illustrated in Figure 2, are widely distributed, ranging between 1.2 and 5.5 m\({}^{3}\)/year/ha, with median and mean values of 1.5 and 2.3 m\({}^{3}\)/year/ha, respectively. To identify the factors that significantly impact the estimation of the supply potential, the estimation conditions set by each study are tabulated (Table 1). The results shown in Figure 2 can be categorized into three groups based on the estimation period, biomass rate, and extraction rate (Figure 3). Groups 1 and 2 represent the long-term estimation outcomes, with Group 3 corresponding to the short-term estimation results. Group 1 included the five cases from Table 1, namely Cases 1 through 5, which exhibited relatively large values. In these cases, the biomass rate was set to 50% or more for thinning and 25% for final felling (except for Case 1), resulting in larger values. Additionally, because the number of cases in Group 1 was small and the biomass rate was high, the utilization of branches and leaves did not have a significant impact on the results. Group 2 included 19 cases from Cases 6 through 24 in Table 1, with smaller values. The estimation method for these cases was nearly identical, as the biomass rate for both thinning and final felling was set at 15% and no consideration was  
Figure 1: The share of the target forested area relative to the total forested area in the study area. given to the utilization of branches and leaves. This resulted in a relatively concentrated distribution of results. Finally, Group 3 resulted in short-term estimations and included eight cases from Cases 25 through 32 in Table 1, with values falling between those of Groups 1 and 2 and exhibiting a relatively wide distribution. Notably, although the study areas, estimation methods, and conditions were nearly identical for Group 3 Case 25 and Group 1 Cases 4 and 5, Case 25 produced larger estimates than Cases 4 and 5. This difference may be attributed to the contrast between the long-term and short-term estimates.