Stand volume can be estimated from other stand variables by using multiple linear regression (MLR) or other ordinary regression models. MLR, however, only produces global parameter estimates that cannot reveal spatial variations in stand variables. In this study,we used a geographical weighted regression (GWR) method to investigate local spatial variations in the relationship between stand volume, stand age, and basal area of Acacia mangium plantations,and to examine whether a GWR model could provide better prediction accuracy than an MLR model. Stand data and geographical coordinates were obtained from 247 plantation sample plots. We analyzed the data using MLR and GWR methods by formulating a linear model that relates stand volume to stand age and basal area. Performance of the GWR model was compared with the MLR model in terms of their parameter estimates and goodness-of-fit statistics. We found that the GWR model was not only able to reveal local spatial variations in the relationship between stand volume, stand age, and basal area, but it also produced better prediction accuracy than the MLR model. The GWR model reduced AIC by 2%, increased R²_adj up to 3%, and reduced RMSE by 14%, compared with those of the MLR model. The GWR model, therefore, could be useful for modeling spatial variations in stand attributes that cannot be revealed by ordinary regression models. Stand volume can be estimated from other stand variables by using multiple linear regression (MLR) or other ordinary regression models. MLR, however, only produces global parameter estimates that cannot reveal spatial variations in stand variables. In this study,we used a geographical weighted regression (GWR) method to investigate local spatial variations in the relationship between stand volume, stand age, and basal area of Acacia mangium plantations,and to examine whether a GWR model could provide better prediction accuracy than an MLR model. Stand data and geographical coordinates were obtained from 247 plantation sample plots. We analyzed the data using MLR and GWR methods by formulating a linear model that relates stand volume to stand age and basal area. Performance of the GWR model was compared with the MLR model in terms of their parameter estimates and goodness-of-fit statistics. We found that the GWR model was not only able to reveal local spatial variations in the relationship between stand volume, stand age, and basal area, but it also produced better prediction accuracy than the MLR model. The GWR model reduced AIC by 2%, increased R²_adj up to 3%, and reduced RMSE by 14%, compared with those of the MLR model. The GWR model, therefore, could be useful for modeling spatial variations in stand attributes that cannot be revealed by ordinary regression models.

This study assesses the applicability of combining the general standardization procedure (GSP) with principal component analysis (PCA) in ecological data analysis. For this purpose, we conducted a comparison of the performance of combined GSP and PCA with detrended correspondence analysis (DCA) in classifying the structure of species composition in natural forest stands at the Kwangneung Experimental Forest. Prior to analyzing the data using PCA, it was standardized using GSP to avoid the tendency of involutions accompanying PCA. Results showed that both approaches were successful in classifying stand species composition and provided ordination surfaces showing three separate groupsconiferous, deciduous and mixed forests. In terms of total explained variance, GSP-PCA seemed to demonstrate better performance than DCA. However, in classifying species composition structures by visual inspection of the ordination graphs, the ordination plots obtained using DCA were more effective than those generated using GSP-PCA.

This study evaluates whether wind data at local meteorological stations can be used for studying wind damage in forested areas. Data from four Automated Meteorological Data Acquisition System (AMeDAS) stations and one weather station, located in the northern and southern portions of Hokkaido Island, was compared with wind data collected at flux towers located in the Teshio and Tomakomai regional forests. Anemometers were affixed to the flux towers at a height of 32 m in Teshio and 40 m in Tomakomai; thus, the data was assumed to adequately represent wind conditions in a forested area without vegetation effects. Mean wind speed at the AMeDAS stations and weather station sites was converted to extreme wind speed using roughness length on eight directions. This comparison was based on the storm (October to May) and typhoon (August and September) seasons. Subsequently, a distance-limited topographic exposure index (TOPEX) was calculated for all anemometer positions using 1, 2, 5, and 10 km distances from the position. We found that wind at sites with low TOPEX scores and small roughness length could significantly represent wind conditions in nearby forested areas. Wind speeds with high TOPEX scores but small roughness length occasionally showed correlation with conditions at the flux tower. Although additional study is required, using TOPEX with roughness length could be beneficial for deriving suitable wind data sets that correlate with wind conditions in nearby forested areas.

We investigate the effect of strip cutting under a strip shelterwood management scheme with adjacency requirements among strips. We compare results from an ordinary spatially constrained solution to a solution with strip windows in the management units. The comparison of management schemes is considered as a spatially constrained harvest scheduling problem, which is solved using the SSMART (Scheduling System of Management Alternatives foR Timberharvest) hybrid heuristic. SSMART uses a partitioning heuristic to solve spatially constrained harvest scheduling problems. Our experimental analysis shows that using strip windows to embed additional spatial buffers into the management scheme reduces profit by almost 30%. In our Slovakian Forest Enterprise case study, it reduces the harvest flow level and harvested area by approximately 30%, while the calculated flow fluctuation over time is 10 times smaller than that from the ordinary adjacency problem without strip windows. However, strip windows could play an indirect role in preserving some resources for future harvest, possibly meeting sustainable management objectives.

This paper discusses development of a multi-country, multicommodity linear trade model that includes intermediate goods. This new model improves the author’s previous model by rigidly formulating the supply and demand conditions for each good according to the final demand for that good as a linear function of gross domestic product (GDP). Parameter domains of ϕ^o_K (i.e., the level of public benefit - in monetary terms - provided by the forestry sector in country K, assuming that the forestry sector maintains its present output level) are investigated where the pattern of forestry specialization in each country reverses from its primary state. These domains were identified in three-dimensional ϕ^o_K spaces. Public benefit was assumed to be directly proportionate to the country’s forestry output. Calculations were made using data from the “Asian International Input-Output Table 2000.” Simulations were conducted to examine interactions between Japan, the U.S., and China. Results showed that (1) if the present public benefit from the forestry sector in each country is not considered at all, then forestry output should be decreased in Japan, (2) when public benefit is considered, a “reverse domain” (in which desirable outputs increase) certainly exists within the range of ϕ^o_J =0 − 1.0(10¹⁰$/year) in the three-dimensional ϕ^o_K spaces, and (3) when the agriculture, forestry, and fishery sectors are aggregated into one sector and public benefits from these sectors are evaluated together, this “reverse domain”exists within the range of ϕ^o_J =0 − 70(10¹⁰$/year) in the same spaces.

本稿は, ノンパラメトリック・アプローチを用いて日本の製材生産における技術効率性を分析したものである. 分析の際, 各都道府県を一つの生産単位とし, 投入要素は国産材入荷量, 外材入荷量, 従業者数, 動力出力数を, また産出は, 建築用製材出荷量とその他用製材出荷量とした. 分析の結果, 平均的な技術効率性は0.958, 規模効率性は0.988 であり, 高い技術効率性に恵まれていることが示された. ノンパラメトリック手法を用いた事後検定によると, 時間とともに技術効率性が減っていること, 生産の活発な地域が高い技術効率性を示しているものの, 動力出力数や素材の樹種とは関係がないことが示された.

人工林の施業計画の中で間伐作業と枝打ち作業は特に緊急性が低いと考えられ, 経済環境の悪化から遅れることが多い. 間伐作業など個々の森林作業の森林の育成への影響を評価する方法を考案した. システム収穫表の手法は林分全体の成長予測を行うのに対し, 今回は施業計画の作業実施後, 残すべき一部の立木に着目して計画との乖離を評価した. 林分密度管理図と施業体系図を活用し, 間伐効果を明示し機会費用の考え方を導入した. 間伐実施と未実施の場合を比較し, 各々の場合の10 年後と50 年後の森林の状態を予測した. そして未実施の場合の損失（機会費用）を試算した.

直下型の航空機レーザー測距で林冠断面を計測し, 毎木調査結果と対応させて広範囲の林分蓄積量等を推定する場合, レーザーが切り取る垂直方向の林冠断面は立木の中心を通過しているとは限らないため, 樹冠形状や立木密度によってはその林分を代表する標本断面とはなっていない可能性がある. そこで単木単位で樹冠断面から推定される樹冠投影立体体積の期待値を理論的に考察すると, 樹冠形状に関わらず推定に偏りはないものと考えられた. ただし推定値のばらつきは林冠閉鎖度が疎になるほど, また樹冠形状が先細りになるほど大きくなることが示唆された.

富山県西部の森林にはカワイダニスギと呼ばれるスギ品種が多く植えられており, これらは2004 年の台風23 号で甚大な被害を受けた. このスギ林木の風害の発生機構を検討するために「片持ち梁」理論に基づく林木の力学的モデルを構築した. モデルの構築に必要な樹幹形や樹幹ヤング率などの資料を富山県西部のカワイダニスギ林から収集した. 根返りモーメントは県内の3箇所のスギ林で測定した. このモデルに林木のサイズをインプットして, その木が根返りまたは幹折れのどちらの被害タイプを示すのかを推定した. このモデルの適合性を検討するため, カワイダニスギのサイズや被害タイプを調べた. 推定結果と観察結果とを比較したところ, 幹折れの正解率は高かったが, 根返りのそれは低かった. 幹折れの高さは推定値と観察値がほぼ一致した. 胸高直径が同じであれば樹高の高い林木は幹折れを, 低い林木は根返りを生じる傾向が認められた.

本研究では丸太生産と化石燃料代替としての木質バイオマス生産を考慮した森林管理のための動的計画法モデルを構築し, 丸太生産と木質バイオマス生産の最適な組み合わせを探求することにより, 木質バイオマス生産が森林の最適間伐計画に与える影響を分析した. ここでは, 森林が担う2 つの温室効果ガス削減効果: 1）丸太生産を通した直接的な炭素吸収効果, 2）化石燃料代替のための木質バイオマス利用による炭素排出削減効果, を考慮した. 丸太生産については丸太価格, また木質バイオマス生産については熱効率換算によるA 重油価格を用いてそれぞれの便益を算出し, 丸太生産に伴う歩留率(丸太として利用される割合) を新たな決定変数として木質バイオマス生産の最適化を行った. 分析の結果, 1 リットル当たりのA 重油価格が80 円以上になると丸太歩留率は最小値, 以下になると最大値になり, 木質バイオマス生産, または丸太生産に特化する計画がそれぞれの場合に対し最適となった. すなわち, このA 重油価格が閾値となり管理計画は極端に変化する. また温室効果ガス削減効果について木質バイオマス生産と丸太生産に特化した最適解を比較した結果, 熱効率換算の違いにより材積1m³ 当たりの炭素削減効果は丸太生産が大きくなるものの, 間伐材による効果を考慮しない場合,間伐材による化石燃料の代替効果を常に伴う木質バイオマス生産が丸太生産に比べて炭素削減効果が上回る結果となった.