北亚热带日本落叶松纸浆林最佳轮伐期研究
|
摘要
日本落叶松(Larix kaempferi)是北亚热带地区重要的引种栽培树种,目前该区域的栽培面积已超过33.3万公顷。北亚热带中山山地是我国日本落叶松最适宜引种区,在该地区,日本落叶松表现出早期速生、适应性强、材质优良、不与农业争地、抗冰雪及病虫等自然灾害能力强等特性。日本落叶松是优良的造纸原料,相比其他种类落叶松而言,其生物质产量和纸浆得率最高,卡伯值较低,纤维最长,打浆能耗低,制浆造纸工艺易于控制,成纸性能稳定,最具造纸原料应用潜力。作为短周期纸浆用材树种,日本落叶松对实现林纸一体化有着广阔的市场前景。但由于该区日本落叶松引种时间较短,对纸浆材的轮伐收获周期尚未进行针对性的研究,因此如何科学合理的采伐利用成为当前日本落叶松培育中亟待解决的问题,因此本研究通过对日本落叶松各种成熟龄的探讨,开展了日本落叶松最佳轮伐期的研究,以期为北亚热带日本落叶松的生长经营提供经营指导。主要研究方法和结论如下:
通过生长模型法和多元非线性回归的方法研究了北亚热带日本落叶松的数量成熟龄,最终优选出Schumacher修正模型建立的蓄积量生长方程,求算出不同立地质量和林分密度的日本落叶松的数量成熟龄为28-42a,林分密度越大,立地指数越高,则数量成熟龄越大。
通过测定北亚热带日本落叶松不同年龄植株的制浆造纸特性、纤维特性和纸浆物理强度,在对比不同指标间随年龄变化趋势和差异的基础上,综合判断得出了北亚热带日本落叶松的制浆工艺成熟龄为13-22a。同时,利用方差分析的方法对不同立地质量、不同林分密度的日本落叶松和不同树体部位(上部、中部、下部树干和枝)的制浆性能进行了分析,得出结论为立地质量和林分密度对日本落叶松制浆造纸性能无显著影响,不同部位树干间差异也不显著,但树干造纸性能均显著优于枝。
在讨论适用于林业经济分析的合理贴现率的基础上,通过改进后的DCF方法(折现金流)分析方法(土地期望值法LEV、年均净现值法ANPV和内部收益率法IRR)和目前较为先进的实物期权法(Real Options)分析技术,探讨了日本落叶松纸浆林的经济成熟龄。得出的结论为立地指数为13、15、17、19和21的日本落叶松林分的LEV成熟龄分别为25-26a、24-26a、22-24a、20-23a、20-21a;ANPV成熟龄分别为24a、23-24a、21-22a、18-21a、18-19a; IRR经济成熟龄分别为26-27a、24-26a、21-24a、18-22a、17-19a;在当前价格水平下,五种立地指数的实物期权经济成熟龄分别为25-27a、24-26a、22-23a、21-22a、19-22a。分析结果还表明,立地质量越高或林分密度(合理范围内)越高,则经济成熟龄越小,经济收益越高。
对不同立地质量和林分密度的日本落叶松林分价格、贴现率和营林成本在假设水平下的变化基础上的经济收益变化进行了敏感性分析。结果表明,纸浆材价格的降低、营林成本和贴现率的上升,均使得日本落叶松纸浆林的经济收益减小;最显著影响因素是贴现率,其次是纸浆材价格及营林成本。
通过实物期权法分析日本落叶松纸浆林的经济成熟龄,得出了不同林龄的各种日本落叶松林分的采伐价格阈值(Harvest price thresholds)和最短轮伐期。采伐价格阈值的涵义是某一林龄的林分实施采伐的纸浆材最低价格,即当某一林龄的日本落叶松林分大于该林龄对应的价格阈值时应选择采伐策略,而小于此阈值则应选择等待策略。最短轮伐期的涵义是在纸浆材价格较高时不同日本落叶松林分的最短采伐林龄,而在低于此林龄时,无论纸浆材价格为何值均应选择等待策略(即推迟采伐)。结果显示,日本落叶松纸浆林的采伐价格阈值均随林龄的增大而减小,且随立地指数的增加和林分密度的增加而减小。最短轮伐期具有随林分密度的增加而减小的趋势,五种立地指数(13、15、17、19和21)的日本落叶松纸浆林的在较高价格情形下的最短轮伐期分别为22-25a、21-23a、19-21a和17a。
依据层次分析法和日本落叶松纸浆林轮伐期确定要素,遵循“以工艺成熟为基础,重点考虑经济成熟,兼顾数量成熟”的理念,构建了日本落叶松纸浆林最佳轮伐期的综合决策体系,确定了不同成熟龄的评价权重。通过综合决策体系各指标的权重,得出不同立地指数的日本落叶松的最佳综合轮伐期为:立地指数为13和15的日本落叶松林分的最佳综合轮伐期为18-19a;而立地指数为17、19和21的日本落叶松林分为17-18a。最佳轮伐期问题是一个多准则的综合决策的复杂问题,需要综合各种成熟评价指标进行综合判断。森林的经济成熟是国外许多学者研究森林的最佳轮伐期所重点讨论的问题,我国拥有着丰富的用材林资源,随着我国市场化进程的不断加快和木材需求的不断增加,从经济成熟角度来探讨最佳轮伐期将是众多国内学者研究的热点和重点。在本研究中着重讨论的实物期权法,充分考虑了日本落叶松经营过程中的价格变化风险和人的管理柔性价值,为日本落叶松的市场化经营提供了稳健且灵活的经营策略,是评价森林经济成熟的更为科学的方法。
综上所述,本研究论述的各种日本落叶松成熟龄及综合决策最佳轮伐期,为北亚热带日本落叶松栽培区域的生产和经营提供了解决日本落叶松森林资源经营和利用的指导性方法和理论依据。
Larix kaempferi is one of important tree species in north sub-tropical area in China, where is the most appreciate area for L. kaempferi cultivation and in which it had been planted over 0.33 million ha. In this area, L. kaempferi grows fast at early ages and usually has better wood properties, and never occupies lands for agriculture with better acclimation ability and anti-disaster ability. Moreover, it had been proved that L. kaempferi is one kind of good pulping material compared with other kind of Larix because of its higher biomass yield and pulping yield, longest fiber, lowest kappa number and pulp beating energy consumption, easier controlled pulping procedure , stable properties of paper and the potential for paper-making. Therefore, L. kaempferi has broadly market prospects and it is significant to forest-pulp-paper integration as a species to short-rotation and pulping-making. However, due to relatively short introdction period of L. kaempferi in this area, the rotation problem of has not been researched. Consequently, how to harvest L. kaempferi scientifically has become a significant problem in L. kaempferi plantation management. Therefore, this paper studied the optimal rotation age of L. kaempferi by discussion of various maturity ages in order to guiding management and production in this area.
The main methods and conclusion are:
The Quantitative Maturity Age for L. kaempferi was studied by Growth Model method and non-linear regression technology. The results showed that Extended-Schumacher model was perfect to describe the stand stocks growth for L. kaempferi. The Quantitative Maturity Age of L. kaempferi in various site index and stand density ranged from 28-42a, and the stand with higher site index and stand density usually had older Quantitative Maturity Age.
The Technology Maturity Age for L. kaempferi was discussed with synthetic judgment of pulping-making properties, fiber characters and physical strength of pulp of L. kaempferi with different age in sub-tropical area. The result indicated that Technology Maturity Age of L. kaempferi is 13-22a. Furthermore, the differences of pulping properties of L. kaempferi in various site index, stand density and different parts of the tree(upper, middle and lower parts of trunk and branch) were researched by ANOVA analysis. The results showed that there are no different between L. kaempferi of various site index and stand density, however, the pulping-properties of trunk is better than branch significantly. Moreover, the difference between different parts of trunk is not significant.
The Economical Maturity Ages for L. kaempferi were analyzed by Improved-DCF method (Land expectation value, Annual net present value and Inner return of rate) and Real Options method which is advanced method at present, based on discussion of the appreciate discount rate for forestry management. The results indicated that the LEV maturity ages for L. kaempferi in site index 13,15,17,19 and 21 were 25-26a、24-26a、22-24a、20-23a、20-21a respectively; the corresponding ANPV maturity age were 24a、23-24a、21-22a、18-21a、18-19a respectively and the corresponding IRR maturity age were 26-27a、24-26a、21-24a、18-22a、17-19a respectively; Meanwhile, the RO maturity age were 25-27a、24-26a、22-23a、21-22a、19-22a respectively at the current pulpwood price level. The results also showed that the L. kaempferi plantation with higher site index or stand density (within reasonable range) usually had more profitable gain and shorter economical maturity age.
Sensitivity analysis was evaluated to L. kaempferi in various site index and stand density with the changing of pulpwood price, discount rate and the cost of plantation management. It was indicated that the economical gain of pulpwood plantation would decreased with the increase of discount rate and decrease of pulpwood price and management cost; Furthermore, the most influential factor is discount rate, followed by pulpwood price and management cost.
The Harvest Price Thresholds and the Shortest Rotation Age were concluded by discussing the economical maturity age of L. kaempferi with Real Options method. The Harvest Price Thresholds means the lowest wood price to harvest a plantation at a certain age, which means Harvest Option should be chosen when the wood price was higher than the price threshold at a certain age, otherwise Wait Option (deferring harvest) should be chosen. The Shortest Rotation Age means the shortest rotation age of a plantation as the wood price keeping at a high level, in other words, the Wait Option should be taken whatever the wood price is when the stand age to be smaller than the shortest rotation age. The results showed that the Harvest Price Thresholds decreased with the increasing of stand density and the Shortest Rotation Age of L. kaempferi plantation with the site index 13,15,17,19 and 21 were 22-25a、21-23a、19-21 and 17a respectively.
The Integrated Decision-Making System of the optimal rotation age of L. kaempferi was established by Analytic Hierarchy Process (AHP) technique, following the concept of“Based on technology maturity, focused on economical maturity age, and take Quantitative maturity into consideration”. The optimal rotation age of various L. kaempferi plantation with different site index were figured out by the weight of various factors determined by Integrated Decision-Making System, and it was indicated that the optimal rotation age of L. kaempferi plantation with site index 13 and 15 were18-19a, and the plantation with site index 17,19 and 21 were 17-18a.
The Optimal Rotation Age is a complex integrated multiple-criteria problem which needs to be evaluated by various maturity criteria. Moreover, the economical maturity problem is a focus issue in forest management discussed by researchers all over the world. Furthermore, it will be the hotspot and focusing point that considering the optimal rotation age from economical maturity aspect in China, because the rich timber forest resource and the accelerating process of market. In this study, the Real Options method was the main method to cope with rotation age, as the pulpwood price fluctuation and management flexibility were taken fully account, which has provided flexible and sound management strategy and could be viewed as a preferable method to evaluate forest economical maturity age.
As mentioned above, the Integrated Decision-Making system and various maturity ages of L. kaempferi concluded in this study have provided guidance approach and theoretical basis for L. kaempferi management and production in sub-tropical area in China.
通过生长模型法和多元非线性回归的方法研究了北亚热带日本落叶松的数量成熟龄,最终优选出Schumacher修正模型建立的蓄积量生长方程,求算出不同立地质量和林分密度的日本落叶松的数量成熟龄为28-42a,林分密度越大,立地指数越高,则数量成熟龄越大。
通过测定北亚热带日本落叶松不同年龄植株的制浆造纸特性、纤维特性和纸浆物理强度,在对比不同指标间随年龄变化趋势和差异的基础上,综合判断得出了北亚热带日本落叶松的制浆工艺成熟龄为13-22a。同时,利用方差分析的方法对不同立地质量、不同林分密度的日本落叶松和不同树体部位(上部、中部、下部树干和枝)的制浆性能进行了分析,得出结论为立地质量和林分密度对日本落叶松制浆造纸性能无显著影响,不同部位树干间差异也不显著,但树干造纸性能均显著优于枝。
在讨论适用于林业经济分析的合理贴现率的基础上,通过改进后的DCF方法(折现金流)分析方法(土地期望值法LEV、年均净现值法ANPV和内部收益率法IRR)和目前较为先进的实物期权法(Real Options)分析技术,探讨了日本落叶松纸浆林的经济成熟龄。得出的结论为立地指数为13、15、17、19和21的日本落叶松林分的LEV成熟龄分别为25-26a、24-26a、22-24a、20-23a、20-21a;ANPV成熟龄分别为24a、23-24a、21-22a、18-21a、18-19a; IRR经济成熟龄分别为26-27a、24-26a、21-24a、18-22a、17-19a;在当前价格水平下,五种立地指数的实物期权经济成熟龄分别为25-27a、24-26a、22-23a、21-22a、19-22a。分析结果还表明,立地质量越高或林分密度(合理范围内)越高,则经济成熟龄越小,经济收益越高。
对不同立地质量和林分密度的日本落叶松林分价格、贴现率和营林成本在假设水平下的变化基础上的经济收益变化进行了敏感性分析。结果表明,纸浆材价格的降低、营林成本和贴现率的上升,均使得日本落叶松纸浆林的经济收益减小;最显著影响因素是贴现率,其次是纸浆材价格及营林成本。
通过实物期权法分析日本落叶松纸浆林的经济成熟龄,得出了不同林龄的各种日本落叶松林分的采伐价格阈值(Harvest price thresholds)和最短轮伐期。采伐价格阈值的涵义是某一林龄的林分实施采伐的纸浆材最低价格,即当某一林龄的日本落叶松林分大于该林龄对应的价格阈值时应选择采伐策略,而小于此阈值则应选择等待策略。最短轮伐期的涵义是在纸浆材价格较高时不同日本落叶松林分的最短采伐林龄,而在低于此林龄时,无论纸浆材价格为何值均应选择等待策略(即推迟采伐)。结果显示,日本落叶松纸浆林的采伐价格阈值均随林龄的增大而减小,且随立地指数的增加和林分密度的增加而减小。最短轮伐期具有随林分密度的增加而减小的趋势,五种立地指数(13、15、17、19和21)的日本落叶松纸浆林的在较高价格情形下的最短轮伐期分别为22-25a、21-23a、19-21a和17a。
依据层次分析法和日本落叶松纸浆林轮伐期确定要素,遵循“以工艺成熟为基础,重点考虑经济成熟,兼顾数量成熟”的理念,构建了日本落叶松纸浆林最佳轮伐期的综合决策体系,确定了不同成熟龄的评价权重。通过综合决策体系各指标的权重,得出不同立地指数的日本落叶松的最佳综合轮伐期为:立地指数为13和15的日本落叶松林分的最佳综合轮伐期为18-19a;而立地指数为17、19和21的日本落叶松林分为17-18a。最佳轮伐期问题是一个多准则的综合决策的复杂问题,需要综合各种成熟评价指标进行综合判断。森林的经济成熟是国外许多学者研究森林的最佳轮伐期所重点讨论的问题,我国拥有着丰富的用材林资源,随着我国市场化进程的不断加快和木材需求的不断增加,从经济成熟角度来探讨最佳轮伐期将是众多国内学者研究的热点和重点。在本研究中着重讨论的实物期权法,充分考虑了日本落叶松经营过程中的价格变化风险和人的管理柔性价值,为日本落叶松的市场化经营提供了稳健且灵活的经营策略,是评价森林经济成熟的更为科学的方法。
综上所述,本研究论述的各种日本落叶松成熟龄及综合决策最佳轮伐期,为北亚热带日本落叶松栽培区域的生产和经营提供了解决日本落叶松森林资源经营和利用的指导性方法和理论依据。
Larix kaempferi is one of important tree species in north sub-tropical area in China, where is the most appreciate area for L. kaempferi cultivation and in which it had been planted over 0.33 million ha. In this area, L. kaempferi grows fast at early ages and usually has better wood properties, and never occupies lands for agriculture with better acclimation ability and anti-disaster ability. Moreover, it had been proved that L. kaempferi is one kind of good pulping material compared with other kind of Larix because of its higher biomass yield and pulping yield, longest fiber, lowest kappa number and pulp beating energy consumption, easier controlled pulping procedure , stable properties of paper and the potential for paper-making. Therefore, L. kaempferi has broadly market prospects and it is significant to forest-pulp-paper integration as a species to short-rotation and pulping-making. However, due to relatively short introdction period of L. kaempferi in this area, the rotation problem of has not been researched. Consequently, how to harvest L. kaempferi scientifically has become a significant problem in L. kaempferi plantation management. Therefore, this paper studied the optimal rotation age of L. kaempferi by discussion of various maturity ages in order to guiding management and production in this area.
The main methods and conclusion are:
The Quantitative Maturity Age for L. kaempferi was studied by Growth Model method and non-linear regression technology. The results showed that Extended-Schumacher model was perfect to describe the stand stocks growth for L. kaempferi. The Quantitative Maturity Age of L. kaempferi in various site index and stand density ranged from 28-42a, and the stand with higher site index and stand density usually had older Quantitative Maturity Age.
The Technology Maturity Age for L. kaempferi was discussed with synthetic judgment of pulping-making properties, fiber characters and physical strength of pulp of L. kaempferi with different age in sub-tropical area. The result indicated that Technology Maturity Age of L. kaempferi is 13-22a. Furthermore, the differences of pulping properties of L. kaempferi in various site index, stand density and different parts of the tree(upper, middle and lower parts of trunk and branch) were researched by ANOVA analysis. The results showed that there are no different between L. kaempferi of various site index and stand density, however, the pulping-properties of trunk is better than branch significantly. Moreover, the difference between different parts of trunk is not significant.
The Economical Maturity Ages for L. kaempferi were analyzed by Improved-DCF method (Land expectation value, Annual net present value and Inner return of rate) and Real Options method which is advanced method at present, based on discussion of the appreciate discount rate for forestry management. The results indicated that the LEV maturity ages for L. kaempferi in site index 13,15,17,19 and 21 were 25-26a、24-26a、22-24a、20-23a、20-21a respectively; the corresponding ANPV maturity age were 24a、23-24a、21-22a、18-21a、18-19a respectively and the corresponding IRR maturity age were 26-27a、24-26a、21-24a、18-22a、17-19a respectively; Meanwhile, the RO maturity age were 25-27a、24-26a、22-23a、21-22a、19-22a respectively at the current pulpwood price level. The results also showed that the L. kaempferi plantation with higher site index or stand density (within reasonable range) usually had more profitable gain and shorter economical maturity age.
Sensitivity analysis was evaluated to L. kaempferi in various site index and stand density with the changing of pulpwood price, discount rate and the cost of plantation management. It was indicated that the economical gain of pulpwood plantation would decreased with the increase of discount rate and decrease of pulpwood price and management cost; Furthermore, the most influential factor is discount rate, followed by pulpwood price and management cost.
The Harvest Price Thresholds and the Shortest Rotation Age were concluded by discussing the economical maturity age of L. kaempferi with Real Options method. The Harvest Price Thresholds means the lowest wood price to harvest a plantation at a certain age, which means Harvest Option should be chosen when the wood price was higher than the price threshold at a certain age, otherwise Wait Option (deferring harvest) should be chosen. The Shortest Rotation Age means the shortest rotation age of a plantation as the wood price keeping at a high level, in other words, the Wait Option should be taken whatever the wood price is when the stand age to be smaller than the shortest rotation age. The results showed that the Harvest Price Thresholds decreased with the increasing of stand density and the Shortest Rotation Age of L. kaempferi plantation with the site index 13,15,17,19 and 21 were 22-25a、21-23a、19-21 and 17a respectively.
The Integrated Decision-Making System of the optimal rotation age of L. kaempferi was established by Analytic Hierarchy Process (AHP) technique, following the concept of“Based on technology maturity, focused on economical maturity age, and take Quantitative maturity into consideration”. The optimal rotation age of various L. kaempferi plantation with different site index were figured out by the weight of various factors determined by Integrated Decision-Making System, and it was indicated that the optimal rotation age of L. kaempferi plantation with site index 13 and 15 were18-19a, and the plantation with site index 17,19 and 21 were 17-18a.
The Optimal Rotation Age is a complex integrated multiple-criteria problem which needs to be evaluated by various maturity criteria. Moreover, the economical maturity problem is a focus issue in forest management discussed by researchers all over the world. Furthermore, it will be the hotspot and focusing point that considering the optimal rotation age from economical maturity aspect in China, because the rich timber forest resource and the accelerating process of market. In this study, the Real Options method was the main method to cope with rotation age, as the pulpwood price fluctuation and management flexibility were taken fully account, which has provided flexible and sound management strategy and could be viewed as a preferable method to evaluate forest economical maturity age.
As mentioned above, the Integrated Decision-Making system and various maturity ages of L. kaempferi concluded in this study have provided guidance approach and theoretical basis for L. kaempferi management and production in sub-tropical area in China.
引文
艾卿,梁建萍,江萍等.水杉木材化学成分变异模式及其纸浆林的采伐年龄[J].华东森林经理,2004,18(4):8~12.
曹武,李注滋. AHP在林区路网多目标综合决策中的作用[J].中南林业科技大学学报,2008, 28(3):152~155.
蔡文祥. PUS-01阴离子淀粉在马尾松枝桠材浆造纸中的应用研究[J].造纸科学与技术, 2001,20(1):25~27.
陈安宁.自然资源利用贴现率探讨[J].资源科学,2000,22(3):13~16.
陈平留,刘健,郑德祥.速生丰产优质杉木林经济效益分析及伐期的确定[J].林业科学,2001,37 (专刊1):47~51.
陈祥伟,王文波,夏祥友.小流域水源涵养林优化配置[J].应用生态学报,2007,18(2):267~271.
陈永芳.人工林生长与收获预测模型的研究[J].林业资源管理, 2001(1): 50~54.
陈文汇,胡明形,刘俊昌.中国木材价格波动的动态均衡模型及实证分析[J].统计与信息论坛,2001,25(1):58~62.
陈则生.杉木人工林经济成熟龄的研究[J].华东森林经理,2004,18(3):1~5.
邓立斌,刘德晶.基于层次分析法的尖峰岭自然保护区生态评价[J].中南林业科技大学学报,2010, 30(7):26~31.
丁贵杰.马尾松人工纸浆材林经济成熟的研究[J].林业科学,2000,36(1):15~20.
丁凤梅,鲁法典,侯占勇等.杨树速生丰产林经济成熟与经济效益分析[J].山东农业大学学报(自然科学版), 2008,39(2):233~238.
丁凤梅,鲁法典,王迎.不同造林密度杨树速生丰产林成熟龄的研究[J].河北林果研究,2007(3):242~246.
杜纪山.林木生长和收获预估模型的研究动态[J].世界林业研究,1999,1(4):19~22.
董希斌,王立海.落叶松人工林采集作业模式的优选[J].林业科学,2007,43(9):46~52.
董健,赵文华,黄国学等.日本落叶松纸浆林合理轮伐期研究[J].辽宁林业科技,2001(1):11~14.
董健,赵文华,王喜武等.日本落叶松纸浆林造纸性能及工艺成熟期的研究[J],辽宁林业科技, 1997(1):26~29.
费世民,向成华.四川盆地丘陵区坡地农林复合系统林带类型、农作物复种方式的选择[J].林业科学,2000,36(1):21~27.
冯佳多(德),惠刚盈.森林生长与干扰模拟[M]. IUFRO-SPDC Textbook Project No. 2 Gottingen: Cuvillier,1998:18.
冯祥锦,黄和亮.工业原料林投资经济效果评价利率选取的探讨[J].中国林业经济,2006,5(78):14~15.
傅家骥,仝允桓.工业技术经济学[M].北京:清华大学出版社,1991:51~53.
高泽兵,李卫忠,贺征兵.巴山松生长及数量成熟龄初步研究[J].西北林学院学报,2009, 24(2): 130~135.
管兰华,曹建,祁万宜等.几种落叶松在鄂西生长比较研究[J].林业科技,2005,30(1):14~17. 国家林业局.中国第七次森林资源清查报告[M].北京:中国林业出版社,2009:4~5.
郭晋平,王惠恭,王世昌等.五台山华北落叶松人工林数量成熟龄及其经营[J].林业科技通讯,1996,10:29~30.
郭世芳,张丽华,丁长富等.内蒙古大兴安岭林区人工落叶松林数量成熟龄及工艺成熟龄的确定[J]. 内蒙古林业调查设计,2003,28(4):28~29.
何晓群,刘文卿.应用回归分析(第二版)[M].北京:中国人民大学出版社,2007:107.
胡卫平,王献荣,徐剑青.浙西山区天然林阔叶树数量成熟龄的确定[J].华东森林经理,2008,22(1):36~39.
黄东,彭道黎,郑小贤.净现值法在林分经济成熟中的应用探讨[J].中南林业调查规划, 2004,23(1):50~53.
黄国胜,王雪军,孙玉军等.河北山区森林生态环境质量评价[J].北京林业大学学报,2005,27(5):75~80.
黄启堂,游永生,黄榕辉等.运用层次分析法评价木质藤本观赏植物资源[J].福建林学院学报,1997, 17(3): 269~272.
黄庆丰,孙启祥,吴泽民等.长江滩地杨树人工林主伐年龄的研究[J],林业科学,2002,38(6):154~158.
黄清麟,冯文钦,林云青.短周期阔叶林经济成熟龄的研究[J].福建林学院学报,1997,17 (4):344~347.
黄荣凤,鲍甫成,张冬梅.杨树材性成熟龄模型的建立及树体内幼龄材的分布[J].林业科学, 2005,41(3):103~109.
贺铿.关于通货膨胀预期的问题[J].求是, 2010 (3): 46~47.
江波,袁位高,戚连忠等.杨树人工林合理轮伐期的研究[J].浙江林学院学报,2001,18(1):26~31.
蒋伊尹,李凤日.兴安落叶松天然林生长与收获的研究[J].林业科学,1989,25(5):477~472.
焦媛媛,韩文秀,杜军.确定最优轮伐期的实物期权方法[J].西北农林科技大学学报(自然科学版), 2003,31(5): 169~172 .
揭建林,詹有生,吴克选.江西省杉木人工林合理轮伐期的研究[J].江西林业科技,2006(6):4~8.
亢新刚.森林资源经营管理[M].北京:中国林业出版社,2001:168~201.
亢新刚,黄庆丰.华北次生林结构调整研究[J].北京林业大学学报,2000,22(3):41~43.
李春明.抚育间伐对人工林分生长的影响研究[D].中国林业科学研究院硕士学位论文,2003,9~10.
李春静,智长贵,何军旗.杨树农田防护林带全林生长模型研究[J].信阳示范学院学报(自然科学版), 2007,20(3):325~327.
李进,陈如轩.长岭岗林场日本落叶松材积生长规律研究[J].现代农业科技,2008, 4:10~11
梁红,张仲芳.我国原木和木浆进口数量与价格变化及其影响因素分析[J].贵州财经学院学报, 2006(5): 29~33.
林金国,陆继策,林凤涛等.运用AHP法评价地板木树种资源[J].东北林业大学学报,2000,28(4):100~102.
林如青,郑少玲.人工林生长与收获预测模型应用探讨[J]林业资源管理,2001(2): 48~50.
林山海.杉木采伐年龄的研究[J].林业勘察设计,2008(2):206~213.
刘洪斌.纤维特性与纸页撕裂性能关系的研究[D].天津科技大学硕士学位论文,2004.
刘平,马履一,王玉涛等.油松中幼人工林单木胸径生长模型研究[J].沈阳农业大学学报,2009,40(2):197~201.
刘平,王宁,孙清江.新疆伊犁地区速生杨树生长模型及数量成熟研究[J].新疆农业大学学报. 2003,26(4):45~48.
刘瑞龙,王发武,石山等.中国农业百科全书(林业卷)[M].北京:农业出版社,1989:123~631..
刘盛全,江泽慧.不同种群白桦纤维形态特征变异及优良种群选择[J].世界林业研究,1995(8)专集: 274~278.
刘玉雪,王章虎.层次分析法(AHP)在风险分析与评价中的应用[J].工程与建设,2008,22(1):22~24.
吕郁彪.马尾松造纸原料林主伐年龄的研究[J].中南林业调查规划,1997,16(2):19~21.
马常耕.落叶松种和种源选择[M].北京:北京农业大学出版社,1992:4~5.
马常耕,王建华.我国发展日本落叶松区域的探讨[J].林业科技通讯,1990(4):26~28.
马丰丰,贾黎明.林分生长和收获模型研究进展[J].世界林业研究,2008,21(3):21~27.
马利春,刘志超.湿地松造纸主伐年龄的研究[J].四川林勘设计,1995,3:22~30.
孟春,王立海.小兴安岭天然次生林经营模拟与评价[J].东北林业大学学报,2005,33(6):25~29.
孟全省.确立经济成熟在编制森林经营方案中的指导地位[J].世界林业研究,1995,3:21~26.
孟宪宇.测树学[M]北京:中国林业出版社,2006:59~276
皮尔森·皮特H.林业经济学概论[M].张道卫译.北京:中国林业出版社,1994:112~119.
钱志能,龚益广,李国新.西江林场杉木的经济轮伐期[J].中南林学院学报,2006,26(5):117~120.
秦建华.林分生长与产量模型系统研究综述[J].林业科学,2002,38(1):122~129.
施本俊.高峰林场杉木第二代人工林主伐年龄[J].云南林业调查规划设计,2000,25(2):7~9.
司海忠,杨双,李晶等.日本落叶松引种研究[J].林业科技通讯,1999(11):5~7.
石丽萍,冯仲科.人工林生长与收获预测模型的基本方法[J].北京林业大学学报,2005,27(增刊2):222~225.
石淑兰,谢新良,胡惠仁等.不同树龄日本落叶松的化学组成与制浆特性[J].林业科学, 2006 ,42(7):90~94.
施新程,谢文全.豫南杉木经济成熟龄研究[J],安徽农业科学,2009,37(23):11281~11283.
施新程,王洪友,黄旺志等.豫南杉木人工林主伐年龄研究[J].福建林业科技,2009,36(3):49~ 53.
沈慧,姜凤岐.水土保持林土壤改良效益评价指标体系的研究[J].北京林业大学学报,2000,22(5):96~99.
盛炜彤,惠刚盈,罗云伍.大岗山杉木人工林主伐年龄的研究[J].林业科学研究,1991,4(2):113~ 121.
盛炜彤,惠刚盈,张守攻等.杉木人工林优化栽培模式[M].北京:中国科学技术出版社,2004:93.
苏金德,张锡象,李月英.造林密度对巨尾桉生长量与轮伐期的影响[J].林业科技开发,2000,14(4):15~17.
覃林,何义发.模糊综合评判法确定人工林主伐年龄的研究[J].湖北民族学院学报(自然科学版), 1999,17(2):51~54.
田志和,董健,王喜武等.日本落叶松木材纸浆性能及速生丰产林投入产出分析[J].辽宁林业科技, 1994(5):51~54.
唐守正,郎奎建,李海奎等.统计和生物数学模型计算(Forstat教程).北京:科学出版社,2009: 291~347.
童方平.湿地松纸浆材与建筑材定向培育技术研究[D].中南林学院硕士学位论文,2002:42~45.
童方平,龙应忠,吴际友等.我国主要立地火炬松纸浆材、建筑材林合理轮伐期的研究[J].林业科技通讯,1997 (11) :9~12.
王炳云,孙述涛.木材解剖分子生长锥法确定数量成熟龄[J].华东森林经理,1994,8(2):30~33.
王军辉,陆熙娴,张守攻.落叶松纸浆造纸适应性及开发利用前景[J].中国造纸, 2004,23(6):47~52.
王军辉,张守攻,石淑兰等.日本落叶松AS-AQ浆和KP浆的漂白特性比较[J].北京林业大学学报,2006,28(1):93~97.
王军辉,张红杰,石淑兰等.楸树枝桠材硫酸盐法制浆的研究[J].中国造纸学报,2010,25(4):10~13.
王立海,杨学春,郝霞等.层次分析法在集材方式选择上的应用[J].东北林业大学学报,1996, 24(1):68~71.
王乃江,张文辉,同金霞等.黄土高原蔡家川林场森林质量评价[J].林业科学,2010,46(9):7~14.
王树力,李凤山,胡秀云.小黑杨纸浆林经济效益的研究[J].东北林业大学学报,1998,26(1):45~48.
王树力,吴济生,仲崇淇.长白落叶松纸浆林木材材性及纸浆特性的研究[J].林业科学,1997,33(3):283~288.
魏均.基于实物期权方法的林业投资项目评价问题的研究[D].北京林业大学硕士学位论文,2006:1~58.
魏均,梅斌,张绍文.基于实物期权的林业项目评估[J].商业研究,2006(6):44~47.
韦新良,郭仁鉴,赵斌.浙江省马尾松天然林生长模型及采伐年龄的确定[J].浙江林学院学报,2001,18(4):333~336.
吴立勋,汤玉喜,吴敏等.滩地不同密度杨树人工林主伐年龄的研究[J].湖南林业科技,2003,30 (3):24~26.
吴喜之.统计学:从数据到结论(第三版)[M].北京:中国统计出版社,2009:132~136.
谢新良.日本落叶松制浆造纸特性的研究[D].天津科技大学硕士学位论文,2003:1~14.
徐宏远,陈章水.不同密度I-69杨丰产林林分的生长预测及数量成熟龄[J].东北林业大学学报,1994,22(2):17~23.
徐有明.火炬松纸浆材材性变异和优质原料培育期的确定[J].林业科学研究,1995, 8(5):544~549
徐有明.木材学[M],北京:中国林业出版社,2006:1~8.
徐有明,方洪元,黄吉田.意杨纸浆材材性变异的研究[J].木材工业,1994,8(1):38~44.
徐有明,林汉,万伏红.马尾松纸浆材材性变异和采伐林龄的确定[J].浙江林学院学报,1997,14(1):8~15.
杨斌,杨国州,张延东.运用层次分析法优选临夏北塬农田防护林树种[J].林业科学,2006,42(6): 49~55.
于长玲,陈海龙,张思宏等.长白落叶松人工林最佳经济成熟龄的确定[J].林业科技,1999,24(1): 17~19
喻庆国.基于自然度的森林景观时空分异研究[D].北京林业大学博士学位论文,2007:49~52.
张建国,段爱国.理论生长方程对杉木人工林林分直径结构的模拟研究[J].林业科学,2003,39(6): 51~56.
张建国,刘盛全. I-69杨木材纤维形态和化学成分的研究[C].中国林学会木材科学分会第九次学术研讨会论文集,2004:1~8.
张钦相,陈绘画.杉木人工林经济成熟初探[J].浙江林学院学报,1995,12(1):106~109.
张宋智,王军辉,张守攻等.日本落叶松AS-AQ法制浆特性[J].东北林业大学学报,2005, 33(2):34~37.
张永峰.林分数量成熟与林木数量成熟关系初探[J].北京林业大学学报,1988,10(增刊):22~26.
赵刚,姜以斌.长白落叶松人工林三种成熟龄的研究[J].辽宁林业科技,1995(2):30~34.
郑小贤.森林经营与森林文化[J].中国林业教育,2000(2):18~20.
中国农业银行.凭证式国债利率. http://www.95599.sh.cn/lcms/bank/quotation/pzsgzratelist_cx.jsp.
中国造纸协会.中国造纸工业2009年度报告[J].造纸信息, 2010(6): 6~15.
中华人民共和国林业部.中华人民共和国林业行业标准——日本落叶松速生丰产林LY1058- 91[S]. 1991.
中华人民共和国统计局.中国统计年鉴[M].北京:中国统计出版社,1991-2009.
纸和造纸杂志编辑部.我国造纸工业2009年纸和纸板产量和进口情况[J].纸和造纸,2010(3):1~2.
周彬,郑小贤,钟艳等.林分物种多样性指标体系的研究[J].北京林业大学学报,2002,24(2):22~26.
周国模,郭仁鉴,韦新良等.浙江省杉木人工林生长模型及主伐年龄的确定[J].浙江林学院学报, 2001,18(3): 219~222.
朱春全,刘晓东,宋显林等.集约与粗放经营杨树人工林生长规律[J].东北林业大学学报,1998, 26(1):14~18.
Gregory G R.森林资源经济学[M].许伍权,赵克绳,张承襄,等译.北京:中国林业出版社,1985:308~315.
Abildtrup. J. Optimal Thinning of Forest Stands: An Option Value Analysis—Preliminary Results [J]. Scandinavian Forest Economics, 1999(37):1~13.
Ananda J, Herath G. The Use of Analytic Hierarchy Process to Incorporate Stakeholder Preferences into Regional Forest Planning[J]. Forest Policy and Economics, 2003(5):13~26.
Duku-Kaakyire A, Nanang D M. Application of Real Option Theory to Forestry Investment Analysis [J]. Forest Policy and Economics,2004 (6):539~552.
Yoshimoto A. Searching For an Optimal Rotation Age for Forest Stand Management under Stochastic Log Prices [J]. European Journal of Operational Research, 1998(105):100~112.
Yoshimoto A. Stochastic Control Modeling for Forest Stand Management under Uncertain Price Dynamics through Geometric Brownian Motion[J]. Journal of Forest Research, 2002(7):81~90.
Brazee R J. Introduction—The Faustmann Formula: Fundamental To Forest Economics 150 Years After Publication [J]. Forest Science , 2001,47 (4):441~442.
Brazee R J, Mendelsohn R. Timber Harvesting with Fluctuating Prices [J]. Forest Science, 1988(34):359~372.
Brock W A, Rothschild M, Stiglitz J E. Stochastic Capital Theory: In Joan Robinson and Modern Economic Theory[M]. New York: New York University Press, 1989: 591~622.
Bruce D, Wensel L C. Modeling Forest Growth Approaches, Definitions and Problems In Proceeding of IUFRO Conference: Forest Growth Modeling and Prediction[R].USDA Forest Service General Technical Report NC-120. Minneapolis, Minnesota, 1987:1~8.
Brukas V, Thorsen B J, Helles F, et al. Discount Rate and Harvest Policy: Implications for Baltic Forestry[J].Forest Policy And Economics, 2001(2):143~156.
Bruce M, Kurt N. What is the Relevance of Option Pricing for Forest Valuation in New Zealand [J]. Forest Policy and Economics, 2010(12):299~307.
Cheng S, Xu Z, Su Y,et al. Spatial and Temporal Flows of China’s Forest Resource: Development of
A Framework for Evaluating Resource Efficiency[J].Ecological Economics, 2010(69):1405~1415. Clarke H R, Reed W J. The Tree-Cutting Problem in a Stochastic Environment [J]. Journal of Economic Dynamics and Control, 1989(13):569~595.
Curtis R O, Clendenen G W, Reukema D L, et al. A New Stand Simulator for Coastal Douglas firDFSM User’s Guide[R]. USDA For Ser Gen Tech Rep PNW, 1981:79.
Davis L S, Johnson K N. Forest management [M]. New York: Mcgraw-Hill Book Company,1987: 1~8.
Diaz-Balteiro L, Romero C. Making Forest Decisions With Multiple Criteria: A Review and An Assessment[J]. Forest Ecology and Management, 2008(255):3222~3241.
Dixit A K, Pindyck R S. Investment under Uncertainty[M]. Princeton University Press, 1994: 1~12. Faustmann M. Berechnung Ses Werthes, Welchen Waldboden Sowie Nach Nicht Haubare HolzbestanDe Fur Die Weldwirtschaft Besitze [J]. AIIegemeime Forest und Jagd Zeitung, 1849(25): 441.
Gilliams S, Raymaekers D, Muys B, et al. Comparing Multiple Criteria Decision Methods to Extend a Geographical Information System on Afforestation[J]. Computer Electronic of Agriculture, 2005(49): 142~158.
Grado S C, Strauss C H, Blankenhorn P R. Short Rotation Woody Biomass Plantations: Technical Requirements and Costs for Establishment[J] . Biomass, 1988, 17(4):277~289.
Guthrie G. Real Options in Theory And Practice [M]. USA, Oxford University Press,2009: 347~361.
Haight R G, Holmes T P. Stochastic Price Models and Optimal Tree Cutting: Results for Loblolly Pine [J]. Natural Resource Modeling,1991,5 (4):423~443.
Hjortso C N, Straede S.Strategic Multiple-Use Forest Planning in Lithuania—Applying Multi-Criteria Decision-Making and Scenario Analysis for Decision Support in An Economy in Transition[J]. Forest Policy and Economics, 2001(3):175~188.
Tee J, Scarpa R, Marsh D, et al. A Binomial Tree Approach to Valuing Fixed Rotation Forests And Flexible Rotation Forests under a Mean Reverting Timber Price Process [C]. New Zealand Agricultural and Resource Economics Society Conference, 2010.
Jacobsen J B. The Regeneration Decisions: A Sequential Two-Option Approach [J]. Canadian Journal of Forest Research, 2007,37(2):439~448.
Johansson P O, Lefgren K G. The Economics of Forestry And Natural Resources [M]. Basil Blackwell, 1985: 73~89.
Kangas J. A Multi-Attribute Preference Model for Evaluating the Reforestation Chain Alternatives of A Forest Stand[J]. Forest Ecology Management,1993(59): 271~288.
Kangas J, Kangas A. Multiple Criteria Decision Support in Forest Management—The Approach, Methods Applied, and Experiences Gained [J]. Forest Ecology and Management, 2005 (207): 133~ 143.
Kangas J, Kuusipalo J. Integrating Biodiversity into Forest Management Planning and Decision- making[J]. Forest Ecology and Management,1993(61):1~15.
Kangas J, Laasonen L, Pukkala T. A Method for Estimating Forest Landowners Landscape Preferences[J]. Scandinavian Journal of Forest Research,1993(8): 408~417.
Kangas J. Multiple-Use Planning of Forest Resources by Using the Analytic Hierarchy Process[J]. Scandinavian Journal of Forest Research, 1992(7):259~268.
Kangas J, Pukkala T. A Decision Theoretic Approach Applied to Goal Programming of Forest Managemen t[J]. Silva Fennica, 1992(26):169~176.
Kronrad G D, De Steiguer J E. Relationship between Discount Rates and Investment Length among Non Industrial Private Forest Landowners[C]. Raleigh(NC):Small Woodlot R&D Program,North Carolina State University. Research Notes Series No.19, 1983.
Kuusipalo J, Kangas J. Managing Biodiversity in a Forest Environment[J]. Conservation of Biology,1994(8): 450~460.
Lembersky M R, Johnson K N. Optimal Policies for Managed Stands: An Infinite Horizon Markov Chain Decision Process Approach [J]. Forest Science, 1975, 21 (2):109~122.
Levy J K, Kilgour D M, Hipel K W. Web-Based Multiple Criteria Decision Analysis: Web- HIPRE and The Management of Environmental Uncertainty[J]. INFOR , 2000(38): 221~244.
Liu A, Collins A, Yao S. A Multi-Objective and Multi-Design Evaluation Procedure for Environ- mental Protection Forestry[J]. Environment Resource and Economics,1998(12): 225~240.
Lothner D C , Hoganson H M, Rubin P A. Examining Short-Rotation Hybrid Poplar Investments by Using Stochastic Simulation[J]. Canadian Journal of Forest Research, 1986,16 (6):1207~1213.
Luehrman T A. Investment Opportunities as Real Options: Getting Started On The Numbers [J], Harvard Business Review, 1998, July– August.
Insley M. A Real Options Approach to The Valuation of A Forestry Investment [J]. Journal Of Environmental Economics and Management, 2002(44):471~492
Mayers S C. Determinants of Corporate Borrowing[J].Journal of Financial Economics, 1977 (5) :147~175.
Matta J , Alavalapati J , Tanner G. A Framework for Developing Marked-Based Policies to Further Biodiversity on Non-industrial Private forests (NIPF) [J] .Forest Policy and Economics,2007 (9) : 779~788.
Mendoza G A, Dalton W J. Multi-Stakeholder Assessment of Forest Sustainability: Multi-Criteria Analysis and the Case of the Ontario Forest Assessment System[J]. Forest Chronicle, 2005 (81) : 222~228.
Mendoza G A, Prabhu R. Development of A Methodology for Selecting Criteria and Indicators of Sustainable Forest Management: A Case Study on Participatory Assessment[J]. Environment Ma
nagement, 2000(26): 659~673. Mikkila M, Kolehmainen O, Pukkala T. Multi-Attribute Assessment of Acceptability of Operations in the Pulp and Paper Industries[J]. Forest Policy and Economics, 2005(7):227~243.
Miller R A, Voltaire K. A Stochastic Analysis of the Tree Paradigm [J]. Journal of Economic Dynamic and Control, 1983(6):371~386.
Morck R, Schwartz E, Stangeland D. The Valuation Of Forestry Resources Under Stochastic Prices And Inventories[J]. The Journal of Financial and Quantitative Analysis, 1989,24 (4):473~487.
Munro D D. Forest Growth Models-A Prognosis in Growth Models for Tree and Stand Simulation[R]. Stockholm: Department of Forest Yield Research, Royal College of Forestry, 1974:7~21.
Newham R M, Smith J H G. Development and Testing of Stand Models for Douglas Fir and Lodgeploe Pine[J]. Forest Chron, 1964(40):492~502.
Newman D H. Forestry's Golden Rule and The Development of The Optimal Forest Rotation Literature[J]. Journal of Forest Economics, 2002,8(1):5~27.
Gjolberg O, Guttormsen A G. Real Options in the Forest: What If Prices Are Mean-Reverting [J].Forest Policy And Economics, 2002(4):13~20.
McCarthy P, Lei L. Regional Demand for Pulp and Paper[J].Journal Of Forest Economics, 2010(16):127~144.
Peterson D L, Silsbee D G, Schmoldt D L. A Case Study of Resources Management Planning with Mmultiple Objectives and Projects[J]. Environment Management,1994(18): 729~742. PASW Statistics 18, Rel. 18.0.0. 2009. Chicago: SPSS Inc.
Rauscher H M, Lloyd F T, Loftis D L, et al. A Practical Decision-Analysis Process for Forest Ecosystem Management[J]. Computer Electronic Agriculture, 2000(27): 195~226.
Reynolds K M, Holsten E. Relative Importance of Risk Factors for Spruce Beetle Outbreaks [J]. Canada Journal of Forest Research,1994(24):2089~2095.
Riedl L, Vacik H, Kalasek R. MapModels: A New Approach for Spatial Decision Support in Silvicultural Decision Making[J]. Computer Electronic Agriculture,2000(25): 407~412.
Ross S A. The Arbitrage Theory of Capital Asset Pricing[J]. Journal of Economic Theory,1976(13):341~360.
Row C, Kaiser H F, Sessions J. Discount Rate for Long-Term Forest Service Investments [J]. Journal of Forestry,1981(79):367~369.
Samuelson P A. Economics of Forestry in an Evolving Society[J]. Economic Inquiry, 1976(14):466~492. Saaty T L. The Analytic hierarchy process[M]. New York: McGraw Hill, 1980: 1~2.
Schumacher F X. A New Growth Curve and Its Application to Timber-Yield Studies[J]. Journal of Forestry, 1939(37):819~820.
Schmoldt D L, Peterson D L, Silsbee D G. Developing Inventory and Monitoring Programs Based on Multiple Objectives[J]. Environment Management,1994(18):707~727.
Sedjo R A. An economic assessment of industrial forest plantations [J]. Forest Ecology and Management, 1984,9 (4):245~257.
Sell J, Koellner T,Wendy P, et al. Ecosystem Services From Tropical Forestry Projects—The Choice of International Market Actors[J]. Forest Policy and Economics, 2007(9):496~515.
Shashi K. Extending The Boundaries of Forest Economics [J]. Forest Policy and Economics, 2003, 5(1):36~39.
Strager M P, Rosenberger R S. Incorporating Stakeholder Preferences for Land Conservation: Weights and Measures in Spatial MCA [J]. Ecology and Economics, 2005(57): 627~639.
Sugimura K, Haward T E. Incorporating Social Factors to Improve the Japanese Forest Zoning Process[J]. Forest Policy and Economics, 2008(10):161~173.
Sun J C. Determination of the Optimal Rotation Age: A Theoretical Analysis [J].Forest Ecology and Management, 1984 (8):137~147.
Sun J C. One Formula, Myriad Conclusions, 150 Years of Practicing The Faustmann Formula In Central Europe and The USA [J]. Forest Policy and Economics, 2001(2):97~99.
Taylor R G, Fortson J C. Optimum Plantation Planting Density and Rotation Age Based on Financial Risk and Return [J]. Forest Science, 1991, 37 (3) :886~902.
Thomas A T. Optimal Forest Rotation When Stumpage Prices Follow A Diffusion Process[J]. Land Economics 1992(68): 329~342.
Thorson B J. Afforestation as a Real Option: Some Policy Implications [J]. Forest Science,1999(45): 171~178.
Vacik H, Lexer M J. Application of a Spatial Decision Support System in Managing the Protection Forest of Vienna for Sustained Yield of Water Resource[J]. Forest Ecology and Management, 2001(143):67~76.
William F S. Portfolio Theoty and Capital Markets [M].New York: McGraw Hill, 1970: 45~69 Wood Resource International LLC. Global wood fibre market update. Wood Resource Quarterly (4Q/2009, 2Q/2010, 3Q/2010)[J]. WRI-Ltd, 2009-2010.
Zhang D. Faustmann in An Uncertain Policy Environment [J]. Forest Policy and Economics , 2001 (2): 203~210.
Chladna Z. Determination of Optimal Rotation Period under Stochastic Wood And Carbon Prices [J]. Forest Policy and Economics, 2007(9):1031~1045.
曹武,李注滋. AHP在林区路网多目标综合决策中的作用[J].中南林业科技大学学报,2008, 28(3):152~155.
蔡文祥. PUS-01阴离子淀粉在马尾松枝桠材浆造纸中的应用研究[J].造纸科学与技术, 2001,20(1):25~27.
陈安宁.自然资源利用贴现率探讨[J].资源科学,2000,22(3):13~16.
陈平留,刘健,郑德祥.速生丰产优质杉木林经济效益分析及伐期的确定[J].林业科学,2001,37 (专刊1):47~51.
陈祥伟,王文波,夏祥友.小流域水源涵养林优化配置[J].应用生态学报,2007,18(2):267~271.
陈永芳.人工林生长与收获预测模型的研究[J].林业资源管理, 2001(1): 50~54.
陈文汇,胡明形,刘俊昌.中国木材价格波动的动态均衡模型及实证分析[J].统计与信息论坛,2001,25(1):58~62.
陈则生.杉木人工林经济成熟龄的研究[J].华东森林经理,2004,18(3):1~5.
邓立斌,刘德晶.基于层次分析法的尖峰岭自然保护区生态评价[J].中南林业科技大学学报,2010, 30(7):26~31.
丁贵杰.马尾松人工纸浆材林经济成熟的研究[J].林业科学,2000,36(1):15~20.
丁凤梅,鲁法典,侯占勇等.杨树速生丰产林经济成熟与经济效益分析[J].山东农业大学学报(自然科学版), 2008,39(2):233~238.
丁凤梅,鲁法典,王迎.不同造林密度杨树速生丰产林成熟龄的研究[J].河北林果研究,2007(3):242~246.
杜纪山.林木生长和收获预估模型的研究动态[J].世界林业研究,1999,1(4):19~22.
董希斌,王立海.落叶松人工林采集作业模式的优选[J].林业科学,2007,43(9):46~52.
董健,赵文华,黄国学等.日本落叶松纸浆林合理轮伐期研究[J].辽宁林业科技,2001(1):11~14.
董健,赵文华,王喜武等.日本落叶松纸浆林造纸性能及工艺成熟期的研究[J],辽宁林业科技, 1997(1):26~29.
费世民,向成华.四川盆地丘陵区坡地农林复合系统林带类型、农作物复种方式的选择[J].林业科学,2000,36(1):21~27.
冯佳多(德),惠刚盈.森林生长与干扰模拟[M]. IUFRO-SPDC Textbook Project No. 2 Gottingen: Cuvillier,1998:18.
冯祥锦,黄和亮.工业原料林投资经济效果评价利率选取的探讨[J].中国林业经济,2006,5(78):14~15.
傅家骥,仝允桓.工业技术经济学[M].北京:清华大学出版社,1991:51~53.
高泽兵,李卫忠,贺征兵.巴山松生长及数量成熟龄初步研究[J].西北林学院学报,2009, 24(2): 130~135.
管兰华,曹建,祁万宜等.几种落叶松在鄂西生长比较研究[J].林业科技,2005,30(1):14~17. 国家林业局.中国第七次森林资源清查报告[M].北京:中国林业出版社,2009:4~5.
郭晋平,王惠恭,王世昌等.五台山华北落叶松人工林数量成熟龄及其经营[J].林业科技通讯,1996,10:29~30.
郭世芳,张丽华,丁长富等.内蒙古大兴安岭林区人工落叶松林数量成熟龄及工艺成熟龄的确定[J]. 内蒙古林业调查设计,2003,28(4):28~29.
何晓群,刘文卿.应用回归分析(第二版)[M].北京:中国人民大学出版社,2007:107.
胡卫平,王献荣,徐剑青.浙西山区天然林阔叶树数量成熟龄的确定[J].华东森林经理,2008,22(1):36~39.
黄东,彭道黎,郑小贤.净现值法在林分经济成熟中的应用探讨[J].中南林业调查规划, 2004,23(1):50~53.
黄国胜,王雪军,孙玉军等.河北山区森林生态环境质量评价[J].北京林业大学学报,2005,27(5):75~80.
黄启堂,游永生,黄榕辉等.运用层次分析法评价木质藤本观赏植物资源[J].福建林学院学报,1997, 17(3): 269~272.
黄庆丰,孙启祥,吴泽民等.长江滩地杨树人工林主伐年龄的研究[J],林业科学,2002,38(6):154~158.
黄清麟,冯文钦,林云青.短周期阔叶林经济成熟龄的研究[J].福建林学院学报,1997,17 (4):344~347.
黄荣凤,鲍甫成,张冬梅.杨树材性成熟龄模型的建立及树体内幼龄材的分布[J].林业科学, 2005,41(3):103~109.
贺铿.关于通货膨胀预期的问题[J].求是, 2010 (3): 46~47.
江波,袁位高,戚连忠等.杨树人工林合理轮伐期的研究[J].浙江林学院学报,2001,18(1):26~31.
蒋伊尹,李凤日.兴安落叶松天然林生长与收获的研究[J].林业科学,1989,25(5):477~472.
焦媛媛,韩文秀,杜军.确定最优轮伐期的实物期权方法[J].西北农林科技大学学报(自然科学版), 2003,31(5): 169~172 .
揭建林,詹有生,吴克选.江西省杉木人工林合理轮伐期的研究[J].江西林业科技,2006(6):4~8.
亢新刚.森林资源经营管理[M].北京:中国林业出版社,2001:168~201.
亢新刚,黄庆丰.华北次生林结构调整研究[J].北京林业大学学报,2000,22(3):41~43.
李春明.抚育间伐对人工林分生长的影响研究[D].中国林业科学研究院硕士学位论文,2003,9~10.
李春静,智长贵,何军旗.杨树农田防护林带全林生长模型研究[J].信阳示范学院学报(自然科学版), 2007,20(3):325~327.
李进,陈如轩.长岭岗林场日本落叶松材积生长规律研究[J].现代农业科技,2008, 4:10~11
梁红,张仲芳.我国原木和木浆进口数量与价格变化及其影响因素分析[J].贵州财经学院学报, 2006(5): 29~33.
林金国,陆继策,林凤涛等.运用AHP法评价地板木树种资源[J].东北林业大学学报,2000,28(4):100~102.
林如青,郑少玲.人工林生长与收获预测模型应用探讨[J]林业资源管理,2001(2): 48~50.
林山海.杉木采伐年龄的研究[J].林业勘察设计,2008(2):206~213.
刘洪斌.纤维特性与纸页撕裂性能关系的研究[D].天津科技大学硕士学位论文,2004.
刘平,马履一,王玉涛等.油松中幼人工林单木胸径生长模型研究[J].沈阳农业大学学报,2009,40(2):197~201.
刘平,王宁,孙清江.新疆伊犁地区速生杨树生长模型及数量成熟研究[J].新疆农业大学学报. 2003,26(4):45~48.
刘瑞龙,王发武,石山等.中国农业百科全书(林业卷)[M].北京:农业出版社,1989:123~631..
刘盛全,江泽慧.不同种群白桦纤维形态特征变异及优良种群选择[J].世界林业研究,1995(8)专集: 274~278.
刘玉雪,王章虎.层次分析法(AHP)在风险分析与评价中的应用[J].工程与建设,2008,22(1):22~24.
吕郁彪.马尾松造纸原料林主伐年龄的研究[J].中南林业调查规划,1997,16(2):19~21.
马常耕.落叶松种和种源选择[M].北京:北京农业大学出版社,1992:4~5.
马常耕,王建华.我国发展日本落叶松区域的探讨[J].林业科技通讯,1990(4):26~28.
马丰丰,贾黎明.林分生长和收获模型研究进展[J].世界林业研究,2008,21(3):21~27.
马利春,刘志超.湿地松造纸主伐年龄的研究[J].四川林勘设计,1995,3:22~30.
孟春,王立海.小兴安岭天然次生林经营模拟与评价[J].东北林业大学学报,2005,33(6):25~29.
孟全省.确立经济成熟在编制森林经营方案中的指导地位[J].世界林业研究,1995,3:21~26.
孟宪宇.测树学[M]北京:中国林业出版社,2006:59~276
皮尔森·皮特H.林业经济学概论[M].张道卫译.北京:中国林业出版社,1994:112~119.
钱志能,龚益广,李国新.西江林场杉木的经济轮伐期[J].中南林学院学报,2006,26(5):117~120.
秦建华.林分生长与产量模型系统研究综述[J].林业科学,2002,38(1):122~129.
施本俊.高峰林场杉木第二代人工林主伐年龄[J].云南林业调查规划设计,2000,25(2):7~9.
司海忠,杨双,李晶等.日本落叶松引种研究[J].林业科技通讯,1999(11):5~7.
石丽萍,冯仲科.人工林生长与收获预测模型的基本方法[J].北京林业大学学报,2005,27(增刊2):222~225.
石淑兰,谢新良,胡惠仁等.不同树龄日本落叶松的化学组成与制浆特性[J].林业科学, 2006 ,42(7):90~94.
施新程,谢文全.豫南杉木经济成熟龄研究[J],安徽农业科学,2009,37(23):11281~11283.
施新程,王洪友,黄旺志等.豫南杉木人工林主伐年龄研究[J].福建林业科技,2009,36(3):49~ 53.
沈慧,姜凤岐.水土保持林土壤改良效益评价指标体系的研究[J].北京林业大学学报,2000,22(5):96~99.
盛炜彤,惠刚盈,罗云伍.大岗山杉木人工林主伐年龄的研究[J].林业科学研究,1991,4(2):113~ 121.
盛炜彤,惠刚盈,张守攻等.杉木人工林优化栽培模式[M].北京:中国科学技术出版社,2004:93.
苏金德,张锡象,李月英.造林密度对巨尾桉生长量与轮伐期的影响[J].林业科技开发,2000,14(4):15~17.
覃林,何义发.模糊综合评判法确定人工林主伐年龄的研究[J].湖北民族学院学报(自然科学版), 1999,17(2):51~54.
田志和,董健,王喜武等.日本落叶松木材纸浆性能及速生丰产林投入产出分析[J].辽宁林业科技, 1994(5):51~54.
唐守正,郎奎建,李海奎等.统计和生物数学模型计算(Forstat教程).北京:科学出版社,2009: 291~347.
童方平.湿地松纸浆材与建筑材定向培育技术研究[D].中南林学院硕士学位论文,2002:42~45.
童方平,龙应忠,吴际友等.我国主要立地火炬松纸浆材、建筑材林合理轮伐期的研究[J].林业科技通讯,1997 (11) :9~12.
王炳云,孙述涛.木材解剖分子生长锥法确定数量成熟龄[J].华东森林经理,1994,8(2):30~33.
王军辉,陆熙娴,张守攻.落叶松纸浆造纸适应性及开发利用前景[J].中国造纸, 2004,23(6):47~52.
王军辉,张守攻,石淑兰等.日本落叶松AS-AQ浆和KP浆的漂白特性比较[J].北京林业大学学报,2006,28(1):93~97.
王军辉,张红杰,石淑兰等.楸树枝桠材硫酸盐法制浆的研究[J].中国造纸学报,2010,25(4):10~13.
王立海,杨学春,郝霞等.层次分析法在集材方式选择上的应用[J].东北林业大学学报,1996, 24(1):68~71.
王乃江,张文辉,同金霞等.黄土高原蔡家川林场森林质量评价[J].林业科学,2010,46(9):7~14.
王树力,李凤山,胡秀云.小黑杨纸浆林经济效益的研究[J].东北林业大学学报,1998,26(1):45~48.
王树力,吴济生,仲崇淇.长白落叶松纸浆林木材材性及纸浆特性的研究[J].林业科学,1997,33(3):283~288.
魏均.基于实物期权方法的林业投资项目评价问题的研究[D].北京林业大学硕士学位论文,2006:1~58.
魏均,梅斌,张绍文.基于实物期权的林业项目评估[J].商业研究,2006(6):44~47.
韦新良,郭仁鉴,赵斌.浙江省马尾松天然林生长模型及采伐年龄的确定[J].浙江林学院学报,2001,18(4):333~336.
吴立勋,汤玉喜,吴敏等.滩地不同密度杨树人工林主伐年龄的研究[J].湖南林业科技,2003,30 (3):24~26.
吴喜之.统计学:从数据到结论(第三版)[M].北京:中国统计出版社,2009:132~136.
谢新良.日本落叶松制浆造纸特性的研究[D].天津科技大学硕士学位论文,2003:1~14.
徐宏远,陈章水.不同密度I-69杨丰产林林分的生长预测及数量成熟龄[J].东北林业大学学报,1994,22(2):17~23.
徐有明.火炬松纸浆材材性变异和优质原料培育期的确定[J].林业科学研究,1995, 8(5):544~549
徐有明.木材学[M],北京:中国林业出版社,2006:1~8.
徐有明,方洪元,黄吉田.意杨纸浆材材性变异的研究[J].木材工业,1994,8(1):38~44.
徐有明,林汉,万伏红.马尾松纸浆材材性变异和采伐林龄的确定[J].浙江林学院学报,1997,14(1):8~15.
杨斌,杨国州,张延东.运用层次分析法优选临夏北塬农田防护林树种[J].林业科学,2006,42(6): 49~55.
于长玲,陈海龙,张思宏等.长白落叶松人工林最佳经济成熟龄的确定[J].林业科技,1999,24(1): 17~19
喻庆国.基于自然度的森林景观时空分异研究[D].北京林业大学博士学位论文,2007:49~52.
张建国,段爱国.理论生长方程对杉木人工林林分直径结构的模拟研究[J].林业科学,2003,39(6): 51~56.
张建国,刘盛全. I-69杨木材纤维形态和化学成分的研究[C].中国林学会木材科学分会第九次学术研讨会论文集,2004:1~8.
张钦相,陈绘画.杉木人工林经济成熟初探[J].浙江林学院学报,1995,12(1):106~109.
张宋智,王军辉,张守攻等.日本落叶松AS-AQ法制浆特性[J].东北林业大学学报,2005, 33(2):34~37.
张永峰.林分数量成熟与林木数量成熟关系初探[J].北京林业大学学报,1988,10(增刊):22~26.
赵刚,姜以斌.长白落叶松人工林三种成熟龄的研究[J].辽宁林业科技,1995(2):30~34.
郑小贤.森林经营与森林文化[J].中国林业教育,2000(2):18~20.
中国农业银行.凭证式国债利率. http://www.95599.sh.cn/lcms/bank/quotation/pzsgzratelist_cx.jsp.
中国造纸协会.中国造纸工业2009年度报告[J].造纸信息, 2010(6): 6~15.
中华人民共和国林业部.中华人民共和国林业行业标准——日本落叶松速生丰产林LY1058- 91[S]. 1991.
中华人民共和国统计局.中国统计年鉴[M].北京:中国统计出版社,1991-2009.
纸和造纸杂志编辑部.我国造纸工业2009年纸和纸板产量和进口情况[J].纸和造纸,2010(3):1~2.
周彬,郑小贤,钟艳等.林分物种多样性指标体系的研究[J].北京林业大学学报,2002,24(2):22~26.
周国模,郭仁鉴,韦新良等.浙江省杉木人工林生长模型及主伐年龄的确定[J].浙江林学院学报, 2001,18(3): 219~222.
朱春全,刘晓东,宋显林等.集约与粗放经营杨树人工林生长规律[J].东北林业大学学报,1998, 26(1):14~18.
Gregory G R.森林资源经济学[M].许伍权,赵克绳,张承襄,等译.北京:中国林业出版社,1985:308~315.
Abildtrup. J. Optimal Thinning of Forest Stands: An Option Value Analysis—Preliminary Results [J]. Scandinavian Forest Economics, 1999(37):1~13.
Ananda J, Herath G. The Use of Analytic Hierarchy Process to Incorporate Stakeholder Preferences into Regional Forest Planning[J]. Forest Policy and Economics, 2003(5):13~26.
Duku-Kaakyire A, Nanang D M. Application of Real Option Theory to Forestry Investment Analysis [J]. Forest Policy and Economics,2004 (6):539~552.
Yoshimoto A. Searching For an Optimal Rotation Age for Forest Stand Management under Stochastic Log Prices [J]. European Journal of Operational Research, 1998(105):100~112.
Yoshimoto A. Stochastic Control Modeling for Forest Stand Management under Uncertain Price Dynamics through Geometric Brownian Motion[J]. Journal of Forest Research, 2002(7):81~90.
Brazee R J. Introduction—The Faustmann Formula: Fundamental To Forest Economics 150 Years After Publication [J]. Forest Science , 2001,47 (4):441~442.
Brazee R J, Mendelsohn R. Timber Harvesting with Fluctuating Prices [J]. Forest Science, 1988(34):359~372.
Brock W A, Rothschild M, Stiglitz J E. Stochastic Capital Theory: In Joan Robinson and Modern Economic Theory[M]. New York: New York University Press, 1989: 591~622.
Bruce D, Wensel L C. Modeling Forest Growth Approaches, Definitions and Problems In Proceeding of IUFRO Conference: Forest Growth Modeling and Prediction[R].USDA Forest Service General Technical Report NC-120. Minneapolis, Minnesota, 1987:1~8.
Brukas V, Thorsen B J, Helles F, et al. Discount Rate and Harvest Policy: Implications for Baltic Forestry[J].Forest Policy And Economics, 2001(2):143~156.
Bruce M, Kurt N. What is the Relevance of Option Pricing for Forest Valuation in New Zealand [J]. Forest Policy and Economics, 2010(12):299~307.
Cheng S, Xu Z, Su Y,et al. Spatial and Temporal Flows of China’s Forest Resource: Development of
A Framework for Evaluating Resource Efficiency[J].Ecological Economics, 2010(69):1405~1415. Clarke H R, Reed W J. The Tree-Cutting Problem in a Stochastic Environment [J]. Journal of Economic Dynamics and Control, 1989(13):569~595.
Curtis R O, Clendenen G W, Reukema D L, et al. A New Stand Simulator for Coastal Douglas firDFSM User’s Guide[R]. USDA For Ser Gen Tech Rep PNW, 1981:79.
Davis L S, Johnson K N. Forest management [M]. New York: Mcgraw-Hill Book Company,1987: 1~8.
Diaz-Balteiro L, Romero C. Making Forest Decisions With Multiple Criteria: A Review and An Assessment[J]. Forest Ecology and Management, 2008(255):3222~3241.
Dixit A K, Pindyck R S. Investment under Uncertainty[M]. Princeton University Press, 1994: 1~12. Faustmann M. Berechnung Ses Werthes, Welchen Waldboden Sowie Nach Nicht Haubare HolzbestanDe Fur Die Weldwirtschaft Besitze [J]. AIIegemeime Forest und Jagd Zeitung, 1849(25): 441.
Gilliams S, Raymaekers D, Muys B, et al. Comparing Multiple Criteria Decision Methods to Extend a Geographical Information System on Afforestation[J]. Computer Electronic of Agriculture, 2005(49): 142~158.
Grado S C, Strauss C H, Blankenhorn P R. Short Rotation Woody Biomass Plantations: Technical Requirements and Costs for Establishment[J] . Biomass, 1988, 17(4):277~289.
Guthrie G. Real Options in Theory And Practice [M]. USA, Oxford University Press,2009: 347~361.
Haight R G, Holmes T P. Stochastic Price Models and Optimal Tree Cutting: Results for Loblolly Pine [J]. Natural Resource Modeling,1991,5 (4):423~443.
Hjortso C N, Straede S.Strategic Multiple-Use Forest Planning in Lithuania—Applying Multi-Criteria Decision-Making and Scenario Analysis for Decision Support in An Economy in Transition[J]. Forest Policy and Economics, 2001(3):175~188.
Tee J, Scarpa R, Marsh D, et al. A Binomial Tree Approach to Valuing Fixed Rotation Forests And Flexible Rotation Forests under a Mean Reverting Timber Price Process [C]. New Zealand Agricultural and Resource Economics Society Conference, 2010.
Jacobsen J B. The Regeneration Decisions: A Sequential Two-Option Approach [J]. Canadian Journal of Forest Research, 2007,37(2):439~448.
Johansson P O, Lefgren K G. The Economics of Forestry And Natural Resources [M]. Basil Blackwell, 1985: 73~89.
Kangas J. A Multi-Attribute Preference Model for Evaluating the Reforestation Chain Alternatives of A Forest Stand[J]. Forest Ecology Management,1993(59): 271~288.
Kangas J, Kangas A. Multiple Criteria Decision Support in Forest Management—The Approach, Methods Applied, and Experiences Gained [J]. Forest Ecology and Management, 2005 (207): 133~ 143.
Kangas J, Kuusipalo J. Integrating Biodiversity into Forest Management Planning and Decision- making[J]. Forest Ecology and Management,1993(61):1~15.
Kangas J, Laasonen L, Pukkala T. A Method for Estimating Forest Landowners Landscape Preferences[J]. Scandinavian Journal of Forest Research,1993(8): 408~417.
Kangas J. Multiple-Use Planning of Forest Resources by Using the Analytic Hierarchy Process[J]. Scandinavian Journal of Forest Research, 1992(7):259~268.
Kangas J, Pukkala T. A Decision Theoretic Approach Applied to Goal Programming of Forest Managemen t[J]. Silva Fennica, 1992(26):169~176.
Kronrad G D, De Steiguer J E. Relationship between Discount Rates and Investment Length among Non Industrial Private Forest Landowners[C]. Raleigh(NC):Small Woodlot R&D Program,North Carolina State University. Research Notes Series No.19, 1983.
Kuusipalo J, Kangas J. Managing Biodiversity in a Forest Environment[J]. Conservation of Biology,1994(8): 450~460.
Lembersky M R, Johnson K N. Optimal Policies for Managed Stands: An Infinite Horizon Markov Chain Decision Process Approach [J]. Forest Science, 1975, 21 (2):109~122.
Levy J K, Kilgour D M, Hipel K W. Web-Based Multiple Criteria Decision Analysis: Web- HIPRE and The Management of Environmental Uncertainty[J]. INFOR , 2000(38): 221~244.
Liu A, Collins A, Yao S. A Multi-Objective and Multi-Design Evaluation Procedure for Environ- mental Protection Forestry[J]. Environment Resource and Economics,1998(12): 225~240.
Lothner D C , Hoganson H M, Rubin P A. Examining Short-Rotation Hybrid Poplar Investments by Using Stochastic Simulation[J]. Canadian Journal of Forest Research, 1986,16 (6):1207~1213.
Luehrman T A. Investment Opportunities as Real Options: Getting Started On The Numbers [J], Harvard Business Review, 1998, July– August.
Insley M. A Real Options Approach to The Valuation of A Forestry Investment [J]. Journal Of Environmental Economics and Management, 2002(44):471~492
Mayers S C. Determinants of Corporate Borrowing[J].Journal of Financial Economics, 1977 (5) :147~175.
Matta J , Alavalapati J , Tanner G. A Framework for Developing Marked-Based Policies to Further Biodiversity on Non-industrial Private forests (NIPF) [J] .Forest Policy and Economics,2007 (9) : 779~788.
Mendoza G A, Dalton W J. Multi-Stakeholder Assessment of Forest Sustainability: Multi-Criteria Analysis and the Case of the Ontario Forest Assessment System[J]. Forest Chronicle, 2005 (81) : 222~228.
Mendoza G A, Prabhu R. Development of A Methodology for Selecting Criteria and Indicators of Sustainable Forest Management: A Case Study on Participatory Assessment[J]. Environment Ma
nagement, 2000(26): 659~673. Mikkila M, Kolehmainen O, Pukkala T. Multi-Attribute Assessment of Acceptability of Operations in the Pulp and Paper Industries[J]. Forest Policy and Economics, 2005(7):227~243.
Miller R A, Voltaire K. A Stochastic Analysis of the Tree Paradigm [J]. Journal of Economic Dynamic and Control, 1983(6):371~386.
Morck R, Schwartz E, Stangeland D. The Valuation Of Forestry Resources Under Stochastic Prices And Inventories[J]. The Journal of Financial and Quantitative Analysis, 1989,24 (4):473~487.
Munro D D. Forest Growth Models-A Prognosis in Growth Models for Tree and Stand Simulation[R]. Stockholm: Department of Forest Yield Research, Royal College of Forestry, 1974:7~21.
Newham R M, Smith J H G. Development and Testing of Stand Models for Douglas Fir and Lodgeploe Pine[J]. Forest Chron, 1964(40):492~502.
Newman D H. Forestry's Golden Rule and The Development of The Optimal Forest Rotation Literature[J]. Journal of Forest Economics, 2002,8(1):5~27.
Gjolberg O, Guttormsen A G. Real Options in the Forest: What If Prices Are Mean-Reverting [J].Forest Policy And Economics, 2002(4):13~20.
McCarthy P, Lei L. Regional Demand for Pulp and Paper[J].Journal Of Forest Economics, 2010(16):127~144.
Peterson D L, Silsbee D G, Schmoldt D L. A Case Study of Resources Management Planning with Mmultiple Objectives and Projects[J]. Environment Management,1994(18): 729~742. PASW Statistics 18, Rel. 18.0.0. 2009. Chicago: SPSS Inc.
Rauscher H M, Lloyd F T, Loftis D L, et al. A Practical Decision-Analysis Process for Forest Ecosystem Management[J]. Computer Electronic Agriculture, 2000(27): 195~226.
Reynolds K M, Holsten E. Relative Importance of Risk Factors for Spruce Beetle Outbreaks [J]. Canada Journal of Forest Research,1994(24):2089~2095.
Riedl L, Vacik H, Kalasek R. MapModels: A New Approach for Spatial Decision Support in Silvicultural Decision Making[J]. Computer Electronic Agriculture,2000(25): 407~412.
Ross S A. The Arbitrage Theory of Capital Asset Pricing[J]. Journal of Economic Theory,1976(13):341~360.
Row C, Kaiser H F, Sessions J. Discount Rate for Long-Term Forest Service Investments [J]. Journal of Forestry,1981(79):367~369.
Samuelson P A. Economics of Forestry in an Evolving Society[J]. Economic Inquiry, 1976(14):466~492. Saaty T L. The Analytic hierarchy process[M]. New York: McGraw Hill, 1980: 1~2.
Schumacher F X. A New Growth Curve and Its Application to Timber-Yield Studies[J]. Journal of Forestry, 1939(37):819~820.
Schmoldt D L, Peterson D L, Silsbee D G. Developing Inventory and Monitoring Programs Based on Multiple Objectives[J]. Environment Management,1994(18):707~727.
Sedjo R A. An economic assessment of industrial forest plantations [J]. Forest Ecology and Management, 1984,9 (4):245~257.
Sell J, Koellner T,Wendy P, et al. Ecosystem Services From Tropical Forestry Projects—The Choice of International Market Actors[J]. Forest Policy and Economics, 2007(9):496~515.
Shashi K. Extending The Boundaries of Forest Economics [J]. Forest Policy and Economics, 2003, 5(1):36~39.
Strager M P, Rosenberger R S. Incorporating Stakeholder Preferences for Land Conservation: Weights and Measures in Spatial MCA [J]. Ecology and Economics, 2005(57): 627~639.
Sugimura K, Haward T E. Incorporating Social Factors to Improve the Japanese Forest Zoning Process[J]. Forest Policy and Economics, 2008(10):161~173.
Sun J C. Determination of the Optimal Rotation Age: A Theoretical Analysis [J].Forest Ecology and Management, 1984 (8):137~147.
Sun J C. One Formula, Myriad Conclusions, 150 Years of Practicing The Faustmann Formula In Central Europe and The USA [J]. Forest Policy and Economics, 2001(2):97~99.
Taylor R G, Fortson J C. Optimum Plantation Planting Density and Rotation Age Based on Financial Risk and Return [J]. Forest Science, 1991, 37 (3) :886~902.
Thomas A T. Optimal Forest Rotation When Stumpage Prices Follow A Diffusion Process[J]. Land Economics 1992(68): 329~342.
Thorson B J. Afforestation as a Real Option: Some Policy Implications [J]. Forest Science,1999(45): 171~178.
Vacik H, Lexer M J. Application of a Spatial Decision Support System in Managing the Protection Forest of Vienna for Sustained Yield of Water Resource[J]. Forest Ecology and Management, 2001(143):67~76.
William F S. Portfolio Theoty and Capital Markets [M].New York: McGraw Hill, 1970: 45~69 Wood Resource International LLC. Global wood fibre market update. Wood Resource Quarterly (4Q/2009, 2Q/2010, 3Q/2010)[J]. WRI-Ltd, 2009-2010.
Zhang D. Faustmann in An Uncertain Policy Environment [J]. Forest Policy and Economics , 2001 (2): 203~210.
Chladna Z. Determination of Optimal Rotation Period under Stochastic Wood And Carbon Prices [J]. Forest Policy and Economics, 2007(9):1031~1045.
© 2004-2018 中国地质图书馆版权所有 京ICP备05064691号 京公网安备11010802017129号 地址：北京市海淀区学院路29号 邮编：100083 电话：办公室：(+86 10)66554848；文献借阅、咨询服务、科技查新：66554700 |