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林业研究（英文版）
林业研究（英文版）

杨传平

季刊

1007-662X

jfr@mail.nefu.edu.cn

0451-82191144，82190464

150040

哈尔滨市动力区和兴路26号（林大123信箱）

林业研究（英文版）/Journal Journal of Forestry ResearchCSCDCSTPCD北大核心SCI
查看更多>>《林业研究》（英文版）(Journal of Forestry Research)是中国生态学学会与东北林业大学主办、国家教育部主管的林业学术期刊。协办单位有吉林省林科院、辽宁省林科院。创办于1990年，季刊，大16开，国内外公开发行。 1.办刊宗旨与报道范围 　　本刊宗旨是贯彻党的科技路线和“双百”方针，坚持科技是第一生产力的原则，宣传和报道国内外森林生态学和森林资源学基础研究与应用研究方面的学术成果，为活跃学术空气、促进国际学术交流和科教兴国服务。 　　主要刊登：森林经营、林木育种、造林、森林生态、森林土壤、森林保护、野生动物生态与管理、野生动物保护与利用、生物科学、木材科学、木材加工工艺、森林采运技术等方面的原始论文。同时，也刊登研究综述、研究简报、会议消息、书评方面的稿件。 2．国际化程度 　　向国际化发展是本刊既定的目标。经过辛勤的耕耘和不懈的努力，本刊在国内外的知名度和影响不断提高。 （1）国际文献数据库收录 本刊现已入编美国生物学文摘（BA）、国际生物学文献文摘（CAB Abstracts）、俄罗斯文摘杂志（Abstract Journal of VINITI(AJ)）等17个国际性重要数据库，及中国科学引文数据库（CSCD）等十几个国内重要数据库，并成为中国科学引文数据库（CSCD）核心库来源期刊、中国科技论文统计源期刊（中国科技核心期刊），中国学术期刊综合评价数据库来源期刊、中国科技期刊统计源期刊及《中国学术期刊（光盘版）》全文收录期刊。加入这些数据库，标志着本刊已发展成为一种英文核心学术期刊，在国内外具有较高的影响力，在国际学术交流方面起着重要作用。 （2）国际化编委会 目前本刊编委会成员36名，其中有海外编委17名, 来自12个国家。 （3）国际合作出版 2007年《林业研究》与国际著名出版商—Springer 公司开展国际出版合作。本刊已获得网络版刊号--ISSN1993-0607（Online),每期都直接上传Http:// 国际网络平台。这标志着本刊正式登上国际舞台，走上国际化、信息化、网络化发展道路，扩大了国际影响，实现了真正意义上的国际化。《林业研究》（英文版） 在国际知名电子期刊网（http://）上全文下载次数逐年急剧上升，2007年全年为5,300次，2008年全年为10,023次, 2009年全年将突破35,000次，2010年为28,000次，证明该刊的国际检索利用率在不断提高。另外，本刊还实现了优先出版（Online first）。据ISI Web of Knowledge 统计显示：2008年《林业研究》（英文版） 2006-2007年文章被引用的次数为 58次，国际影响因子达到0.4。 （4）稿件组成 《林业研究》（英文）创刊以来，一直受到广大作者及读者的关心与厚爱。经过不懈的努力，本刊逐渐发展成为一种在国内外具有一定影响的英文林业学术期刊，在宣传报道我国林业研究成果和促进国际学术交流方面发挥着重要作用。本刊以出精品为目标，注重优秀稿件和基金资助课题稿件的征集和选取，刊登的论文绝大部分具有学科前沿水平，国家及省部级基金课题的论文比例达60%以上。国内来稿覆盖全国各省市自治区，国外稿件覆盖美国、日本、印度、瑞典、尼日利亚、澳大利亚等40多个国家。 3. 编辑队伍 　《林业研究》编辑部长期以来十分重视编辑人才的培养，鼓励并创造条件培养编辑人员的实践能力、自我完善能力、英语写作能力、信息捕捉能力和对稿荐的驾御能力。目前编辑部已具备一支结构合理、素质高的编辑队伍。有名誉主编 1人，兼职主编1人，兼职副主编3人，专职副主编1人，专职编辑3人，语言编辑1人（兼职）。专职编辑人员中，编审1名、副编审1名、编辑2名，全部为林业专业出身科技人员。编辑人员注重自身的修养和自我提高，除了经常参加一些编辑和专业方面的研讨会之外，编辑部还经常开展“稿件修改研讨会”，针对稿件容易出现英文语法错误如何修改进行讨论，组织学习国外专家改过的稿件。 4．期刊信息化水平 2004年本刊建立有自己独立网站。本网站同时具备中文和英文2套版本，可同时以满足国内和国外访问者的需要，具备期刊介绍、文章检索（包括本期和过刊）、稿件查询、订阅指南、投稿须知、审稿标准、审稿人数据库等功能。2010年采用” Editorial Manager”国际通用在线投审稿系统，实现在线投稿审稿。投稿者请登录并注册，然后按系统提示逐步完成投稿。
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    Developing kNN forest data imputation for Catalonia

    Timo PukkalaNúria AquiluéAriadna JustJordi Corbera...
    158-171页
    查看更多>>摘要：The combined use of LiDAR(Light Detection And Ranging)scanning and field inventories can provide spatially continuous wall-to-wall information on forest characteristics.This information can be used in many ways in forest mapping,scenario analyses,and forest manage-ment planning.This study aimed to find the optimal way to obtain continuous forest data for Catalonia when using kNN imputation(kNN stands for"k nearest neighbors").In this method,data are imputed to a certain location from k field-measured sample plots,which are the most similar to the location in terms of LiDAR metrics and topographic variables.Weighted multidimensional Euclidean distance was used as the similarity measure.The study tested two different methods to optimize the distance measure.The first method optimized,in the first step,the set of LiDAR and topographic variables used in the measure,as well as the transformations of these variables.The weights of the selected variables were optimized in the second step.The other method optimized the variable set as well as their transformations and weights in one single step.The two-step method that first finds the variables and their transfor-mations and subsequently optimizes their weights resulted in the best imputation results.In the study area,the use of three to five nearest neighbors was recommended.Altitude and latitude turned out to be the most important variables when assessing the similarity of two locations of Catalan forests in the context of kNN data imputation.The optimal distance measure always included both LiDAR metrics and topographic variables.The study showed that the optimal similarity measure may be different for different regions.Therefore,it was suggested that kNN data imputation should always be started with the optimization of the measure that is used to select the k nearest neighbors.
      原文链接:
    • 万方数据
    • 维普

    Species-specific and generalized allometric biomass models for eight Fagaceae species in the understory of evergreen broadleaved forests in subtropical China

    Shengwang MengYu Lei
    172-186页
    查看更多>>摘要：Quantifying the biomass of saplings in the regeneration component is critical for understanding biogeochemical processes of forest ecosystems.However,accurate allometric equations have yet to be developed in sufficient detail.To develop species-specific and generalized allometric equations,154 saplings of eight Fagaceae tree species in subtropical China's evergreen broadleaved forests were collected.Three dendrometric variables,root collar diameter(d),height(h),and crown area(ca)were applied in the model by the weighted nonlinear seemingly unrelated regression method.Using only d as an input variable,the species-specific and generalized allometric equations estimated the aboveground biomass reasonably,with R2adj values generally＞0.85.Adding h and/or ca improved the fitting of some biomass components to a certain extent.Generalized equations showed a relatively large coefficient of variation but comparable bias to species-specific equations.Only in the absence of species-specific equations at a given location are generalized equations for mixed species recommended.The developed regression equations can be used to accurately calculate the aboveground biomass of understory Fagaceae regeneration trees in China's subtropical evergreen broadleaved forests.
      原文链接:
    • 万方数据
    • 维普

    A new method of calculating crown projection area and its comparative accuracy with conventional calculations for asymmetric tree crowns

    Mingrui ZhangHuiquan BiXingji JinMichael McLean...
    207-224页
    查看更多>>摘要：This paper introduces a new method of calculating crown projection area(CPA),the area of level ground covered by a vertical projection of a tree crown from measured crown radii through numerical interpolation and integration.This novel method and other four existing methods of calculating CPA were compared using detailed crown radius measurements from 30 tall trees of Eucalyptus pilularis variable in crown size,shape,and asymmetry.The four existing methods included the polygonal approach and three ways of calculating CPA as the area of a circle using the arithmetic,geometric and quadratic mean radius.Comparisons were made across a sequence of eight non-consecutive numbers(from 2 to 16)of measured crown radii for each tree over the range of crown asymmetry of the 30 trees through generalized linear models and multiple comparisons of means.The sequence covered the range of the number of crown radii measured for calculating the CPA of a tree in the literature.A crown asymmetry index within the unit interval was calculated for each tree to serve as a normative measure.With a slight overestimation of 2.2％on average and an overall mean error size of 7.9％across the numbers of crown radii that were compared,our new method was the least biased and most accurate.Calculating CPA as a circle using the quadratic mean crown radius was the second best,which had an average overestimation of 4.5％and overall mean error size of 8.8％.These two methods remained by and large unbiased as crown asymmetry increased,while the other three methods showed larger bias of underestimation.For the conventional method of using the arithmetic mean crown radius to calculate CPA as a circle,bias correction factors were developed as a function of crown asymmetry index to delineate the increasing magnitude of bias associated with greater degrees of crown asymmetry.This study reveals and demonstrates such relationships between the accuracy of CPA calculations and crown asymmetry and will help increase awareness among researchers and practitioners on the existence of bias in their CPA calculations and for the need to use an unbiased method in the future.Our new method is recommended for calculating CPA where at least four crown radius measurements per tree are available because that is the minimum number required for its use.
      原文链接:
    • 万方数据
    • 维普

    Morphological and molecular evidence for natural hybridization between Sorbus pohuashanensis and S.discolor(Rosaceae)

    Yuxia WuXuedan YuWei TangWenhua Yang...
    225-237页
    查看更多>>摘要：In overlapping distribution areas of Sorbus pohuashanensis and S.discolor in North China(Mount Tuoliang,Mount Xiling and Mount Baihua),Sorbus indi-viduals were found with pink fruit,which have never been recorded for the flora of China.Fourteen morphological characters combined with four chloroplast DNA markers and internal transcribed spacer(ITS)were used to analyze the origin of the Sorbus individuals with pink fruits and their relationship to S.pohuashanensis and S.discolor.PCA,SDA and one-way(taxon)ANOVA of morphological characters provided convincing evidence of the hybrid ori-gin of Sorbus individuals with pink fruits based on a novel morphological character and many intermediate characters.Haplotype analysis based on four cpDNA markers showed that either S.pohuashanensis or S.discolor were maternal parents of Sorbus individuals with pink fruits.Incongru-ence of the position of Sorbus individuals with pink fruits between cpDNA and ITS in cluster trees supported by DNA sequence comparative analysis,implying former hybridiza-tion events between S.pohuashanensis and S.discolor.Mul-tiple hybridization events between S.pohuashanensis and S.discolor might have contributed to the generation of Sorbus individuals with pink fruits.This study has provided insights into hybridization between species of the same genus in sympatric areas,which is of great significance for the study of interspecific hybridization.
      原文链接:
    • 万方数据

    BACNN:Multi-scale feature fusion-based bilinear attention convolutional neural network for wood NIR classification

    Zihao WanHong YangJipan XuHongbo Mu...
    246-258页
    查看更多>>摘要：Effective development and utilization of wood resources is critical.Wood modification research has become an integral dimension of wood science research,however,the similarities between modified wood and original wood render it challenging for accurate identification and classi-fication using conventional image classification techniques.So,the development of efficient and accurate wood classi-fication techniques is inevitable.This paper presents a one-dimensional,convolutional neural network(i.e.,BACNN)that combines near-infrared spectroscopy and deep learn-ing techniques to classify poplar,tung,and balsa woods,and PVA,nano-silica-sol and PVA-nano silica sol modified woods of poplar.The results show that BACNN achieves an accuracy of 99.3％on the test set,higher than the 52.9％of the BP neural network and 98.7％of Support Vector Machine compared with traditional machine learning meth-ods and deep learning based methods;it is also higher than the 97.6％of LeNet,98.7％of AlexNet and 99.1％of VGG-Net-11.Therefore,the classification method proposed offers potential applications in wood classification,especially with homogeneous modified wood,and it also provides a basis for subsequent wood properties studies.
      原文链接:
    • 万方数据