三明市杉木,马尾松人工林材种出材率表编制的研究

三明市材种出材率表编制是根据部，省有关材种规格标准，进行现场造材，共收集１１６４株样木，其中杉木５５６株，马尾松６０８株。采用电子计算机对样木进行计算和分析，以确定各树种树高级，径阶、材积、树皮率、出材量和出材率。     

马尾松人工林材种出材率表的编制

应用马尾松人工林现场造材样木,根据胸径、树高与各材种出材率的关系,编制了二元材种出材率表,该表经检验证明适用。在此基础上,通过建立胸径、树高、地径之间的相关数学模型,导出了一元材种出材率表和地径出材率表。     

苍梧县杉木削度方程与材积比方程研究

在苍梧县并青林场等集体林场的伐区，随机量测样木５４８株，年龄为２０～２１年，直径分布６～２６ｃｍ，树高６～１６ｍ按２ｍ区分段，量测各段中央处的带皮直径，去皮直径，并现场造材，记录不同材种的出材率，并选择模型７为最适宜削度方程，方程１１为最适宜材积方程，确定了不同材种不同材长的出材率，编制了苍梧县杉木出材率表。     

苍梧县杉木削度方程与材积比方程研究

在苍梧县共青林场等集体林场的伐区,随机量测样木548株,年龄为20～21年,直径分布6～26cm,树高6～16m,按2m区分段,量测各段中央处的带皮直径、去皮直径,并现场造材,记录不同材种的出材率。并选择模型7为最适宜削度方程,方程11为最适宜材积方程,确定了不同材种不同材长的出材率,编制了苍梧县杉木出材率表。     

洋口林场杉木人工林材种出材率表的研究

根据洋口国有林场有代表性的杉木人工林样木资料,应用逐步回归技术和遗传算法建立可变参数削度方程,编制杉木人工林单木二元材种出材率表,为准确估算材种出材量提供了科学依据。     

永安巨桉一元材种出材率表编制研究

在永安市巨桉(Eucalyptus Garndis)林分选择并设置10个标准地,分别进行林分因子调查,以4m段材长分径阶进行样木伐倒造材,应用区分求积式进行材积计算,以实际造材各材种出材率为基础拟合一元材积比方程,根据相关系选择较优的一元材积比方程进行理论造材并编制巨桉林分一元材种出材率表,并进行精度检验,表明精度可达90%以上,可为桉树生产提供一定的参考。     

隆缘桉立木材种出材率表

隆缘桉是雷州林业局七十年代以前营造桉树的主要树种,有林面积达五十余万亩。根据栽培矿柱材为主的经营目的,掌握单位面积产材量的材种出材率,它是衡量林分经济效果的重要标志,是编制林业计划的可靠依据。本文,材种出材率表取用1973年编制立木材积表的样木来试行编制,兹分述如     

湿地松材积出材率表的研究

根据５３２株湿地松伐倒木测径数据，通过１４组削度方程的比选，选定了符合湿地松树种的削度方程。此削度方程对任意直径限处的材长、任意高度处的直径及树干全材积等可获得高精度的估计。通过计算机理论造材，编制出湿地松一元和二元材种出材率表，各技术程序全部采用数学模型进行模拟，改变了过去用图解法传统编制材种数表的技术方法，提高了材种数表的精度     

隆缘桉人工林林分材种出材率表

隆缘桉是桉树人工林主要树种。仅雷州林业局有林面积达五十余万亩,以栽培矿柱材为主要经营目的。掌握单位面积产材量的材种出材率,是衡量林分经济效果的重要标志,是编制林业生产计划的可靠依据。为了隆缘桉人工林进行伐区施工设计工作和调查研究工作的需要。本文,取用1979年为编制1980年林业生产计划而进行的伐区调查,所收集的样地资料用来试编隆缘桉人工林林分材种出材率表。共调查样地43块,每块样地面积一市亩,而每块样地样木58—160株。     

吉林省蒙古栎削度方程与材种出材率表研究

利用在吉林省各县(市、区)所采集3 157株蒙古栎编表、验表样木数据,运用削度方程计算立木材积和材种出材率表,结果表明:运用削度方程可以灵活地反映树干上任意部位直径、既定直径处材长、材积、出材率、树干上任意分段材积和全树干材积;同时根据林分树高差异调整树高式参数,编制的材种出材率表精度高、适用性强,更符合林分中林木生长实际状况     

应用削度方程编制湿地松材积表和出材率表的研究

在树干形状研究的基础上,利用样木资料建立了一个适合湿地松人工林干形变化规律的可变参数削度方程,据以编制了一元材积表、二元材积表、一元材种出材率表和二元材种出材率表,这些数表经检验误差较小,精度较高,可在林业生产上推广应用。     

速生丰产林培育目标和主伐年龄研究

林木培育目标应根据林分立地条件类型、林分生长类型等级、森林经营集约度和社会材种需求综合确定。通过林木定向培育提早主伐年龄以获得较高目的材种产量。对大径材培育主伐年龄应先与工艺成熟龄比较后确定。良种化林木培育是森林经营水平的重要标志，与Ⅰ类林分相比仍提早主伐年龄，增加材种产量１倍左右。应具体分析目前速生丰产林生长状况，林龄面积分布等，调整林木培育目标和主伐年龄，以保证森林资源的永续利用。     

杉木人工林材种结构的立地及密度效应研究

采用30年生未间伐的杉木人工林连续观测数据,研究了不同林龄立地质量、林分密度对林分材种结构的影响。结果表明:初植密度相同时,立地质量越好各材种出现时间及达到最大出材率的时间越早,22立地指数初植密度1 667株·hm^-2的小径材最大出材率出现时间较16立地指数初植密度1 667株·hm^-2早4 a,中径材最大出材率出现的时间早6 a;立地指数相同时,随初植密度增加小径材出材率的峰度及峰值均减小,20立地指数样地中,初植密度为1 667株·hm^-2的小径材出材率峰值较初植密度为10 000株·hm^-2的高17%,而初植密度对中径材、大径材影响不大;在林分发展的不同时期,林分密度对材种出材率的影响不同,30年生时林分蓄积相近的但初植密度不同的样地,初植密度越大小径材出材率越高,大径材出材率越低。     

冷杉腐朽病研究：Ⅳ.冷杉腐朽病对经济出材影响的研究

在四川本部高山冷杉林区，冷杉腐朽病的危害性在于降低了林分出材率，改变了林木材料结构。通过２８４９株冷杉伐倒木测定表明，冷杉林木发生腐朽后，林种结构有明显的变化，优良林种下降，加工材增加。在冷杉林木出材率方面，腐朽木较健康木下降８．４－２８．８％（平均１４．９）。冷杉林区冷杉林分出材率，与林分年龄的腐朽率，林分径级的腐朽率均呈极显著的负相关。回归方程分别如下：Ｙ＝８１．４６－０．２１ｘ１，Ｙ＝８２．     

南亚热带杉木人工林材种结构长期立地与密度效应

[目的]揭示南亚热带杉木人工林材种发育的长期立地和密度动态效应规律。[方法]以广西大青山A(1667株·hm^-2)、B(3333株·hm^-2)、C(5000株·hm^-2)、D(6667株·hm^-2)、E(10000株·hm^-2株)5种初植密度、36 a生杉木(Ctmninghamia lanceolata)密度试验林为研究对象,分析密度和立地影响下材种株数与材种材积分布的动态变化规律。[结果]杉木林分小径材株数和材积比率在初期随林龄增长而递增,达峰值后随林龄增长而减少,初植密度越小、立地指数级越高,减少速度越快;中、大径材株数和材积比率随林龄增长而增加,初植密度越小、立地指数级越高,增速越快。18立地指数级D及以下密度林分28 a生前中径材材积比例约50%;36 a生时A密度林分大径材材积比例约50%。16立地指数级中低初植密度林分中径材材积比例均超过45%,且以C密度林分最高、约48%;36 a生时A密度林分大径材材积比例超过26%。14立地指数级,A密度林分中径材材积比例24 a生时达44%,A、B、D密度林分小径材材积分别于12、18、24 a生时达83%、76%、69%o 10立地指数级C、E密度林分36 a生时小径材材积比例分别达71%、61%。[结论]杉木林材种形成与立地、密度和林龄关系密切,立地质量具决定性作用,而培育高规格材种时初植密度亦可成为关键限制因素。初植密度越低、立地指数越高,越利于中、大径材形成。在杉木南带产区,10指数级立地短周期经营时只适宜培育小径材及小条木。14指数级立地适宜培育中、小径材,若以中径材为第一培育材种时初植密度宜低。16指数级立地适宜培育中径材,长周期经营时也可培育大径材,但初植密度不宜超1667株·hm^-2。18指数级立地中径材生产潜力很大,但更宜培育大径材,且初植密度宜控制在A密度,轮伐期不宜低于36 a。     

Timber yield projections for tropical tree species: The influence of fast juvenile growth on timber volume recovery

Most growth and yield models for tropical tree species use diameter growth data obtained from permanent sample plots. A potential disadvantage of this data source is that slow-growing, suppressed juvenile trees are included of which only a small fraction will attain harvestable size. If this is the case, the average growth rate of extant juvenile trees will be lower than the historical, juvenile growth rate of trees of harvestable size. Thus, if juvenile growth rates are obtained from permanent plots, future timber yield may be underestimated. To determine the magnitude of this effect we simulated tree growth based on two types of diameter growth data: long-term tree-ring data from harvestable trees (‘lifetime growth data’) and growth data of the last 10 years from trees of all sizes (‘plot-type growth data’). The latter data type is a proxy for growth data from permanent sample plots. Second, we evaluated which percentage of harvestable timber volume at initial harvest is available at second harvest using lifetime growth data. We obtained tree-ring data from 89 to 98 individuals of three Bolivian timber species over their entire size range. Based on these data tree growth simulations were performed for two scenarios: a second harvest in 20, and in 40 years. A realistic degree of growth autocorrelation was incorporated in the growth projections, for both the lifetime and the plot-type growth data.     

柞、硬阔叶树与软阔叶树原条材种出材量(率)表的编制

我国50～60年代初期,林业部综合队曾编制红松(Pinus koraiensis Sieb.et Zucc.)、云杉(Picea spp.)、马尾松(Pinus massoniana Lamb.)、兴安落叶松(Larix gmelini(Rupr.)Rupr.)、白桦(Betula platyphylla Suk.)等树种材种出材量表,70～80年代各省(区)市、规划院、科研等单位对杉(Cunninghamia lanceolata Hook.)、落叶松、山杨(Populus davidiana     

Household and farm attributes affecting adoption of smallholder timber management practices by tree growers in Gunungkidul region,Indonesia

Farm household characteristics determine the success of programs promoting agroforestry systems and practices. This paper reports household and farm factors affecting the adoption of timber management practices by smallholders in the Gunungkidul region, Central Java, Indonesia. The research used three logistic regression analysis models—based on each household and farm characteristic, and a composite of both together—to identify the key factors influencing farmers’ adoption and management decisions, and their relative importance. A sample of 152 farmers who managed their trees primarily for timber production was compared to a sample of 115 farmers with similar socio-economic characteristics who did not. The household condition and composite models identified both on-farm and off-farm gross incomes as significant factors affecting farmers’ decisions to manage timber trees. The models confirmed that farmers with larger farms, and with higher on- and off-farm incomes, were more likely to manage their trees for timber production. These results have implications for extension programs that promote adoption of commercial timber management by smallholders in the case study and similar regions.     

Comparing model-based approaches with bucking simulation-based approach in the prediction of timber assortment recovery

The aim of the study was to compare model-based approaches inthe prediction of timber assortment recovery with bucking simulationbased on detailed stem data. A correction function for the totallength of saw log fragments and two optional saw log reductionmodels, that is, the MELA96 version and MELA05 version, wereapplied. In the bucking simulation, the volumes by timber assortmentswere calculated using a bucking-to-value simulator. The predictionof saw log recoveries varied between the bucking simulationand different versions of saw log reduction models. The levelof the reduction from the MELA96 version was at the same levelas from the bucking simulation where defects were taken intoaccount, but the saw log reduction had a very low variance dueto a small amount of independent variables. The saw log reductionof the MELA05 version included more variation although the levelof the reductions was higher and the variation did not meetwith the bucking simulation. As a conclusion, the model-basedapproaches seem applicable at least for the prediction of sawlog recovery in the large area forest inventories where thevariance of the standwise timber assortment recoveries neednot be predicted.