Timber assortment structure and outturn model for final felling stands of Cunninghamia lanceolata plantations
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摘要:
目的 明晰杉木主伐林分的材种结构规律并构建合理的林分出材率模型，为我国杉木人工林木材产量提高、营林技术提升以及经营方案优化提供科学依据。 方法 根据福建省6个国有林场近15年的杉木人工林492块伐区调查数据，选用林分平均胸径、平均高、年龄、蓄积量、密度、立地质量等林分因子，探讨林分规格材、非规格材、经济材、薪材、商品材、废材6种材种出材率对各因素的响应。在此基础上筛选影响材种出材率的主要林分因子，构建杉木主伐林分材种出材率模型，并对模型进行适用性评价。 结果 杉木主伐林分的各林分因子中，林分平均胸径和平均高对各材种出材率的影响最大，且远高于其他林分因子，其次为林分蓄积量、年龄和密度，立地质量的影响相对较小。以林分平均胸径和平均高为自变量构建杉木主伐林分的规格材、经济材、薪材出材率模型，模型拟合及检验效果均良好，以此为基础构建非规格材、商品材、废材出材率模型。对不同径阶的各材种出材率模型进行预测误差计算，预测误差均较小，且误差分布较为均匀。 结论 本研究揭示了杉木主伐林分的材种结构规律及其影响因子，建立的出材率模型体系可用于杉木主伐林分的出材率测算，为杉木人工林合理生产计划的制定提供支持。 Abstract:Objective It is an important premise to clarify the timber assortment structure of Cunninghamia lanceolata plantations and build a reasonable outturn model, aiming to increase the wood yield, improve the forest management techniques and optimize the management plan for Cunninghamia lanceolata plantations. Method Based on the 492 felling areas of Cunninghamia lanceolata plantations from 6 state-owned forest farms in Fujian Province of eastern China in the past 15 years, the response of 6 timber assortment outturn (i.e., dimension timber, non-dimension timber, commercial timber, fuel wood, merchantable timber, refuse wood) to each factor, including average DBH, average height, stand age, stand volume, stand density and site quality, was investigated. On this basis, the main stand factors affecting the yield of timber species were screened, the timber outturn model for final felling stands of Cunninghamia lanceolata was constructed and the applicability of the model was evaluated. Result Among the stand factors of Cunninghamia lanceolata final felling stands, average DBH and average height showed much larger influence than other stand factors on the outturn of each timber assortment, followed by stand volume, age and density, and the influence of site quality was relatively small. The dimension timber, commercial timber and fuel wood timber assortment outturn model system using average DBH and average height as predictive variables showed good fitting and validating results. Based on this, the timber assortment outturn model of non-dimension timber, merchantable timber and refuse wood timber assortment outturn model was constructed. The prediction errors of the timber assortment outturn for different diameter classes were small and stable. Conclusion This study reveals the timber assortment structure rule, as well as its influencing factors for Cunninghamia lanceolata final felling stands. The model system can be used to calculate the timber assortment yield of Cunninghamia lanceolata final felling stands, and provide support for the formulation of rational production plan of Cunninghamia lanceolata plantations. -
图 1 根据不同林分因子的伐区数量统计
Figure 1. Number of felling area according to different stand factors
图 2 各材种出材率随林分平均胸径的变化
Figure 2. Change of average outturn percentage with stand average DBH
图 3 各材种出材率随林分平均高的变化
Figure 3. Changes of average outturn percentage with stand average height
图 7 各杉木林分材种出材率在不同径阶的预测误差
箱型图显示了各径阶的出材率预测误差的均值、分位数、最大值、最小值和异常值。The box plots display the whiskers, percentiles and mean of the predicted errors of outturn percentages for each diameter class, as well as outliers.
Figure 7. Predicted errors of outturn percentages against diameter class for Cunninghamia lanceolata
表 1 各伐区主要林分因子统计
Table 1. Statistics of stand factors for each felling area
林分因子 Stand factor 最小值 Minimum value 最大值 Maximum value 均值 Average value SD CV 伐区面积/hm2 Cutting area/ha 0.2 21.0 4.3 3.766 0.876 平均胸径 Average DBH/cm 10.0 30.8 17.1 3.173 0.185 平均高 Average height/m 6.4 21.7 12.0 2.296 0.192 林分年龄/a Stand age/year 18 53 32 7.747 0.240 林分密度/（株·hm−2） Stand density/(tree·ha−1) 360 4 890 1543 719.399 0.466 单位面积蓄积/（m3·hm−2） Stand volume unit area/(m3·ha−1) 25.5 580.5 212.9 100.482 0.472 
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表 2 林分因子与材种出材率相关性分析
Table 2. Correlation analysis between stand factors and outturn percentage
林分因子
Stand factor出材率 Outturn percentage 规格材
Dimension timber非规格材
Non-dimension timber经济材
Commercial timber薪材
Fuel wood商品材
Merchantable timber废材
Refuse wood平均胸径 Average DBH 0.865** −0.444** 0.888** −0.837** 0.808** −0.808** 平均高 Average height 0.854** −0.438** 0.877** −0.651** 0.861** −0.861** 林分年龄 Stand age 0.278** −0.255** 0.219** −0.205** 0.200** −0.200** 林分密度 Stand density −0.310** 0.072 −0.397** 0.841** −0.182** 0.182** 林分蓄积量 Stand volume 0.580** −0.373** 0.527** −0.023 0.673** −0.673** 立地等级 Site level −0.101* −0.009 −0.159** 0.101* −0.165** 0.165** 注：*表示相关性达显著水平（p < 0.05），**表示相关性达极显著水平（p < 0.01）。 Notes: * indicates significant correlation (p < 0.05) and ** indicates extremely significant correlation (p < 0.01).
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表 3 林分各材种出材率在不同立地等级的方差分析及多重比较结果
Table 3. Analysis of variance and multiple comparison results of the yield of various timber species in forest stands at different site levels
材种
Timber assortmentF LSD多重比较 LSD multiple comparison $ {\overline P _1} $ – $ {\overline P _2} $ $ {\overline P _1} $ – $ {\overline P _3} $ $ {\overline P _2} $ – $ {\overline P _3} $ 规格材 Dimension timber 3.361* 1.26 3.32* 2.06 非规格材 Non-dimension timber 1.070 1.00 0.60 −0.39 薪材 Fuel wood 4.028* −0.73* −0.85** −0.12 废材 Refuse wood 8.871** −1.53* −3.08** −1.54* 经济材 Commercial timber 8.474** 2.26* 3.92** 1.66* 商品材 Merchantable timber 8.871** 1.53* 3.08** 1.54* 注：$ {\overline P _1} $、$ {\overline P _2} $、$ {\overline P _3} $分别代表Ⅰ、Ⅱ及Ⅲ类地的林分材种平均出材率。*表示差异显著（p < 0.05），**表示差异极显著（p < 0.01）。Notes: $ {\overline P _1} $, $ {\overline P _2} $ and $ {\overline P _3} $ represent the average outturn percentage in Ⅰ, Ⅱ and Ⅲ site level, respectively. * indicates significant correlation (p < 0.05), and ** indicates extremely significant correlation (p < 0.01).
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表 4 各材种出材率模型拟合结果
Table 4. Fitting results of outturn percentage model
材种 Timber assortment 模型 Model a b c d 均方根误差
Root mean square errorR2 规格材 Dimension timber 1 52.373 1.582 −1 041.905 4 155.411 3.548 0.932 2 7.014 1.201 −0.040 21.756 3.533 0.933 3 0.041 0.762 3.868 0.920 4 −0.837 −0.186 3.675 0.649 27.471 0.074 5 238.370 0.028 −2.864 3.536 0.933 经济材 Commercial timber 1 77.964 1.165 −546.872 1 846.520 2.110 0.954 2 24.608 0.318 0.014 1.184 2.146 0.953 3 13.207 0.196 2.260 0.947 4 0.125 0.012 −0.077 −0.095 8.058 0.813 5 −7.228 0.007 0.615 2.241 0.948 薪材 Fuel wood 1 15.770 −0.501 46.615 −145.045 1.313 0.815 2 202.769 −0.828 −0.036 2.824 1.295 0.821 3 140.439 −0.326 1.340 0.807 4 0.048 0.007 −0.104 −0.038 3.641 0.024 5 127.559 0.210 −8.463 1.359 0.801 注：a、b、c、d为模型求解参数。Note: a, b, c and d are the solving parameters of the model.
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表 5 材种出材率模型适用性检验结果
Table 5. Results of suitability of volume ratio model
材种
Timber assortment模型
Model成对差分均值
Pairwise difference average value成对差分标准差
Pairwise difference standard deviation成对差分均值的标准误差
Standard error of pairwise difference average value平均相对误差
Average relative error/%T检验值
T test valuep 规格材
Dimension timber1 0.309 3.730 0.333 0.142 0.093 0.926 2 0.107 3.843 0.343 0.125 0.079 0.937 3 −0.121 4.239 0.379 −0.557 −0.321 0.749 5 0.272 3.615 0.323 0.437 0.333 0.740 经济材
Commercial timber1 0.166 2.093 0.187 0.279 0.974 0.332 2 0.203 2.134 0.190 0.033 1.066 0.289 3 0.182 2.238 0.200 −0.056 0.834 0.406 5 0.169 2.232 0.199 −2.146 0.850 0.397 薪材 Fuel wood 1 0.628 1.263 0.112 0.628 0.557 0.579 2 0.593 1.239 0.110 −0.040 0.535 0.593 3 0.442 1.284 0.114 −0.152 0.385 0.701 5 0.342 1.313 0.117 −7.112 0.292 0.771
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[1] 郑仁华, 施季森, 苏顺德, 等. 杉木第3代种子园营建技术及应用[J]. 森林与环境学报, 2018, 38(4): 406−413.Zheng R H, Shi J S, Su S D, et al. The establishment technique and application of the third generation seed orchard of Chinese fir[J]. Journal of Forest and Environment, 2018, 38(4): 406−413. [2] Wang Z, Zhang X Q, Chhin S, et al. Disentangling the effects of stand and climatic variables on forest productivity of Chinese fir plantations in subtropical China using a random forest algorithm[J]. Agricultural and Forest Meteorology, 2021, 304−305(11): 108412. [3] 臧颢, 黄锦程, 刘洪生, 等. 杉木人工林碳汇木材多功能经营的最优轮伐期[J]. 北京林业大学学报, 2022, 44(10): 120−128.Zang H, Huang J C, Liu H S, et al. Optimal rotation period of carbon sequestration wood multifunctional management in Chinese fir plantation[J]. Journal of Beijing Forestry University, 2022, 44(10): 120−128. [4] Wang Z, Zhang X Q, Zhang J G, et al. Effects of stand factors on tree growth of Chinese fir in the subtropics of China depends on climate conditions from predictions of a deep learning algorithm: a long-term spacing trial[J]. Forest Ecology and Management, 2022, 520(84): 120363. [5] 宋重升, 王有良, 张利荣, 等. 基于大径材培育下杉木人工林间伐初始期的确定[J]. 北京林业大学学报, 2022, 44(3): 45−54.Song C S, Wang Y L, Zhang L R, et al. Determination of initial thinning period of Chinese fir plantation based on large diameter timber cultivation[J]. Journal of Beijing Forestry University, 2022, 44(3): 45−54. [6] 梁瑞婷, 孙玉军, 周来. 基于分位数回归法的杉木可变指数削度方程构建[J]. 北京林业大学学报, 2021, 43(7): 70−78.Liang R T, Sun Y J, Zhou L. Modeling variable exponential taper function for Cunninghamia lanceolata based on quantile regression[J]. Journal of Beijing Forestry University, 2021, 43(7): 70−78. [7] 索沛蘅, 杜大俊, 王玉哲, 等. 杉木连栽对土壤氮含量和氮转化酶活性的影响[J]. 森林与环境学报, 2019, 39(2): 113−119.Suo P H, Du D J, Wang Y Z, et al. Effects of successive rotation Chinese fir plantations on soil nitrogen content and soil enzyme activities related to nitrogen transformation[J]. Journal of Forest and Environment, 2019, 39(2): 113−119. [8] 韦如萍, 胡德活, 郑会全, 等. 杉木优树生长性状和材质性状的研究[J]. 中南林业科技大学学报, 2013, 33(2): 28−33.Wei R P, Hu D H, Zheng H Q, et al. Study on growth traits and wood properties of superior tree of Cunninghamia lanceolata[J]. Journal of Central South University of Forestry & Technology, 2013, 33(2): 28−33. [9] 张丹丹, 李婧, 郭琪, 等. 氮添加对杉木人工林土壤氮有效性、溶解性有机氮和酸化的影响[J]. 西北农林科技大学学报(自然科学版), 2019, 47(12): 77−85, 114.Zhang D D, Li J, Guo Q, et al. Effects of nitrogen addition on soil nitrogen availability, dissolved organic nitrogen and acidification in a Chinese fir plantation[J]. Journal of Northwest A&F University (Natural Science Edition), 2019, 47(12): 77−85, 114. [10] 孟宪宇. 测树学[M]. 北京: 中国林业出版社, 2006: 143−151.Meng X Y. Mensuration[M]. Beijing: China Forestry Publishing House, 2006: 143−151. [11] Andrezj W, Mariusz B, Agnieszka A, et al. Relationship between stand density and value of timber assortments: a case study for Scots pine stands in north-western Poland[J]. New Zealand Journal of Forestry Science, 2018, 48(1): 1−9. doi: 10.1186/s40490-017-0108-0 [12] Holopainen M, Vastaranta M, Rasinmaki J, et al. Uncertainty in timber assortment estimates predicted from forest inventory data[J]. European Journal of Forest Research, 2010, 129(6): 1131−1142. doi: 10.1007/s10342-010-0401-4 [13] 李晓景, 江希钿, 庄崇洋, 等. 闽北天然阔叶林径阶材种结构分析及出材率表的编制[J]. 西南林业大学学报, 2012, 32(6): 39−42.Li X J, Jiang X D, Zhuang C Y, et al. Compilation of output structure of diameter grade wood assortments and volume ratio table for natural broad-leaved forest tree species in north Fujian Province[J]. Journal of Southwest Forestry University, 2012, 32(6): 39−42. [14] 林剑峰. 马尾松人工林材种出材率表的研究[J]. 北京林业大学学报, 2001, 23(4): 35−38.Lin J F. Research on log rule of timbers from artificial Masson pine forest[J]. Journal of Beijing Forestry University, 2001, 23(4): 35−38. [15] 李骏. 福州市国有林场杉木林林分材种出材率研究[D]. 福州: 福建农林大学, 2017.Li J. The research of outturn percentage of timber species in Fuzhou State-Owned Forest Farm fir[D]. Fuzhou: Fujian Agriculture and Forestry University, 2017. [16] 赵铭臻, 王利艳, 刘静, 等. 间伐和施肥对杉木成熟林生长和材种结构的影响[J]. 浙江农林大学学报, 2022, 39(2): 338−346.Zhao M Z, Wang L Y, Liu J, et al. Effects of thinning and fertilization on growth and timber structure of mature Chinese fir forest[J]. Journal of Zhejiang A&F University, 2022, 39(2): 338−346. [17] 张水松, 陈长发, 吴克选, 等. 杉木林间伐强度材种出材量和经济效果的研究[J]. 林业科学, 2006, 42(7): 37−46.Zhang S S, Chen C F, Wu K X, et al. Studies on the timber assortment outturn and economic benefit of the intermediate cutting intensity for Cunninghamia lanceolata stands[J]. Scientia Silvae Sinicae, 2006, 42(7): 37−46. [18] 邓伦秀. 杉木人工林林分密度效应及材种结构规律研究[D]. 北京: 中国林业科学研究院, 2010.Deng L X. Studies on stand density effect and timber grade structure of Cunninghamia lanceolata plantations[D]. Beijing: Chinese Academy of Forestry, 2010. [19] 郭书彬, 宋熙龙, 尤海舟, 等. 经营密度对华北落叶松人工林生长的影响[J]. 中南林业科技大学学报, 2018, 38(4): 1−5.Guo S B, Song X L, You H Z, et al. Effects of forest density on Larix principis-rupprechtii plantation[J]. Journal of Central South University of Forestry & Technology, 2018, 38(4): 1−5. [20] 相聪伟, 张建国, 段爱国, 等. 杉木人工林材种结构的立地及密度效应研究[J]. 林业科学研究, 2015, 28(5): 654−659.Xiang C W, Zhang J G, Duan A G, et al. Effects of site quality and planting density on wood assortment rate in Chinese fir plantation[J]. Forest Research, 2015, 28(5): 654−659. [21] 王素萍, 江希钿, 杨锦昌. 杉木人工林林分材种出材率变化规律的分析[J]. 福建林学院学报, 2002, 22(2): 146−149.Wang S P, Jiang X D, Yang J C. An analysis on the change law of output of wood sort for Cunninghamia lanceolata plantation[J]. Journal of Fujian College of Forestry, 2002, 22(2): 146−149. [22] 李明阳. 森林经营规划[M]. 北京: 中国林业出版社, 2022: 136−141.Li M Y. Forest management planning[M]. Beijing: China Forestry Publishing House, 2022: 136−141. [23] 福建省市场监督管理局. 森林立地分类与立地质量等级: DB35/T 169—2022[S]. 福州: 福建省市场监督管理局, 2022.Market Supervision Administration of Fujian Province. Forest site classification and site quality grade: DB35/T 169−2022[S]. Fuzhou: Market Supervision Administration of Fujian Province, 2022. [24] 福建省市场监督管理局. 主要用材树种出材量测算方法: DB35/T 1876—2019[S]. 福州: 福建省市场监督管理局, 2019.Market Supervision Administration of Fujian Province. A calculating methods standard on output volume of main timber tree species: DB35/T 1876−2019[S]. Fuzhou: Market Supervision Administration of Fujian Province, 2019. [25] 王梓名, 赵明明, 任云卯, 等. 主伐龄油松建筑材林生长及土壤性质对林分密度的响应[J]. 北京林业大学学报, 2022, 44(12): 88−101.Wang Z M, Zhao M M, Ren Y M, et al. Response of growth and soil properties of Chinese pine building timber forest at felling age to stand density[J]. Journal of Beijing Forestry University, 2022, 44(12): 88−101. [26] 孙余丹, 刘爽, 刘金祥, 等. 不同红树林群落结构与植被碳分布[J]. 东北农业大学学报, 2018, 49(11): 58−64.Sun Y D, Liu S, Liu J X, et al. Community structure and vegetation carbon distribution of different mangrove forests[J]. Journal of Northeast Agricultural University, 2018, 49(11): 58−64. [27] 金菊良, 杨晓华, 丁晶. 标准遗传算法的改进方案—加速遗传算法[J]. 系统工程理论与实践, 2001, 21(4): 8−13.Jin J L, Yang X H, Ding J. An improved simple genetic algorithm-accelerating genetic algorithm[J]. Systems Engineering—Theory & Practice, 2001, 21(4): 8−13. [28] 黄朝法. 相容性杉木人工单木二元材种出材率模型[J]. 武夷学院学报, 2019, 38(6): 33−37.Huang C F. Compatible individual tree two-way merchantable volume model of Cunninghamia lanceolata plantation[J]. Journal of Wuyi University, 2019, 38(6): 33−37. [29] 郭光智, 段爱国, 张建国, 等. 南亚热带杉木人工林材种结构长期立地与密度效应[J]. 林业科学研究, 2020, 33(1): 35−43.Guo G Z, Duan A G, Zhang J G, et al. Long-term effects of site and density on timber assortment structure of Chinese fir plantations in south subtropical area, China[J]. Forest Research, 2020, 33(1): 35−43. [30] 郑鸣鸣, 任正标, 王友良, 等. 间伐强度对杉木中龄林生长和结构的影响[J]. 森林与环境学报, 2020, 40(4): 369−376.Zheng M M, Ren Z B, Wang Y L, et al. Effect of thinning intensity on the growth and structure of a middle-aged Chinese fir forest[J]. Journal of Forest and Environment, 2020, 40(4): 369−376. [31] 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.Zhou G M, Guo R J, Wei X L, et al. Growth model and cutting age of Chinese fir planted forest in Zhejiang Province[J]. Journal of Zhejiang Forestry College, 2001, 18(3): 219−222. [32] 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确定[J]. 林业科学, 2001, 37(增刊1): 47−51. doi: 10.11707/j.1001-7488.2001S109Chen P L, Liu J, Zheng D X. The confirmation of harvesting period and the analysis of economic effect on the productive and high-quality Chinese fir plantation[J]. Scientia Silvae Sinicae, 2001, 37(Suppl.1): 47−51. doi: 10.11707/j.1001-7488.2001S109 -
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