长白落叶松人工林树冠结构及生长模型研究
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摘要
人工林是实现森林可持续经营的重要途径,如何提高人工林产量和木材品质是国内外森林经营面临的难点之一。树冠是树木进行光合作用的主要场所,其结构决定了树木生产力及生态效益的发挥。本研究以黑龙江省东折棱河林场的长白落叶松(Larix olgensis Henry)人工林为研究对象,基于样地调查、树冠枝条解析因子调查、生物量和叶面积测定、树干解析及年轮测定数据的基础上,运用森林经理学、统计学及数学模型的方法对树冠结构及生长进行定量分析与模拟。从枝条、冠层及整体树冠3个层次研究了树冠枝条冠层结构、树冠轮廓大小、生物量和叶面积及生长模型,尝试研究了树冠与树木生长之间的关联,以期为经营、培育有利于光能利用的树冠结构,提高木材产量和木材品质奠定基础。主要研究结论归纳如下：
(1)不同年龄阶段长白落叶松枝条解析因子(枝条数量、直径、长度和角度)的冠层结构及其定量模型研究表明：枝条密度与冠层深度(DINC)、高径比(H/D)变量有显著相关；平均枝条直径随冠层深度的增加而增加,最大枝条直径随冠层深度的增加呈单峰型,在相对冠层深度65-75%出现峰值;枝条长度的垂直结构呈抛物线型,在相对冠层深度60～95%出现最大值；不同年龄间着枝角无显著差异,着枝角随着冠层深度的增加呈增加趋势;建立的最优定量模型能较好估测枝条解析因子
(2)应用主轴切割法和构筑型法相结合求算树冠半径、体积和表面积。通过筛选变量,构建的异速生长模型能较好地模拟树冠轮廓形状、树冠体积、和表面积,最大冠幅冠层高度与冠幅、胸径均有显著相关,最大冠幅上部的树冠轮廓模型以幂函数方程最佳；最佳树冠体积和树冠表面积估测模型均以胸径、冠幅和冠长变量组合为最佳,R2达0.98以上。
(3)自变量个数及变量组合均会影响长白落叶松树冠率、活枝高和冠幅模型拟合精度；林木竞争因子(BA、CCF)和林木大小(DBH、HT)是影响树冠率和活枝高的主要因子,大于对象木的树冠竞争因子(CCFL)是估测冠幅模型的最佳变量；树冠率以Exponential模型为最优,估测树冠生长动态时活枝高模型优于树冠率模型。
(4)不同年龄枝条干重与鲜重存在显著线性关系,枝条生物量异速生长模型以枝条直径变量为最佳,枝生物量的异速生长指数b值接近理论参数值(8/3)；冠层枝和叶生物量在树冠中上层0-5m均随着冠层深度增加而增加,枝、叶生物量累积分布模型以修正Weibull模型为最优,枝和叶生物量累积分布模型分别为：F(BW)=1.305×(1-exp(2.742×RDINC2.544)) F(LW)=1.030×(1-exp(3.337×RDINC2.424))；胸径是树冠生物量模型的最佳预测变量,增加年龄或活枝高能一定程度上提高模型精度。
(5)年龄、冠层是影响长白落叶松比叶面积(SLA)变化的重要因素,SLA随着冠层深度的增加而增加,树冠上层、中层和下层的SLA分别为101.08、117.37和129.91cm2/g,幼龄、中龄、近熟和成熟林的比叶面积分别为145.34、111.55、92.60和128.03cm2/g,平均值为116.39cm2/g;枝条叶面积估测模型以枝径为最佳变量,其次是冠层深度,分段枝条叶面积异速生长模型拟合效果最佳；单变量树冠叶面积估测模型是胸径为异速生长模型的最佳,并在幂指数中引入高径比能提高拟合精度：LA=0.3024×DBH1.944-0.1965×HD；长白落叶松人工叶面积指数在中龄林时增加缓慢、近熟林时保持相对稳定、成熟林时期呈减少趋势。
(6)长白落叶松年轮宽度径向生长过程呈先增后减,达到一定年龄后保持基本稳定,年轮宽度在第3-6年间出现最大值,年轮宽度的变化主要受到早材宽度的影响;幼龄冠是指林木幼、中龄林时期树冠上层短期内(第1～5年)形成的自由冠,幼龄冠对年轮宽度及年轮面积生长保持稳定值；中龄林和近熟林活冠以下短期内的年轮宽度及面积生长保持稳定值,但成熟林时期树干年轮面积在基部有明显增加,其年轮面积随着树干高度的增加而减少；不同年龄阶段年轮宽度及面积生长在树冠内无显著差异,但年轮面积生长在株内间有显著差异。长白落叶松心材形成的初始年龄为5年,30年以下和30年以上的平均心材形成率分别为0.65ring/年和0.96ring/年；心材年龄估测模型以二次曲线方程最优,心材和边材生长模型是以胸径和树高为变量的异速生长方程最优HWV=4.0*10-6DBH2.149250HT1.296038,R2=0.989SWV=1.02*10-4DBH0.750383HT1.673065,R2=0.943树皮厚度随着相对树干高度的增加呈先快速减少后保持缓慢递减趋势,树皮因子随着树干高度的变化呈先增后减的趋势；该地区的长白松树高、去皮胸径和材积生长过程模型以理查德(Richards)模型最佳。
Forest plantation is an important approach for forest sustainable management, how to improve the forest yield and timber quality is one of major tasks in the current forest management. Tree crown is an essential place for the photosynthesis, its structure determines the production and ecological benefit. Knowing the crown structure and development would help to evaluate and forecast the stem growth, wood quality attributes. The thesis based on the data of field inventory, branches attributes, biomass, leaf area, stem rings analysis for the Larix olgensis plantation from different stand ages at Dongzhelenghe forest farm in Heilingjiang province. The methods of forest management, quantitative analysis, mathematical models were used in analyzing and simulating the crown structure and stem development. The canopy structure and quantitative model were analysed and developed for the branches attributes, crown shape and sizes, biomass and leaf area from branches, canopy layer and overall crown in this paper. We tried to discuss the relationship between the crown structure and tree growth, providing the basement for nurturing the crown structure which is benefit for using solar energy to improve timber production and wood quality. The main conclusions are summarized as follows:
(1)The analysis of the canopy structure for branches attributes (branches number, diameter, length and angle) from different growth stages show that branches density significantly related to the distance into canopy (DINC), the ratio of tree height to diameter at breast height (H/D). The average branches diameter increased with DINC from tree top to down, while the maximum branches diameter per canopy increased with the DINC like a single peak shape, showing the largest diameter at the65to75%of relative distance into canopy layer to crown length (RDINC). The vertical structure of branches length showed parabolic shape with a maximum value in the60to95%of RDINC. The branches angle showed no statistically significant differences between different ages, increasing with canopy depth. The developed quantitative models of branches number, diameter, length and angle with a high coefficient of determination.
(2) Based on the main-axis cutting method and crown architecture method calculated the crown radius, volume and surface area. The allometric equation was good for modeling crown shape, crown volume and crown surface area. The height of the largest crown width (HLCR) was significantly related to DBH and crown width. The power equation was optimal for modeling the profile of crown radius increased with DINC above the HLCR, with a94.1%of forecast accuracy. The allometric equation with the combination variables of DBH,crown width and crown length was the optimum equation for estimating crown volume and crown surface area.
(3) The precision of fitting model was affected by the selected variables and its combination for tree crown ratio, height of crown base (HCB) and crown width models. Stand basal area (BA).crown competition factor index (CCF) and tree size (DBH, HT) were significantly related the crown ratio and HCB. The Exponential equation was better than Logistic model for the optimal crown ratio model, the HCB model fitting better than the crown ratio model, with a0.725of determination coefficient. The crown competition factor larger than objective tree (CCFL) was the best predictive variable for crown width model, with an explaining56.6%of variation.
(4) The dry weight of branches linearly correlated with fresh weight, and the branches level-biomass fitted well with allometric relationship from different ages. The exponent value (b) of branches wood biomass allometric equation was close to the theoretical values (8/3). The canopy biomass of foliage and branches increased with the top5m regardless of stand ages. The best fitting models for the vertical cumulative distribution of branches biomass (BW) and leaves biomass (LW) with were the modified weibull model F{BW)=1.305x(1-exp(2.742×RDINC2.544)) and F{LW)=1.030×(1-exp(3.337x RDINC2.424)). DBH is the best predictor for estimating crown biomass, adding the stand age or HCB to some extent improving the fitting accuracy of crown biomass model.
(5) The specific leaf area (SLA) was significantly affected by stand age and crown layer, respectively. SLA increasing from the top canopy layer to the bottom, the SLA of upper, middle and lower crown was101.08,117.37and129.91cm2/g separately. The SLA of young, middle-aged, sub-mature and mature Larix olgensis plantation was145.34,111.55,92.60and128.03cm2/g separately. with an average value116.39cm2/g of different stand ages. Branches-level leaf area model fitting well with allometric equation using branches diameter as prediction variable, a segmented branches leaf area allometric model was developed in order to improve the model precision. The crown leaf area fitted well with a modified power function using DBH and H/D as independent variables:LA=0.3024×DBH1.944-0.1965×HD.The dynamic of the leaf area index of larch plantation with aging show that increasesd in middle-aged forest, maintained stability in sub-mature forest and tended to decrease in mature forest.
(6) The radial growth process of annual ring width shows that increased in the earliest age, attaining a maximum ring width from the third to the sixth year, decreased to about20years, and then remained a relative steady value after20years. The young crown is freedom crown in the first five years, affecting stem ring growth with the same pattern. The average annual ring width and area were not significant difference in the first three and five years. The average annual width and area of the last three or five years were not significant difference under crown base from middle age and sub-mature stands, but there are significant differences in ring area increment during the three or five years under crown base in mature forest, decreasing along stem height from the tree base to top. The annual ring growth within crown showed the same pattern. The initial heartwood formation of Larix olgensis estimate at the fifth years, the average heartwood formation rates were0.65ring/year and0.96ring/year under30years and older than30years, respectively. The best fitting heartwood ring number with cambial age was quadratic curve equation. The heartwood and sapwood volume allometric equations as a function of DBH and HT were fitted well (HWV=4.0*10-6DBH2.149250HT1.296038,R2=0.989, and SWV=1.02*10-4DBH0.750383HT673065, R2=0.943). The bark thickness as a function of relative stem height was fitted well with the logarithmic equation. The trend of bark factor along the stem height turned increase and then decrease to tree top. The optimal model of the diameter inside-bark at breast height, tree height and volume without bark was Richard model for Larix olgensis plantation.
(1)不同年龄阶段长白落叶松枝条解析因子(枝条数量、直径、长度和角度)的冠层结构及其定量模型研究表明：枝条密度与冠层深度(DINC)、高径比(H/D)变量有显著相关；平均枝条直径随冠层深度的增加而增加,最大枝条直径随冠层深度的增加呈单峰型,在相对冠层深度65-75%出现峰值;枝条长度的垂直结构呈抛物线型,在相对冠层深度60～95%出现最大值；不同年龄间着枝角无显著差异,着枝角随着冠层深度的增加呈增加趋势;建立的最优定量模型能较好估测枝条解析因子
(2)应用主轴切割法和构筑型法相结合求算树冠半径、体积和表面积。通过筛选变量,构建的异速生长模型能较好地模拟树冠轮廓形状、树冠体积、和表面积,最大冠幅冠层高度与冠幅、胸径均有显著相关,最大冠幅上部的树冠轮廓模型以幂函数方程最佳；最佳树冠体积和树冠表面积估测模型均以胸径、冠幅和冠长变量组合为最佳,R2达0.98以上。
(3)自变量个数及变量组合均会影响长白落叶松树冠率、活枝高和冠幅模型拟合精度；林木竞争因子(BA、CCF)和林木大小(DBH、HT)是影响树冠率和活枝高的主要因子,大于对象木的树冠竞争因子(CCFL)是估测冠幅模型的最佳变量；树冠率以Exponential模型为最优,估测树冠生长动态时活枝高模型优于树冠率模型。
(4)不同年龄枝条干重与鲜重存在显著线性关系,枝条生物量异速生长模型以枝条直径变量为最佳,枝生物量的异速生长指数b值接近理论参数值(8/3)；冠层枝和叶生物量在树冠中上层0-5m均随着冠层深度增加而增加,枝、叶生物量累积分布模型以修正Weibull模型为最优,枝和叶生物量累积分布模型分别为：F(BW)=1.305×(1-exp(2.742×RDINC2.544)) F(LW)=1.030×(1-exp(3.337×RDINC2.424))；胸径是树冠生物量模型的最佳预测变量,增加年龄或活枝高能一定程度上提高模型精度。
(5)年龄、冠层是影响长白落叶松比叶面积(SLA)变化的重要因素,SLA随着冠层深度的增加而增加,树冠上层、中层和下层的SLA分别为101.08、117.37和129.91cm2/g,幼龄、中龄、近熟和成熟林的比叶面积分别为145.34、111.55、92.60和128.03cm2/g,平均值为116.39cm2/g;枝条叶面积估测模型以枝径为最佳变量,其次是冠层深度,分段枝条叶面积异速生长模型拟合效果最佳；单变量树冠叶面积估测模型是胸径为异速生长模型的最佳,并在幂指数中引入高径比能提高拟合精度：LA=0.3024×DBH1.944-0.1965×HD；长白落叶松人工叶面积指数在中龄林时增加缓慢、近熟林时保持相对稳定、成熟林时期呈减少趋势。
(6)长白落叶松年轮宽度径向生长过程呈先增后减,达到一定年龄后保持基本稳定,年轮宽度在第3-6年间出现最大值,年轮宽度的变化主要受到早材宽度的影响;幼龄冠是指林木幼、中龄林时期树冠上层短期内(第1～5年)形成的自由冠,幼龄冠对年轮宽度及年轮面积生长保持稳定值；中龄林和近熟林活冠以下短期内的年轮宽度及面积生长保持稳定值,但成熟林时期树干年轮面积在基部有明显增加,其年轮面积随着树干高度的增加而减少；不同年龄阶段年轮宽度及面积生长在树冠内无显著差异,但年轮面积生长在株内间有显著差异。长白落叶松心材形成的初始年龄为5年,30年以下和30年以上的平均心材形成率分别为0.65ring/年和0.96ring/年；心材年龄估测模型以二次曲线方程最优,心材和边材生长模型是以胸径和树高为变量的异速生长方程最优HWV=4.0*10-6DBH2.149250HT1.296038,R2=0.989SWV=1.02*10-4DBH0.750383HT1.673065,R2=0.943树皮厚度随着相对树干高度的增加呈先快速减少后保持缓慢递减趋势,树皮因子随着树干高度的变化呈先增后减的趋势；该地区的长白松树高、去皮胸径和材积生长过程模型以理查德(Richards)模型最佳。
Forest plantation is an important approach for forest sustainable management, how to improve the forest yield and timber quality is one of major tasks in the current forest management. Tree crown is an essential place for the photosynthesis, its structure determines the production and ecological benefit. Knowing the crown structure and development would help to evaluate and forecast the stem growth, wood quality attributes. The thesis based on the data of field inventory, branches attributes, biomass, leaf area, stem rings analysis for the Larix olgensis plantation from different stand ages at Dongzhelenghe forest farm in Heilingjiang province. The methods of forest management, quantitative analysis, mathematical models were used in analyzing and simulating the crown structure and stem development. The canopy structure and quantitative model were analysed and developed for the branches attributes, crown shape and sizes, biomass and leaf area from branches, canopy layer and overall crown in this paper. We tried to discuss the relationship between the crown structure and tree growth, providing the basement for nurturing the crown structure which is benefit for using solar energy to improve timber production and wood quality. The main conclusions are summarized as follows:
(1)The analysis of the canopy structure for branches attributes (branches number, diameter, length and angle) from different growth stages show that branches density significantly related to the distance into canopy (DINC), the ratio of tree height to diameter at breast height (H/D). The average branches diameter increased with DINC from tree top to down, while the maximum branches diameter per canopy increased with the DINC like a single peak shape, showing the largest diameter at the65to75%of relative distance into canopy layer to crown length (RDINC). The vertical structure of branches length showed parabolic shape with a maximum value in the60to95%of RDINC. The branches angle showed no statistically significant differences between different ages, increasing with canopy depth. The developed quantitative models of branches number, diameter, length and angle with a high coefficient of determination.
(2) Based on the main-axis cutting method and crown architecture method calculated the crown radius, volume and surface area. The allometric equation was good for modeling crown shape, crown volume and crown surface area. The height of the largest crown width (HLCR) was significantly related to DBH and crown width. The power equation was optimal for modeling the profile of crown radius increased with DINC above the HLCR, with a94.1%of forecast accuracy. The allometric equation with the combination variables of DBH,crown width and crown length was the optimum equation for estimating crown volume and crown surface area.
(3) The precision of fitting model was affected by the selected variables and its combination for tree crown ratio, height of crown base (HCB) and crown width models. Stand basal area (BA).crown competition factor index (CCF) and tree size (DBH, HT) were significantly related the crown ratio and HCB. The Exponential equation was better than Logistic model for the optimal crown ratio model, the HCB model fitting better than the crown ratio model, with a0.725of determination coefficient. The crown competition factor larger than objective tree (CCFL) was the best predictive variable for crown width model, with an explaining56.6%of variation.
(4) The dry weight of branches linearly correlated with fresh weight, and the branches level-biomass fitted well with allometric relationship from different ages. The exponent value (b) of branches wood biomass allometric equation was close to the theoretical values (8/3). The canopy biomass of foliage and branches increased with the top5m regardless of stand ages. The best fitting models for the vertical cumulative distribution of branches biomass (BW) and leaves biomass (LW) with were the modified weibull model F{BW)=1.305x(1-exp(2.742×RDINC2.544)) and F{LW)=1.030×(1-exp(3.337x RDINC2.424)). DBH is the best predictor for estimating crown biomass, adding the stand age or HCB to some extent improving the fitting accuracy of crown biomass model.
(5) The specific leaf area (SLA) was significantly affected by stand age and crown layer, respectively. SLA increasing from the top canopy layer to the bottom, the SLA of upper, middle and lower crown was101.08,117.37and129.91cm2/g separately. The SLA of young, middle-aged, sub-mature and mature Larix olgensis plantation was145.34,111.55,92.60and128.03cm2/g separately. with an average value116.39cm2/g of different stand ages. Branches-level leaf area model fitting well with allometric equation using branches diameter as prediction variable, a segmented branches leaf area allometric model was developed in order to improve the model precision. The crown leaf area fitted well with a modified power function using DBH and H/D as independent variables:LA=0.3024×DBH1.944-0.1965×HD.The dynamic of the leaf area index of larch plantation with aging show that increasesd in middle-aged forest, maintained stability in sub-mature forest and tended to decrease in mature forest.
(6) The radial growth process of annual ring width shows that increased in the earliest age, attaining a maximum ring width from the third to the sixth year, decreased to about20years, and then remained a relative steady value after20years. The young crown is freedom crown in the first five years, affecting stem ring growth with the same pattern. The average annual ring width and area were not significant difference in the first three and five years. The average annual width and area of the last three or five years were not significant difference under crown base from middle age and sub-mature stands, but there are significant differences in ring area increment during the three or five years under crown base in mature forest, decreasing along stem height from the tree base to top. The annual ring growth within crown showed the same pattern. The initial heartwood formation of Larix olgensis estimate at the fifth years, the average heartwood formation rates were0.65ring/year and0.96ring/year under30years and older than30years, respectively. The best fitting heartwood ring number with cambial age was quadratic curve equation. The heartwood and sapwood volume allometric equations as a function of DBH and HT were fitted well (HWV=4.0*10-6DBH2.149250HT1.296038,R2=0.989, and SWV=1.02*10-4DBH0.750383HT673065, R2=0.943). The bark thickness as a function of relative stem height was fitted well with the logarithmic equation. The trend of bark factor along the stem height turned increase and then decrease to tree top. The optimal model of the diameter inside-bark at breast height, tree height and volume without bark was Richard model for Larix olgensis plantation.
引文
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