Study on the factors affecting breast-height basal area increment of evergreen broad-leaved forest in Tianmu Mountain
-
摘要:
目的 研究常绿阔叶林胸高断面积生长模型，探究影响胸高断面积生长量的因素，为常绿阔叶林经营提供理论依据。 方法 以天目山常绿阔叶林为对象，先对胸高断面积生长量与胸径、竞争和地形因子进行相关性分析，随后对不同径级、冠幅等级和竞争等级的胸高断面积生长量进行差异性分析，最后基于岭回归分析法，建立以胸高断面积生长量对数为因变量的单木生长模型，定量描述胸高断面积生长量与胸径、竞争和地形因子的关系。 结果 胸径、冠幅、竞争与胸高断面积生长量的斯皮尔曼(Spearman)相关系数分别为0.531、0.427、−0.340。林木胸高断面积生长量随着林木胸径的增大而增大，不同径级间差异极显著(P＜0.01)。林木胸高断面积生长量随着林木冠幅的增大而增大，不同冠幅等级间差异极显著(P＜0.01)。不同竞争等级的林木胸高断面积生长量差异极显著(P＜0.01)，且低度竞争时的林木胸高断面积生长量最大。基于径阶平均值的单木生长模型优于基于单株林木的单木生长模型，且2类模型中胸径因子的回归参数均达极显著水平(P＜0.01)。 结论 在天目山常绿阔叶林中影响胸高断面积生长量的主要因子是胸径、冠幅和竞争指数。图3表4参45 Abstract:Objective The objective is to study the growth model of breast-height basal area of evergreen broad-leaved forest and to explore the factors affecting breast-height basal area increment (BAI) of evergreen broad-leaved forest, so as to provide a theoretical basis for evergreen broad-leaved forest management. Method Taking the evergreen broad-leaved forest in Tianmu Mountain as the research object. Firstly, the correlation between BAI and diameter at breast height (DBH), competition and terrain factors were analyzed. Secondly, the differences of BAI among different diameter classes, crown diameter classes and competition classes were discussed. And finally, based on the ridge regression analysis, the individual tree growth model with logarithm of BAI as the dependent variable was established to quantitatively describe the relationship between BAI and DBH, competition and terrain factors. Result The Spearman’s correlation coefficients between BAI and DBH, crown diameter, and competition were 0.531, 0.427 and −0.34 respectively. BAI was extremely significant different among trees of different diameter classes ( P＜0.01), and increased with increase of DBH. There was a significant difference (P＜0.01) in BAI among trees with different competition classes, and trees with low competition level had the largest BAI. Individual tree growth models based on average diameter grade were superior to those based on individual tree, and the regression parameters of DBH in both types of models were extremely significant (P＜0.01). Conclusion In the evergreen broad-leaved forest of Tianmu Mountain, the main factors affecting BAI are DBH, crown diameter and competition index. [Ch, 3 fig. 4 tab. 45 ref.] -
图 1 不同径级的胸高断面积生长量
Figure 1 Breast-height basal area increment for different diameter classes
图 2 不同冠幅等级的胸高断面积生长量
Figure 2 Breast-height basal area increment for different crown classes
图 3 不同竞争等级的胸高断面积生长量
Figure 3 Breast-height basal area increment for different competition classes
表 1 各变量统计结果
Table 1. Statistics results of each variable
项目 胸径/cm 冠幅/m 海拔/m 坡度/(°) 坡向指数 竞争指数 2005—2020年胸高断
面积生长量/cm²均值 13.15 1.86 631.53 42.50 0.41 8.44 74.80 标准差 8.70 0.79 19.61 15.88 0.48 16.38 93.61 
下载: 导出CSV
表 2 各变量的相关系数
Table 2. Correlation coefficients of each variable
变量 胸径 冠幅 海拔 坡度 坡向指数 竞争指数 胸高断面积生长量 胸径 1.000 冠幅 0.714** 1.000 海拔 0.069 0.129** 1.000 坡度 −0.024 −0.032 −0.006 1.000 坡向指数 −0.035 −0.078* −0.065 0.052 1.000 竞争指数 −0.618** −0.374** −0.020 −0.068 0.038 1.000 胸高断面积生长量 0.531** 0.427** 0.019 −0.069 0.014 −0.340** 1.000 说明： *P＜0.05；**P＜0.01
下载: 导出CSV
表 3 基于单株林木的单木生长模型
Table 3. Individual tree growth models based on individual tree
模型 常数 lnD D2 Cr lnIC IC Al Sl As R2 调整R2 F 模型1 2.472** 0.350** 0.000** 0.169** −0.063** 0.002 0.000 −0.002* 0.043 0.267 0.258 32.895** 模型2 2.510** 0.438** 0.202** −0.087** 0.002 0.000 −0.003* 0.040 0.248 0.240 34.091** 模型3 3.121** 0.001** 0.226** −0.097** 0.002 0.000 −0.003* 0.038 0.228 0.221 30.639** 模型4 3.435** 0.300** −0.148** 0.002 0.000 −0.003* 0.031 0.165 0.158 23.970** 模型5 2.459** 0.348** 0.000** 0.169** −0.051** 0.000 −0.003* 0.043 0.264 0.256 37.076** 模型6 2.323** 0.369** 0.000** 0.173** 0.001 0.000 −0.002 0.043 0.265 0.258 37.325** 模型7 2.330** 0.367** 0.000** 0.173** 0.000 −0.002* 0.043 0.264 0.258 43.402** 模型8 2.497** 0.437** 0.202** −0.075** 0.000 −0.003* 0.040 0.244 0.238 39.076** 模型9 2.303** 0.473** 0.211** 0.726 0.000 −0.002 0.040 0.242 0.236 38.712** 模型10 3.107** 0.001** 0.226** −0.087** 0.000 −0.003* 0.038 0.225 0.219 35.221** 模型11 2.941** 0.001** 0.238** 0.000 0.000 −0.002 0.037 0.220 0.213 34.109** 说明：D. 胸径； Cr. 冠幅；IC. Hegyi竞争指数；Al. 海拔； Sl. 坡度； As. 坡向指数；*P＜0.05；**P＜0.01；表中数值均为模型回归系数
下载: 导出CSV
表 4 基于径阶平均值的单木生长模型
Table 4. Individual tree growth models based on average of diameter grade
模型 常数 lnD D2 Cr lnIC IC Al Sl As R2 调整R2 F 模型12 11.245* 0.351** 0.000** 0.232** −0.098 −0.037** −0.014 0.013 0.287 0.949 0.917 30.114** 模型13 11.286 1.238** 0.252 −0.102 0.057 −0.019 0.018 0.384 0.956 0.933 43.045** 模型14 12.499* 0.000** 0.266** −0.128** −0.058** −0.015* 0.012 0.232 0.931 0.897 27.004** 模型15 15.728** 0.285** −0.156** −0.063** −0.019* 0.015 0.219 0.843 0.780 13.395** 模型16 9.904 0.470** 0.264** −0.120* −0.013 0.011 0.254 0.951 0.927 39.004** 模型17 13.085* 0.404** 0.000** 0.213** −0.045** −0.018* 0.014 0.243 0.947 0.920 35.603** 模型18 12.101* 0.555** 0.000** 0.249** −0.017* 0.013 0.172 0.945 0.924 43.334** 模型19 13.520* 0.796** 0.293** −0.122 −0.021* 0.019 0.360 0.947 0.925 44.235** 模型20 14.260* 1.341** 0.197 0.045 −0.025* 0.021 0.378 0.952 0.933 49.636** 模型21 12.695** 0.000** 0.283** −0.160** −0.015* 0.010 0.146 0.858 0.802 15.164** 模型22 14.932** 0.000** 0.261** −0.071** −0.019* 0.014 0.154 0.922 0.890 29.406** 说明：D. 胸径； Cr. 冠幅；IC. Hegyi竞争指数；Al. 海拔； Sl. 坡度； As. 坡向指数；*P＜0.05； **P＜0.01；表中数值均为模型回归系数
下载: 导出CSV
-
[1] 唐守正, 杜纪山. 利用树冠竞争因子确定同龄间伐林分的断面积生长过程[J]. 林业科学, 1999, 35(6): 35 − 41. TANG Shouzheng, DU Jishan. Determining basal area growth process of thinnined even aged stands by crown competition factor [J]. Scientia Silvae Sinicae, 1999, 35(6): 35 − 41. [2] 王建军, 曾伟生, 孟京辉. 考虑预估期间林木枯死及采伐影响的杉木单木胸高断面积生长模型研究[J]. 西北林学院学报, 2017, 32(3): 181 − 185. WANG Jianjun, ZENG Weisheng, MENG Jinghui. Individual-tree basal area growth model for Cunninghamia lanceolata with the consideration of thinning and tree mortality in the prediction interval [J]. Journal of Northwest Forestry University, 2017, 32(3): 181 − 185. [3] 卢军. 长白山地区天然混交林单木生长模型的研究[D]. 哈尔滨: 东北林业大学, 2005. LU Jun. Individual Tree Growth Models of Natural Mixed Forest in Changbai Mountains[D]. Harbin: Northeast Forestry University, 2005. [4] 罗保玥. 吉林蛟河针阔叶混交林主要树种单木生长模型[D]. 北京: 北京林业大学, 2020. LUO Baoyue. Individual Tree Growth Model of Main Tree Species in Coniferous and Broad-leaved Mixed Forest in Jiaohe, Jilin[D]. Beijing: Beijing Forestry University, 2020. [5] WYKOFF W R. A basal area increment model for individual conifers in the northern Rocky Mountains [J]. Forest Science, 1990, 36(4): 1077 − 1104. [6] MONSERUD R A, STERBA H. A basal area increment model for individual trees growing in even- and uneven-aged forest stands in Austria [J]. Forest Ecology Management, 1996, 80(1): 57 − 80. [7] OZDEMIR E. Individual tree basal area increment model for sessile oak (Quercus petraea (Matt.) Liebl.) in coppice-originated stands [J/OL]. Environmental Monitoring Assessment , 2021, 193: 357[2022-09-18]. doi: 10.1007/s10661-021-09128-5. [8] STERBA H, BLAB A, KATZENSTEINER K. Adapting an individual tree growth model for Norway spruce (Picea abies L. Karst. ) in pure and mixed species stands [J]. Forest Ecology Management, 2002, 159(1/2): 101 − 110. [9] 满敬銮, 杨薇. 基于多重共线性的处理方法[J]. 数学理论与应用, 2010, 30(2): 105 − 109. MAN Jingluan, YANG Wei. Based on multiple collinearity processing method [J]. Mathematical Theory and Application, 2010, 30(2): 105 − 109. [10] 李丽, 惠淑荣, 惠刚盈, 等. 森林结构调查最小面积的研究[J]. 林业资源管理, 2007(2): 47 − 51. LI Li, HUI Shurong, HUI Gangying,et al. A study on the minimum area of forest spatial investigation [J]. Forest Resources Management, 2007(2): 47 − 51. [11] 包维楷, 刘照光, 刘朝禄, 等. 中亚热带湿性常绿阔叶次生林自然恢复15年来群落乔木层的动态变化[J]. 植物生态学报, 2000, 24(6): 702 − 709. BAO Weikai, LIU Zhaoguang, LIU Chaolu,et al. Fifteen-year changes of tree layer in secondary Castanopsis-Schima humid evergreen broad-leaved forest in central subtropics of western China [J]. Acta Phytoecologica Sinica, 2000, 24(6): 702 − 709. [12] 张毅锋, 汤孟平. 天目山常绿阔叶林空间结构动态变化特征[J]. 生态学报, 2021, 41(5): 1959 − 1969. ZHANG Yifeng, TANG Mengping. Analysis on spatial structure dynamic characteristics of evergreen broad-leaved forest in Tianmu Mountain [J]. Acta Ecologica Sinica, 2021, 41(5): 1959 − 1969. [13] 龙俊松, 汤孟平. 天目山常绿阔叶林空间结构与地形因子的关系[J]. 浙江农林大学学报, 2021, 38(1): 47 − 57. LONG Junsong, TANG Mengping. Relationship spatial structure and terrain factors of evergreen broad-leaved forest in Mount Tianmu [J]. Journal Zhejiang A&F University, 2021, 38(1): 47 − 57. [14] 贺金生, 陈伟烈, 李凌浩. 中国中亚热带东部常绿阔叶林主要类型的群落多样性特征[J]. 植物生态学报, 1998, 22(4): 303 − 311. HE Jinsheng, CHEN Weilie, LI Linghao. Community diversity of the main types of the evergreen broad-leaved forest in the eastern part of the middle subtropical China [J]. Acta Phytoecologica Sinica, 1998, 22(4): 303 − 311. [15] 邱凤英, 肖复明, 郭捷, 等. 江西金盆山林区天然常绿阔叶林生态系统碳储量研究[J]. 中南林业科技大学学报, 2020, 40(1): 105 − 113. QIU Fengying, XIAO Fuming, GUO Jie,et al. Carbon storage of evergreen broad-leaved forest, Jinpenshan, Jiangxi Province [J]. Journal of Central South University of Forestry and Technology, 2020, 40(1): 105 − 113. [16] 汤孟平, 周国模, 施拥军, 等. 天目山常绿阔叶林优势种群及其空间分布格局[J]. 植物生态学报, 2006, 30(5): 743 − 752. doi: 10.17521/cjpe.2006.0096 TANG Mengping, ZHOU Guomo, SHI Yongjun,et al. Study of dominant plant populations and their spatial patterns in evergreen broadleaved forest in Tianmu Mountain, China [J]. Journal of Plant Ecology, 2006, 30(5): 743 − 752. doi: 10.17521/cjpe.2006.0096 [17] 孟宪宇. 测树学[M]. 3版. 北京: 中国林业出版社, 2006: 173 − 174. MENG Xianyu. Forest Mensuration [M]. 3th. ed. Beijing: China Forestry Publishing House, 2006: 173 − 174. [18] 张会儒. 森林经理学研究方法与实践[M]. 北京: 中国林业出版, 2018: 194 − 195. ZHANG Huiru. Research Methods and Practice of Forest Management [M]. Beijing: China Forestry Publishing House, 2018: 194 − 195. [19] WEINER J, DAMGAARD C. Size-asymmetric competition and size-asymmetric growth in a spatially explicit zone-of-influence model of plant competition [J]. Ecological Research, 2006, 21(5): 707 − 712. doi: 10.1007/s11284-006-0178-6 [20] 吴明钦, 孙玉军, 郭孝玉, 等. 长白落叶松树冠体积和表面积模型[J]. 东北林业大学学报, 2014, 42(5): 1 − 5. WU Mingqin, SUN Yujun, GUO Xiaoyu,et al. Predictive models of crown volume and crown surface area for Korean larch [J]. Journal of Northeast Forestry University, 2014, 42(5): 1 − 5. [21] LOONEY C E, D’AMATO A W, PALIK B J,et al. Size-growth relationship, tree spatial patterns, and tree-tree competition influence tree growth and stand complexity in a 160-year red pine chronosequence [J]. Forest Ecology and Management, 2018, 424: 85 − 94. doi: 10.1016/j.foreco.2018.04.044 [22] HEGYI F. A simulation model for managing jack-pine stands [M]//FRIES J. Growth Models for Tree and Stand Simulation. Stockholm: Royal College of Forestry, 1974: 74 − 90. [23] 汤孟平, 陈永刚, 施拥军, 等. 基于Voronoi图的群落优势树种种内种间竞争[J]. 生态学报, 2007, 27(11): 4707 − 4716. doi: 10.3321/j.issn:1000-0933.2007.11.039 TANG Mengping, CHEN Yonggang, SHI Yongjun,et al. Intraspecific and interspecific competition analysis of community dominant plant population based on Voronoi diagram [J]. Acta Ecologica Sinica, 2007, 27(11): 4707 − 4716. doi: 10.3321/j.issn:1000-0933.2007.11.039 [24] COOMES D A, ALLEN R B. Effects of size, competition and altitude on tree growth [J]. Journal of Ecology, 2007, 95(5): 1084 − 1097. doi: 10.1111/j.1365-2745.2007.01280.x [25] STAGE A R, SALAS C. Interactions of elevation, aspect, and slope in models of forest species composition and productivity [J]. Forest Science, 2007, 53(4): 486 − 492. [26] BARIBAULT T W, KOBE R K, FINLEY A O. Tropical tree growth is correlated with soil phosphorus, potassium, and calcium, though not for legumes [J]. Ecological Monographs, 2012, 82(2): 189 − 203. doi: 10.1890/11-1013.1 [27] 陈兵红, 靳全锋, 柴红玲, 等. 浙江省大气 PM2.5时空分布及相关因子分析[J]. 环境科学学报, 2021, 41(3): 817 − 829. CHEN Binghong, JIN Quanfeng, CHAI Hongling,et al. Spatiotemporal distribution and correlation factors of PM2.5 concentrations in Zhejiang Province [J]. Acta Scientiae Circumstantiae, 2021, 41(3): 817 − 829. [28] 付婧婧, 吴志伟, 闫赛佳, 等. 气候、植被和地形对大兴安岭林火烈度空间格局的影响[J]. 生态学报, 2020, 40(5): 1672 − 1682. FU Jingjing, WU Zhiwei, YAN Saijia,et al. Effects of climate, vegetation, and topography on spatial patterns of burn severity in the Great Xing’an Mountains [J]. Acta Ecologica Sinica, 2020, 40(5): 1672 − 1682. [29] CHI Xiulian, TANG Zhiyao, XIE Zhongqiang,et al. Effects of size, neighbors, and site condition on tree growth in a subtropical evergreen and deciduous broad-leaved mixed forest, China [J]. Ecology and Evolution, 2015, 5(22): 5149 − 5161. doi: 10.1002/ece3.1665 [30] FIEN E K P, FRAVER S, TEETS A, et al. Drivers of individual tree growth and mortality in an uneven-aged, mixed-species conifer forest [J/OL]. Forest Ecology and Management, 2019, 449(4): 117446[2022-09-18]. doi: 10.1016/j.foreco.2019.06.043. [31] CANHAM C D, LEPAGE P T, COATES K D. A neighborhood analysis of canopy tree competition: effects of shading versus crowding [J]. Canadian Journal of Forest Research, 2004, 34(4): 778 − 787. doi: 10.1139/x03-232 [32] MULLER-LANDAU H C, CONDIT R S, HARMS K E, et al. Comparing tropical forest tree size distributions with the predictions of metabolic ecology and equilibrium models [J]. Ecology Letters, 2006, 9: 589 − 602. [33] de GROOTE S R E, VANHELLEMONT M, BAETEN L,et al. Competition, tree age and size drive the productivity of mixed forests of pedunculate oak, beech and red oak [J]. Forest Ecology and Management, 2018, 430: 609 − 617. doi: 10.1016/j.foreco.2018.08.050 [34] 窦啸文, 汤孟平. 基于引力模型的林木竞争分析[J]. 应用生态学报, 2022, 33(10): 2695 − 2704. DOU Xiaowen, TANG Mengping. Gravitational model-based competitive analysis of forest trees [J]. Chinese Journal of Applied Ecology, 2022, 33(10): 2695 − 2704. [35] POMPA-GARCÍA M, VIVAR-VIVAR E D, SIGALA-RODRÍGUEZ J A, et al. What are contemporary Mexican conifers telling us? A perspective offered from tree rings linked to climate and the NDVI along a spatial gradient [J/OL]. Remote Sensing, 2022, 14(18): 4506[2022-09-18]. doi: 10.3390/rs14184506. [36] KAHRIMAN A, ŞAHIN A, SÖNMEZ T,et al. A novel approach to selecting a competition index: the effect of competition on individual-tree diameter growth of Calabrian pine [J]. Canadian Journal of Forest Research, 2018, 48(10): 1217 − 1226. doi: 10.1139/cjfr-2018-0092 [37] REICH P B, TJOELKER M G, WALTERS M B,et al. Close association of RGR, leaf and root morphology, seed mass and shade tolerance in seedlings of nine boreal tree species grown in high and low light [J]. Functional Ecology, 1998, 12(3): 327 − 338. doi: 10.1046/j.1365-2435.1998.00208.x [38] BAKER T R, BURSLEM D F R P, SWANIE M D. Associations between tree growth, soil fertility and water availability at local and regional scales in Ghanaian tropical rain forest [J]. Journal of Tropical Ecology, 2003, 19: 109 − 125. [39] REICH P B, OLEKSYN J. Climate warming will reduce growth and survival of Scots pine except in the far north [J]. Ecology Lettets, 2008, 11: 588 − 597. doi: 10.1111/j.1461-0248.2008.01172.x [40] EGHDAMI H, WERNER W, de MARCO A, et al. Influence of ozone and drought on tree growth under field conditions in a 22 year time series [J/OL]. Forests, 2022, 13: 1215[2022-09-18]. doi: 10.3390/f13081215. [41] OUYANG Lei, LU Longwei, WANG Chunlin, et al. A 14-year experiment emphasizes the important role of heat factors in regulating tree transpiration, growth, and water use efficiency of Schima superba in south China [J/OL]. Agricultural Water Management, 2022, 273: 107902[2022-09-18]. doi: 10.1016/j.agwat.2022.107902. [42] 雷相东, 李永慈, 向玮. 基于混合模型的单木断面积生长模型[J]. 林业科学, 2009, 45(1): 74 − 80. LEI Xiangdong, LI Yongci, XIANG Wei. Individual basal area growth model using multi-level linear mixed model with repeated measures [J]. Scientia Silvae Sinicae, 2009, 45(1): 74 − 80. [43] POKHAREL B, DECH J P. Mixed-effects basal area increment models for tree species in the boreal forest of Ontario, Canada using an ecological land classification approach to incorporate site effects [J]. Forestry, 2012, 85(2): 255 − 270. doi: 10.1093/forestry/cpr070 [44] 龚召松, 曾思齐, 贺东北, 等. 湖南楠木次生林断面积生长模型研究[J]. 林业资源管理, 2020(2): 87 − 93, 140. GONG Zhaosong, ZENG Siqi, HE Dongbei,et al. A study on the basal area growth model of Phoebe zhennan secondary forest in Hunan Province [J]. Forest Resources Management, 2020(2): 87 − 93, 140. [45] 陈哲夫, 肖化顺, 龙时胜. 基于混合效应的湖南马尾松次生林单木生长模型[J]. 中南林业科技大学学报, 2021, 41(1): 100 − 108. CHEN Zhefu, XIAO Huashun, LONG Shisheng. Growth model for individual tree of secondary Pinus massoniana forest in Hunan Province based on mixed effect [J]. Journal of Central South University of Forestry and Technology, 2021, 41(1): 100 − 108. -
-
链接本文:
https://zlxb.zafu.edu.cn/article/doi/10.11833/j.issn.2095-0756.20220651
点击查看大图
计量
- 文章访问数: 57
- 被引次数: 0
