幼龄楸树生物量分配规律与异速生长模型

doi:10.17521/cjpe.2024.0042

植物生态学报 ›› 2025, Vol. 49 ›› Issue (2): 356-366.DOI: 10.17521/cjpe.2024.0042 cstr: 32100.14.cjpe.2024.0042

• 研究论文 • 上一篇

幼龄楸树生物量分配规律与异速生长模型

陈文义¹^,², 王智勇¹^,², 周梦岩¹, 麻文俊¹, 王军辉¹, 罗志斌¹^,³^,⁴, 周婧¹^,^*()

¹林木遗传育种国家重点实验室, 国家林业和草原局森林培育重点实验室, 中国林业科学研究院林业研究所, 北京 100091
²西北农林科技大学林学院, 陕西杨凌 712100
³中国林业科学研究院黄河三角洲综合试验中心, 山东东营 257000
⁴国家林业和草原局盐碱地研究中心, 中国林业科学研究院生态保护与修复研究所, 北京 100091

收稿日期:2024-02-07 接受日期:2024-08-23 出版日期:2025-02-20 发布日期:2025-02-20
通讯作者: ^*周婧: (gaha2008@126.com)
基金资助:
国家重点研发计划(2021YFD2200301-4)

Biomass allocation and allometric growth model of young Catalpa bungei

CHEN Wen-Yi¹^,², WANG Zhi-Yong¹^,², ZHOU Meng-Yan¹, MA Wen-Jun¹, WANG Jun-Hui¹, LUO Zhi-Bin¹^,³^,⁴, ZHOU Jing¹^,^*()

¹State Key Laboratory of Tree Genetics and Breeding, Key Laboratory of Silviculture of the National Forestry and Grassland Administration, Research Institute of Forestry, Chinese Academy of Forestry, Beijing 100091, China
²College of Forestry, Northwest A&F University, Yangling, Shaanxi 712100, China
³Comprehensive Experimental Center in Yellow River Delta of Chinese Academy of Forestry, Dongying, Shandong 257000, China
⁴Research Center of Saline and Alkali Land of National Forestry and Grassland Administration, Institute of Ecological Conservation and Restoration, Chinese Academy of Forestry, Beijing 100091, China

Received:2024-02-07 Accepted:2024-08-23 Online:2025-02-20 Published:2025-02-20
Supported by:
National Key R&D Program of China(2021YFD2200301-4)

摘要/Abstract

摘要：

为了探究幼龄楸树(Catalpa bungei)主干、枝条、叶、粗根、细根、整株、地上部分和地下部分各组分生物量分配规律并建立相应的异速生长模型, 在3个相邻省份4个取样点的3-8年幼龄期楸树人工林中, 选取41株胸径(D)范围为3.2-24.8 cm的样木, 采用全称质量法测量楸树各组分生物量并分析其分配规律。分别以D、树高(H)及其复合形式D²H为预测变量, 利用简单幂函数的形式, 构建楸树主干、枝条、叶、粗根、细根、整株、地上部分和地下部分的生物量模型并验证其准确性。幼龄期楸树各组分生物量存在明显异速生长关系。地上部分生物量平均占比为80.54%, 其中主干生物量平均占比为49.29%, 远高于地下部分, 而细根生物量仅占整株的0.29%。在D ≤ 10 cm时, 随D增大, 枝条生物量占比逐渐增大, 而粗根生物量占比减小, 导致地上和地下生物量差距增大; 10 cm < D < 25 cm时, 各组分生物量占比变化放缓。在构建的各组分生物量模型中, 3个预测变量预测精度排序为D > D²H > H, 以D为单一预测变量拟合的主干、枝条、叶、粗根、整株、地上部分和地下部分异速生长模型精度较高, 以D²H为预测变量拟合的细根异速生长模型精度较高; 以不同径级楸树进行抽样, 验证模型准确性的结果显示, 各组分最优预测变量所构建的异速生长模型估测准确度高。幼龄期楸树各组分生物量平均占比顺序为: 主干>枝条>粗根>叶>细根; 随着楸树D增大, 地上部分生物量分配比例呈上升趋势。综合评估异速生长模型的拟合效果可知, D是预测楸树除细根外其他各组分生物量的最可靠变量, D²H是估算细根生物量的可靠变量。利用构建的异速生长模型可预测幼龄楸树的生长规律, 为选育优良楸树无性系提供重要参考。

关键词: 楸树, 生物量分配, 异速生长模型, 生长规律

Abstract:

Aims To explore the biomass allocation of trunk, branch, leaf, coarse root, fine root, total tree, aboveground and belowground of young Catalpa bungei trees, thus to develop corresponding allometric growth models.

Methods Different components of 41 sample trees, with a diameter at breast height (D) ranging from 3.2 to 24.8 cm, were collected from 3 to 8-year-old C. bungei plantation forests at four sampling sites in three neighboring provinces. We utilized the whole mass method to determine the biomass of different components and analyzed their allocation patterns. With D, tree height (H) and their composite form D²H as predictive variables, biomass models for trunk, branch, leaf, coarse root, fine root, total tree, above- and below-ground parts of C. bungei were developed using simple power function. The accuracy of the model was then validated.

Important findings There were obvious allometric growth relationship between the biomass of various components of C. bungei. In average, 80.54% of the total biomass was allocated to above-ground, with an average of 49.29% to the trunks, far exceeding the portion of below-ground biomass, with only 0.29% of the total biomass was allocated to the fine roots. For trees with D≤ 10 cm, the proportion of branch biomass increased, while the coarse root biomass proportion decreased, resulting in a gradual increase in the difference between above- and below-ground biomass with increasing D. Whilst for trees with 10 cm < D< 25 cm, the changes in the proportional biomass of each component diminished. As for allometric models, among the three predictive variables, the accuracy ranking was approximately D > D²H > H. The models using D as a single predictive variable showed highest accuracies for the trunk, branch, leaf, coarse root, total tree, above- and below-ground part biomass, whilst D²H was the best single predictive variable for fine root biomass. Sampling of various diameter classes of C. bungei was used to validate model accuracy, and the results indicated high estimation accuracy of the optimal model for each component. Young C. bungei trees allocated their biomass according to the following order: trunk > branch > coarse root > leaf > fine root. The proportion of above-ground biomass allocation increased as Dincreased. D is the most reliable single variable for predicting the biomass of all components of the C. bungei, except for biomass of the fine roots, which is best predicted by D²H. The optimal allometric growth models constructed can predict the growth rule of young C. bungei accurately, providing significant reference for the selection and breeding of fine C. bungei clones.

Key words: Catalpa bungei, biomass allocation, allometric growth model, growth rule

陈文义, 王智勇, 周梦岩, 麻文俊, 王军辉, 罗志斌, 周婧. 幼龄楸树生物量分配规律与异速生长模型. 植物生态学报, 2025, 49(2): 356-366. DOI: 10.17521/cjpe.2024.0042

CHEN Wen-Yi, WANG Zhi-Yong, ZHOU Meng-Yan, MA Wen-Jun, WANG Jun-Hui, LUO Zhi-Bin, ZHOU Jing. Biomass allocation and allometric growth model of young Catalpa bungei. Chinese Journal of Plant Ecology, 2025, 49(2): 356-366. DOI: 10.17521/cjpe.2024.0042

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https://www.plant-ecology.com/CN/Y2025/V49/I2/356

图/表 9

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样地 Sample site	株数 Number of plants	胸径 D (cm)					年龄 Age (a)	造林密度 Afforestation density (ind.·hm^-2)	年降水量 Mean annual precipitation (mm)	年平均气温 Mean annual air temperature (℃)	土壤类型 Soil type
样地 Sample site	株数 Number of plants	0-5	5-10	10-15	15-20	20-25	年龄 Age (a)	造林密度 Afforestation density (ind.·hm^-2)	年降水量 Mean annual precipitation (mm)	年平均气温 Mean annual air temperature (℃)	土壤类型 Soil type
山东菏泽 Heze, Shandong	9	1	2	2	3	1	5	833	782.6 ± 69.5	15.58 ± 0.05	冲积土 Fluvisol
河南永城 Yongcheng, Henan	8	1	2	3	2	0	4	833	888.1 ± 72.6	16.67 ± 0.11	冲积土 Fluvisol
湖北襄阳 Xiangyang, Hubei	12	1	3	3	2	3	5	833	908.6 ± 100.4	16.40 ± 0.09	始成土 Inceptisol
湖北石首 Shishou, Hubei	12	2	2	3	2	3	3, 8	833	1 222.8 ± 77.8	17.77 ± 0.13	淋溶土 Alfisol
总计 Total	41	5	9	11	9	7	-	-	-	-	-
建模组 Modeling group	28	3	7	7	6	5	-	-	-	-	-
验证组 Testing group	13	2	2	4	3	2	-	-	-	-	-

样地 Sample site	株数 Number of plants	胸径 D (cm)					年龄 Age (a)	造林密度 Afforestation density (ind.·hm^-2)	年降水量 Mean annual precipitation (mm)	年平均气温 Mean annual air temperature (℃)	土壤类型 Soil type
样地 Sample site	株数 Number of plants	0-5	5-10	10-15	15-20	20-25	年龄 Age (a)	造林密度 Afforestation density (ind.·hm^-2)	年降水量 Mean annual precipitation (mm)	年平均气温 Mean annual air temperature (℃)	土壤类型 Soil type
山东菏泽 Heze, Shandong	9	1	2	2	3	1	5	833	782.6 ± 69.5	15.58 ± 0.05	冲积土 Fluvisol
河南永城 Yongcheng, Henan	8	1	2	3	2	0	4	833	888.1 ± 72.6	16.67 ± 0.11	冲积土 Fluvisol
湖北襄阳 Xiangyang, Hubei	12	1	3	3	2	3	5	833	908.6 ± 100.4	16.40 ± 0.09	始成土 Inceptisol
湖北石首 Shishou, Hubei	12	2	2	3	2	3	3, 8	833	1 222.8 ± 77.8	17.77 ± 0.13	淋溶土 Alfisol
总计 Total	41	5	9	11	9	7	-	-	-	-	-
建模组 Modeling group	28	3	7	7	6	5	-	-	-	-	-
验证组 Testing group	13	2	2	4	3	2	-	-	-	-	-

胸径 D (cm)	主干 Trunk (kg·plant^-1)		枝条 Branch (kg·plant^-1)		叶 Leaf (kg·plant^-1)		粗根 Coarse root (kg·plant^-1)		细根 Fine root (kg·plant^-1)
胸径 D (cm)	范围 Range	平均值 Mean	范围 Range	平均值 Mean	范围 Range	平均值 Mean	范围 Range	平均值 Mean	范围 Range	平均值 Mean
0-5	0.83-6.56	2.52^Ad	0.15-5.46	1.55^ABc	0.11-0.55	0.27^Bd	0.51-3.21	1.39^ABd	0.01-0.04	0.02^Bc
5-10	3.47-17.30	8.35^Ad	1.12-6.15	3.23^Bc	0.28-3.41	1.30^BCcd	1.63-10.95	3.71^Bcd	0.01-0.07	0.05^Cc
10-15	14.45-37.18	26.49^Ac	7.33-20.09	13.04^Bc	1.29-6.92	4.06^Dbc	4.75-14.74	8.60^Cc	0.04-0.15	0.11^Ec
15-20	41.87-73.16	55.63^Ab	16.95-76.11	32.92^Bb	1.79-16.09	7.21^CDab	8.40-25.44	16.52^Cb	0.10-0.27	0.19^Db
20-25	53.91-116.49	89.22^Aa	35.50-73.64	56.43^Ba	2.87-19.19	9.61^Da	19.78-42.27	31.02^Ca	0.13-0.56	0.30^Da

胸径 D (cm)	主干 Trunk (kg·plant^-1)		枝条 Branch (kg·plant^-1)		叶 Leaf (kg·plant^-1)		粗根 Coarse root (kg·plant^-1)		细根 Fine root (kg·plant^-1)
胸径 D (cm)	范围 Range	平均值 Mean	范围 Range	平均值 Mean	范围 Range	平均值 Mean	范围 Range	平均值 Mean	范围 Range	平均值 Mean
0-5	0.83-6.56	2.52^Ad	0.15-5.46	1.55^ABc	0.11-0.55	0.27^Bd	0.51-3.21	1.39^ABd	0.01-0.04	0.02^Bc
5-10	3.47-17.30	8.35^Ad	1.12-6.15	3.23^Bc	0.28-3.41	1.30^BCcd	1.63-10.95	3.71^Bcd	0.01-0.07	0.05^Cc
10-15	14.45-37.18	26.49^Ac	7.33-20.09	13.04^Bc	1.29-6.92	4.06^Dbc	4.75-14.74	8.60^Cc	0.04-0.15	0.11^Ec
15-20	41.87-73.16	55.63^Ab	16.95-76.11	32.92^Bb	1.79-16.09	7.21^CDab	8.40-25.44	16.52^Cb	0.10-0.27	0.19^Db
20-25	53.91-116.49	89.22^Aa	35.50-73.64	56.43^Ba	2.87-19.19	9.61^Da	19.78-42.27	31.02^Ca	0.13-0.56	0.30^Da

胸径 D (cm)	整株 Total tree (kg·plant^-1)		地上 Aboveground (kg·plant^-1)		地下 Belowground (kg·plant^-1)		根冠比 Root to shoot ratio
胸径 D (cm)	范围 Range	平均值 Mean	范围 Range	平均值 Mean	范围 Range	平均值 Mean	范围 Range	平均值 Mean
0-5	1.69-15.79	5.76	1.17-12.57	4.34	0.52-3.22	1.42	0.26-0.64	0.42^a
5-10	7.61-34.82	16.63	4.87-23.82	12.87	1.63-11.00	3.76	0.15-0.56	0.32^a
10-15	35.13-68.06	52.29	28.74-55.48	43.58	4.79-14.90	8.71	0.14-0.28	0.20^b
15-20	77.64-180.77	112.47	62.55-111.58	95.76	8.63-25.68	16.71	0.08-0.24	0.18^b
20-25	129.19-248.95	186.59	101.02-209.32	155.27	20.08-42.40	31.32	0.15-0.28	0.20^b

幼龄楸树生物量分配规律与异速生长模型

Biomass allocation and allometric growth model of young Catalpa bungei

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组分生物量 Component biomass	降水量 Precipitation	气温 Air temperature	年龄 Age
整株 Total tree	-0.029	-0.110	0.496^**
地上部分 Aboveground	-0.054	-0.129	0.487^**
地下部分 Belowground	0.043	-0.071	0.566^**
主干 Trunk	-0.015	-0.115	0.507^**
枝条 Branch	-0.085	-0.126	0.427^**
叶 Leaf	-0.215	-0.157	0.141
粗根 Coarse root	0.048	-0.066	0.562^**
细根 Fine root	0.054	-0.110	0.481^**

组分生物量 Component biomass	回归模型 Regression model	a	b	R²	RMSE	AICc
主干 Trunk	ln W = a + bln D	-2.521	2.257	0.949 3	0.296 8	-62.04
	ln W = a + b ln H	-3.978	3.400	0.748 9	0.660 2	-17.27
	ln W = a + b ln (D²H)	-3.123	0.881	0.935 2	0.335 3	-55.21
枝条 Branch	ln W = a + bln D	-4.439	2.716	0.902 7	0.507 4	-32.01
	ln W = a + b ln H	-5.898	3.948	0.663 0	0.944 1	2.76
	ln W = a + bln (D²H)	-5.113	1.053	0.876 9	0.570 6	-25.44
叶 Leaf	ln W = a + bln D	-4.502	2.203	0.839 2	0.548 6	-27.64
	ln W = a + bln H	-5.761	3.239	0.630 6	0.831 5	-4.35
	ln W = a + bln (D²H)	-5.061	0.856	0.818 8	0.582 4	-24.29
粗根 Coarse root	ln W = a + bln D	-2.629	1.894	0.903 0	0.353 2	-52.30
	ln W = a + bln H	-3.895	2.875	0.722 8	0.597 2	-22.89
	ln W = a + bln (D²H)	-3.146	0.741	0.893 6	0.369 9	-49.72
细根 Fine root	ln W = a + bln D	-6.298	1.565	0.777 4	0.476 6	-35.52
	ln W = a + bln H	-7.786	2.591	0.740 3	0.514 8	-31.21
	ln W = a + bln (D²H)	-6.805	0.624	0.798 4	0.453 5	-38.30
整株 Total tree	ln W = a + bln D	-1.836	2.264	0.946 0	0.307 8	-60.00
	ln W = a + bln H	-3.203	3.364	0.726 3	0.692 7	-14.58
	ln W = a + bln (D²H)	-2.424	0.882	0.927 1	0.357 5	-51.62
地上 Aboveground	ln W = a + bln D	-2.313	2.368	0.943 6	0.329 2	-56.23
	ln W = a + bln H	-3.715	3.505	0.718 8	0.735 2	-11.24
	ln W = a + bln (D²H)	-2.923	0.921	0.923 1	0.384 4	-47.56
地下 Belowground	ln W = a + bln D	-2.602	1.889	0.903 8	0.350 6	-52.70
	ln W = a + bln H	-3.863	2.866	0.723 4	0.594 5	-23.14
	ln W = a + bln (D²H)	-3.117	0.739	0.894 4	0.367 3	-50.11

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