幼龄红树生物量模型及幼林红树林碳储量研究*

doi:10.11978/2024141

热带海洋学报 ›› 2025, Vol. 44 ›› Issue (4): 187-199.doi: 10.11978/2024141CSTR: 32234.14.2024141

幼龄红树生物量模型及幼林红树林碳储量研究^*

胡鑫¹(), 熊兰兰¹(), 陈顺洋², 张黄琛¹, 邹易阳¹, 张吉超¹, 刘东熙¹, 何佳潞¹, 吴于琪¹, 朱振杰¹

1.广东省海洋发展规划研究中心, 广东广州 510220
2.自然资源部第三海洋研究所, 福建厦门 361005

收稿日期:2024-07-18 修回日期:2024-08-02 出版日期:2025-07-10 发布日期:2025-07-31
通讯作者: 胡鑫, 熊兰兰
作者简介:
胡鑫(1993—), 男, 江西省吉安市人, 博士, 从事海洋生态学研究。email: huxinest@163.com
^*感谢惠州市林业局、惠东县林业局、惠东县自然资源局和惠东县好招楼湿地公园管理处对本研究的支持
基金资助:
广东省自然资源厅科技项目(GDZRZYKJ2023002)

Study on biomass models of juvenile mangroves and carbon storage in young mangrove ecosystems*

HU Xin¹(), XIONG Lanlan¹(), CHEN Shunyang², ZHANG Huangchen¹, ZOU Yiyang¹, ZHANG Jichao¹, LIU Dongxi¹, HE Jialu¹, WU Yuqi¹, ZHU Zhenjie¹

1. Guangdong Center for Marine Development Research, Guangzhou 510220, China
2. Third Institute of Oceanography, Ministry of Natural Resources, Xiamen 361005, China

Received:2024-07-18 Revised:2024-08-02 Online:2025-07-10 Published:2025-07-31
Contact: HU Xin, XIONG Lanlan
Supported by:
Science and Technology Projects of Guangdong Provincial Department of Natural Resources(GDZRZYKJ2023002)

摘要/Abstract

摘要：

随着全球气候变化日益加剧, 红树林作为重要的滨海蓝碳生态系统备受关注。本研究旨在构建幼龄红树生物量模型, 评估广东考洲洋红树林碳储量, 为快速准确评估人工营造幼林红树林碳储量提供经验方法和科学依据。以考洲洋幼龄白骨壤(Avicennia marina)、红海榄(Rhizophora stylosa)、秋茄(Kandelia obovata)、木榄(Bruguiera gymnorhiza)和桐花树(Aegiceras corniculatum)为研究对象, 使用基径(basal diameter, D)和株高(height, H)及其派生的复合变量构建红树植物生物量与测树因子之间最佳拟合模型, 并进一步评估考洲洋幼林红树林生态系统碳储量。研究发现, 复合变量生物量模型优于单一变量生物量模型(桐花树地下生物量模型除外)。白骨壤、红海榄、木榄和桐花树最优生物量模型均为幂函数模型, 秋茄最优生物量模型为线性模型。考洲洋人工营造幼林红树林碳密度为(91.26±17.32)Mg C·hm^-2, 碳储量约为35964.65Mg C, 土壤碳库占考洲洋幼林红树林碳库78.3%~98.5%。红树植物碳密度从大到小依次为桐花+秋茄群落、红海榄+白骨壤群落、白骨壤群落、木榄群落。本研究结果对广东乃至全国人工营造红树林碳储量评估和生态修复具有重要参考价值。

关键词: 幼龄红树, 生物量模型, 碳密度, 人工营造红树林, 考洲洋

Abstract:

As global climate change intensifies, mangroves—a vital coastal blue carbon ecosystem—have garnered increasing attention. This study aimed to develop biomass models for juvenile mangroves and assess the carbon storage of young mangrove ecosystems in Kaozhouyang Bay. The results provide empirical methods and a scientific basis for the rapid and accurate assessment of carbon stocks in artificially planted young mangroves. The study focuses on five artificially planted juvenile mangrove species in Kaozhouyang Bay: Avicennia marina, Rhizophora stylosa, Kandelia obovata, Bruguiera gymnorhiza, and Aegiceras corniculatum. Various factors derived from basal diameter (D) and tree height (H) were used to construct optimal allometric equations between biomass and dendrometric parameters. Furthermore, the best-performing biomass models were applied to estimate vegetation carbon storage and ecosystem carbon storage in the artificially planted mangroves of Kaozhouyang Bay. The findings indicated that multivariable models generally outperformed univariable models, except for the below-ground biomass model of Aegiceras corniculatum. The optimal biomass models for Avicennia marina, Rhizophora stylosa, Bruguiera gymnorhiza, and Aegiceras corniculatum were power function models, whereas linear models best fit Kandelia obovata. The carbon density of the artificially planted young mangrove ecosystems in Kaozhouyang Bay was (91.26±17.32) Mg C·hm^-2, with a total carbon stock of approximately 35964.65 Mg C. Soil carbon constituted 78.3% to 98.5% of the total carbon stock in these ecosystems. Among the different mangrove communities, vegetation carbon density ranked as follows (from highest to lowest): Aegiceras corniculatum + Kandelia obovata communities, Rhizophora stylosa + Avicennia marina communities, Avicennia marina community, and Bruguiera gymnorhiza community. These results offer valuable insights for assessing carbon storage and guiding ecological restoration efforts in artificially planted mangroves in Guangdong Province and nationwide.

Key words: juvenile mangroves, biomass models, carbon density, artificial mangrove, Kaozhouyang Bay

中图分类号:

胡鑫, 熊兰兰, 陈顺洋, 张黄琛, 邹易阳, 张吉超, 刘东熙, 何佳潞, 吴于琪, 朱振杰. 幼龄红树生物量模型及幼林红树林碳储量研究^*[J]. 热带海洋学报, 2025, 44(4): 187-199.

HU Xin, XIONG Lanlan, CHEN Shunyang, ZHANG Huangchen, ZOU Yiyang, ZHANG Jichao, LIU Dongxi, HE Jialu, WU Yuqi, ZHU Zhenjie. Study on biomass models of juvenile mangroves and carbon storage in young mangrove ecosystems*[J]. Journal of Tropical Oceanography, 2025, 44(4): 187-199.

图/表 7

图1

图2

表1

表2

幼龄红树植物生物量模型构建"

树种	自变量	因变量	R²	P	回归模型	RSS	AIC	RMSE
红海榄地上生物量模型	D	W_t	0.88	<0.01	W_t = 0.0094×D^3.0878	0.62	-114.33	0.14
	D	W_t	0.53	<0.01	W_t = 0.2358×D-0.3383	0.88	-103.79	0.17
	H	W_t	0.61	<0.01	W_t = 0.1037×H^3.072	0.84	-105.40	0.17
	H	W_t	0.54	<0.01	W_t = 0.6918×H-0.493	0.86	-104.52	0.17
	DH	W_t	0.88	<0.01	W_t = 0.0269×(DH)^1.8155	0.28	-135.97	0.10
	DH	W_t	0.77	<0.01	W_t = 0.1608×(DH)-0.1843	0.44	-122.53	0.12
	D²H	W_t	0.90	<0.01	W_t = 0.0175×(D²H)^1.1779	0.23	-136.10	0.11
	D²H	W_t	0.83	<0.01	W_t = 0.0388×(D²H)-0.0554	0.33	-131.72	0.10
	DH²	W_t	0.82	<0.01	W_t = 0.0434×(DH²)^1.197	0.34	-130.33	0.11
	DH²	W_t	0.89	<0.01	W_t = 0.1037×(DH²)-0.0841	0.29	-136.58	0.11
红海榄地下生物量模型	D	W_d	0.88	<0.01	W_d = 0.0022×D^3.4548	0.61	-115.09	0.14
	D	W_d	0.41	<0.01	W_d = 0.1651×D-0.2747	0.63	-113.83	0.15
	H	W_d	0.56	<0.01	W_d = 0.0356×H^2.4809	0.88	-103.94	0.17
	H	W_d	0.34	<0.01	W_d = 0.3549×H-0.2487	0.70	-110.59	0.15
	DH	W_d	0.84	<0.01	W_d = 0.0097×(DH)^1.752	0.59	-113.90	0.14
	DH	W_d	0.62	<0.01	W_d = 0.108×(DH)-0.1492	0.71	-124.90	0.12
	D²H	W_d	0.90	<0.01	W_d = 0.0056×(D²H)^1.2153	0.53	-146.91	0.13
	D²H	W_d	0.76	<0.01	W_d = 0.0289×(D²H)-0.0791	0.75	-139.11	0.09
	DH²	W_d	0.76	<0.01	W_d = 0.0164×(DH²)^0.7605	0.93	-100.30	0.18
	DH²	W_d	0.78	<0.01	W_d = 0.0718×(D²H)-0.0876	0.74	-141.31	0.09
白骨壤地上生物量模型	D	W_t	0.92	<0.01	W_t = 0.0182×D^3.7886	2.35	-74.44	0.28
	D	W_t	0.68	<0.01	W_t = 0.4464×D-0.4502	1.56	-86.62	0.23
	H	W_t	0.74	<0.01	W_t = 0.2047×H^3.722	0.87	-104.18	0.17
	H	W_t	0.73	<0.01	W_t = 0.9049×H-0.4899	1.30	-92.09	0.21
	DH	W_t	0.93	<0.01	W_t = 0.0595×(DH)^2.1007	1.12	-94.54	0.19
	DH	W_t	0.88	<0.01	W_t = 0.28×(DH)-0.1703	0.59	-113.80	0.14
	D²H	W_t	0.95	<0.01	W_t = 0.0383×(D²H)^1.3822	0.71	-131.98	0.14
	D²H	W_t	0.84	<0.01	W_t = 0.0844×(D²H)-0.0159	0.75	-106.71	0.16
	DH²	W_t	0.89	<0.01	W_t = 0.0931×(DH²)^1.3826	0.63	-112.00	0.14
	DH²	W_t	0.91	<0.01	W_t = 0.1705×(DH²)-0.0315	0.43	-123.03	0.12
白骨壤地下生物量模型	D	W_d	0.93	<0.01	W_d = 0.01×D^3.145	0.20	-148.92	0.08
	D	W_d	0.61	<0.01	W_d = 0.1179×D-0.0983	0.17	-152.36	0.08
	H	W_d	0.80	<0.01	W_d = 0.1062×H^3.4719	0.18	-176.96	0.05
	H	W_d	0.75	<0.01	W_d = 0.2913×H-0.1313	0.11	-165.76	0.06
	DH	W_d	0.93	<0.01	W_d = 0.031×(DH)^1.7634	0.14	-156.55	0.07
	DH	W_d	0.79	<0.01	W_d = 0.0803×(DH)-0.0281	0.10	-168.47	0.06
	D²H	W_d	0.94	<0.01	W_d = 0.0206×(D²H)^1.144	0.12	-163.05	0.09
	D²H	W_d	0.74	<0.01	W_d =0.0239×(D²H)+0.0099	0.12	-162.04	0.06
	DH²	W_d	0.90	<0.01	W_d = 0.0473×(DH²)^1.1905	0.17	-150.86	0.08
	DH²	W_d	0.83	<0.01	W_d =0.0526×(D²H)+0.0067	0.08	-175.10	0.05
桐花树地上生物量模型	D	W_t	0.90	<0.01	W_t = 0.011×D^2.3301	0.03	-208.12	0.03
	D	W_t	0.57	<0.01	W_t = 0.0704×D-0.0731	0.04	-196.34	0.04
	H	W_t	0.33	<0.01	W_t = 0.1184×H^2.1268	0.07	-179.13	0.05
	H	W_t	0.24	<0.01	W_t = 0.1877×H-0.0587	0.13	-161.70	0.07
桐花树地上生物量模型	DH	W_t	0.84	<0.01	W_t = 0.0378×(DH)^1.5403	0.02	-210.19	0.03
	DH	W_t	0.67	<0.01	W_t = 0.0825×(DH)-0.0402	0.03	-202.75	0.03
	D²H	W_t	0.90	<0.01	W_t = 0.0227×(D²H)^0.9647	0.02	-214.66	0.03
	D²H	W_t	0.84	<0.01	W_t = 0.0275×(D²H)-0.0109	0.02	-203.74	0.02
	DH²	W_t	0.71	<0.01	W_t = 0.065×(DH²)^1.0197	0.03	-199.39	0.03
	DH²	W_t	0.68	<0.01	W_t = 0.0881×(DH²)-0.0127	0.03	-203.57	0.03
桐花树地下生物量模型	D	W_d	0.90	<0.01	W_d = 0.0038×D^2.4588	0.00	-299.13	0.01
	D	W_d	0.65	<0.01	W_d = 0.0241×D-0.0234	0.00	-269.91	0.01
	H	W_d	0.36	<0.01	W_d = 0.0462×H^2.2983	0.00	-250.07	0.01
	H	W_d	0.31	<0.01	W_d = 0.0662×H-0.0201	0.00	-249.42	0.02
	DH	W_d	0.84	<0.01	W_d = 0.0143×(DH)^1.5553	0.00	-288.83	0.01
	DH	W_d	0.74	<0.01	W_d = 0.0272×(DH)-0.0104	0.00	-276.19	0.01
	D²H	W_d	0.88	<0.01	W_d = 0.0084×(D²H)^0.9858	0.00	-296.93	0.01
	D²H	W_d	0.88	<0.01	W_d = 0.009×(D²H)-0.0008	0.00	-299.49	0.01
	DH²	W_d	0.70	<0.01	W_d = 0.0247×(DH²)^1.0295	0.00	-275.08	0.01
	DH²	W_d	0.74	<0.01	W_d = 0.0293×(D²H)-0.0017	0.00	-276.52	0.01
木榄地上生物量模型	D	W_t	0.73	<0.01	W_t = 0.0043×D^3.6814	0.05	-191.85	0.04
	D	W_t	0.87	<0.01	W_t = 0.1475×D-0.1976	0.04	-199.76	0.03
	H	W_t	0.86	<0.01	W_t = 0.2561×H^3.4544	0.12	-164.76	0.06
	H	W_t	0.58	<0.01	W_t = 0.3593×H-0.1392	0.12	-163.59	0.06
	DH	W_t	0.95	<0.01	W_t = 0.0353×(DH)^2.1235	0.04	-199.35	0.04
	DH	W_t	0.88	<0.01	W_t = 0.1151×(DH)-0.0631	0.04	-198.12	0.03
	D²H	W_t	0.91	<0.01	W_t = 0.0158×(D²H)^1.413	0.06	-184.64	0.04
	D²H	W_t	0.93	<0.01	W_t = 0.0333×(D²H)-0.0128	0.06	-200.10	0.03
	DH²	W_t	0.95	<0.01	W_t = 0.0767×(DH²)^1.3609	0.06	-184.47	0.04
	DH²	W_t	0.83	<0.01	W_t = 0.1054×(DH²)-0.0152	0.05	-188.28	0.04
木榄地下生物量模型	D	W_d	0.57	<0.01	W_d = 0.0013×D^3.8032	0.01	-228.58	0.02
	D	W_d	0.78	<0.01	W_d = 0.0452×D-0.0568	0.01	-249.71	0.02
	H	W_d	0.92	<0.01	W_d = 0.1168×H^4.2022	0.01	-226.94	0.02
	H	W_d	0.67	<0.01	W_d = 0.1263×H-0.049	0.01	-238.25	0.02
	DH	W_d	0.88	<0.01	W_d = 0.0106×(DH)^2.4009	0.02	-216.43	0.03
	DH	W_d	0.84	<0.01	W_d = 0.0369×(DH)-0.0177	0.00	-258.62	0.01
	D²H	W_d	0.80	<0.01	W_d = 0.0044×(D²H)^1.5536	0.02	-213.67	0.03
	D²H	W_d	0.83	<0.01	W_d = 0.0102×(D²H)-0.0004	0.01	-255.70	0.01
	DH²	W_d	0.93	<0.01	W_d = 0.026×(DH²)^1.5795	0.02	-251.75	0.02
	DH²	W_d	0.80	<0.01	W_d =0.0338×(D²H)-0.0025	0.01	-251.02	0.01
秋茄地上生物量模型	D	W_t	0.91	<0.01	W_t = 0.0243×D^2.0144	4.83	-52.82	0.40
	D	W_t	0.82	<0.01	W_t = 0.274×D-0.4659	3.23	-64.85	0.33
	H	W_t	0.87	<0.01	W_t = 0.2833×H^3.4024	6.38	-44.44	0.46
	H	W_t	0.66	<0.01	W_t = 1.7532×H-1.1884	6.51	-43.82	0.47
	DH	W_t	0.95	<0.01	W_t = 0.0569×(DH)^1.3385	1.21	-92.22	0.20
	DH	W_t	0.96	<0.01	W_t = 0.1588×(DH)-0.1618	0.83	-103.62	0.17
	D²H	W_t	0.94	<0.01	W_t = 0.04×(D²H)^0.8104	2.54	-70.04	0.29
	D²H	W_t	0.84	<0.01	W_t = 0.011×(D²H)+0.1818	3.03	-64.78	0.32
	DH²	W_t	0.95	<0.01	W_t = 0.0882×(DH²)^0.9796	0.58	-114.47	0.14
	DH²	W_t	0.97	<0.01	W_t = 0.085×(DH²) + 0.0237	0.54	-116.38	0.13
秋茄地下生物量模型	D	W_d	0.95	<0.01	W_d = 0.0073×D^2.3728	4.02	-58.33	0.37
	D	W_d	0.87	<0.01	W_d = 0.1571×D-0.2736	0.80	-106.59	0.16
	H	W_d	0.85	<0.01	W_d = 0.1209×H^3.8117	2.58	-71.63	0.29
	H	W_d	0.60	<0.01	W_d = 0.9006×H-0.5968	2.38	-74.00	0.28
	DH	W_d	0.96	<0.01	W_d = 0.0202×(DH)^1.5373	0.71	-108.20	0.15
	DH	W_d	0.97	<0.01	W_d = 0.0887×(DH)-0.1029	0.20	-146.39	0.08
	D²H	W_d	0.96	<0.01	W_d = 0.0134×(D²H)^0.9392	1.80	-80.48	0.24
	D²H	W_d	0.89	<0.01	W_d = 0.0063×(D²H)-0.0678	1.20	-92.60	0.20
	DH²	W_d	0.94	<0.01	W_d = 0.0334×(DH²)^1.1147	0.20	-146.77	0.08
	DH²	W_d	0.98	<0.01	W_d = 0.0473×(D²H)-0.0102	0.14	-156.31	0.07

表2

图3

表3

图4

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树种	基径/cm	株高/m	树龄/a	地上生物量/kg	地下生物量/kg	地上碳密度系数/%	地下碳密度系数/%
红海榄	1.05~4.14	0.46~1.73	1~5	0.012~1.416	0.002~1.069	43.79~44.66	31.66~40.61
白骨壤	0.70~3.60	0.36~1.63	1~5	0.004~1.531	0.001~0.570	41.87~44.55	35.47~38.79
桐花树	0.60~3.30	0.32~0.91	1~3	0.002~0.326	0.001~0.104	36.67~40.39	35.96~42.20
木榄	0.96~3.76	0.32~1.03	1~3	0.006~0.437	0.001~0.131	43.06~43.93	31.28~37.26
秋茄	0.65~14.32	0.36~2.15	1~5	0.006~3.822	0.003~2.215	39.28~46.54	32.45~40.60

站位	物种	密度/(ind·hm^-2)	基径/cm	株高/m
C1	白骨壤	11067	3.17±0.54	1.34±0.26
C1	红海榄	12667	2.41±0.58	0.70±0.24
C2	木榄	10667	2.46±1.14	1.02±0.37
C3	桐花树	11200	2.43±0.51	0.87±0.11
C3	秋茄	3600	3.80±2.90	0.85±0.45
C4	白骨壤	26000	2.08±0.80	1.09±0.19
C5	白骨壤	11200	2.49±0.38	0.77±0.11
C5	红海榄	22000	2.09±0.42	0.77±0.08

幼龄红树生物量模型及幼林红树林碳储量研究^*

Study on biomass models of juvenile mangroves and carbon storage in young mangrove ecosystems*

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