森林生态系统细根周转规律及影响因素

doi:10.11983/CBB19231

植物学报 ›› 2020, Vol. 55 ›› Issue (3): 308-317.DOI: 10.11983/CBB19231

森林生态系统细根周转规律及影响因素

赵佳宁¹,梁韵²,柳莹³,王玉珏¹,杨倩茹¹,肖春旺^1,^*()

¹中央民族大学生命与环境科学学院, 北京 100081
²中国科学院植物研究所, 植被与环境变化国家重点实验室, 北京 100093
³西安科技大学测绘科学与技术学院, 西安 710054

收稿日期:2019-11-29 接受日期:2020-02-26 出版日期:2020-05-01 发布日期:2020-07-06
通讯作者: 肖春旺
基金资助:
国家自然科学基金(31770501);国家自然科学基金(31370462);中央民族大学理工科拔尖创新人才培养实验班项目;国家大学生创新创业训练计划(GCCX2019110017)

Patterns and Influence Factors of Fine Root Turnover in Forest Ecosystems

Jianing Zhao¹,Yun Liang²,Ying Liu³,Yujue Wang¹,Qianru Yang¹,Chunwang Xiao^1,^*()

¹College of Life and Environmental Sciences, Minzu University of China, Beijing 100081, China
²State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China
³College of Geomatics, Xi’an University of Science and Technology, Xi’an 710054, China

Received:2019-11-29 Accepted:2020-02-26 Online:2020-05-01 Published:2020-07-06
Contact: Chunwang Xiao

1. 附录1 70 个研究样点的数据来源.pdf(304KB)

摘要/Abstract

摘要： 根系周转是陆地生态系统碳循环的关键过程, 对研究土壤碳库变化及全球气候变化均具有重要意义。然而由于根系周转率的测量计算方法较多, 不同方法得出的结果差异较大, 且目前对全球区域尺度上森林生态系统根系周转的研究还不够充分, 使得全球森林生态系统根系周转变化规律仍不清楚。该研究通过收集文献数据并统一周转率计算方法, 对全球5种森林类型的细根周转空间格局进行整合, 同时结合土壤理化性质和气候数据, 得出影响森林生态系统细根周转的因子。结果表明, 不同森林类型细根周转率存在显著差异, 且随着纬度的升高逐渐降低; 森林生态系统细根周转率与年平均温度和年平均降水量呈正相关; 森林生态系统细根周转率与土壤有机碳含量呈正相关但与土壤pH值呈负相关。该研究为揭示森林生态系统细根周转规律及机制提供了科学依据。

关键词: 细根周转, 全球森林尺度, 气候因子, 土壤性质

Abstract: Root turnover is a key process in the carbon cycle of terrestrial ecosystems, and plays an important role in studying soil carbon pool changes and global climate change. Various methods for measuring root turnover rate have been described, from which highly variable results are obtained. Moreover, the studies on root turnover in large regional scales are not sufficient, making the patterns of root turnover in global forest ecosystem still not clear. This study integrates the fine root turnover spatial pattern of five forest types in the world by collecting literature data and unifying the calculation method of turnover rate. Combined with soil physical and chemical properties and climate data, several factors driving the fine root turnover of forest ecosystems are obtained. We show that there was a significant difference in the different forest ecosystems and the fine root turnover rate almost decreased with the increase of latitude. The fine root turnover rate of forest ecosystems was positively correlated to the mean annual temperature and the mean annual precipitation. The fine root turnover rate of forest ecosystems was positively correlated to the soil organic carbon content but negatively correlated to soil pH. This study provides a model to study the fine root turnover laws and mechanisms of forest ecosystems.

Key words: fine root turnover, global forest scale, climate factor, soil properties

赵佳宁, 梁韵, 柳莹, 王玉珏, 杨倩茹, 肖春旺. 森林生态系统细根周转规律及影响因素. 植物学报, 2020, 55(3): 308-317.

Jianing Zhao, Yun Liang, Ying Liu, Yujue Wang, Qianru Yang, Chunwang Xiao. Patterns and Influence Factors of Fine Root Turnover in Forest Ecosystems. Chinese Bulletin of Botany, 2020, 55(3): 308-317.

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链接本文: https://www.chinbullbotany.com/CN/10.11983/CBB19231

https://www.chinbullbotany.com/CN/Y2020/V55/I3/308

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参考文献 49

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Forest type	Data number	Means ± SE
Tropical rainforest	11	1.312±0.182 a
Subtropical evergreen broad-leaved forest	9	0.802±0.161 b
Warm temperate deciduous broad-leaved forest	13	0.724±0.859 b
Temperate coniferous and broad-leaved mixed forest	30	0.766±0.995 b
Cold temperate coniferous forest	7	0.602±0.106 b

Forest type	Data number	Means ± SE
Tropical rainforest	11	1.312±0.182 a
Subtropical evergreen broad-leaved forest	9	0.802±0.161 b
Warm temperate deciduous broad-leaved forest	13	0.724±0.859 b
Temperate coniferous and broad-leaved mixed forest	30	0.766±0.995 b
Cold temperate coniferous forest	7	0.602±0.106 b

	MAT	MAP	Soil organic carbon	Soil pH	Soil bulk density	CEC	Sand fraction	Clay fraction	Silt fraction	lg (fine root turnover rate)
Latitude	-0.867**	-0.609**	-0.164	0.168	0.348**	0.157	0.124	0.097	0.105	-0.367**
MAT		0.576**	-0.029	-0.009	-0.332**	-0.03	-0.211	-0.011	0.361**	0.233*
MAP			-0.101	-0.094	-0.254*	-0.048	-0.167	0.052	0.221	0.240*
Soil organic carbon				-0.449**	0.14	0.11	0.126	-0.171	0.029	0.254*
Soil pH					0.026	0.235	-0.041	0.231	-0.165	-0.297*
Soil bulk density						-0.464**	0.900**	-0.599**	-0.852**	-0.098
CEC							-0.545**	0.376*	0.491**	-0.071
Sand fraction								-0.823**	-0.772**	0.038
Clay fraction									0.284*	-0.146
Silt fraction										0.104

	MAT	MAP	Soil organic carbon	Soil pH	Soil bulk density	CEC	Sand fraction	Clay fraction	Silt fraction	lg (fine root turnover rate)
Latitude	-0.867**	-0.609**	-0.164	0.168	0.348**	0.157	0.124	0.097	0.105	-0.367**
MAT		0.576**	-0.029	-0.009	-0.332**	-0.03	-0.211	-0.011	0.361**	0.233*
MAP			-0.101	-0.094	-0.254*	-0.048	-0.167	0.052	0.221	0.240*
Soil organic carbon				-0.449**	0.14	0.11	0.126	-0.171	0.029	0.254*
Soil pH					0.026	0.235	-0.041	0.231	-0.165	-0.297*
Soil bulk density						-0.464**	0.900**	-0.599**	-0.852**	-0.098
CEC							-0.545**	0.376*	0.491**	-0.071
Sand fraction								-0.823**	-0.772**	0.038
Clay fraction									0.284*	-0.146
Silt fraction										0.104

森林生态系统细根周转规律及影响因素

Patterns and Influence Factors of Fine Root Turnover in Forest Ecosystems

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Plot	Continent	Country	Longitude and latitude	Plot	Continent	Country	Longitude and latitude
1	Asia	India	77°15'E, 8°28'59"N	36	Asia	China	128°5'40.56"E, 42°23'57.48"N
2	Asia	India	76°49'59"E, 9°22'1"N	37	Asia	China	128°4'59.88"E, 42°24'N
3	Asia	India	77°25'58.8"E, 9°31'58.8"N	38	Asia	China	128°6'29.16"E, 42°25'15.24"N
4	Asia	India	79°55'1.2"E, 12°10'58.8"N	39	Asia	China	128°30'E, 43°4'58.8"N
5	Asia	China	110°31'19.2"E, 20°1'1.2"N	40	Asia	China	127°31'48"E, 44°22'48"N
6	Asia	China	112°49'58.8"E, 22°34'1.2"N	41	Asia	China	88°13'48"E, 44°37'12"N
7	Asia	China	117°18'E, 23°35'24"N	42	Asia	Japan	142°6'E, 45°3'N
8	Asia	India	91°55'58.8"E, 25°34'1.2"N	43	Asia	China	128°53'13.2"E, 47°10'51.6"N
9	Asia	China	117°57'E, 26°28'1.2"N	44	Asia	China	127°54'36"E, 47°13'48"N
10	Asia	China	110°7'58.8"E, 27°9'N	45	North America	Panama	82°15'W, 8°45'N
11	Asia	China	119°10'48"E, 27°52'12"N	46	North America	Puerto Rico	65°49'1.2"W, 18°40'1.2"N
12	Asia	China	113°1'48"E, 28°7'12"N	47	North America	USA	84°30'W, 31°15'N
13	Asia	China	91°19'58.8"E, 29°40'1.2"N	48	North America	USA	92°W, 32°N
14	Asia	China	121°46'58.8"E, 29°48'N	49	North America	USA	111°45'W, 35°16'1.2"N
15	Asia	China	103°25'1.2"E, 29°58'58.8"N	50	North America	USA	76°27'43.2"W, 36°31'58.8"N
16	Asia	China	102°48'E, 30°1'1.2"N	51	North America	USA	82°22'1.2"W, 39°10'58.8"N
17	Asia	China	117°24'E, 30°22'12"N	52	North America	USA	78°45'57.6"W, 41°35'52.8"N
18	Asia	China	117°43'48"E, 30°22'48"N	53	North America	USA	72°11'24"W, 42°31'51.6"N
19	Asia	India	79°56'24"E, 30°28'58.8"N	54	North America	USA	71°45'W, 43°55'58.8"N
20	Asia	China	117°53'24"E, 30°34'48"N	55	North America	USA	72°13'1.2"W, 44°N
21	Asia	China	117°54'E, 30°34'48"N	56	North America	USA	122°13'1.2"W, 44°13'58.8"N
22	Asia	China	121°54'25.2"E, 30°52'55.2"N	57	North America	USA	121°34'1.2"W, 44°25'58.8"N
23	Asia	India	75°40'12"E, 30°54'N	58	North America	USA	68°41'6"W, 44°55'19.2"N
24	Asia	China	119°13'58.8"E, 31°58'58.8"N	59	North America	USA	122°W, 46°N
25	Asia	Japan	131°12'E, 32°3'N	60	North America	Canada	89°28'58.8"W, 49°32'24"N
26	Asia	China	108°7'58.8"E, 33°58'1.2"N	61	Europe	Italy	14°33'E, 41°43'1.2"N
27	Asia	Japan	135°37'1.2"E, 34°4'58.8"N	62	Europe	France	3°49'4.8"E, 43°41'16.8"N
28	Asia	China	116°49'58.8"E, 35°52'58.8"N	63	Europe	France	4°37'48"E, 49°45'36"N
29	Asia	Japan	104°7'55.2"E, 36°N	64	Europe	Germany	10°26'2.4"E, 51°4'48"N
30	Asia	Japan	140°13'1.2"E, 36°6'N	65	Europe	Belgium	3°51'E, 51°6'N
31	Asia	Korea	127°42'E, 37°30'N	66	Europe	Estonia	26°45'E, 58°46'1.2"N
32	Asia	China	112°31'1.2"E, 37°39'N	67	Europe	Finland	30°58'1.2"E, 62°46'58.8"N
33	Asia	China	115°25'8.4"E, 39°57'N	68	South America	Brazil	56°58'59"W, 3°4'1"S
34	Asia	China	87°51'25.2"E, 40°27'57.6"N	69	South America	Brazil	47°56'56"W, 1°17'53"S
35	Asia	China	117°15'E, 42°19'12"N	70	Africa	C?te d'Ivoire	5°13'1.2"W, 6°16'59"N

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