北方草地及农牧交错区草地植被碳储量及其影响因素

doi:10.3864/j.issn.0578-1752.2020.13.022

中国农业科学 ›› 2020, Vol. 53 ›› Issue (13): 2757-2768.doi: 10.3864/j.issn.0578-1752.2020.13.022

• 生态产业示范及区域尺度分析 • 上一篇

北方草地及农牧交错区草地植被碳储量及其影响因素

辛晓平¹(),丁蕾¹,程伟¹,朱晓昱¹,陈宝瑞¹,刘钟龄²,何广礼³,青格勒¹,杨桂霞¹,唐华俊¹

¹中国农业科学院农业资源与农业区划研究所/呼伦贝尔草原生态系统国家野外科学观测研究站,北京 100081
²内蒙古大学生态与环境学院,呼和浩特 010021
³锡林郭勒职业学院草原生态与畜牧业学院,内蒙古锡林浩特 026000

收稿日期:2019-09-23 接受日期:2020-02-19 出版日期:2020-07-01 发布日期:2020-07-16
通讯作者: 辛晓平
基金资助:
国家重点研发计划(2016YFC0500600);国家重点研发计划(2017YFE0104500);国家自然科学基金(41771205);现代农业产业技术体系建设专项资金(CARS-34)

Biomass Carbon Storage and Its Effect Factors in Steppe and Agro-Pastoral Ecotones in Northern China

XIN XiaoPing¹(),DING Lei¹,CHENG Wei¹,ZHU XiaoYu¹,CHEN BaoRui¹,LIU ZhongLing²,HE GuangLi³,QING GeLe¹,YANG GuiXia¹,TANG HuaJun¹

¹Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences/National Hulunber Grassland Ecosystem Observation and Research Station, Beijing 100081
²Department of Environmental Sciences, Inner Mongolia University, Huhhot 010021
³Department of Grassland Ecology and Animal Husbandry, Xilingol Vocational College, Xilinhot 026000, Inner Mongolia

Received:2019-09-23 Accepted:2020-02-19 Online:2020-07-01 Published:2020-07-16
Contact: XiaoPing XIN

摘要/Abstract

摘要：

【目的】 草地生态系统在全球碳平衡中有重要的意义,草地植被碳库及其变化机制研究是植被生态学的重要命题。本文研究北方草地和农牧交错区草地植被碳密度及其空间格局,解析不同区域草地植被碳密度的关键影响因素,分析了气候、土壤、放牧等因素对地上地下植被碳库的相对贡献。【方法】 基于2002—2009年北方草地及农牧交错带草地植被调查数据,结合同期MODIS/NDVI遥感影像和1﹕100万草地类型图,建立了我国主要草地类型的生物量估算模型;整合野外考察数据和前人研究结果,探讨了研究区地上地下生物碳库及其空间格局;基于研究区255个县级行政单元,分析了不同类型草地植被碳库与气候要素、土壤要素及家畜承载量的关系,应用一般线性模型（GLM）解析了不同影响因素对草地碳密度的相对贡献。【结果】 （1）北方草地与农牧交错区草地地上平均生物碳密度为36.9 g C·m^-2,地下生物碳密度为362.9 g C·m^-2,地下生物碳密度高于地上10倍,均呈从东到西递减的趋势,频率分布图基本服从对数正态分布,不同草地类型的生物碳密度存在明显差异;（2）整个研究区及草原亚区、荒漠亚区、农牧交错亚区内,地上生物量与年降水量（MAP）呈极显著正相关、与年均气温（MAT）均呈极显著负相关,与土壤黏粒含量（Clay%）呈显著正相关、与土壤砂粒含量（Sand%）呈显著负相关,整个研究区家畜承载量与草地地上生物量之间呈极显著正相关;（3）一般线性模型（GLM）分析结果表明,年平均降水量（MAP）、年均气温（MAT）、土壤黏粒含量（Clay%）、放牧强度对地上生物量空间变异的解释率分别达到29.6%（P<0.001）、5.8%（P<0.001）、0.8%（P<0.05）、1.3%（P<0.001）;地下生物量的空间变异主要来自于年降水量（MAP）、年均气温（MAT）、土壤砂粒含量（Sand%）,对方差的解释率分别达到12.1%（P<0.001）、6.8%（P<0.001）、1.9%（P<0.005）,放牧强度没有明显贡献。【结论】 气候条件尤其是年降水量是草地生物量碳库的主要影响因素,但对地上生物量影响更为明显;土壤质地对植被生物碳库也有显著贡献,尤其对地下生物量的影响更加显著;放牧强度只能解释地上生物量变化的1.3%、对地下生物量没有显著贡献,这一发现意味着气候对生物量碳库的贡献远大于放牧影响。

关键词: 北方草地及农牧交错区, 植被碳储量, 气候因素, 家畜承载量, 土壤质地

Abstract:

【Objective】 The grassland ecosystem plays an important role in the global carbon balance. The study of grassland carbon pool and its driving force is a hot point of vegetation ecology. This study investigated the vegetation carbon density and its spatial pattern in the steppe and agro-pastoral ecotones of northern China. The major factors driving the spatial variation of grassland vegetation carbon density were identified, as well as the relative contribution of climate, soil texture, grazing intensity and other factors to the grassland vegetation carbon pool. 【Method】 Using the survey data of the grassland vegetation in northern grassland during 2002 and 2009, combined with the MODIS/NDVI remote sensing data and 1:1 million grassland type map, the estimation model of above- and below-ground biomass in the main grassland types of northern China was established. Based on 255 county-level administrative units in the study area, the relationship between grassland vegetation carbon density and climate factors, soil texture and livestock carrying capacity were explored, and derived the relative contribution of different driving factors to grassland carbon density using the general linear model (GLM). 【Result】 (1) The average above-ground biomass (AGB) of the steppe and agro-pastoral ecotones of northern China was 36.9 g C·m^-2, and the below-ground biomass (BGB) was 362.9 g C·m^-2, nearly 10 times the AGB. Both the above- and below-ground biomass decreased from east to west, and followed logarithmic normal distribution. The biomass carbon density of grassland types was significantly different. (2) In the whole study region and steppe sub-region, desert sub-region, agro-pastoral sub-region, the AGB showed a significantly positive correlation with mean annual precipitation (MAP) and soil clay content (Clay%), a significantly negative relationship with the mean annual temperature (MAT) and soil sand content (Sand%). The AGB increased with livestock carrying capacity except in the steppe sub-region where were very heavily grazed. (3) General Linear Model (GLM) analysis indicated that the MAP, MAT, Clay% and grazing intensity explained 29.6% (P<0.001), 5.8% (P<0.001), 0.8% (P<0.05) and 1.3% (P<0.001) of AGB variation, respectively, and the MAP, MAT and Sand% contributed to 12.1% (P<0.001), 6.8% (P<0.001) and 1.9% (P<0.005) to BGB variation, respectively, and the grazing intensity had minor contribution to BGB. 【Conclusion】 Climate factors especially MAP was the dominate driving factor of grassland vegetation carbon density, and its impact on AGB was more obvious than on BGB. Soil texture also had a significant contribution to the grassland vegetation carbon density, especially on the BGB. Grazing intensity explained only 1.3% of the AGB and had no impact on BGB. This finding indicated that the climate factors were major contributor grassland vegetation carbon density comparing with grazing intensity.

Key words: steppe and agro-pastoral ecotones in northern China, biomass carbon storage, climate, livestock capacity, soil texture

辛晓平,丁蕾,程伟,朱晓昱,陈宝瑞,刘钟龄,何广礼,青格勒,杨桂霞,唐华俊. 北方草地及农牧交错区草地植被碳储量及其影响因素[J]. 中国农业科学, 2020, 53(13): 2757-2768.

XIN XiaoPing,DING Lei,CHENG Wei,ZHU XiaoYu,CHEN BaoRui,LIU ZhongLing,HE GuangLi,QING GeLe,YANG GuiXia,TANG HuaJun. Biomass Carbon Storage and Its Effect Factors in Steppe and Agro-Pastoral Ecotones in Northern China[J]. Scientia Agricultura Sinica, 2020, 53(13): 2757-2768.

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参考文献 34

[1]	BOLIN B. Changes of land biota and their importance for the carbon cycle. Science, 1977,196(4290):613-615.
[2]	AJTAY G. Terrestrial primary production and phytomass. The Global Carbon Cycle, 1979:129-181.
[3]	ROY J, SAUGIER B, MOONEY H. Global Terrestrial Productivity: Past, Present and Future. San Diego: Academic Press, 2001.
[4]	BAAH-ACHEAMFOUR M, CHANG S X, CARLYLE C N, BORK E W. Carbon pool size and stability are affected by trees and grassland cover types within agroforestry systems of western Canada. Agriculture, Ecosystems & Environment, 2015,213:105-113.
[5]	ZHOU G Y, QIN L, JIE C Y, MIAO H, YAN Z L, DOUGLAS F, HUI H Y, LING F Y, CHENG Z B, HUI Z X. Effects of livestock grazing on grassland carbon storage and release override impacts associated with global climate change. Global Change Biology, 2019,25(3):1119-1132.
[6]	NI J. Carbon storage in terrestrial ecosystems of China: Estimates at different spatial resolutions and their responses to climate change. Climatic Change, 2001,49(3):339-358.
[7]	NI J. Carbon storage in grasslands of China. Journal of Arid Environments, 2002,50(2):205-218.
[8]	NI J. Forage yield-based carbon storage in grasslands of China. Climatic Change, 2004,67(2/3):237-246.
[9]	FAN J W, ZHONG H P, HARRIS W, YU G R, WANG S Q, HU Z M, YUE Y Z. Carbon storage in the grasslands of China based on field measurements of above- and below-ground biomass. Climatic Change, 2008,86(3):375-396.
[10]	FANG J Y, GUO Z D, PIAO S L, CHEN A P. Terrestrial vegetation carbon sinks in China, 1981-2000. Science in China Series D: Earth Sciences, 2007,50(9):1341-1350.
[11]	FANG J Y, LIU G H, XU S L. The carbon cycle of terrestrial ecosystems in China and its global significance in China//Monitoring and Relevant Process of Greenhouse Gas Concentration and Emission, Beijing: Chinese Environmental Science Publishing House, 1996: 129-139.
[12]	PIAO S L, FANG J Y, ZHOU L M, TAN K, TAO S. Changes in biomass carbon stocks in China's grasslands between 1982 and 1999. Global Biogeochemical Cycles, 2007,21(2):1-10.
[13]	MA W H, FANG J Y, YANG Y H, MOHAMMAT A. Biomass carbon stocks and their changes in northern China’s grasslands during 1982-2006. Science China Life Sciences, 2010,53(7):841-850.
[14]	MA W H, LIU Z L, WANG Z H, WANG W, LIANG C Z, TANG Y H, HE J S, FANG J Y. Climate change alters interannual variation of grassland aboveground productivity: Evidence from a 22-year measurement series in the Inner Mongolian grassland. Journal of Plant Research, 2010,123(4):509-517.
[15]	李克让, 王绍强, 曹明奎. 中国植被和土壤碳贮量. 中国科学: 地球科学, 2003,33(1):72-80.
	LI K R, WANG S Q, CAO M K. Carbon storage of vegetation and soil in China. Science in China (Series D ), 2003,33(1):72-80. (in Chinese)
[16]	NI J, SYKES M T, PRENTICE I C, CRAMER W. Modelling the vegetation of China using the process-based equilibrium terrestrial biosphere model BIOME3. Global Ecology and Biogeography, 2000,9(6):463-479.
[17]	王玉辉, 周广胜. 内蒙古羊草草原植物群落地上初级生产力时间动态对降水变化的响应. 生态学报, 2004,24(6):1140-1145.
	WANG Y H, ZHOU G S. Response of temporal dynamics of aboveground net primary productivity of Leymus chinensis community to precipitation fluctuation in Inner Mongolia. Acta Ecologica Sinica, 2004,24(6):1140-1145
[18]	BAI Y F, HAN X G, WU J G, CHEN Z Z, LI L H. Ecosystem stability and compensatory effects in the Inner Mongolia grassland. Nature, 2004,431(7005):181-184.
[19]	BAI Y F, WU J G, XING Q, PAN Q M, HUANG J H, YANG D L, HAN X G. Primary production and rain use efficiency across a precipitation gradient on the Mongolia Plateau. Ecology, 2008,89(8):2140-2153.
[20]	何楷迪, 孙建, 陈秋计. 气候要素和土壤质地对青藏高原草地净初级生产力和降水利用率的影响. 草业科学, 2019,36(4):140-152.
	HE K D, SUN J, CHEN Q J. Response of climate and soil texture to net primary productivity and precipitation-use efficiency in the Tibetan Plateau. Pratacultural Science, 2019,36(4):140-152.
[21]	郭群. 草原生态系统生产力对降水格局响应的研究进展. 应用生态学报, 2019,30(7):2201-2210.
	GUO Q. Responses of grassland ecosystem productivity to altered precipitation regime: A review. Chinese Journal of Applied Ecology, 2019,30(7):2201-2210. (in Chinese)]
[22]	WALTER J, GRANT K, BEIERKUHNLEIN C, KREYLING J, JENTSCH A. Increased rainfall variability reduces biomass and forage quality of temperate grassland largely independent of mowing frequency. Agriculture Ecosystems & Environment, 2012,148:1-10.
[23]	VALENTINI R, MATTEUCCI G, DOLMAN A, SCHULZE E-D, REBMANN C, MOORS E, GRANIER A, GROSS P, JENSEN N, PILEGAARD K. Respiration as the main determinant of carbon balance in European forests. Nature, 2000,404(6780):861-865.
[24]	LISKI J, ILVESNIEMI H, MäKELä A, WESTMAN C J. CO₂ emissions from soil in response to climatic warming are overestimated -The decomposition of old soil organic matter is tolerant of temperature. Ambio, 1999,28(2):171-174.
[25]	LI L, CHEN Z, WANG Q, LIU X, LI Y. Changes in soil carbon storage due to over-grazing in Leymus chinensis steppe in the Xilin River Basin of Inner Mongolia. Journal of Environmental Sciences, 1997,9(4):104-108.
[26]	OJIMA D S, DIRKS B O M, GLENN E P, OWENSBY C E, SCURLOCK J O. Assessment of C budget for grasslands and drylands of the world. Water, Air, and Soil Pollution, 1993,70(1):95-109.
[27]	朴世龙, 方精云, 贺金生, 肖玉. 中国草地植被生物量及其空间分布格局. 植物生态学报, 2004,28(4):491-498.
	PIAO S L, FANG J Y, HE J S, X Y. Spatial distribution of grassland biomass in China. Acta Phytoecologica Sinica, 2004,28(4):491-498. (in Chinese)
[28]	王道龙, 辛晓平. 北方草地及农牧交错区生态--生产功能分析与划分. 北京: 中国农业科学技术出版社, 2011.
	WANG D L, XIN X P. Ecology of Grassland and Pastoral Area in North China-Production Function Analysis and Division.. Beijing: China Agricultural Science and Technology Press, 2011. (in Chinese)
[29]	POST W M, EMANUEL W R, ZINKE P J, STANGENBERGER A G. Soil carbon pools and world life zones. Nature, 1982,298(5870):156-159.
[30]	贺金生, 王政权, 方精云. 全球变化下的地下生态学: 问题与展望. 科学通报, 2004,49(13):1226-1233.
	HE J S, WANG Z Q, FANG J Y. Underground ecology under global change: Problems and prospects. Chinese Science Bulletin, 2004,49(13):1226-1233. (in Chinese)
[31]	吴伊波, 崔骁勇. 草地植物根系碳储量和碳流转对CO₂浓度升高的响应. 生态学报, 2009,29(1):378-388.
	WU Y B, CUI X Y. Responses of root carbon reserves and root turnover to experimental CO₂ enrichment in grasslands. Acta Ecologica Sinica, 2009,29(1):378-388. (in Chinese)
[32]	方精云, 杨元合, 马文红, 安尼瓦尔·买买提, 沈海花. 中国草地生态系统碳库及其变化. 中国科学: 生命科学, 2010,40(7):566-576.
	FANG J Y, YANG Y H, MA W H, ANIWAER M M T, SHEN H H. Ecosystem carbon stocks and their changes in China’s grasslands. Scientia Sinica Vitae, 2010,40(7):566-576.
[33]	YANG Y H, FANG J Y, MA W H, GUO D L, MOHAMMAT A. Large-scale pattern of biomass partitioning across China’s grasslands. Global Ecology and Biogeography, 2010,19(2):268-277.
[34]	孙元丰, 万宏伟, 赵玉金, 陈世苹, 白永飞. 中国草地生态系统根系周转的空间格局和驱动因子. 植物生态学报, 2018,42(3):337-348.
	SUN Y F, WAN H W, ZHAO Y J, CHEN S P, BAI Y F. Spatial patterns and drivers of root turnover in grassland ecosystems in China. Chinese Journal of Plant Ecology, 2018,42(3):337-348. (in Chinese)

草地类型 Grassland Type	面积 Area (×10⁴km²)	碳密度 Carbon density (g C·m^-2)			碳储量 Carbon storage (Tg)
草地类型 Grassland Type	面积 Area (×10⁴km²)	地上AGB	地下BGB	总量Total	地上AGB	地下BGB	总量Total
TMS	14.13	65.46	582.44	647.90	9.25	82.30	91.54
TS	36.04	38.65	341.04	379.69	13.93	122.92	136.85
TDS	13.59	29.27	255.00	284.27	3.98	34.66	38.64
TD	32.36	19.02	151.01	170.03	6.16	48.87	55.03
LM	11.80	47.50	662.64	710.14	5.60	78.17	83.77
MM	2.11	67.92	365.99	433.91	1.43	7.71	9.15
AM	1.96	38.43	1456.2	1494.62	0.75	28.60	29.36
AS	1.58	17.31	482.71	500.02	0.27	7.63	7.90
Other	1.70	67.31	443.07	510.38	1.15	7.55	8.70
Total	115.28	36.89	362.95	399.84	42.52	418.42	460.94

相关系数 Correlation Coefficient	草原区 Steppe area	荒漠区 Desert area	农牧交错区 Agro-pasture area	研究区 Research region
年均气温MAT	-0.65***	-0.69***	-0.53***	-0.46***
年降水量MAP	0.50***	0.81***	0.53***	0.72***
家畜承载量Livestock capacity	0.09	0.45*	0.34***	0.25***
砂砾含量Sand%	-0.65***	-0.63**	-0.23**	-0.42***
黏粒含量Clay%	0.54***	0.73***	0.46***	0.59***

草地类型 Grassland type	朴世龙^[27]	YANG^[32]	MA^[14]	FAN^[9]	R/S used in this study^[28] 本研究使用王道龙^[28]
草地类型 Grassland type	朴世龙^[27]	YANG^[32]	MA^[14]	FAN^[9]	Sample No.	R/S
温性草甸草原Temperate meadow steppe	5.26	5.20	7.00	11.85	108	7.48(±4.74)
温性草原类Typical steppe	4.25	5.60	5.54	10.80	86	9.36(±6.35)
温性荒漠草原类Temperate desert steppe	7.89	6.40	5.19	6.71	100	6.73(±5.87)
高寒草甸草原类Alpine meadow steppe	7.91			42.67
高寒草原类Alpine steppe	4.25	5.20		39.51	139	27.89(±13.23)
高寒荒漠草原类Alpine desert steppe	7.89			24.38
温性草原化荒漠 Temperate desert steppe	7.89			5.31	87	5.92(±4.95)
温性荒漠类Temperate desert	7.89			1.09
高寒荒漠类Alpine desert	7.89			15.67
暖性草丛类Warm temperate herbosa	4.42			3.67
暖性灌草丛类Warm temperate shrub herbosa	4.42			1.52
热性草丛类Tropical herbosa	4.42
热性灌草丛类Tropical shrub herbosa	4.42
低地草甸类Lowland meadow	6.31			2.04	37	6.84(±3.12)
山地草甸类Mountain meadow	6.23	3.50	5.71	9.67	20	5.39(±2.48)
高寒草甸类Alpine meadow	7.92	6.80		20.06	129	37.8(±22.10)
沼泽类Marsh	15.68			12.57

源 Source	df	地上生物量Above-ground biomass			地下生物量Below-ground biomass
源 Source	df	SS%	F	Sig.	SS%	F	Sig.
校正模型Adjusted model	5	68.81	107.242	0.000	48.20	45.223	0.000
年均气温MAT	1	5.8	45.190	0.000	6.79	31.850	0.000
年降水量MAP	1	29.56	230.312	0.000	12.12	56.875	0.000
放牧强度Livestock capacity	1	1.34	10.465	0.001	0.49	2.307	0.130
黏粒含量Clay%	1	0.78	6.044	0.015	0.02	0.076	0.783
砂粒含量Sand%	1	0.05	0.371	0.543	1.91	8.978	0.003
误差Residuals	243	31.19			51.80
总计R²	248
校正的总计Adjusted R²	248	R² = 0.688（调整Adjusted R² = 0.682）			R² = 0.482（调整Adjusted R² = 0.471）

北方草地及农牧交错区草地植被碳储量及其影响因素

Biomass Carbon Storage and Its Effect Factors in Steppe and Agro-Pastoral Ecotones in Northern China

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[2]	钟亮,郭熙,国佳欣,韩逸,朱青,熊杏. 基于数据挖掘技术的高光谱土壤质地分类研究[J]. 中国农业科学, 2020, 53(21): 4449-4459.
[3]	盛月凡,王海燕,乔鈜元,王玫,陈学森,沈向,尹承苗,毛志泉. 不同土壤质地对平邑甜茶幼苗连作障碍程度的影响[J]. 中国农业科学, 2019, 52(4): 715-724.
[4]	肖婧，徐虎，蔡岸冬，黄敏，张琪，孙楠，张文菊，徐明岗. 生物质炭特性及施用管理措施对作物产量影响的整合分析[J]. 中国农业科学, 2017, 50(10): 1827-1837.
[5]	吴焕焕12, 吕家珑2, 段英华1, 张文菊1, 徐明岗1. 激光衍射法测定中国典型土壤颗粒分布的模型建立与验证[J]. 中国农业科学, 2013, 46(20): 4293-4300.
[6]	翟清云, 张娟娟, 熊淑萍, 刘娟, 杨阳, 马新明. 基于不同土壤质地的小麦叶片氮含量高光谱差异及监测模型构建[J]. 中国农业科学, 2013, 46(13): 2655-2667.
[7]	李春轩, 罗毅, 包安明, 张艳, 杨传杰, 崔林林. 基于对数比转换的成分数据空间插值研究[J]. 中国农业科学, 2012, 45(4): 648-655.
[8]	. 县域尺度表层土壤质地空间变异与因素分析 [J]. 中国农业科学, 2011, 44(6): 1154-1164 .
[9]	李潮海,王小星,王群,郝四平. 不同质地土壤玉米根际生物活性研究[J]. 中国农业科学, 2007, 40(2): 412-418 .
[10]	郭天财. 土壤质地对不同面筋含量冬小麦品种籽粒淀粉合成关键酶活性的影响[J]. 中国农业科学, 2005, 38(01): 191-196 .
[11]	李潮海,李胜利,王群. 不同质地土壤对玉米根系生长动态的影响[J]. 中国农业科学, 2004, 37(09): 1334-1340 .