青藏高原高寒灌丛草甸和草原化草甸CO2通量动态及其限制因子

doi:10.17521/cjpe.2017.0266

植物生态学报 ›› 2018, Vol. 42 ›› Issue (1): 6-19.DOI: 10.17521/cjpe.2017.0266

所属专题：青藏高原植物生态学：生态系统生态学；生态系统碳水能量通量

青藏高原高寒灌丛草甸和草原化草甸CO₂通量动态及其限制因子

柴曦^1,³,李英年²,段呈^1,³,张涛⁴,宗宁¹,石培礼^1,^3,^*(),何永涛^1,³,张宪洲^1,³

¹ 中国科学院地理科学与资源研究所生态系统网络观测与模拟重点实验室, 北京 100101
² 中国科学西北高原生物研究所, 西宁 810001
³ 中国科学院大学资源与环境学院, 北京 100190
⁴ 沈阳农业大学农学院, 沈阳 110866

出版日期:2018-01-20 发布日期:2018-03-08
通讯作者: 石培礼 ORCID: 0000-0002-1120-0003
基金资助:
国家自然科学基金(41703079);国家自然科学基金(41271067);国家重点研发计划(2016YFC0502001);国家重点研发计划(2017YFA0604801)

CO₂ flux dynamics and its limiting factors in the alpine shrub-meadow and steppe-meadow on the Qinghai-Xizang Plateau

CHAI Xi^1,³,LI Ying-Nian²,DUAN Cheng^1,³,ZHANG Tao⁴,ZONG Ning¹,SHI Pei-Li^1,^3,^*(),HE Yong-Tao^1,³,ZHANG Xian-Zhou^1,³

¹ Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China

² Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China

³ College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China

⁴ College of Agronomy, Shenyang Agricultural University, Shenyang 110866, China

Online:2018-01-20 Published:2018-03-08
Contact: SHI Pei-Li, ORCID: 0000-0002-1120-0003
Supported by:
Supported by the National Natural Science Foundation of China(41703079);Supported by the National Natural Science Foundation of China(41271067);the National Key Research and Development Project of China(2016YFC0502001);the National Key Research and Development Project of China(2017YFA0604801)

摘要/Abstract

摘要：

高寒灌丛草甸和草甸均是青藏高原广泛分布的植被类型, 在生态系统碳通量和区域碳循环中具有极其重要的作用。然而迄今为止, 对其碳通量动态的时空变异还缺乏比较分析, 对碳通量的季节和年际变异的主导影响因子认识还不够清晰, 不利于深入理解生态系统碳通量格局及其形成机制。该研究选取位于青藏高原东部海北站高寒灌丛草甸和高原腹地当雄站高寒草原化草甸年降水量相近的5年(2004-2008年)的涡度相关CO₂通量连续观测数据, 对生态系统净初级生产力(NEP)及其组分, 包括总初级生产力(GPP)和生态系统呼吸的季节、年际动态及其影响因子进行了对比分析。结果表明: 灌丛草甸的CO₂通量无论是季节还是年际累积量均高于草原化草甸, 并且连续5年表现为“碳汇”, 平均每年NEP为70 g C·m ^-2·a ^-1, 高寒草原化草甸平均每年NEP为-5 g C·m ^-2·a ^-1, 几乎处于碳平衡状态, 但其源/汇动态极不稳定, 在2006年-88 g C·m ^-2·a ^-1的“碳源”至2008年54 g C·m ^-2·a ^-1的“碳汇”之间转换, 具有较大的变异性。这两种高寒生态系统源/汇动态的差异主要源于归一化植被指数(NDVI)的差异, 因为NDVI无论在年际水平还是季节水平都是NEP最直接的影响因子; 其次, 灌丛草甸还具有较高的碳利用效率(CUE, CUE = NEP/GPP), 而年降水量和NDVI是决定两生态系统CUE大小的关键因子。两地区除了CO₂通量大小的差异外, 其环境影响因子也有所不同。采用结构方程模型进行的通径分析表明, 灌丛草甸生长季节CO₂通量的主要限制因子是温度, NEP和GPP主要受气温控制, 随着气温升高而增加; 而草原化草甸的CO₂通量多以季节性干旱导致的水分限制为主, 其次才是气温的影响, 受二者的共同限制。此外, 两生态系统生长季节生态系统呼吸主要受GPP和5 cm土壤温度的直接影响, 其中GPP起主导作用, 非生长季节生态系统呼吸主要受5 cm土壤温度影响。该研究还表明, 水热因子的协调度是决定青藏高原高寒草地GPP和NEP的关键要素。

关键词: 青藏高原, 高寒草地生态系统, CO₂通量, 温度, 土壤含水量, 涡度相关

Abstract:

Aims Alpine shrub-meadows and steppe-meadows are the two dominant vegetation types on the Qinghai-Xizang Plateau, and plays an important role in regional carbon cycling. However, little is known about the temporal-spatial patterns and drivers of CO₂ fluxes in these two ecosystem types.

Methods Based on five years of consecutive eddy covariance measurements (2004-2008) in an eastern alpine shrub-meadow at Haibei and a hinterland alpine steppe-meadow at Damxung, we investigated the seasonal and annual variation of net ecosystem productivity (NEP) and its components, i.e. gross primary productivity (GPP) and ecosystem respiration (R_e).

Important findings The CO₂ fluxes (NEP, GPP and R_e) were larger in the shrub-meadow than in the steppe-meadow during the study period. The shrub-meadow functioned as a carbon sink through the five years, with the mean annual NEP of 70 g C·m ^-2·a ^-1. However, the steppe-meadow acted as a carbon neutral, with mean annual NEP of -5 g C·m ^-2·a ^-1. The CO₂ fluxes of steppe-meadow exhibited large variability due to the inter-annual and seasonal variations in precipitation, ranging from a carbon sink (54 g C·m ^-2·a ^-1) in 2008 to a carbon source (-88 g C·m ^-2·a ^-1) in 2006. The differences in carbon budget between the two alpine ecosystems were firstly attributed to the discrepancy of normalized difference vegetation index (NDVI) because NDVI was the direct factor regulating the seasonal and inter-annual NEP. Secondly, the shrub-meadow had higher carbon use efficiency (CUE), which was substantially determined by annual precipitation (PPT) and NDVI. Our results also indicated that the environmental drivers of CO₂ fluxes were also different between these two alpine ecosystems. The structure equation model analyses showed that air temperature (T_a) determined the seasonal variations of CO₂ fluxes in the shrub-meadow, with NEP and GPP being positively correlated with T_a. By contrast, the seasonal CO₂ fluxes in the steppe-meadow were primarily co-regulated by soil water content (SWC) and T_a, and increased with the increase of SWC and T_a. In addition, the changes of R_e during the growing season in two ecosystems were directly affected by GPP and soil temperature at 5 cm depth (T_s), while R_e during non-growing season were determined by T_s. These results demonstrate that the synergy of soil water and temperature played crucial roles in determining NEP and GPP of the two alpine meadows on the Qinghai-Xizang Plateau.

Key words: Qinghai-Xizang Plateau, alpine meadow ecosystems, CO₂ fluxes, temperature, soil water content, eddy covariance

柴曦, 李英年, 段呈, 张涛, 宗宁, 石培礼, 何永涛, 张宪洲. 青藏高原高寒灌丛草甸和草原化草甸CO₂通量动态及其限制因子. 植物生态学报, 2018, 42(1): 6-19. DOI: 10.17521/cjpe.2017.0266

CHAI Xi, LI Ying-Nian, DUAN Cheng, ZHANG Tao, ZONG Ning, SHI Pei-Li, HE Yong-Tao, ZHANG Xian-Zhou. CO₂ flux dynamics and its limiting factors in the alpine shrub-meadow and steppe-meadow on the Qinghai-Xizang Plateau. Chinese Journal of Plant Ecology, 2018, 42(1): 6-19. DOI: 10.17521/cjpe.2017.0266

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链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2017.0266

https://www.plant-ecology.com/CN/Y2018/V42/I1/6

图/表 6

图1 2004-2008年高寒灌丛草甸(A)和草原化草甸(B)能量闭合分析。图中数据分别是每日潜热通量(LE)与感热通量(H)的和以及净辐射(Rn)与土壤热通量(G)的差。黑色线为线性拟合线。

Fig. 1 Energy balance during 2004-2008 at the alpine shrub-meadow (A) and steppe-meadow (B). Data are the daily sums of latent (LE) and sensible (H) heat flux and net radiation (Rn) minus soil heat storage (G), respectively. Black lines are linear fitting lines.

图2 高寒灌丛草甸和草原化草甸生长季节(GS)和年际(Ann) CO2通量(包括生态系统净初级生产力(NEP)、总初级生产力(GPP)和生态系统呼吸(Re))的总值、环境因子(平均气温(Ta)和降水总量(PPT))以及年际碳利用效率(CUE)、Re/GPP、归一化植被指数(NDVI)以及各因子年际变异系数(CV)对比。

Fig. 2 Comparison of annual (Ann) and growing season (GS) accumulative values of CO2 fluxes (including net ecosystem productivity (NEP ), gross primary productivity (GPP) and ecosystem respiration (Re)) and environmental factors (including mean air temperature (Ta) and total precipitation (PPT )) as well as annual carbon use efficiency (CUE), Re/GPP, normalized difference vegetation index (NDVI) and coefficients of variation (CV) of these factors in the alpine shrub-meadow and steppe-meadow.

图3 2004-2008年高寒灌丛草甸和草原化草甸月平均光合有效辐射(A, PAR, μmol·m-2·s-1)、月平均空气温度(B, Ta, ℃)、月平均 5 cm土壤温度(C, Ts, ℃)、月平均饱和水汽压差(D, VPD, kPa)、月平均5 cm土壤含水量(E, SWC, m3·m-3)、月降水量(E, PPT, mm)和归一化植被指数(F, NDVI)16天平均值的季节动态。黑色点线和黑色柱形图代表灌丛草甸, 灰色点线和灰色柱形图代表草原化草甸。

Fig. 3 Seasonal dynamic of monthly average photosynthetically active radiation (A, PAR, μmol·m-2·s-1), monthly average air temperature (B, Ta, ℃), monthly average soil temperature at a depth of 5 cm (C, Ts, ℃), monthly average vapor press deficit (D, VPD, kPa), monthly average soil water content at a depth of 5 cm (E, SWC, m3·m-3), and monthly total precipitation (E, PPT, mm), 16-day mean normalized difference vegetation index (F, NDVI) in the alpine shrub-meadow and steppe-meadow form 2004 to 2008. The black squares and histograms represent the shrub-meadow and the grey circles and histograms denote the steppe-meadow.

图4 2004-2008年高寒灌丛草甸和草原化草甸生态系统净初级生产力(NEP, A), 总初级生产力(GPP, B)和生态系统呼吸(Re, C)日值(g C·m-2·d-1)的季节变化动态。灰色点代表草原化草甸, 黑色点代表灌丛草甸。

Fig. 4 Seasonal patterns of daily (g C·m-2·d-1) values of net ecosystem productivity (NEP, A), gross primary productivity (GPP, B) and ecosystem respiration (Re, C) for the alpine shrub-meadow and the steppe-meadow from 2004 to 2008. The black solid circles represent shrub-meadow and the grey hollow circles denote steppe-meadow.

图5 高寒灌丛草甸和草原化草甸2004-2008年16天平均生物和环境影响因子(气温, Ta, ℃; 5 cm土壤温度, Ts, ℃; 5 cm土壤含水量, SWC, m3·m-3; 降水量PPT, mm; 光合有效辐射, PAR, μmol·m-2·s-1; 归一化植被指数, NDVI)对CO2通量(净初级生产力, NEP, g C·m-2·d-1; 总初级生产力, GPP, g C·m-2·d-1; 生态系统呼吸, Re, g C·m-2·d-1)的结构方程模型图。A, C, E, 海北高寒灌丛草甸。B, D, F, 当雄高寒草原化草甸。A, B, C, D, 生长季节。E, F, 非生长季。黑色箭头是正相关, 灰色箭头是负相关, 实线箭头表示p ≤ 0.05, 虚线箭头表示p > 0.05, 箭头上的数字代表通径系数, 箭头的宽窄代表通径系数的大小。

Fig. 5 Path diagrams illustrating the effects of 16-day mean biotic and abiotic factors (air temperature, Ta, ℃; soil temperature at the depth of 5 cm, Ts, ℃; soil water content at the depth of 5 cm, SWC, m3·m-3; precipitation, PPT, mm; photosynthetically active radiation, PAR, μmol·m-2·s-1; normalized difference vegetation index, NDVI) on 16-day mean CO2 fluxes (net ecosystem productivity, NEP, g C·m-2·d-1, gross primary productivity, GPP, g C·m-2·d-1 and ecosystem respiration, Re, g C·m-2·d-1) during the growing season (A-D) and non-growing season (E, F) from 2004-2008 in the alpine shrub-meadow (A, C, E) and steppe-meadow (B, D, F). The grey solid arrows represent significantly negative correlation and the black solid arrows denote significantly positive correlation (p ≤ 0.05). The dashed arrows represent non-significantly correlation (p > 0.05). Data on the arrows are the standardized SEM coefficients. The thickness of the arrows reflects the magnitude of the standardized SEM coefficient.

图6 2004-2008年两生态系统年累积净初级生产力NEP (g C·m-2·a-1)与年碳利用效率CUE (A)、年归一化植被指数NDVI (B)的相关关系。△海北高寒灌丛草甸。〇当雄高寒草原化草甸。Adj.R2, 调整过的决定系数。

Fig. 6 The correlative relationships of annual accumulative net ecosystem productivity (NEP, g C·m-2·a-1) with annual carbon use efficiency (CUE, A) and normalized difference vegetation index (NDVI, B) from 2004 to 2008. Hollow triangles represent the alpine shrub- meadow in Haibei (△) and hollow circles denote the alpine steppe-meadow in Damxung (〇). Adj.R2, adjusted coefficient of determination.

参考文献 59

[1]	Adams JM, Faure H, Fauredenard L, Mcglade JM, Woodward FI ( 1990). Increases in terrestrial carbon storage from the Last Glacial Maximum to the present. Nature, 348, 711-714. DOI URL
[2]	Adrianv R, Michaell G ( 2009). Why is marsh productivity so high? New insights from eddy covariance and biomass measurements in a Typha marsh. Agricultural and Forest Meteorology, 149, 159-168. DOI URL
[3]	Cai JB, Liu J, Xu D, Shi BC ( 2008). Sensitivity analysis of winter wheat shortage diagnostic index based on the principle of path analysis. Journal of Hydraulic Engineering, 39(1), 83-90. DOI URL
	[ 蔡甲冰, 刘钰, 许迪, 史宝成 ( 2008). 基于通径分析原理的冬小麦缺水诊断指标敏感性分析. 水利学报, 39(1), 83-90. DOI URL
[4]	Cao XS ( 2011). A SEM-based study on urban community resident’s travel behavior in Guangzhou. Acta Geographica Sinica, 66, 167-177.
	[ 曹小曙 ( 2011). 基于结构方程模型的广州城市社区居民出行行为. 地理学报, 66, 167-177.]
[5]	Chai X, Shi PL, Zong N, Niu B, He YT, Zhang XZ ( 2017). Biophysical regulation of carbon flux in different rainfall regime in a northern Tibetan alpine meadow. Journal of Resources and Ecology, 8, 30-41. DOI URL
[6]	Deyn GBD, Cornelissen JHC, Bardgett RD ( 2008). Plant functional traits and soil carbon sequestration in contrasting biomes. Ecology Letters, 11, 516-531. DOI URL PMID
[7]	Du Q, Liu H ( 2013). Seven years of carbon dioxide exchange over a degraded grassland and a cropland with maize ecosystems in a semiarid area of China. Agriculture, Ecosystems and Environment, 173, 1-12. DOI URL
[8]	Flanagan LB ( 2002). Seasonal and interannual variation in carbon dioxide exchange and carbon balance in a northern temperate grassland. Global Change Biology, 8, 599-615. DOI URL
[9]	Fu YL, Yu GR, Sun XM, Li YN, Wen XF, Zhang LM, Li ZQ, Zhao L, Hao YB ( 2006). Depression of net ecosystem CO2 exchange in semi-arid Leymus chinensis steppe and alpine shrub. Agricultural and Forest Meteorology, 137, 234-244.
[10]	Gao YX ( 1980). Principles and basis of soil classification in Tibet. Tibet Journal of Agriculture Science, 1, 18-30.
	[ 高以信 ( 1980). 西藏土壤分类的原则和依据. 西藏农业科技, 1, 18-30.]
[11]	Ge ZM, Kellom?ki S, Zhou X, Wang KY, Peltola H ( 2011). Evaluation of carbon exchange in a boreal coniferous stand over a 10-year period: An integrated analysis based on ecosystem model simulations and eddy covariance measurements. Agricultural and Forest Meteorology, 151, 191-203. DOI URL
[12]	Gilmanov TG, Soussana JF, Aires L, Allard V, Ammann C, Balzarolo M, Barcza Z Bernhofer C, Campbell CL, Cernusca A ( 2007). Partitioning European grassland net ecosystem CO2 exchange into gross primary productivity and ecosystem respiration using light response function analysis. Agriculture, Ecosystems and Environment, 121, 93-120. DOI URL
[13]	Gitta L, Markus R, Dario P, Andrewd R, Almut A, Alan B, Paul S, Georg W ( 2010). Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: Critical issues and global evaluation. Global Change Biology, 16, 187-208. DOI URL
[14]	Gu S ( 2003). Short-term variation of CO2 flux in relation to environmental controls in an alpine meadow on the Qinghai-Tibetan Plateau. Journal of Geophysical Research, 108(D21), 4670. DOI: 10.1029/2003JD003584. DOI URL
[15]	Guo Q, Li S, Hu Z, Zhao W, Wang M ( 2015). Response of gross primary productivity to water availability at different temporal scales in a typical steppe in Inner Mongolia temperate steppe. Journal of Desert Research, 35, 616-623. DOI URL
[16]	Hoff JHV ( 1898). über die zunehmende bedeutung der anorganischen chemie. Vortrag, gehalten auf der 70. Versammlung der gesellschaft deutscher naturforscher und rzte zu düsseldorf. Zeitschrift Für Anorganische Chemie, 18, 1-13. DOI URL
[17]	Jensen R, Herbst M, Friborg T ( 2017). Direct and indirect controls of the interannual variability in atmospheric CO2 exchange of three contrasting ecosystems in Denmark. Agricultural and Forest Meteorology, 233, 12-31. DOI URL
[18]	Jia X, Zha TS, Wu B, Zhang YQ, Gong JN, Qin SG, Chen GP, Qian D, Kellom?ki S, Peltola H ( 2014). Biophysical controls on net ecosystem CO2 exchange over a semiarid shrubland in northwest China. Biogeosciences, 11, 4679-4693. DOI URL
[19]	Jongen M, Unger S, Santos PJ ( 2014). Effects of precipitation variability on carbon and water fluxes in the understorey of a nitrogen-limited montado ecosystem. Oecologia, 176, 1199-1212. DOI URL PMID
[20]	Kato T ( 2004). Seasonal patterns of gross primary production and ecosystem respiration in an alpine meadow ecosystem on the Qinghai-Tibetan Plateau. Journal of Geophysical Research, 109. DOI URL
[21]	Kato T, Hirota M, Tang YH, Cui XY, Li YN, Zhao XQ, Oikawa T ( 2005). Strong temperature dependence and no moss photosynthesis in winter CO2 flux for a Kobresia meadow on the Qinghai-Tibetan Plateau. Soil Biology & Biochemistry, 37, 1966-1969. DOI URL
[22]	Kato T, Tang Y, Gu S, Cui XY, Hirota M, Du MY, Li YN, Zhao XQ, Oikawa T ( 2004). Carbon dioxide exchange between the atmosphere and an alpine meadow ecosystem on the Qinghai-Tibetan Plateau, China. Agricultural and Forest Meteorology, 124, 121-134. DOI URL
[23]	Knapp AK, Fay PA, Blair JM, Collins SL, Smith MD, Carlisle JD, Harper CW, Danner BT, Lett MS, McCarron JK ( 2002). Rainfall variability, carbon cycling, and plant species diversity in a mesic grassland. Science, 298, 2202-2205. DOI URL PMID
[24]	Lasslop G, Reichstein M, Papale D, Richardson AD, Arneth A, Barr A, Stoy P, Wohlfahrt G ( 2010). Separation of net ecosystem exchange into assimilation and respiration using a light response curve approach: Critical issues and global evaluation. Global Change Biology, 16, 187-208. DOI URL
[25]	Li D ( 2005). A primary study on CO2 emission from Alpine Potentilla fruticosa scrub meadow ecosystem. Acta Agrestia Sinica, 13(2), 4-9. DOI URL
	[ 李东 ( 2005). 海北高寒灌丛草甸生态系统CO2释放的初步研究. 草业科学, 13(2), 4-9.] DOI URL
[26]	Li HQ, Zhang FW, Li YN, Wang JB, Zhang LM, Zhao L, Cao GM, Zhao XQ, Du MY ( 2016). Seasonal and inter-annual variations in CO2 fluxes over 10 years in an alpine shrubland on the Qinghai-Tibetan Plateau, China. Agricultural and Forest Meteorology, 228, 95-103. DOI URL
[27]	Li YN ( 2006). Seasonal variation of net ecosystem CO2 exchange and its environmental controlling mechanisms of Potentilla fruticosa meadows in the Qinghai-Xizang Plateau. Science in China Series. D Earth Sciences, 36(A01), 163-173.
	[ 李英年 ( 2006). 青藏高原金露梅灌丛草甸净生态系统CO2交换量的季节变异及其环境控制机制. 中国科学D辑地球科学, 36(A01), 163-173.]
[28]	Liu R, Li Y, Wang QX, Xu H, Zheng XJ ( 2011). Seasonal and annual variations of carbon dioxide fluxes in desert ecosystem. Journal of Desert Research, 31(1), 108-114.
	[ 刘冉, 李彦, 王勤学, 许皓, 郑新军 ( 2011). 盐生荒漠生态系统二氧化碳通量的年内、年际变异特征. 中国沙漠, 31(1), 108-114.]
[29]	Liu R, Pan LP, Jenerette GD, Wang QX, Cieraad E, Li Y ( 2012). High efficiency in water use and carbon gain in a wet year for a desert halophyte community. Agricultural and Forest Meteorology, 162, 127-135. DOI URL
[30]	Lu WZ, Xiao JG, Liu F, Zhang Y, Liu F, Lin GH ( 2017). Contrasting ecosystem CO2 fluxes of inland and coastal wetlands: A meta-analysis of eddy covariance data. Global Change Biology, 23, 1180-1198. DOI URL PMID
[31]	Lu YZ ( 1982). The draft of the soil classification in the Xizang. Chinese Journal of Soil Science, ( 5), 1-4.
	[ 卢耀曾 ( 1982). 《西藏土壤分类》草案. 土壤通报, ( 5), 1-4.]
[32]	Ma WL, Shi PL, Li WH, He YT, Zhang XZ ( 2010). Changes in individual plant traits and biomass allocation in alpine meadow with elevation variation on the Qinghai-Tibetan Plateau. Science China Life Science, 53, 1142-1151. DOI URL
[33]	Meyers TP ( 2001). A comparison of summertime water and CO2 fluxes over rangeland for well-watered and drought conditions. Agricultural and Forest Meteorology, 106, 205-214. DOI URL
[34]	Nagler PL, Cleverly J, Glenn E, Lampkin D, Huete A, Wan ZG, Shen ZC, Chai SY ( 2005). Predicting riparian evapotranspiration from MODIS vegetation indices and meteorological data. Remote Sensing of Environment, 94, 17-30. DOI URL
[35]	Peichl M, Leahy P, Kiely G ( 2010). Six-year stable annual uptake of carbon dioxide in intensively managed humid temperate grassland. Ecosystems, 14, 112-126. DOI URL
[36]	Piao SL, Tan K, Nan HJ, Ciais P, Fang JY, Wang T, Vuichard N, Zhu B ( 2012). Impacts of climate and CO2 changes on the vegetation growth and carbon balance of Qinghai- Xizang grasslands over the past five decades. Global and Planetary Change, 98- 99, 73-80. DOI URL
[37]	Polley HW, Emmerich W, Bradford JA, Sims PL, Johnson DA, Saliendra NZ, Svejcar T, Angell R, Frank AB, Phillips RL ( 2010). Physiological and environmental regulation of interannual variability in CO2 exchange on rangelands in the western United States. Global Change Biology, 16, 990-1002. DOI URL
[38]	Polley HW, Mielnick PC, Dugas WA, Johnson HB, Sanabria J ( 2006). Increasing CO2 from subambient to elevated concentrations increases grassland respiration per unit of net carbon fixation. Global Change Biology, 12, 1390-1399. DOI URL
[39]	Ruimy A, Jarvis PG, Baldocchi DD, Saugier B ( 1995). CO2 fluxes over plant canopies and solar radiation: A review. Advances in Ecological Research, 26, 1-68. DOI URL
[40]	Ryan EM, Ogle K, Zelikova TJ, LeCain DR, Williams DG, Morgan JA, Pendall E ( 2015). Antecedent moisture and temperature conditions modulate the response of ecosystem respiration to elevated CO2 and warming. Global Change Biology, 21, 2588-2602. DOI URL PMID
[41]	Saito M, Kato T, Tang Y ( 2009). Temperature controls ecosystem CO2 exchange of an alpine meadow on the northeastern Tibetan Plateau. Global Change Biology, 15, 221-228. DOI URL
[42]	Shi PL, Sun XM, Xu LL, Zhang XZ, He YT, Zhang DQ, Yu GR ( 2006). Net ecosystem CO2 exchange and controlling factors in a steppe— Kobresia meadow on the Tibetan Plateau. Science in China Series D: Earth Sciences, 49, 207-218.
[43]	Street L, Shaver G, Williams M, Wijk MTV ( 2007). What is the relationship between changes in canopy leaf area and changes in photosynthetic CO2 flux in arctic ecosystems? Journal of Ecology, 95, 139-150. DOI URL
[44]	Suyker AE ( 2003). Interannual variability in NEE of a native tallgrass prairie. Global Change Biology, 9, 255-265.
[45]	Wan S, Xia J, Liu W, Niu S ( 2009). Photosynthetic overcompensation under nocturnal warming enhances grassland carbon sequestration. Ecology, 90, 2700-2710. DOI URL PMID
[46]	Wang YF, Cui XY, Hao YB, Mei XR, Yu GR, Huang XZ, Kang XM, Zhou XQ ( 2011). The fluxes of CO2 from grazed and fenced temperate steppe during two drought years on the Inner Mongolia Plateau, China. Science of The Total Environment, 410- 411, 182-190. DOI URL PMID
[47]	Wang YS , Chu, CJ ( 2011). A brief introduction of structural equation model and its application in ecology. Chinese Journal of Plant Ecology, 35, 337-344. DOI URL
	[ 王酉石, 储诚进 ( 2011). 结构方程模型及其在生态学中的应用. 植物生态学报, 35, 337-344.] DOI URL
[48]	Wolf S, Eugster W, Potvin C, Potvin C, Buchmann N ( 2011). Strong seasonal variations in net ecosystem CO2 exchange of a tropical pasture and afforestation in Panama. Agricultural and Forest Meteorology, 151, 1139-1151. DOI URL
[49]	Xie ZL ( 1996). Analysis of the problem in path. System Sciences and Comprehensive Studies in Agriculture, 12(3), 161-167.
	[ 谢仲伦 ( 1996). 相关性通径分析问题剖析. 农业系统科学与综合研究, 12(3), 161-167.]
[50]	Xu L, Baldocchi DD ( 2004). Seasonal variation in carbon dioxide exchange over a Mediterranean annual grassland in California. Agricultural and Forest Meteorology, 123, 79-96. DOI URL
[51]	Xu X, Shi Z, Li DJ, Zhou XH, Sherry RA, Luo YQ ( 2015). Plant community structure regulates responses of prairie soil respiration to decadal experimental warming. Global Change Biology, 21, 3846-3853. DOI URL PMID
[52]	Yang FL, Zhou GS, Hunt JE, Zhang F ( 2011). Biophysical regulation of net ecosystem carbon dioxide exchange over a temperate desert steppe in Inner Mongolia, China. Agriculture, Ecosystems and Environment, 142, 318-328. DOI URL
[53]	Yashiro Y ( 2010). The role of shrub ( Potentilla fruticosa) on ecosystem CO2 fluxes in an alpine shrub meadow. Journal of Plant Ecology, 3, 89-97.
[54]	Yu GR, Zhu XJ, Fu YL, He HL, Wang QF, Wen XF, Li XR, Zhang LM, Zhang L, Su W ( 2013). Spatial patterns and climate drivers of carbon fluxes in terrestrial ecosystems of China. Global Change Biology, 19, 798-810. DOI URL PMID
[55]	Yuan W, Luo Y, Richardson AD, Oren R, Luyssaert S, Janssens IA, Ceulemans R, Zhou XH, Gruenwald T, Aubinet M, Berhofer C, Baldocchi DD, Chen J, Dunn AL, Deforest JL, Dragoni D, Goldstein AH, Moors E, Munger JW, Monson RK, Suyker AE, Star G, Scott RL, Tenhunen J, Verma SB, Vesala T, Wofsy SC ( 2009). Latitudinal patterns of magnitude and interannual variability in net ecosystem exchange regulated by biological and environmental variables. Global Change Biology, 15, 2905-2920. DOI URL
[56]	Zhao GS, Shi PL, Zong N, He YT, Zhang XZ, He HL, Zhang J ( 2017). Declining precipitation enhances the effect of warming on phenological variation in a semiarid Tibetan meadow steppe. Journal of Resources and Ecology, 8, 50-56. DOI URL
[57]	Zhao L ( 2006). Relations between carbon dioxide fluxes and environmental factors of Kobresia humilis meadows and Potentilla fruticosa meadows. Acta Botanica Boreali- Occidentalia Sinica, 26, 133-142. DOI URL
	[ 赵亮 ( 2006). 青藏高原矮嵩草草甸和金露梅灌丛草甸CO2通量变化与环境因子的关系. 西北植物学报, 26, 133-142.] DOI URL
[58]	Zhao L, Li YN, Gu S, Zhao XQ, Xu SX, Yu GR ( 2005). Carbon dioxide exchange between the atmosphere and an alpine shrubland meadow during the growing season on the Qinghai-Tibetan Plateau. Journal of Integrative Plant Biology, 47, 271-282. DOI URL
[59]	Zhou X, Wan S, Luo Y ( 2007). Source components and interannual variability of soil CO2 efflux under experimental warming and clipping in a grassland ecosystem. Global Change Biology, 13, 761-775. DOI URL

青藏高原高寒灌丛草甸和草原化草甸CO₂通量动态及其限制因子

CO₂ flux dynamics and its limiting factors in the alpine shrub-meadow and steppe-meadow on the Qinghai-Xizang Plateau

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