Arid
DOI10.1186/s13021-020-00141-8
Remotely monitoring ecosystem respiration from various grasslands along a large-scale east-west transect across northern China
Tang, Xuguang1,2; Zhou, Yanlian3; Li, Hengpeng4; Yao, Li1; Ding, Zhi1; Ma, Mingguo1,2; Yu, Pujia1,2
通讯作者Yu, Pujia
来源期刊CARBON BALANCE AND MANAGEMENT
ISSN1750-0680
出版年2020
卷号15期号:1
英文摘要Background Grassland ecosystems play an important role in the terrestrial carbon cycles through carbon emission by ecosystem respiration (R-e) and carbon uptake by plant photosynthesis (GPP). Surprisingly, given R-e occupies a large component of annual carbon balance, rather less attention has been paid to developing the estimates of R-e compared to GPP. Results Based on 11 flux sites over the diverse grassland ecosystems in northern China, this study examined the amounts of carbon released by R-e as well as the dominant environmental controls across temperate meadow steppe, typical steppe, desert steppe and alpine meadow, respectively. Multi-year mean R-e revealed relatively less CO2 emitted by the desert steppe in comparison with other grassland ecosystems. Meanwhile, C emissions of all grasslands were mainly controlled by the growing period. Correlation analysis revealed that apart from air and soil temperature, soil water content exerted a strong effect on the variability in R-e, which implied the great potential to derive R-e using relevant remote sensing data. Then, these field-measured R-e data were up-scaled to large areas using time-series MODIS information and remote sensing-based piecewise regression models. These semi-empirical models appeared to work well with a small margin of error (R-2 and RMSE ranged from 0.45 to 0.88 and from 0.21 to 0.69 g C m(-2) d(-1), respectively). Conclusions Generally, the piecewise models from the growth period and dormant season performed better than model developed directly from the entire year. Moreover, the biases between annual mean R-e observations and the remotely-derived products were usually within 20%. Finally, the regional R-e emissions across northern China's grasslands was approximately 100.66 Tg C in 2010, about 1/3 of carbon fixed from the MODIS GPP product. Specially, the desert steppe exhibited the highest ratio, followed by the temperate meadow steppe, typical steppe and alpine meadow. Therefore, this work provides a novel framework to accurately predict the spatio-temporal patterns of R-e over large areas, which can greatly reduce the uncertainties in global carbon estimates and climate projections.
英文关键词Ecosystem respiration Grassland MODIS Piecewise regression
类型Article
语种英语
国家Peoples R China
开放获取类型Green Submitted, Green Published, gold
收录类别SCI-E
WOS记录号WOS:000529949800001
WOS关键词WATER-USE EFFICIENCY ; SOIL HETEROTROPHIC RESPIRATION ; GROSS PRIMARY PRODUCTION ; EDDY-COVARIANCE ; CARBON SEQUESTRATION ; CO2 EXCHANGE ; AUTOTROPHIC RESPIRATION ; SEMIARID ECOSYSTEMS ; VEGETATION INDEX ; ENERGY-BALANCE
WOS类目Environmental Sciences
WOS研究方向Environmental Sciences & Ecology
来源机构南京大学
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/318981
作者单位1.Southwest Univ, State Cultivat Base Ecoagr Southwest Mountainous, Chongqing 400715, Peoples R China;
2.Southwest Univ, Minist Educ, Chongqing Jinfo Mt Field Sci Observat & Res Stn K, Chongqing 400715, Peoples R China;
3.Nanjing Univ, Int Inst Earth Syst Sci, Nanjing 210023, Peoples R China;
4.Chinese Acad Sci, Nanjing Inst Geog & Limnol, Nanjing 210008, Peoples R China
推荐引用方式
GB/T 7714
Tang, Xuguang,Zhou, Yanlian,Li, Hengpeng,et al. Remotely monitoring ecosystem respiration from various grasslands along a large-scale east-west transect across northern China[J]. 南京大学,2020,15(1).
APA Tang, Xuguang.,Zhou, Yanlian.,Li, Hengpeng.,Yao, Li.,Ding, Zhi.,...&Yu, Pujia.(2020).Remotely monitoring ecosystem respiration from various grasslands along a large-scale east-west transect across northern China.CARBON BALANCE AND MANAGEMENT,15(1).
MLA Tang, Xuguang,et al."Remotely monitoring ecosystem respiration from various grasslands along a large-scale east-west transect across northern China".CARBON BALANCE AND MANAGEMENT 15.1(2020).
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