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Remote Sens. 2017, 9(6), 615; doi:10.3390/rs9060615

Satellite-Based Inversion and Field Validation of Autotrophic and Heterotrophic Respiration in an Alpine Meadow on the Tibetan Plateau

1
Lhasa Plateau Ecosystem Research Station, Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
2
University of Chinese Academy of Sciences, Beijing 100049, China
3
Institute for Agro-Environmental Sciences, National Agriculture and Food Research Organization, 3-1-3 Kannondai, Tsukuba, Ibaraki 305-8604, Japan
4
College of Global Change and Earth System Sciences, Beijing Normal University, Beijing 100875, China
5
College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100190, China
*
Author to whom correspondence should be addressed.
Academic Editors: Lalit Kumar, Soe Myint and Prasad S. Thenkabail
Received: 9 May 2017 / Revised: 30 May 2017 / Accepted: 13 June 2017 / Published: 15 June 2017
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Abstract

Alpine meadow ecosystem is among the highest soil carbon density and the most sensitive ecosystem to climate change. Partitioning autotrophic (Ra) and heterotrophic components (Rm) of ecosystem respiration (Re) is critical to evaluating climate change effects on ecosystem carbon cycling. Here we introduce a satellite-based method, combining MODerate resolution Imaging Spectroradiometer (MODIS) products, eddy covariance (EC) and chamber-based Re components measurements, for estimating carbon dynamics and partitioning of Re from 2009 to 2011 in a typical alpine meadow on the Tibetan Plateau. Six satellite-based gross primary production (GPP) models were employed and compared with GPP_EC, all of which appeared to well explain the temporal GPP_EC trends. However, MODIS versions 6 GPP product (GPP_MOD) and GPP estimation from vegetation photosynthesis model (GPP_VPM) provided the most reliable GPP estimation magnitudes with less than 10% of relative predictive error (RPE) compared to GPP_EC. Thus, they together with MODIS products and GPP_EC were used to estimate Re using the satellite-based method. All satellite-based Re estimations generated an alternative estimation of Re_EC with negligible root mean square errors (RMSEs, g C m−2 day−1) either in the growing season (0.12) or not (0.08). Moreover, chamber-based Re measurements showed that autotrophic contributions to Re (Ra/Re) could be effectively reflected by all these three satellite-based Re partitions. Results showed that the Ra contribution of Re were 27% (10–48%), 43% (22–59%) and 56% (33–76%) from 2009 to 2011, respectively, of which inter-annual variation is mainly attributed to soil water dynamics. This study showed annual temperature sensitivity of Ra (Q10,Ra) with an average of 5.20 was significantly higher than that of Q10,Rm (1.50), and also the inter-annual variation of Q10,Ra (4.14–7.31) was larger than Q10,Rm (1.42–1.60). Therefore, our results suggest that the response of Ra to temperature change is stronger than that of Rm in this alpine meadow. View Full-Text
Keywords: remote sensing; autotrophic respiration; eddy covariance; chamber; alpine meadow; Tibetan Plateau remote sensing; autotrophic respiration; eddy covariance; chamber; alpine meadow; Tibetan Plateau
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Niu, B.; He, Y.; Zhang, X.; Zong, N.; Fu, G.; Shi, P.; Zhang, Y.; Du, M.; Zhang, J. Satellite-Based Inversion and Field Validation of Autotrophic and Heterotrophic Respiration in an Alpine Meadow on the Tibetan Plateau. Remote Sens. 2017, 9, 615.

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