Resolving systematic errors in estimates of net ecosystem exchange of CO2 and ecosystem respiration in a tropical forest biome

被引:37
|
作者
Hutyra, Lucy R. [1 ]
Munger, J. William [1 ,2 ]
Hammond-Pyle, Elizabeth [1 ,2 ]
Saleska, Scott R. [3 ]
Restrepo-Coupe, Natalia [3 ]
Daube, Bruce C. [1 ,2 ]
de Camargo, Plinio B. [4 ]
Wofsy, Steven C. [1 ,2 ]
机构
[1] Harvard Univ, Dept Earth & Planetary Sci, Cambridge, MA 02138 USA
[2] Harvard Univ, Sch Engn & Appl Sci, Cambridge, MA 02138 USA
[3] Univ Arizona, Tucson, AZ USA
[4] CENA USP, Lab Ecol lsotop, BR-13400970 Piracicaba, SP, Brazil
基金
美国国家航空航天局;
关键词
carbon; Eddy correlation; LBA; respiration; Amazon; tropical rainforest;
D O I
10.1016/j.agrformet.2008.03.007
中图分类号
S3 [农学(农艺学)];
学科分类号
0901 ;
摘要
The controls on uptake and release Of CO2 by tropical rainforests, and the responses to a changing climate, are major uncertainties in global climate change models. Eddy-covariance measurements potentially provide detailed data on CO2 exchange and responses to the environment in these forests, but accurate estimates of the net ecosystem exchange of CO2 (NEE) and ecosystem respiration (R-eco) require careful analysis of data representativity, treatment of data gaps, and correction for systematic errors. This study uses the comprehensive data from our study site in an old-growth tropical rainforest near Santarem, Brazil, to examine the biases in NEE and R-eco potentially associated with the two most important sources of systematic error in Eddy-covariance data: lost nighttime flux and missing canopy storage measurements. We present multiple estimates for the net carbon balance and Reco at our site, including the conventional "u* filter", a detailed bottom-up budget for respiration, estimates by similarity with Rn-122, and an independent estimate of respiration by extrapolation of daytime Eddy flux data to zero light. Eddy-covariance measurements between 2002 and 2006 showed a mean net ecosystem carbon loss of 0.25 +/- 0.04 mu mol m(-2) s(-1), with a mean respiration rate of 8.60 +/- 10.11 mu mol m(-2) s(-1) at our site. We found that lost nocturnal flux can potentially introduce significant bias into these results. We develop robust approaches to correct for these biases, showing that, where appropriate, a site-specific u* threshold can be used to avoid systematic bias in estimates of carbon exchange. Because of the presence of gaps in the data and the day-night asymmetry between storage and turbulence, inclusion of canopy storage is essential to accurate assessments of NEE. We found that short-terrn measurements of storage may be adequate to accurately model storage for use in obtaining ecosystem carbon balance, at sites where storage is not routinely measured. The analytical framework utilized in this study can be applied to other Eddy-covariance sites to help correct and validate measurements of the carbon cycle and its components. (C) 2008 Elsevier B.V. All rights reserved.
引用
收藏
页码:1266 / 1279
页数:14
相关论文
共 50 条
  • [1] Seasonal variation in net ecosystem CO2 exchange of a Brazilian seasonally dry tropical forest
    Keila R. Mendes
    Suany Campos
    Lindenberg L. da Silva
    Pedro R. Mutti
    Rosaria R. Ferreira
    Salomão S. Medeiros
    Aldrin M. Perez-Marin
    Thiago V. Marques
    Tarsila M. Ramos
    Mariana M. de Lima Vieira
    Cristiano P. Oliveira
    Weber A. Gonçalves
    Gabriel B. Costa
    Antonio C. D. Antonino
    Rômulo S. C. Menezes
    Bergson G. Bezerra
    Cláudio M. Santos e Silva
    Scientific Reports, 10
  • [2] Seasonal variations of net ecosystem (CO2) exchange in the Indian tropical mangrove forest of Pichavaram
    Gnanamoorthy, Palingamoorthy
    Selvam, V
    Burman, Pramit Kumar Deb
    Chakraborty, S.
    Karipot, A.
    Nagarajan, R.
    Ramasubramanian, R.
    Song, Qinghai
    Zhang, Yiping
    Grace, John
    ESTUARINE COASTAL AND SHELF SCIENCE, 2020, 243
  • [3] Seasonal variation in net ecosystem CO2 exchange of a Brazilian seasonally dry tropical forest
    Mendes, Keila R.
    Campos, Suany
    da Silva, Lindenberg L.
    Mutti, Pedro R.
    Ferreira, Rosaria R.
    Medeiros, Salomao S.
    Perez-Marin, Aldrin M.
    Marques, Thiago V.
    Ramos, Tarsila M.
    Vieira, Mariana M. de Lima
    Oliveira, Cristiano P.
    Goncalves, Weber A.
    Costa, Gabriel B.
    Antonino, Antonio C. D.
    Menezes, Romulo S. C.
    Bezerra, Bergson G.
    Santos e Silva, Claudio M.
    SCIENTIFIC REPORTS, 2020, 10 (01)
  • [4] Net ecosystem CO2 exchange and carbon cycling in tropical lowland flooded rice ecosystem
    P. Bhattacharyya
    S. Neogi
    K. S. Roy
    P. K. Dash
    R. Tripathi
    K. S. Rao
    Nutrient Cycling in Agroecosystems, 2013, 95 : 133 - 144
  • [5] Net ecosystem CO2 exchange and carbon cycling in tropical lowland flooded rice ecosystem
    Bhattacharyya, P.
    Neogi, S.
    Roy, K. S.
    Dash, P. K.
    Tripathi, R.
    Rao, K. S.
    NUTRIENT CYCLING IN AGROECOSYSTEMS, 2013, 95 (01) : 133 - 144
  • [6] Seasonal variations in the net ecosystem CO2 exchange of a mature Amazonian transitional tropical forest (cerradao)
    Vourlitis, GL
    Priante, N
    Hayashi, MMS
    Nogueira, JD
    Caseiro, FT
    Campelo, JH
    FUNCTIONAL ECOLOGY, 2001, 15 (03) : 388 - 395
  • [7] Dynamics of net ecosystem CO2 exchange and heterotrophic soil respiration following clearfelling in a drained peatland forest
    Makiranta, Paivi
    Riutta, Terhi
    Penttilae, Timo
    Minkkinen, Kari
    AGRICULTURAL AND FOREST METEOROLOGY, 2010, 150 (12) : 1585 - 1596
  • [8] Net ecosystem CO2 exchange over a larch forest in Hokkaido, Japan
    Wang, HM
    Saigusa, N
    Yamamoto, S
    Kondo, H
    Hirano, T
    Toriyama, A
    Fujinuma, Y
    ATMOSPHERIC ENVIRONMENT, 2004, 38 (40) : 7021 - 7032
  • [9] Net ecosystem CO2 exchange over a larch forest in Hokkaido, Japan
    Natl. Inst. Adv. Indust. Sci. T., 16-1 Onogawa, Tsukuba Science City 305-8569, Japan
    不详
    不详
    1600, 7021-7032 (December 2004):
  • [10] Multiple sources of predictive uncertainty in modeled estimates of net ecosystem CO2 exchange
    Mitchell, Stephen
    Beven, Keith
    Freer, Jim
    ECOLOGICAL MODELLING, 2009, 220 (23) : 3259 - 3270