RichardsonAndersonArainEtAl2012

Reference

Richardson, A.D., Anderson, R.S., Arain, M.A., Barr, A.G., Bohrer, G., Chen, G., Chen, J.M., Ciais, P., Davis, K.J., Desai, A.R., Dietze, M.C., Dragoni, D., Garrity, S.R., Gough, C.M., Grant, R., Hollinger, D.Y., Margolis, H.A., Mccaughey, H., Migliavacca, M., Monson, R.K., Munger, J.W., Poulter, B., Raczka, B.M., Ricciuto, D.M., Sahoo, A.K., Schaefer, K., Tian, H., Vargas, R., Verbeeck, H., Xiao, J. and Xue, Y. (2012) Terrestrial biosphere models need better representation of vegetation phenology: Results from the North American Carbon Program Site Synthesis. Global Change Biology, 18(2):566-584. (Scopus )

Abstract

Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem-scale CO 2 exchange, in 14 models participating in the North American Carbon Program Site Synthesis. Model predictions were evaluated using long-term measurements (emphasizing the period 2000-2006) from 10 forested sites within the AmeriFlux and Fluxnet-Canada networks. In deciduous forests, almost all models consistently predicted that the growing season started earlier, and ended later, than was actually observed; biases of 2 weeks or more were typical. For these sites, most models were also unable to explain more than a small fraction of the observed interannual variability in phenological transition dates. Finally, for deciduous forests, misrepresentation of the seasonal cycle resulted in over-prediction of gross ecosystem photosynthesis by +160 ± 145 g C m -2 yr -1 during the spring transition period and +75 ± 130 g C m -2 yr -1 during the autumn transition period (13% and 8% annual productivity, respectively) compensating for the tendency of most models to under-predict the magnitude of peak summertime photosynthetic rates. Models did a better job of predicting the seasonality of CO 2 exchange for evergreen forests. These results highlight the need for improved understanding of the environmental controls on vegetation phenology and incorporation of this knowledge into better phenological models. Existing models are unlikely to predict future responses of phenology to climate change accurately and therefore will misrepresent the seasonality and interannual variability of key biosphere-atmosphere feedbacks and interactions in coupled global climate models. © 2011 Blackwell Publishing Ltd.

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@ARTICLE { RichardsonAndersonArainEtAl2012,
    AUTHOR = { Richardson, A.D. and Anderson, R.S. and Arain, M.A. and Barr, A.G. and Bohrer, G. and Chen, G. and Chen, J.M. and Ciais, P. and Davis, K.J. and Desai, A.R. and Dietze, M.C. and Dragoni, D. and Garrity, S.R. and Gough, C.M. and Grant, R. and Hollinger, D.Y. and Margolis, H.A. and Mccaughey, H. and Migliavacca, M. and Monson, R.K. and Munger, J.W. and Poulter, B. and Raczka, B.M. and Ricciuto, D.M. and Sahoo, A.K. and Schaefer, K. and Tian, H. and Vargas, R. and Verbeeck, H. and Xiao, J. and Xue, Y. },
    TITLE = { Terrestrial biosphere models need better representation of vegetation phenology: Results from the North American Carbon Program Site Synthesis },
    JOURNAL = { Global Change Biology },
    YEAR = { 2012 },
    VOLUME = { 18 },
    PAGES = { 566-584 },
    NUMBER = { 2 },
    ABSTRACT = { Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem-scale CO 2 exchange, in 14 models participating in the North American Carbon Program Site Synthesis. Model predictions were evaluated using long-term measurements (emphasizing the period 2000-2006) from 10 forested sites within the AmeriFlux and Fluxnet-Canada networks. In deciduous forests, almost all models consistently predicted that the growing season started earlier, and ended later, than was actually observed; biases of 2 weeks or more were typical. For these sites, most models were also unable to explain more than a small fraction of the observed interannual variability in phenological transition dates. Finally, for deciduous forests, misrepresentation of the seasonal cycle resulted in over-prediction of gross ecosystem photosynthesis by +160 ± 145 g C m -2 yr -1 during the spring transition period and +75 ± 130 g C m -2 yr -1 during the autumn transition period (13% and 8% annual productivity, respectively) compensating for the tendency of most models to under-predict the magnitude of peak summertime photosynthetic rates. Models did a better job of predicting the seasonality of CO 2 exchange for evergreen forests. These results highlight the need for improved understanding of the environmental controls on vegetation phenology and incorporation of this knowledge into better phenological models. Existing models are unlikely to predict future responses of phenology to climate change accurately and therefore will misrepresent the seasonality and interannual variability of key biosphere-atmosphere feedbacks and interactions in coupled global climate models. © 2011 Blackwell Publishing Ltd. },
    COMMENT = { Export Date: 20 February 2012 Source: Scopus doi: 10.1111/j.1365-2486.2011.02562.x },
    ISSN = { 13541013 (ISSN) },
    KEYWORDS = { Autumn senescence, Carbon cycle, Land surface model (LSM), Leaf area index (LAI), Model error, North American Carbon Program (NACP), Phenology, Seasonal dynamics, Spring onset },
    OWNER = { Luc },
    TIMESTAMP = { 2012.02.20 },
    URL = { http://www.scopus.com/inward/record.url?eid=2-s2.0-84855855291&partnerID=40&md5=2f98e63ca834434a17ed9f2a2aa8a254 },
}

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