Ghent University Academic Bibliography

Advanced

Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis

Andrew D Richardson, Ryan S Anderson, M Altaf Arain, Alan G Barr, Gil Bohrer, Guangsheng Chen, Jing M. Chen, Philippe Ciais, Kenneth J Davis and Ankur R. Desai, et al. (2012) GLOBAL CHANGE BIOLOGY. 18(2). p.566-584
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 CO2 exchange, in 14 models participating in the North American Carbon Program Site Synthesis. Model predictions were evaluated using long-term measurements (emphasizing the period 20002006) 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 CO2 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 biosphereatmosphere feedbacks and interactions in coupled global climate models.
Please use this url to cite or link to this publication:
author
organization
year
type
journalArticle (original)
publication status
published
subject
keyword
carbon cycle, autumn senescence, land surface model (LSM), leaf area index (LAI), model error, North American Carbon Program (NACP), phenology, seasonal dynamics, spring onset, NET ECOSYSTEM PRODUCTIVITY, LEAF-AREA INDEX, SUB-ALPINE FOREST, DECIDUOUS FOREST, SPRING PHENOLOGY, TEMPERATE REGIONS, HIGH-ELEVATION, SATELLITE DATA, CLIMATE-CHANGE, UNITED-STATES
journal title
GLOBAL CHANGE BIOLOGY
Glob. Change Biol.
volume
18
issue
2
pages
566 - 584
Web of Science type
Article
Web of Science id
000299042500015
JCR category
ENVIRONMENTAL SCIENCES
JCR impact factor
6.91 (2012)
JCR rank
5/209 (2012)
JCR quartile
1 (2012)
ISSN
1354-1013
DOI
10.1111/j.1365-2486.2011.02562.x
language
English
UGent publication?
yes
classification
A1
copyright statement
I have transferred the copyright for this publication to the publisher
id
1986101
handle
http://hdl.handle.net/1854/LU-1986101
date created
2012-01-13 14:22:05
date last changed
2012-09-28 10:39:10
@article{1986101,
  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 CO2 exchange, in 14 models participating in the North American Carbon Program Site Synthesis. Model predictions were evaluated using long-term measurements (emphasizing the period 20002006) 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 CO2 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 biosphereatmosphere feedbacks and interactions in coupled global climate models.},
  author       = {Richardson, Andrew D and Anderson, Ryan S and Arain, M Altaf and Barr, Alan G and Bohrer, Gil and Chen, Guangsheng and Chen, Jing M. and Ciais, Philippe and Davis, Kenneth J and Desai, Ankur R. and Dietze, Michael C and Dragoni, Danilo and Garrity, Steven R and Gough, Christopher M and Grant, Robert and Hollinger, David Y and Margolis, Hank A and McCaughey, Harry and Migliavacca, Mirco and Monson, Russell K and Munger, J William and Poulter, Benjamin and Raczka, Brett M and Ricciuto, Daniel M and Sahoo, Alok K and Schaefer, Kevin and Tian, Hanqin and Vargas, Rodrigo and Verbeeck, Hans and Xiao, Jingfeng and Xue, Yongkang},
  issn         = {1354-1013},
  journal      = {GLOBAL CHANGE BIOLOGY},
  keyword      = {carbon cycle,autumn senescence,land surface model (LSM),leaf area index (LAI),model error,North American Carbon Program (NACP),phenology,seasonal dynamics,spring onset,NET ECOSYSTEM PRODUCTIVITY,LEAF-AREA INDEX,SUB-ALPINE FOREST,DECIDUOUS FOREST,SPRING PHENOLOGY,TEMPERATE REGIONS,HIGH-ELEVATION,SATELLITE DATA,CLIMATE-CHANGE,UNITED-STATES},
  language     = {eng},
  number       = {2},
  pages        = {566--584},
  title        = {Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis},
  url          = {http://dx.doi.org/10.1111/j.1365-2486.2011.02562.x},
  volume       = {18},
  year         = {2012},
}

Chicago
Richardson, Andrew D, Ryan S Anderson, M Altaf Arain, Alan G Barr, Gil Bohrer, Guangsheng Chen, Jing M. Chen, et al. 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.
APA
Richardson, A. D., Anderson, R. S., Arain, M. A., Barr, A. G., Bohrer, G., Chen, G., Chen, J. M., et al. (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.
Vancouver
1.
Richardson AD, Anderson RS, Arain MA, Barr AG, Bohrer G, Chen G, et al. Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis. GLOBAL CHANGE BIOLOGY. 2012;18(2):566–84.
MLA
Richardson, Andrew D, Ryan S Anderson, M Altaf Arain, et al. “Terrestrial Biosphere Models Need Better Representation of Vegetation Phenology: Results from the North American Carbon Program Site Synthesis.” GLOBAL CHANGE BIOLOGY 18.2 (2012): 566–584. Print.