Regional contribution to variability and trends of global gross primary productivity

[en] Terrestrial gross primary productivity (GPP) is the largest component of the global carbon cycle and a key process for understanding land ecosystems dynamics. In this study, we used GPP estimates from a combination of eight global biome models participating in the Inter-Sectoral Impact-Model Intercomparison Project phase 2a (ISIMIP2a), the Moderate Resolution Spectroradiometer (MODIS) GPP product, and a data-driven product (Model Tree Ensemble, MTE) to study the spatiotemporal variability of GPP at the regional and global levels. We found the 2000–2010 total global GPP estimated from the model ensemble to be 117 ± 13 Pg C yr −1 (mean ± 1 standard deviation), which was higher than MODIS (112 Pg C yr −1 ), and close to the MTE (120 Pg C yr −1 ). The spatial patterns of MODIS, MTE and ISIMIP2a GPP generally agree well, but their temporal trends are different, and the seasonality and inter-annual variability of GPP at the regional and global levels are not completely consistent. For the model ensemble, Tropical Latin America contributes the most to global GPP, Asian regions contribute the most to the global GPP trend, the Northern Hemisphere regions dominate the global GPP seasonal variations, and Oceania is likely the largest contributor to inter-annual variability of global GPP. However, we observed large uncertainties across the eight ISIMIP2a models, which are probably due to the differences in the formulation of underlying photosynthetic processes. The results of this study are useful in understanding the contributions of different regions to global GPP and its spatiotemporal variability, how the model- and observational-based GPP estimates differ from each other in time and space, and the relative strength of the eight models. Our results also highlight the models’ ability to capture the seasonality of GPP that are essential for understanding the inter-annual and seasonal variability of GPP as a major component of the carbon cycle.

Disciplines :

Earth sciences & physical geography

Author, co-author :

Chen, Min

Rafique, Rashid

Asrar, Ghassem R.

Bond-Lamberty, Ben

Ciais, Philippe

Zhao, Fang

Reyer, Christopher P. O.

Ostberg, Sebastian

Chang, Jinfeng

Ito, Akihiko

More authors (17 more)

Language :

English

Title :

Regional contribution to variability and trends of global gross primary productivity

Publication date :

2017

Journal title :

Environmental Research Letters

eISSN :

1748-9326

Publisher :

Institute of Physics Publishing, Bristol, United Kingdom

Volume :

Issue :

Pages :

105005

Peer reviewed :

Peer Reviewed verified by ORBi

Additional URL :

http://stacks.iop.org/1748-9326/12/i=10/a=105005

Available on ORBi :

since 01 July 2018

Statistics

Number of views

70 (4 by ULiège)

Number of downloads

1 (1 by ULiège)

More statistics

Scopus citations^®

Scopus citations^®
without self-citations

OpenCitations

OpenAlex citations

Bibliography

Ahlström A et al 2015 The dominant role of semi-arid ecosystems in the trend and variability of the land CO2 sink Science 348 895
Anav A et al 2015 Spatiotemporal patterns of terrestrial gross primary production: a review Rev. Geophys. 53 785-818
Anav A, Friedlingstein P, Kidston M, Bopp L, Ciais P, Cox P, Jones C, Jung M, Myneni R and Zhu Z 2013 Evaluating the land and ocean components of the global carbon cycle in the CMIP5 Earth system models J. Clim. 26 6801-43
Beer C et al 2010 Terrestrial gross carbon dioxide uptake: global distribution and covariation with climate Science 329 834-8
Bond-Lamberty B and Thomson A 2010 Temperature-associated increases in the global soil respiration record Nature 464 579-82
Bondeau A et al 2007 Modelling the role of agriculture for the 20th century global terrestrial carbon balance Glob. Change Biol. 13 679-706
Campbell J E, Berry J A, Seibt U, Smith S J, Montzka S A, Launois T, Belviso S, Bopp L and Laine M 2017 Large historical growth in global terrestrial gross primary production Nature 544 84-7
Chang J et al 2017 Benchmarking carbon fluxes of the ISIMIP2a biome models Environ. Res. Lett. 12 045002
Chen M, Melaas E K, Gray J M, Friedl M A and Richardson A D 2016 A new seasonal-deciduous spring phenology submodel in the community land model 4.5: impacts on carbon and water cycling under future climate scenarios Glob. Change Biol. 22 3675-88
Chen M and Zhuang Q 2014 Evaluating aerosol direct radiative effects on global terrestrial ecosystem carbon dynamics from 2003 to 2010 Tellus B 66 21808
Chen M, Zhuang Q, Cook D R, Coulter R, Pekour M and Bible K 2011 Quantification of terrestrial ecosystem carbon dynamics in the conterminous United States combining a process-based biogeochemical model and MODIS and AmeriFlux data Biogeosciences 8 2665-88
Ciais P et al 2013 Carbon and other biogeochemical cycles Climate Change 2013: The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change ed T F Stocker et al (Cambridge: Cambridge University Press)
Clark D B et al 2011 The joint UK land environment simulator (JULES), model description - Part 2: carbon fluxes and vegetation dynamics Geosci. Model Dev. 4 701-22
Conway T J, Tans P P, Waterman L S, Thoning K W, Kitzis D R, Masarie K A and Zhang N 1994 Evidence for interannual variability of the carbon cycle from the National Oceanic and Atmospheric Administration/Climate Monitoring and Diagnostics Laboratory Global Air Sampling Network J. Geophys. Res. Atmos. 99 22831-55
Dury M, Hambuckers A, Warnant P, Henrot A, Favre E, Ouberdous M and François L 2011 Responses of European forest ecosystems to 21st century climate: assessing changes in interannual variability and fire intensity iForest: Biogeosci. Forest. 4 82-99
Friedlingstein P, Cadule P, Piao S L, Ciais P and Sitch S 2010 The African contribution to the global climate-carbon cycle feedback of the 21st century Biogeosciences 7 513-9
Gebremichael M and Barros A P 2006 Evaluation of MODIS gross primary productivity (GPP) in tropical monsoon regions Remote Sens. Environ. 100 150-66
Gobron N, Belward A, Pinty B and Knorr W 2010 Monitoring biosphere vegetation 1998-2009 Geophys. Res. Lett. 37 L15402
Huntzinger D N et al 2013 The North American carbon program multi-scale synthesis and terrestrial model intercomparison project - Part 1: overview and experimental design Geosci. Model Dev. 6 2121-33
Ito A and Inatomi M 2011 Water-use efficiency of the terrestrial biosphere: a model analysis focusing on interactions between the global carbon and water cycles J. Hydrometeorol. 13 681-94
Jiang C and Ryu Y 2016 Multi-scale evaluation of global gross primary productivity and evapotranspiration products derived from Breathing Earth System Simulator (BESS) Remote Sens. Environ. 186 528-47
de Jong R, Verbesselt J, Schaepman M E and de Bruin S 2012 Trend changes in global greening and browning: contribution of short-term trends to longer-term change Glob. Change Biol. 18 642-55
Jung M, Reichstein M and Bondeau A 2009 Towards global empirical upscaling of FLUXNET eddy covariance observations: validation of a model tree ensemble approach using a biosphere model Biogeosciences 6 2001-13
Jung M et al 2010 Recent decline in the global land evapotranspiration trend due to limited moisture supply Nature 467 951-4
Jung M et al 2011 Global patterns of land-atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations J. Geophys. Res. Biogeosci. 116 G00J07
Jung M, Verstraete M, Gobron N, Reichstein M, Papale D, Bondeau A, Robustelli M and Pinty B 2008 Diagnostic assessment of European gross primary production Glob. Change Biol. 14 2349-64
De Kauwe M G, Keenan T F, Medlyn B E, Prentice I C and Terrer C 2016 Satellite based estimates underestimate the effect of CO2 fertilization on net primary productivity Nat. Clim. Change 6 892-3
Keenan T F, Davidson E, Moffat A M, Munger W and Richardson A D 2012 Using model-data fusion to interpret past trends, and quantify uncertainties in future projections, of terrestrial ecosystem carbon cycling Glob. Change Biol. 18 2555-69
Kim Y, Knox R G, Longo M, Medvigy D, Hutyra L R, Pyle E H, Wofsy S C, Bras R L and Moorcroft P R 2012 Seasonal carbon dynamics and water fluxes in an Amazon rainforest Glob. Change Biol. 18 1322-34
Koffi E N, Rayner P J, Scholze M and Beer C 2012 Atmospheric constraints on gross primary productivity and net ecosystem productivity: Results from a carbon-cycle data assimilation system Glob. Biogeochem. Cycles 26 GB1024
Krinner G, Viovy N, de Noblet-Ducoudré N, Ogée J, Polcher J, Friedlingstein P, Ciais P, Sitch S and Prentice I C 2005 A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system Glob. Biogeochem. Cycles 19 GB1015
Lee J-E et al 2013 Forest productivity and water stress in Amazonia: observations from GOSAT chlorophyll fluorescence Proc. R. Soc. B 280 20130171
Liu D, Cai W, Xia J, Dong W, Zhou G, Chen Y, Zhang H and Yuan W 2014 Global validation of a process-based model on vegetation gross primary production using eddy covariance observations PLoS One 9 e110407
Ma J, Yan X, Dong W and Chou J 2015 Gross primary production of global forest ecosystems has been overestimated Sci. Rep. 5 10820
Morton D C, Nagol J, Carabajal C C, Rosette J, Palace M, Cook B D, Vermote E F, Harding D J and North P R J 2014 Amazon forests maintain consistent canopy structure and greenness during the dry season Nature 506 221-4
Nightingale J M, Fan W, Coops N C and Waring R H 2008 Predicting tree diversity across the United States as a function of modeled gross primary production Ecol. Appl. 18 93-103
Pan S et al 2014 Complex spatiotemporal responses of global terrestrial primary production to climate change and increasing atmospheric CO2 in the 21st century PLOS ONE 9 e112810
Pau S, Wolkovich E M, Cook B I, Davies T J, Kraft N J B, Bolmgren K, Betancourt J L and Cleland E E 2011 Predicting phenology by integrating ecology, evolution and climate science Glob. Change Biol. 17 3633-43
Piao S, Friedlingstein P, Ciais P, Viovy N and Demarty J 2007 Growing season extension and its impact on terrestrial carbon cycle in the Northern Hemisphere over the past 2 decades Glob. Biogeochem. Cycles 21 GB3018
Piao S et al 2013 Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends Glob. Change Biol. 19 2117-32
Prentice I C, Liang X, Medlyn B E and Wang Y-P 2015 Reliable, robust and realistic: the three R's of next-generation land-surface modelling Atmos. Chem. Phys. 15 5987-6005
Le Quéré C et al 2016 Global carbon budget 2016 Earth Syst. Sci. Data 8 605-49
Rafique R, Kumar S, Luo Y, Kiely G and Asrar G 2015 An algorithmic calibration approach to identify globally optimal parameters for constraining the DayCent model Ecol. Modell. 297 196-200
Restrepo-Coupe N et al 2017 Do dynamic global vegetation models capture the seasonality of carbon fluxes in the Amazon basin? A data-model intercomparison Glob. Change Biol. 23 191-208
Richardson A D et al 2012 Terrestrial biosphere models need better representation of vegetation phenology: results from the North American carbon program site synthesis Glob. Change Biol. 18 566-84
Richardson A D, Keenan T F, Migliavacca M, Ryu Y, Sonnentag O and Toomey M 2013 Climate change, phenology, and phenological control of vegetation feedbacks to the climate system Agric. Forest Meteorol. 169 156-73
Running S W, Nemani R R, Heinsch F A, Zhao M, Reeves M and Hashimoto H 2004 A continuous satellite-derived measure of global terrestrial primary production Bioscience 54 547-60
Saleska S R, Didan K, Huete A R and da Rocha H R 2007 Amazon forests green-up during 2005 drought Science 318 612
Saleska S R, Wu J, Guan K, Araujo A C, Huete A, Nobre A D and Restrepo-Coupe N 2016 Dry-season greening of Amazon forests Nature 531 E4-5
Schaefer K et al 2012 A model-data comparison of gross primary productivity: results from the North American carbon program site synthesis J. Geophys. Res. Biogeosci. 117 G03010
Sitch S et al 2008 Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five dynamic global vegetation models (DGVMs) Glob. Change Biol. 14 2015-39
Sjöström M et al 2013 Evaluation of MODIS gross primary productivity for Africa using eddy covariance data Remote Sens. Environ. 131 275-86
Smith B, Prentice I C and Sykes M T 2001 Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space Glob. Ecol. Biogeogr. 10 621-37
Tian H et al 2015 North American terrestrial CO2 uptake largely offset by CH4 and N2O emissions: toward a full accounting of the greenhouse gas budget Clim. Change 129 413-26
Tian H, Xu X, Liu M, Ren W and Zhang C 2010 Spatial and temporal patterns of CH4 and N2O fluxes in terrestrial ecosystems of North America during 1979-2008: application of a global biogeochemistry model Biogeosciences 7 2673-94
Trenberth K E, Stepaniak D P, Hurrell J W and Fiorino M 2001 Quality of reanalyses in the tropics J. Clim. 14 1499-510
Turner D P et al 2006 Evaluation of MODIS NPP and GPP products across multiple biomes Remote Sens. Environ. 102 282-92
Warszawski L, Frieler K, Huber V, Piontek F, Serdeczny O and Schewe J 2014 The Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP): project framework Proc. Natl Acad. Sci. 111 3228-32
Welp L R, Keeling R F, Meijer H A J, Bollenbacher A F, Piper S C, Yoshimura K, Francey R J, Allison C E and Wahlen M 2011 Interannual variability in the oxygen isotopes of atmospheric CO2 driven by El Nino Nature 477 579-82
Wu J et al 2016 Leaf development and demography explain photosynthetic seasonality in Amazon evergreen forests Science 351 LP-972-76
Wu J, Serbin S P, Xu X, Albert L P, Chen M, Meng R, Saleska S R and Rogers A 2017 The phenology of leaf quality and its within-canopy variation is essential for accurate modeling of photosynthesis in tropical evergreen forests Glob. Change Biol. https://doi.org/10.1111/gcb.13725
Xia J et al 2015 Joint control of terrestrial gross primary productivity by plant phenology and physiology Proc. Natl Acad. Sci. 112 2788-93
Yuan W et al 2010 Global estimates of evapotranspiration and gross primary production based on MODIS and global meteorology data Remote Sens. Environ. 114 1416-31
Zeng N, Qian H, Roedenbeck C and Heimann M 2005 Impact of 1998-2002 midlatitude drought and warming on terrestrial ecosystem and the global carbon cycle Geophys. Res. Lett. 32 L22709
Zhang Y et al 2016 Precipitation and carbon-water coupling jointly control the interannual variability of global land gross primary production 6 39748
Zhao M and Running S W 2010 Drought-induced reduction in global terrestrial net primary production from 2000 through 2009 Science 329 940-3
Zhou L, Tian Y, Myneni R B, Ciais P, Saatchi S, Liu Y Y, Piao S, Chen H and Hwang T 2014 Widespread decline of Congo rainforest greenness in the past decade Nature 509 86-90
Zhu H, Lin A, Wang L, Xia Y and Zou L 2016 Evaluation of MODIS gross primary production across multiple biomes in China using eddy covariance flux data Remote Sens. 8 395
Zscheischler J et al 2014 A few extreme events dominate global interannual variability in gross primary production Environ. Res. Lett. 9 35001