Climate Dynamics

, Volume 40, Issue 9–10, pp 2535–2548 | Cite as

Does the integration of the dynamic nitrogen cycle in a terrestrial biosphere model improve the long-term trend of the leaf area index?

  • B. GuenetEmail author
  • P. Cadule
  • S. Zaehle
  • S. L. Piao
  • P. Peylin
  • F. Maignan
  • P. Ciais
  • P. Friedlingstein


The carbon cycle strongly interacts with the nitrogen cycle. Several observations show that the effects of global change on primary production and carbon storage in plant biomass and soils are partially controlled by N availability. Nevertheless, only a small number of terrestrial biosphere models represent explicitly the nitrogen cycle, despite its importance on the carbon cycle and on climate. These models are difficult to evaluate at large spatiotemporal scales because of the scarcity of data at the global scale over a long time period. In this study, we benchmark the capacity of the O–CN global terrestrial biosphere model to reproduce temporal changes in leaf area index (LAI) at the global scale observed by NOAA_AVHRR satellites over the period 1982–2002. Using a satellite LAI product based on the normalized difference vegetation index of global inventory monitoring and modelling studies dataset, we estimate the long-term trend of LAI and we compare it with the results from the terrestrial biosphere models, either with (O–CN) or without (O–C) a dynamic nitrogen cycle coupled to the carbon–water-energy cycles. In boreal and temperate regions, including a dynamic N cycle (O–CN) improved the fit between observed and modeled temporal changes in LAI. In contrast, in the tropics, simulated LAI from the model without the dynamic N cycle (O–C) better matched observed changes in LAI over time. Despite differential regional trends, the satellite estimate suggests an increase in the global average LAI during 1982–2002 by 0.0020 m2 m−2 y−1. Both versions of the model substantially overestimated the rate of change in LAI over time (0.0065 m2 m−2 y−1 for O–C and 0.0057 m2 m−2 y−1 for O–CN), suggesting that some additional limitation mechanisms are missing in the model. We also estimated the relative importance of climate, CO2 and N deposition as potential drivers of the temporal changes in LAI. We found that recent climate change better explained temporal changes in LAI when the dynamic N cycle was included in the model (higher ranked fit for O–CN vs. O–C). Using the O–C configuration to estimate the direct effect of climate on LAI, we quantified the importance of climate-N cycle feedbacks in explaining the LAI response. We found that the warming-induced release of N from soil organic matter decomposition explains 17.5 % of the global trend in LAI over time, however, reaching up to 40.9 % explained variance in the boreal zone, which is a more important contribution than increasing anthropogenic nitrogen deposition. Our analysis supports a strong connection between warming, N cycling, and vegetation productivity. These findings underscore the importance of including N cycling in global-scale models of vegetation response to environmental change.


Leaf area index Carbon cycle Nitrogen cycle Model benchmarking Nitrogen mineralization 



The authors acknowledge financial support from the European FP7 projects COMBINE and Greencycles II (grant agreement n° [238366]) and J. Ryder for his valuable comments on the manuscript.


  1. Bacour C, Breon F, Maignan F (2006) Normalization of the directional effects in NOAA–AVHRR reflectance measurements for an improved monitoring of vegetation cycles. Remote Sens Environ 102:402–413CrossRefGoogle Scholar
  2. Baker DF, Law RM, Gurney KR, Rayner P, Peylin P, Denning AS, Bousquet P, Bruhwiler L, Chen Y-H, Ciais P, Fung IY, Heimann M, John J, Maki T, Maksyutov S, Masarie K, Prather M, Pak B, Taguchi S, Zhu Z (2006) TransCom 3 inversion intercomparison: Impact of transport model errors on the interannual variability of regional CO2 fluxes, 1988–2003. Global Biogeochem Cy 20:1988–2003CrossRefGoogle Scholar
  3. Beck HE, McVicar TR, van Dijk AIJM, Schellekens J, de Jeu RAM, Bruijnzeel LA (2011) Global evaluation of four AVHRR–NDVI data sets: Intercomparison and assessment against Landsat imagery. Remote Sens Environ 115:2547–2563CrossRefGoogle Scholar
  4. Brohan P, Kennedy JJ, Harris I, Tett SFB, Jones PD (2006) Uncertainty estimates in regional and global observed temperature changes: a new data set from 1850. J Geophys Res 111:D12CrossRefGoogle Scholar
  5. Cadule P, Friedlingstein P, Bopp L, Sitch S, Jones CD, Ciais P, Piao SL, Peylin P (2010) Benchmarking coupled climate-carbon models against long-term atmospheric CO2 measurements. Global Biogeochem Cy 24:GB2016CrossRefGoogle Scholar
  6. Churkina G, Brovkin V, von Bloh W, Trusilova K, Jung M, Dentener F (2009) Synergy of rising nitrogen depositions and atmospheric CO2 on land carbon uptake moderately offsets global warming. Global Biogeochem Cy 23(4):GB4027CrossRefGoogle Scholar
  7. Cox PM, Betts R, Jones CD, Spall S, Totterdell IJ (2000) Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature 408:184–187CrossRefGoogle Scholar
  8. Cramer W, Bondeau A, Woodward FI, Prentice IC, Betts RA, Brovkin V, Cox PM, V Fisher, Foley JA, Friend AD, Kucharik C, Lomas MR, Ramankutty N, Sitch S, Smith B (2001) Global response of terrestrial ecosystem structure and function to CO2 and climate change: results from six dynamic global vegetation models. Global Change Biol 7:357–373CrossRefGoogle Scholar
  9. de Jong R, de Bruin S (2012) Linear trends in seasonal vegetation time series and the modifiable temporal unit problem. Biogeosciences 9(1):71–77CrossRefGoogle Scholar
  10. Dentener F, Drevet J, Lamarque JF, Bey I, Eickhout B, Fiore AM, Hauglustaine D, Horowitz LW, Krol M, Kulshrestha UC, Lawrence M, Galy-Lacaux C, Rast S, Shindell D, Stevenson D, Van Noije T, Atherton C, Bell N, Bergman D, Butler T, Cofala J, Collins B, Doherty R, Ellingsen K, Galloway J, Gauss M, Montanaro V, Müller JF, Pitari G, Rodriguez J, Sanderson M, Solmon F, Strahan S, Schultz M, Sudo K, Szopa S, Wild O (2006) Nitrogen and sulfur deposition on regional and global scales: a multimodel evaluation. Global Biogeochem Cy 20:GB4003CrossRefGoogle Scholar
  11. Dufresne J-L, Quass J, Boucher O, Denvil S, Fairhead L (2005) Contrasts in the effects on climate of anthropogenic sulfate aerosols between the 20th and 21st century. Geophys Res Lett 32:L21703CrossRefGoogle Scholar
  12. Esser G, Kattge J, Sakalli A (2011) Feedback of carbon and nitrogen cycles enhances carbon sequestration in the terrestrial biosphere. Glob Change Biol 17:819–842CrossRefGoogle Scholar
  13. Etheridge DM, Steele LP, Langenfelds RL, Francey RJ, Barnola J-M, Morgan VI (1996) Natural and anthropogenic changes in atmospheric CO2 over the last 1000 years from air in Antarctic ice and firn. J Geophys Res 101:4115–4128CrossRefGoogle Scholar
  14. Friedlingstein P, Joel G, Field CB, Fung IY (1999) Toward an allocation scheme for the global terrestrial carbon models. Glob Change Biol 5:795–817CrossRefGoogle Scholar
  15. Friedlingstein P, Cox P, Betts R, Bopp L, Von Bloh W, Brovkin V, Cadule P, Doney S, Eby M, Fung I, Bala G, John J, Jones C, Joos F, Kato T, Kawamiya M, Knorr W, Lindsay K, Matthews HD, Raddatz T, Rayner P, Reick C, Roeckner E, Schnitzler KG, Schnur R, Strassmann K, Weaver AJ, Yoshikawa C, Zeng N (2006) Climate-carbon cycle feedback analysis: Results from the C4MIP model intercomparison. J Climate 19:3337–3353CrossRefGoogle Scholar
  16. Friend AD (1998) Parameterisation of a global daily weather generator for terrestrial ecosystem and biogeochemical modelling. Ecol Model 109:121–140CrossRefGoogle Scholar
  17. Friend AD, Kiang NY (2005) Land-surface model development for the GISS GCM: effects of improved canopy physiology on simulated climate. J Clim 18:2883–2902CrossRefGoogle Scholar
  18. Galloway JN, Dentener FJ, Capone DG, Boyer EW, Howarth RW, Seitzinger SP, Asner GP, Cleveland CC, Green P, Holland E, Karl DM, Michaels F, Porter JH, Townsend R, Vösömarty CJ (2004) Nitrogen cycles: past, present and future. Biogeochemistry 70:153–226CrossRefGoogle Scholar
  19. Garrigues S, Lacaze R, Baret F, Morisette JT, Weiss M, Nickeson JE, Fernandes R, Plummer S, Shabanov NV, Myneni RB, Knyazikhin Y, Yang W (2008) Validation and intercomparison of global leaf area index products derived from remote sensing data. J Geophys Res 113:G2CrossRefGoogle Scholar
  20. Gerber S, Hedin LO, Oppenheimer M, Pacala SW, Shevliakova E (2010) Nitrogen cycling and feedbacks in a global dynamic land model. Global Biogeochem Cy 24(1):1–15CrossRefGoogle Scholar
  21. Hungate BA, Dukes JS, Shaw MR, Luo Y, Field CB (2003) Nitrogen and climate change. Science 302:1512–1513CrossRefGoogle Scholar
  22. Hungate B, van Groenigen KJ, Six J, Jastrow JD, Luo Y, de Graaff M-A, van Kessel C, Osenberg C, Craig W (2009) Assessing the effect of elevated carbon dioxide on soil carbon: a comparison of four meta-analyses. Global Change Biol 15:2020–2034CrossRefGoogle Scholar
  23. IPCC (2007) Summary for policymakers. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt KB, Tignor M, Miller HL (eds) Climate change 2007: the physical science basis. Contribution of working group I to the fourth assessment report of the intergovernmental panel on climate change. Cambridge University Press, CambridgeGoogle Scholar
  24. Jain A, Yang X, Kheshgi H, McGuire D, Post W, Kicklighter D (2009) Nitrogen attenuation of terrestrial carbon cycle response to global environmental factors. Global Biogeochem Cy 23(4):1–13CrossRefGoogle Scholar
  25. Keeling CD, Whorf TP (2006) Atmopheric CO2 records from sites in the SIO air sampling network, Carbon Dioxide Inf. Anal. Cent., Oak Ridge Natl. Lab. U.S. Dept. of Energy, Oak Ridge, TennGoogle Scholar
  26. Krinner G, Viovy N, de Noblet-Ducoudré N, Ogée J, Polcher J, Friedlingstein P, Ciais P, Sitch S, Prentice IC (2005) A dynamic global vegetation model for studies of the coupled atmosphere-biosphere system. Global Biogeochem Cycles 19:GB1015CrossRefGoogle Scholar
  27. Loveland T, Reed B, Brown J, Ohlen D, Zhu Z, Yang L, Merchant J (2000) Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data. Int J Remote Sens 21:1303–1330CrossRefGoogle Scholar
  28. Lucht W, Prentice IC, Myneni RB, Sitch S, Friedlingstein P, Cramer W, Bousquet P, Buermann W, Smith B (2002) Climatic control of the high-latitude vegetation greening trend and Pinatubo effect. Science 296:1687–1689CrossRefGoogle Scholar
  29. Mercado LM, Bellouin N, Sitch S, Boucher O, Huntingford C, Wild M, Cox PM (2009) Impact of changes in diffuse radiation on the global land carbon sink. Nature 458:1014–1017CrossRefGoogle Scholar
  30. Mitchell TD, Carter TR, Jones PD, Hulme M, New M (2004) A comprehensive set of high-resolution grids of monthly climate for Europe and the globe: the observed record (1901–2000) and 16 scenarios (2001–2100). Tyndall Center for Climate Change Research, University of East Anglia, Norwich, p 33Google Scholar
  31. Myneni RB, Keeling CD, Tucker CJ, Asrar G (1997a) Increased plant growth in the northern high latitudes from 1981 to 1991. Nature 386:698–702CrossRefGoogle Scholar
  32. Myneni RB, Ramakrishna R, Nemani R, Running SW (1997b) Estimation of global leaf area index and absorbed par using radiative transfer models. IEEE Geosci Remote Sens Lett 35:1380–1393CrossRefGoogle Scholar
  33. Parton WJ, Schimel DS, Cole CV, Ojima DS (1987) Analysis of factors controlling soil organic matter levels in great plains grasslands. Soil Sci Soc Am J 51:1173–1179CrossRefGoogle Scholar
  34. Piao SL, Friedlingstein P, Ciais P, Zhou L, Chen A (2006) Effect of climate and CO2 changes on the greening of the Northern Hemisphere over the past two decades. Geophys Res Lett 33:L23402CrossRefGoogle Scholar
  35. Piao SL, Ciais P, Friedlingstein P, Peylin P, Reichstein M, Luyssaert S, Margolis H, Fang YJ, Barr A, Chen AP, Grelle A, Hollinger DY, Laurilia T, Lindroth A, Richardson AD, Vesala T (2008) Net carbon dioxide losses of northern ecosystems in response to autumn warming. Nature 451:49–53CrossRefGoogle Scholar
  36. Richardson CW, Wright DA (1984) WGEN: a model for generating daily weather variables. US Department of Agriculture, Agricultural Research Service, ARS-8, 83 pGoogle Scholar
  37. Shinozaki K, Yoda K, Hozumi K, Kira T (1964) A quantitative analysis of the plant form: the pipe model theory. Jpn J Ecol 14:98–104Google Scholar
  38. Sitch S, Huntingford C, Gedney N, Levy PE, Lomas M, Piao SL, Betts R, Ciais P, Cox P, Friedlingstein P, Jones CD, Prentice IC, Woodward FI (2008) Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five dynamic global vegetation models (DGVMs). Global Change Biol 14:2015–2039CrossRefGoogle Scholar
  39. Sokolov AP, Kicklighter DW, Melillo JM, Felzer BS, Schlosser CA, Cronin TW (2008) Consequences of considering carbon–nitrogen interactions on the feedbacks between climate and the terrestrial carbon cycle. J Climate 21:3776–3796CrossRefGoogle Scholar
  40. Thoning KW, Tans PP, Komhyr WD (1989) Atmospheric carbon-dioxide at Mauna Loa Observatory. 2. Analysis of the NOAA GMCC data, 1974–1985. J Geophys Res 94:8549–8565CrossRefGoogle Scholar
  41. Thornton PE, Lamarque JF, Rosenbloom N, Mahowald NM (2007) Influence of carbon-nitrogen cycle coupling on land model response to CO2 fertilization and climate variability. Global Biogeochem Cy 21(4):1–15CrossRefGoogle Scholar
  42. Thornton PE, Doney SC, Lindsay K, Moore JK, Mahowald N, Randerson JT, Fung I, Lamarque J-F, Feddema JJ, Lee Y-H (2009) Carbon-nitrogen interactions regulate climate-carbon cycle feedbacks: results from an atmosphere-ocean general circulation model. Biogeosciences 6:2099–2120CrossRefGoogle Scholar
  43. Wang X, Piao SL, Ciais P, Li J, Friedlingstein P, Koven C, Chen A (2011) Spring temperature change and its implication in the change of vegetation growth in North America from 1982 to 2006. Proc Natl Acad Sci USA 108:1240–1245CrossRefGoogle Scholar
  44. Zaehle S, Dalmonech D (2011) Carbon–nitrogen interactions on land at global scales: current understanding in modelling climate biosphere feedbacks. Curr Opin Environ Sustain 3:311–320CrossRefGoogle Scholar
  45. Zaehle S, Friend AD (2010) Carbon and nitrogen cycle dynamics in the O–CN land surface model: 1. Model description, site-scale evaluation, and sensitivity to parameter estimates. Global Biogeochem Cy 24:GB1005Google Scholar
  46. Zaehle S, Sitch S, Prentice IC, Liski J, Cramer W, Erhard M, Hickler T, Smith B (2006) The importance of age-related decline in forest NPP for modeling regional carbon balances. Ecol Appl 16:1555–1574CrossRefGoogle Scholar
  47. Zaehle S, Friend AD, Friedlingstein P, Dentener F, Peylin P, Schulz M (2010a) Carbon and nitrogen cycle dynamics in the O–CN land surface model: 2. Role of the nitrogen cycle in the historical terrestrial carbon balance. Global Biogeochem Cy 24:GB1006Google Scholar
  48. Zaehle S, Friedlingstein P, Friend AD (2010b) Terrestrial nitrogen feedbacks may accelerate future climate change. Geophys Res Lett 37:1–5CrossRefGoogle Scholar
  49. Zaehle S, Ciais P, Friend AD, Prieur V (2011) Carbon benefits of anthropogenic reactive nitrogen offset by nitrous oxide emissions. Nat Geosci 4:601–605CrossRefGoogle Scholar

Copyright information

© Springer-Verlag 2012

Authors and Affiliations

  • B. Guenet
    • 1
    Email author
  • P. Cadule
    • 1
  • S. Zaehle
    • 2
  • S. L. Piao
    • 3
  • P. Peylin
    • 1
  • F. Maignan
    • 1
  • P. Ciais
    • 1
  • P. Friedlingstein
    • 4
  1. 1.Unité Mixte de Recherche CEA-CNRS-UVSQ, Laboratoire des Sciences du Climat et de l’EnvironnementGif-sur-YvetteFrance
  2. 2.Department for Biogeochemical SystemsMax Planck Institute for BiogeochemistryJenaGermany
  3. 3.Department of Ecology, College of Urban and Environmental SciencesPeking UniversityBeijingChina
  4. 4.College of Engineering, Mathematics and Physical SciencesUniversity of ExeterExeterUK

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