, Volume 21, Issue 3, pp 410–425 | Cite as

Converging Climate Sensitivities of European Forests Between Observed Radial Tree Growth and Vegetation Models

  • Zhen Zhang
  • Flurin Babst
  • Valentin Bellassen
  • David Frank
  • Thomas Launois
  • Kun Tan
  • Philippe Ciais
  • Benjamin Poulter


The impacts of climate variability and trends on European forests are unevenly distributed across different bioclimatic zones and species. Extreme climate events are also becoming more frequent and it is unknown how they will affect feedbacks of CO2 between forest ecosystems and the atmosphere. An improved understanding of species differences at the regional scale of the response of forest productivity to climate variation and extremes is thus important for forecasting forest dynamics. In this study, we evaluate the climate sensitivity of aboveground net primary production (NPP) simulated by two dynamic global vegetation models (DGVM; ORCHIDEE and LPJ-wsl) against tree ring width (TRW) observations from about 1000 sites distributed across Europe. In both the model simulations and the TRW observations, forests in northern Europe and the Alps respond positively to warmer spring and summer temperature, and their overall temperature sensitivity is larger than that of the soil-moisture-limited forests in central Europe and Mediterranean regions. Compared with TRW observations, simulated NPP from ORCHIDEE and LPJ-wsl appear to be overly-sensitive to climatic factors. Our results indicate that the models lack biological processes that control time lags, such as carbohydrate storage and remobilization, that delay the effects of radial growth dynamics to climate. Our study highlights the need for re-evaluating the physiological controls on the climate sensitivity of NPP simulated by DGVMs. In particular, DGVMs could be further enhanced by a more detailed representation of carbon reserves and allocation that control year-to-year variation in plant growth.


DGVM climate response tree ring width forest growth ORCHIDEE LPJ NPP carbon cycle 



This work was funded by the European Commission FP7 Project CARBO-Extreme (FP7-ENV-2008-1-226701). ZZ acknowledges funding by the CCES MAIOLICA project #42-01 and the National Natural Science Foundation of China (Y411391001). FB acknowledges funding from the EU Horizon-2020 project “BACI” (Grant 640176) and the Swiss National Science Foundation (Grant P300P2_154543). We thank all tree-ring data collectors for sharing their data on the International Tree-Ring Data Bank.


  1. Anderegg WRL, Schwalm C, Biondi F, Camarero JJ, Koch G, Litvak M, Ogle K, Shaw JD, Shevliakova E, Williams AP, Wolf A, Ziaco E, Pacala S. 2015. Pervasive drought legacies in forest ecosystems and their implications for carbon cycle models. Science 349:528–32.CrossRefPubMedGoogle Scholar
  2. Babst F, Alexander MR, Szejner P, Bouriaud O, Klesse S, Roden J, Ciais P, Poulter B, Frank D, Moore DP, Trouet V. 2014a. A tree-ring perspective on the terrestrial carbon cycle. Oecologia 176:307–22.CrossRefPubMedGoogle Scholar
  3. Babst F, Bouriaud O, Alexander R, Trouet V, Frank D. 2014b. Toward consistent measurements of carbon accumulation: a multi-site assessment of biomass and basal area increment across Europe. Dendrochronologia 32:153–61.CrossRefGoogle Scholar
  4. Babst F, Poulter B, Trouet V, Tan K, Neuwirth B, Wilson R, Carrer M, Grabner M, Tegel W, Levanic T, Panayotov M, Urbinati C, Bouriaud O, Ciais P, Frank D. 2013. Site- and species-specific responses of forest growth to climate across the European continent. Glob Ecol Biogeogr 22:706–17.CrossRefGoogle Scholar
  5. Ball JT, Woodrow I, Berry J. 1987. A model predicting stomatal conductance and its contribution to the control of photosynthesis under different environmental conditions. In: Biggins J, Ed. Progress in photosynthesis research. Netherlands: Springer. pp 221–4.Google Scholar
  6. Beer C, Reichstein M, Tomelleri E, Ciais P, Jung M, Carvalhais N, Rödenbeck C, Arain MA, Baldocchi D, Bonan GB, Bondeau A, Cescatti A, Lasslop G, Lindroth A, Lomas M, Luyssaert S, Margolis H, Oleson KW, Roupsard O, Veenendaal E, Viovy N, Williams C, Woodward FI, Papale D. 2010. Terrestrial gross carbon dioxide uptake: global distribution and Covariation with climate. Science 329:834–8.CrossRefPubMedGoogle Scholar
  7. Bellassen V, Le Maire G, Dhôte JF, Ciais P, Viovy N. 2010. Modelling forest management within a global vegetation model—part 1: model structure and general behaviour. Ecol Model 221:2458–74.CrossRefGoogle Scholar
  8. Bellassen V, Viovy N, Luyssaert S, Le Maire G, Schelhaas M-J, Ciais P. 2011. Reconstruction and attribution of the carbon sink of European forests between 1950 and 2000. Glob Chang Biol 17:3274–92.CrossRefGoogle Scholar
  9. Berninger F, Hari P, Nikinmaa E, Lindholm M, Meriläinen J. 2004. Use of modeled photosynthesis and decomposition to describe tree growth at the northern tree line. Tree Physiol 24:193–204.CrossRefPubMedGoogle Scholar
  10. Breitenmoser P, Brönnimann S, Frank D. 2014. Forward modelling of tree-ring width and comparison with a global network of tree-ring chronologies. Clim Past 10:437–49.CrossRefGoogle Scholar
  11. Charney ND, Babst F, Poulter B, Record S, Trouet VM, Frank D, Enquist BJ, Evans MEK. 2016. Observed forest sensitivity to climate implies large changes in 21st century North American forest growth. Ecol Lett 19:1119–28.CrossRefPubMedGoogle Scholar
  12. Ciais P, Reichstein M, Viovy N, Granier A, Ogee J, Allard V, Aubinet M, Buchmann N, Bernhofer C, Carrara A, Chevallier F, De Noblet N, Friend AD, Friedlingstein P, Grunwald T, Heinesch B, Keronen P, Knohl A, Krinner G, Loustau D, Manca G, Matteucci G, Miglietta F, Ourcival JM, Papale D, Pilegaard K, Rambal S, Seufert G, Soussana JF, Sanz MJ, Schulze ED, Vesala T, Valentini R. 2005. Europe-wide reduction in primary productivity caused by the heat and drought in 2003. Nature 437:529–33.CrossRefPubMedGoogle Scholar
  13. Collatz GJ, Ball JT, Grivet C, Berry JA. 1991. Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer. Agric For Meteorol 54:107–36.CrossRefGoogle Scholar
  14. D’Orangeville L, Duchesne L, Houle D, Kneeshaw D, Côté B, Pederson N. 2016. Northeastern North America as a potential refugium for boreal forests in a warming climate. Science 352:1452–5.CrossRefPubMedGoogle Scholar
  15. Farquhar GD, von Caemmerer S, Berry JA. 1980. A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species. Planta 149:78–90.CrossRefPubMedGoogle Scholar
  16. Fatichi S, Leuzinger S, Körner C. 2014. Moving beyond photosynthesis: from carbon source to sink-driven vegetation modeling. New Phytol 201:1086–95.CrossRefPubMedGoogle Scholar
  17. Frank DC, Poulter B, Saurer M, Esper J, Huntingford C, Helle G, Treydte K, Zimmermann NE, Schleser GH, Ahlstrom A, Ciais P, Friedlingstein P, Levis S, Lomas M, Sitch S, Viovy N, Andreu-Hayles L, Bednarz Z, Berninger F, Boettger T, D`Alessandro CM, Daux V, Filot M, Grabner M, Gutierrez E, Haupt M, Hilasvuori E, Jungner H, Kalela-Brundin M, Krapiec M, Leuenberger M, Loader NJ, Marah H, Masson-Delmotte V, Pazdur A, Pawelczyk S, Pierre M, Planells O, Pukiene R, Reynolds-Henne CE, Rinne KT, Saracino A, Sonninen E, Stievenard M, Switsur VR, Szczepanek M, Szychowska-Krapiec E, Todaro L, Waterhouse JS, Weigl M. 2015. Water-use efficiency and transpiration across European forests during the Anthropocene. Nature Clim. Change 5: 579–83.Google Scholar
  18. Friedlingstein P, Meinshausen M, Arora VK, Jones CD, Anav A, Liddicoat SK, Knutti R. 2013. Uncertainties in CMIP5 climate projections due to carbon cycle feedbacks. J Clim 27:511–26.CrossRefGoogle Scholar
  19. Gessler A, Ferrio JP, Hommel R, Treydte K, Werner RA, Monson RK. 2014. Stable isotopes in tree rings: towards a mechanistic understanding of isotope fractionation and mixing processes from the leaves to the wood. Tree Physiol 34:796–818.CrossRefPubMedGoogle Scholar
  20. Girardin MP, Bouriaud O, Hogg EH, Kurz W, Zimmermann NE, Metsaranta JM, de Jong R, Frank DC, Esper J, Büntgen U, Guo XJ, Bhatti J. 2016. No growth stimulation of Canada’s boreal forest under half-century of combined warming and CO2 fertilization. Proceedings of the National Academy of Sciences.Google Scholar
  21. Girardin MP, Guo XJ, De Jong R, Kinnard C, Bernier P, Raulier F. 2014. Unusual forest growth decline in boreal North America covaries with the retreat of Arctic sea ice. Glob Chang Biol 20:851–66.CrossRefPubMedGoogle Scholar
  22. Girardin MP, Raulier F, Bernier PY, Tardif JC. 2008. Response of tree growth to a changing climate in boreal central Canada: a comparison of empirical, process-based, and hybrid modelling approaches. Ecol Model 213:209–28.CrossRefGoogle Scholar
  23. Harris I, Jones PD, Osborn TJ, Lister DH. 2014. Updated high-resolution grids of monthly climatic observations—the CRU TS3.10 Dataset. Int J Climatol 34:623–42.CrossRefGoogle Scholar
  24. Haxeltine A, Prentice IC. 1996. BIOME3: an equilibrium terrestrial biosphere model based on ecophysiological constraints, resource availability, and competition among plant functional types. Glob Biogeochem Cycles 10:693–709.CrossRefGoogle Scholar
  25. Hijmans RJ, Cameron SE, Parra JL, Jones PG, Jarvis A. 2005. Very high resolution interpolated climate surfaces for global land areas. Int J Climatol 25:1965–78.CrossRefGoogle Scholar
  26. Hoch G, Körner C. 2009. Growth and carbon relations of tree line forming conifers at constant vs. variable low temperatures. J Ecol 97:57–66.CrossRefGoogle Scholar
  27. IPCC. 2013. Climate change 2013: the physical science basis. contribution of working group I to the fifth assessment report of the intergovernmental panel on climate change. Cambridge: Cambridge University Press. p 1535.Google Scholar
  28. Jacob D, Petersen J, Eggert B, Alias A, Christensen O, Bouwer L, Braun A, Colette A, Déqué M, Georgievski G, Georgopoulou E, Gobiet A, Menut L, Nikulin G, Haensler A, Hempelmann N, Jones C, Keuler K, Kovats S, Kröner N, Kotlarski S, Kriegsmann A, Martin E, van Meijgaard E, Moseley C, Pfeifer S, Preuschmann S, Radermacher C, Radtke K, Rechid D, Rounsevell M, Samuelsson P, Somot S, Soussana J-F, Teichmann C, Valentini R, Vautard R, Weber B, Yiou P. 2014. EURO-CORDEX: new high-resolution climate change projections for European impact research. Reg Environ Chang 14:563–78.CrossRefGoogle Scholar
  29. Keeling CD, Whorf TP. 2005. Atmospheric CO2 records from sites in the SIO air sampling network. In: Trends: a compendium of data on global change. pp 16–26.Google Scholar
  30. Keenan TF, Davidson E, Moffat AM, Munger W, Richardson AD. 2012. Using model-data fusion to interpret past trends, and quantify uncertainties in future projections, of terrestrial ecosystem carbon cycling. Glob Chang Biol 18:2555–69.CrossRefGoogle Scholar
  31. Keyan F, David F, Yan Z, Feifei Z, Heikki S. 2015. Moisture stress of a hydrological year on tree growth in the Tibetan Plateau and surroundings. Environ Res Lett 10:034010.CrossRefGoogle Scholar
  32. 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. Glob Biogeochem Cycles 19: n/a–n/a.Google Scholar
  33. Le Quéré C, Moriarty R, Andrew RM, Peters GP, Ciais P, Friedlingstein P, Jones SD, Sitch S, Tans P, Arneth A, Boden TA, Bopp L, Bozec Y, Canadell JG, Chini LP, Chevallier F, Cosca CE, Harris I, Hoppema M, Houghton RA, House JI, Jain AK, Johannessen T, Kato E, Keeling RF, Kitidis V, Klein Goldewijk K, Koven C, Landa CS, Landschützer P, Lenton A, Lima ID, Marland G, Mathis JT, Metzl N, Nojiri Y, Olsen A, Ono T, Peng S, Peters W, Pfeil B, Poulter B, Raupach MR, Regnier P, Rödenbeck C, Saito S, Salisbury JE, Schuster U, Schwinger J, Séférian R, Segschneider J, Steinhoff T, Stocker BD, Sutton AJ, Takahashi T, Tilbrook B, van der Werf GR, Viovy N, Wang YP, Wanninkhof R, Wiltshire A, Zeng N. 2015. Global carbon budget 2014. Earth Syst Sci Data 7:47–85.CrossRefGoogle Scholar
  34. Li G, Harrison SP, Prentice IC, Falster D. 2014. Simulation of tree-ring widths with a model for primary production, carbon allocation, and growth. Biogeosciences 11:6711–24.CrossRefGoogle Scholar
  35. Lindner M, Maroschek M, Netherer S, Kremer A, Barbati A, Garcia-Gonzalo J, Seidl R, Delzon S, Corona P, Kolström M, Lexer MJ, Marchetti M. 2010. Climate change impacts, adaptive capacity, and vulnerability of European forest ecosystems. For Ecol Manag 259:698–709.CrossRefGoogle Scholar
  36. McCree KJ. 1974. Equations for the rate of dark respiration of white clover and grain sorghum, as functions of dry weight, photosynthetic rate, and temperature. Crop Sci 14:509–14.CrossRefGoogle Scholar
  37. Misson L. 2004. MAIDEN: a model for analyzing ecosystem processes in dendroecology. Can J For Res 34:874–87.CrossRefGoogle Scholar
  38. Mitchell TD, Jones PD. 2005. An improved method of constructing a database of monthly climate observations and associated high-resolution grids. Int J Climatol 25:693–712.CrossRefGoogle Scholar
  39. Nehrbass-Ahles C, Babst F, Klesse S, Nötzli M, Bouriaud O, Neukom R, Dobbertin M, Frank D. 2014. The influence of sampling design on tree-ring-based quantification of forest growth. Glob Chang Biol 20:2867–85.CrossRefPubMedGoogle Scholar
  40. Nepstad DC, Tohver IM, Ray D, Moutinho P, Cardinot G. 2007. Mortality of large trees and lianas following experimental drought in an amazon forest. Ecology 88:2259–69.CrossRefPubMedGoogle Scholar
  41. Nippert JB, Duursma RA, Marshall JD. 2004. Seasonal variation in photosynthetic capacity of montane conifers. Funct Ecol 18:876–86.CrossRefGoogle Scholar
  42. Piao S, Sitch S, Ciais P, Friedlingstein P, Peylin P, Wang X, Ahlström A, Anav A, Canadell JG, Cong N, Huntingford C, Jung M, Levis S, Levy PE, Li J, Lin X, Lomas MR, Lu M, Luo Y, Ma Y, Myneni RB, Poulter B, Sun Z, Wang T, Viovy N, Zaehle S, Zeng N. 2013. Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends. Glob Chang Biol 19:2117–32.CrossRefPubMedGoogle Scholar
  43. Poulter B, Frank DC, Hodson EL, Zimmermann NE. 2011. Impacts of land cover and climate data selection on understanding terrestrial carbon dynamics and the CO2 airborne fraction. Biogeosciences 8:2027–36.CrossRefGoogle Scholar
  44. Poulter B, Hattermann F, Hawkins ED, Zaehle S, Sitch S, Restrepo-Coupe N, Heyder U, Cramer W. 2010. Robust dynamics of Amazon dieback to climate change with perturbed ecosystem model parameters. Glob Chang Biol 16:2476–95.CrossRefGoogle Scholar
  45. Rammig A, Wiedermann M, Donges JF, Babst F, von Bloh W, Frank D, Thonicke K, Mahecha MD. 2015. Coincidences of climate extremes and anomalous vegetation responses: comparing tree ring patterns to simulated productivity. Biogeosciences 12:373–85.CrossRefGoogle Scholar
  46. Richardson AD, Anderson RS, Arain MA, Barr AG, Bohrer G, Chen G, Chen JM, Ciais P, Davis KJ, Desai AR, Dietze MC, Dragoni D, Garrity SR, Gough CM, Grant R, Hollinger DY, Margolis HA, McCaughey H, Migliavacca M, Monson RK, Munger JW, Poulter B, Raczka BM, Ricciuto DM, Sahoo AK, Schaefer K, Tian H, Vargas R, Verbeeck H, Xiao J, Xue Y. 2012. Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis. Glob Chang Biol 18:566–84.CrossRefGoogle Scholar
  47. Ruimy A, Dedieu G, Saugier B. 1996. TURC: a diagnostic model of continental gross primary productivity and net primary productivity. Glob Biogeochem Cycles 10:269–85.CrossRefGoogle Scholar
  48. Sitch S, Friedlingstein P, Gruber N, Jones SD, Murray-Tortarolo G, Ahlström A, Doney SC, Graven H, Heinze C, Huntingford C, Levis S, Levy PE, Lomas M, Poulter B, Viovy N, Zaehle S, Zeng N, Arneth A, Bonan G, Bopp L, Canadell JG, Chevallier F, Ciais P, Ellis R, Gloor M, Peylin P, Piao SL, Le Quéré C, Smith B, Zhu Z, Myneni R. 2015. Recent trends and drivers of regional sources and sinks of carbon dioxide. Biogeosciences 12:653–79.CrossRefGoogle Scholar
  49. Sitch S, Smith B, Prentice IC, Arneth A, Bondeau A, Cramer W, Kaplan JO, Levis S, Lucht W, Sykes MT, Thonicke K, Venevsky S. 2003. Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model. Glob Chang Biol 9:161–85.CrossRefGoogle Scholar
  50. Tolwinski-Ward SE, Evans MN, Hughes MK, Anchukaitis KJ. 2010. An efficient forward model of the climate controls on interannual variation in tree-ring width. Clim Dyn 36:2419–39.CrossRefGoogle Scholar
  51. Wieser G, Matyssek R, Luzian R, Zwerger P, Pindur P, Oberhuber W, Gruber A. 2009. Effects of atmospheric and climate change at the timberline of the Central European Alps. Ann For Sci 66:402.CrossRefPubMedCentralPubMedGoogle Scholar
  52. Wigley TML, Briffa KR, Jones PD. 1984. On the average value of correlated time series, with applications in dendroclimatology and hydrometeorology. J Clim Appl Meteorol 23:201–13.CrossRefGoogle Scholar
  53. Zhang Z, Zimmermann NE, Kaplan JO, Poulter B. 2016. Modeling spatiotemporal dynamics of global wetlands: comprehensive evaluation of a new sub-grid TOPMODEL parameterization and uncertainties. Biogeosciences 13:1387–408.CrossRefGoogle Scholar
  54. Zhao M, Running SW. 2010. Drought-induced reduction in global terrestrial net primary production from 2000 through 2009. Science 329:940–3.CrossRefPubMedGoogle Scholar
  55. Zobler L. 1986. A world soil file for global climate modeling: National Aeronautics and Space Administration. New York: Goddard Space Flight Center, Institute for Space Studies.Google Scholar

Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  • Zhen Zhang
    • 1
    • 2
    • 3
  • Flurin Babst
    • 1
    • 4
  • Valentin Bellassen
    • 5
  • David Frank
    • 6
  • Thomas Launois
    • 7
  • Kun Tan
    • 7
  • Philippe Ciais
    • 7
  • Benjamin Poulter
    • 2
    • 8
  1. 1.Swiss Federal Research Institute WSLBirmensdorfSwitzerland
  2. 2.Institute on Ecosystems and Department of EcologyMontana State UniversityBozemanUSA
  3. 3.Northwest Institute of Eco-Environment and ResourcesChinese Academy of SciencesLanzhouChina
  4. 4.W. Szafer Institute of BotanyPolish Academy of SciencesKarkowPoland
  5. 5.INRA, UMR1041 CESAERUniversité Bourgogne Franche-ComtéDijonFrance
  6. 6.Laboratory of Tree-Ring ResearchUniversity of ArizonaTucsonUSA
  7. 7.Laboratoire des Sciences du Climat et de l’EnvironnementGif-Sur-YvetteFrance
  8. 8.Biospheric Science LaboratoryNASA Goddard Space Flight CenterGreenbeltUSA

Personalised recommendations