The overestimated negative temperature sensitivity of the carbon sink in ecosystem models

Abstract

Understanding how the terrestrial carbon cycle responds to temperature rise is of great importance in studies on global climate change and carbon budget. This study collected eddy covariance (EC) data from 27 FLUXNET sites with over 10 years of continuous observations in mid- and high- latitude ecosystems to assess the temperature sensitivities of gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP) simulated by eight terrestrial carbon cycle models. Results showed that the temperature sensitivities of GPP, ER, and NEP were highest in spring and wet regions. The eight models could well capture seasonal patterns of the temperature sensitivities, but failed to reproduce their spatial variations, which are critical for representing regional differences in carbon–climate feedbacks. This limitation can lead to biased estimates of ecosystem carbon dynamics under future warming scenarios. Overall, model-simulated temperature sensitivities of GPP and NEP were significantly lower than those derived from EC measurements, which resulted in overestimation of carbon losses under climate warming. It indicates that current terrestrial ecosystem models overestimate the negative effects of warming on ecosystem carbon sink. These findings highlight the biases in the simulation of temperature sensitivities and an urgent need to improve the temperature response modeling in order to obtain accurate predictions of carbon cycle dynamics.

Graphical abstract

Keywords

terrestrial carbon cycle / ecosystem model / climate warming / temperature sensitivity / carbon loss

References

[1] Arain M A, Yuan F, Black T A (2006). Soil–plant nitrogen cycling modulated carbon exchanges in a western temperate conifer forest in Canada.Agric For Meteorol, 140(1−4): 171–192

[2] Atkin O K, Tjoelker M G (2003). Thermal acclimation and the dynamic response of plant respiration to temperature.Trends Plant Sci, 8: 343–351

[3] Berthelot M, Friedlingstein P, Ciais P, Dufresne J L, Monfray P (2005). How uncertainties in future climate change predictions translate into future terrestrial carbon fluxes.Glob Change Biol, 11(6): 959–970

[4] Best M J, Pryor M, Clark D, Rooney G G, Essery R, Ménard C, Edwards J, Hendry M, Porson A, Gedney N (2011). The Joint UK Land Environment Simulator (JULES), model description–Part 1: energy and water fluxes.Geosci Model Dev, 4(3): 677–699

[5] Bonan G B, Lombardozzi D L, Wieder W R, Oleson K W, Lawrence D M, Hoffman F M, Collier N (2019). Model structure and climate data uncertainty in historical simulations of the terrestrial carbon cycle (1850–2014).Global Biogeochem Cycles, 33: 1310–1326

[6] Booth B B, Jones C D, Collins M, Totterdell I J, Cox P M, Sitch S, Huntingford C, Betts R A, Harris G R, Lloyd J (2012). High sensitivity of future global warming to land carbon cycle processes.Environ Res Lett, 7(2): 024002

[7] Buermann W, Parida B, Jung M, MacDonald G M, Tucker C J, Reichstein M (2014). Recent shift in Eurasian boreal forest greening response may be associated with warmer and drier summers.Geophys Res Lett, 41(6): 1995–2002

[8] Chen J M, Ju W, Cihlar J, Price D, Liu J, Chen W, Pan J, Black A, Barr A (2003). Spatial distribution of carbon sources and sinks in Canada’s forests.Tellus B, 55(2): 622–641

[9] Cox P M, Betts R A, Jones C D, Spall S A, Totterdell I J (2000). Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model.Nature, 408(6809): 184–187

[10] Cramer W, Bondeau A, Woodward F I, Prentice I C, Betts R A, Brovkin V, Cox P M, Fisher V, Foley J A, Friend A D (2001). Global response of terrestrial ecosystem structure and function to CO₂ and climate change: results from six dynamic global vegetation models.Glob Change Biol, 7(4): 357–373

[11] D’Arrigo R, Wilson R, Liepert B, Cherubini P (2008). On the ‘divergence problem’in northern forests: a review of the tree-ring evidence and possible causes.Global Planet Change, 60(3−4): 289–305

[12] Denman K, Brasseur G, Chidthaisong A, Ciais P, Cox P M, Dickinson R E, Hauglustaine D, Heinze C, Holland E, Jacob D, Lohmann U, Ramachandran S, da Silva Dias P L, Wofsy S C, Zhang X (2007). Couplings between changes in the climate system and biogeochemistry. In: Solomon S, Qin D, Manning M, Chen Z, Marquis M, Averyt K B, Tignor M, Miller H L, 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, Cambridge, United Kingdom and New York, NY, USA

[13] Famiglietti C A, Smallman T L, Levine P A, Flack-Prain S, Quetin G R, Meyer V, Parazoo N C, Stettz S G, Yang Y, Bonal D (2021). Optimal model complexity for terrestrial carbon cycle prediction.Biogeosciences, 18: 2727–2754

[14] Field C B, Lobell D B, Peters H A, Chiariello N R (2007). Feedbacks of terrestrial ecosystems to climate change.Annu Rev Environ Resour, 32: 1–29

[15] Friedlingstein P, Cox P, Betts R, Bopp L, von Bloh W, Brovkin V, Cadule P, Doney S, Eby M, Fung I (2006). Climate–carbon cycle feedback analysis: results from the C4MIP model intercomparison.J Clim, 19(14): 3337–3353

[16] Huang J, Yu H, Guan X, Wang G, Guo R (2012). Accelerated dryland expansion under climate change.Nat Clim Chang, 6(2): 166–171

[17] 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 [Stocker T F, Qin D, Plattner GK, Tignor M, Allen S K, Boschung J, Nauels A, Xia Y, Bex V, Midgley P M (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA, pp 1535

[18] IPCC (2021). Summary for Policymakers. In: Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Stocker T F, Qin D, Plattner G K, Tignor M, Allen S K, Boschung J, Nauels A, Xia Y, Bex V, Midgley P M (eds.)]. Cambridge University Press, Cambridge, United Kingdom and New York, NY, USA

[19] Ito A, Saigusa N, Murayama S, Yamamoto S (2005). Modeling of gross and net carbon dioxide exchange over a cool-temperate deciduous broad-leaved forest in Japan: analysis of seasonal and interannual change.Agric For Meteorol, 134(1−4): 122–134

[20] Kato E, Kinoshita T, Ito A, Kawamiya M, Yamagata Y (2013). Evaluation of spatially explicit emission scenario of land-use change and biomass burning using a process based biogeochemical model.J Land Use Sci, 8: 104–122

[21] Keeling C D, Whorf T P (2005). Atmospheric CO2 records from sites in the SIO air sampling network. Trends: a compendium of data on global change, 16–26

[22] Keller K M, Lienert S, Bozbiyik A, Stocker T F, Frank D C, Klesse S, Koven C D, Leuenberger M, Riley W J, Saurer M (2017). 20th century changes in carbon isotopes and water-use efficiency: tree-ring-based evaluation of the CLM4.5 and LPX-Bern models.Biogeosciences, 14(10): 2641–2673

[23] Krinner G, Viovy N, de Noblet‐Ducoudré N, Ogée J, Polcher J, Friedlingstein P, Ciais P, Sitch S, Prentice I C (2005). A dynamic global vegetation model for studies of the coupled atmosphere‐biosphere system.Global Biogeochem Cycles, 19(1): GB1015

[24] Lang W, Chen X, Qian S, Liu G, Piao S (2019). A new process-based model for predicting autumn phenology: how is leaf senescence controlled by photoperiod and temperature coupling.Agric For Meteorol, 268: 124–135

[25] Lawrence D M, Oleson K W, Flanner M G, Thornton P E, Swenson S C, Lawrence P J, Zeng X, Yang Z L, Levis S, Sakaguchi K (2011). Parameterization improvements and functional and structural advances in version 4 of the Community Land Model.J Adv Model Earth Syst, 3(3): M03001

[26] Lin X, Li J, Luo J, Wu X, Tian Y, Wang W (2015). Precipitation mediates the response of carbon cycle to rising temperature in the mid-to-high latitudes of the northern hemisphere.PLoS One, 10(7): e0132663

[27] Liu Y, Piao S, Lian X, Ciais P, Smith W K (2017). Seasonal responses of terrestrial carbon cycle to climate variations in CMIP5 models: evaluation and projection.J Clim, 30(16): 6481–6503

[28] Lombardozzi D L, Smith N G, Cheng S J, Dukes J S, Sharkey T D, Rogers A, Fisher R, Bonan G B (2018). Triose phosphate limitation in photosynthesis models reduces leaf photosynthesis and global terrestrial carbon storage.Environ Res Lett, 13(7): 074025

[29] Lu M, Zhou X, Yang Q, Li H, Luo Y, Fang C, Chen J, Yang X, Li B (2013). Responses of ecosystem carbon cycle to experimental warming: a meta‐analysis.Ecology, 94(3): 726–738

[30] Luo Y (2007). Terrestrial carbon–cycle feedback to climate warming.Annu Rev Ecol Evol Syst, 38: 683–712

[31] Mahecha M D, Reichstein M, Carvalhais N, Lasslop G, Lange H, Seneviratne S I, Vargas R, Ammann C, Arain M A, Cescatti A (2010). Global convergence in the temperature sensitivity of respiration at ecosystem level.Science, 329(5993): 838–840

[32] Matthews B, Schume H (2022). Tall tower eddy covariance measurements of CO₂ fluxes in Vienna, Austria.Atmos Environ, 274: 118941

[33] Matthews H D, Weaver A J, Meissner K J (2005). Terrestrial carbon cycle dynamics under recent and future climate change.J Clim, 18(10): 1609–1628

[34] Messori G, Ruiz-Pérez G, Manzoni S, Vico G (2019). Climate drivers of the terrestrial carbon cycle variability in Europe.Environmental Research Letters, 14(6): 063001

[35] Niu S, Wu M, Han Y, Xia J, Li L, Wan S (2008). Water-mediated responses of ecosystem carbon fluxes to climatic change in a temperate steppe.New Phytol, 177(1): 209–219

[36] Norton A J, Bloom A A, Parazoo N C, Levine P A, Ma S, Braghiere R K, Smallman T L (2023). Improved process representation of leaf phenology significantly shifts climate sensitivity of ecosystem carbon balance.Biogeosciences, 20(12): 2455–2484

[37] Pappas C S, Fatichi S, Leuzinger A, Wolf , Burlando P (2013). Sensitivity analysis of a process-based ecosystem model: pinpointing parameterization and structural issues.J Geophys Res Biogeosci, 118: 505–528

[38] (). .,

[39] Piao S, Ciais P, Friedlingstein P, Peylin P, Reichstein M, Luyssaert S, Margolis H, Fang J, Barr A, Chen A (2008). Net carbon dioxide losses of northern ecosystems in response to autumn warming.Nature, 451(7174): 49–52

[40] Piao S, Nan H, Huntingford C, Ciais P, Friedlingstein P, Sitch S, Peng S, Ahlström A, Canadell J G, Cong N (2014). Evidence for a weakening relationship between interannual temperature variability and northern vegetation activity.Nat Commun, 5(1): 5018

[41] Piao S, Sitch S, Ciais P, Friedlingstein P, Peylin P, Wang X, Ahlström A, Anav A, Canadell J G, Cong N (2013). Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO₂ trends.Glob Change Biol, 19(7): 2117–2132

[42] Raddatz T, Reick C, Knorr W, Kattge J, Roeckner E, Schnur R, Schnitzler K G, Wetzel P, Jungclaus J (2007). Will the tropical land biosphere dominate the climate–carbon cycle feedback during the twenty-first century.Clim Dyn, 29: 565–574

[43] Randerson J T, Hoffman F M, Thornton P E, Mahowald N M, Lindsay K, Lee Y H, Nevison C D, Doney S C, Bonan G, Stöckli R, Covey C, Running S W, Fung I Y (2009). Systematic assessment of terrestrial biogeochemistry in coupled climate-carbon models.Glob Change Biol, 15: 2462–2484

[44] Reichstein M, Falge E, Baldocchi D, Papale D, Aubinet M, Berbigier P, Bernhofer C, Buchmann N, Gilmanov T, Granier A (2005). On the separation of net ecosystem exchange into assimilation and ecosystem respiration: review and improved algorithm.Glob Change Biol, 11(9): 1424–1439

[45] Richardson A D, Andy Black T, Ciais P, Delbart N, Friedl M A, Gobron N, Hollinger D Y, Kutsch W L, Longdoz B, Luyssaert S (2010). Influence of spring and autumn phenological transitions on forest ecosystem productivity.Philos Trans R Soc Lond B Biol Sci, 365(1555): 3227–3246

[46] Richardson A D, Hollinger D Y, Dail D B, Lee J T, Munger J W, O’keefe J (2009). Influence of spring phenology on seasonal and annual carbon balance in two contrasting New England forests.Tree Physiol, 29(3): 321–331

[47] Schneck R, Gayler V, Nabel J E M S, Raddatz T, Reick C H, Schnur R (2022). Assessment of JSBACHv4.30 as a land component of ICON-ESM-V1 in comparison to its predecessor JSBACHv3.2 of MPI-ESM1.2.Geosci Model Dev, 15: 8581–8611

[48] Sitch S, Friedlingstein P, Gruber N, Jones S D, Murray-Tortarolo G, Ahlström A, Doney S C, Graven H, Heinze C, Huntingford C (2015). Recent trends and drivers of regional sources and sinks of carbon dioxide.Biogeosciences, 12(3): 653–679

[49] Smith N G, Dukes J S (2013). Plant respiration and photosynthesis in global-scale models: incorporating acclimation to temperature and CO2.Glob Change Biol, 19: 45–63

[50] Song J, Wan S, Piao S, Knapp A K, Classen A T, Vicca S, Ciais P, Hovenden M J, Leuzinger S, Beier C (2019). A meta-analysis of 1, 119 manipulative experiments on terrestrial carbon-cycling responses to global change.Nat Ecol Evol, 3(9): 1309–1320

[51] Sun Q, Zhu J, Li B, Zhu S, Huang J, Chen X, Yuan W (2024). Drier August and colder September slow down the delaying trend of leaf senescence in herbaceous plants on the Qinghai–Tibetan Plateau.Sci Total Environ, 908: 168504

[52] Tanja S, Berninger F, Vesala T, Markkanen T, Hari P, Mäkelä A, Ilvesniemi H, Hänninen H, Nikinmaa E, Huttula T (2003). Air temperature triggers the recovery of evergreen boreal forest photosynthesis in spring.Glob Change Biol, 9(10): 1410–1426

[53] Vuichard N, Papale D (2015). Filling the gaps in meteorological continuous data measured at FLUXNET sites with ERA-Interim reanalysis.Earth Syst Sci Data, 7(2): 157–171

[54] Wang Y, Law R, Pak B (2010). A global model of carbon, nitrogen and phosphorus cycles for the terrestrial biosphere.Biogeosciences, 7(7): 2261–2282

[55] Wolf A, Blyth E, Harding R, Jacob D, Keup-Thiel E, Goettel H, Callaghan T (2008). Sensitivity of an ecosystem model to hydrology and temperature.Clim Change, 87: 75–89

[56] Wu X, Liu H, Li X, Piao S, Ciais P, Guo W, Yin Y, Poulter B, Peng C, Viovy N (2017). Higher temperature variability reduces temperature sensitivity of vegetation growth in Northern Hemisphere.Geophys Res Lett, 44(12): 6173–6181

[57] Wu X, Liu H, Wang Y, Deng M (2013). Prolonged limitation of tree growth due to warmer spring in semi-arid mountain forests of Tianshan, northwest China.Environ Res Lett, 8(2): 024016

[58] Xu B, Yang Y, Li P, Shen H, Fang J (2014). Global patterns of ecosystem carbon flux in forests: a biometric data-based synthesis.Global Biogeochem Cycles, 28(9): 962–973

[59] Yuan W, Liang S, Liu S, Weng E, Luo Y, Hollinger D, Zhang H (2012). Improving model parameter estimation using coupling relationships between vegetation production and ecosystem respiration.Ecol Modell, 240: 29–40

RIGHTS & PERMISSIONS

Higher Education Press